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An Assessment of Environmental and Economic Effects of in Communities Around Wli Waterfalls and Lake Bosomtwi in Ghana

A Thesis Presented to

ENVIRONMENTAL SCIENCE PROGRAMME

(INSTITUTE OF ENVIRONMENT AND SANITATION STUDIES)

UNIVERSITY OF GHANA

BY

AMPEM DARKO ANIAPAM

(10097013)

In partial fulfillment of the requirements for the award of

DOCTOR OF PHILOSOPHY

in

ENVIRONMENTAL SCIENCE

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DECLARATION

I, the undersigned student of Environmental Science Programme of the University of

Ghana, hereby declare that this thesis is a true representation of the outcome of my own research findings under the supervision of Prof. Alex B. Asiedu of the Department of

Geography and Resource Development; Prof. Frank K. Nyame of the Department of

Earth Science and Dr. Yaw B. Osei–Asare of the Department of Agricultural Economics and Agricultural Business. And that all references have duly been acknowledged.

SIGN…………………………. SIGN………………………………

AMPEM DARKO ANIAPAM PROF. ALEX B. ASIEDU (Student) (Principal Supervisor) Date…………………………… Date……………………………….

SIGN……………………………… PROF. FRANK K. NYAME (Co–Supervisor) Date……………………………….

SIGN………………………………

DR. YAW B. OSEI–ASARE (Co–Supervisor) Date……………………………….

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DEDICATION

This work is affectionately dedicated to my dear wife, Akua Akonorbea Aniapam and my children, Nana Darko, Maame Nhyira and Barima Owusu (My Little Domestic Warriors) whose sympathetic understanding, encouragement and support enabled me jump over the numerous obstacles along the way. It also goes to Naana Oye Aniapam for her sisterly love, financial support and priceless gifts which I am lucky to have enjoyed throughout the duration of my post graduate university education.

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ACKNOWLEDGEMENT

I wish to first and foremost thank the Omnipotent God for the wisdom, health and protection that he has given me throughout my education.

My next sincere gratitude goes to my dynamic supervisors, Prof. Alex B. Asiedu, Prof.

Frank K. Nyame and Dr. Y. B. Osei–Asare through whose help, this dream of yesteryears has become a reality. Their guidance, encouragement, constructive criticisms, suggestions and, above all, patience with me even when everything seemed lost has been invaluable.

I also wish to show my appreciation to Mr. Lawrence Offei Asare of the Methodist

University without whose help this educational endeavor would not have been completed.

Again, I gratefully acknowledge the immense assistance and care given to me by my brothers Payin, Junior, Kwaku and Kofi Asiedu for accompanying me on the trips to the study sites most of the time.

I also appreciate the assistance given to me by officials of the Environmental Biology and Health and the Environmental Chemistry Divisions of the Water Research Institute of

CSRIR (most especially Dr. Ampofo, Alhaji Bello, Mr. K. and Mike) for taking time out of their busy schedule to help with the bacteriological and physico–chemical analysis.

Similarly, I am indebted to the following, whose assistance and encouragement cannot be left unmentioned. They are Dr. Ernest Mensah Abraham and Mr. Edward Koomson of the University of Professional Studies, for their immense contribution towards the completion of this work.

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Mention must also be made of Richmond Arhin (Abanga), Patrick Sarpong (Old School),

Alexander Ampomah (Cosby) and Paul Otu for availing themselves as field assistants for data collection.

Last but not the least, I am greatly indebted to Ms. Leticia Gampson (Week End School -

UPSA) for the wonderful typing skills she exhibited in typing some portions of this work.

To all and sundry, I say “A big thank you and God Richly Bless You”.

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ABSTRACT The study sought to assess the effects of tourism on the environment and economic activities in the communities around Lake Bosomtwi and Wli Waterfalls. Methodology used included analysis of water samples from the Lake and Waterfall. Satellite images covering the period between 1990 and 2010 of land use around the Lake Bosomtwi and

Wli Waterfalls were also analyzed to see if tourism is affecting vegetative cover around the Lake Bosomtwi and Wli Waterfalls. In addition, a social survey and detailed observation of anthropogenic activities were also made to determine the perceived effects of tourism on environment and economic activities. Also, the relationship between environmental effects on socio–economic activities was investigated. Finally, the level of participation of residents in the management of the tourism resources in their community was assessed. Values recorded for physical parameters in the Wli Waterfalls were below the acceptable limits for WHO standards for drinking water. The values ranged between

o o o 23.6 C to 27.9 C (mean= 25.8 C), 6.1-8.7 (mean= 7.5), 2.217µS/cm to 101.117µS/cm

(mean= 43.217µS/cm), 5.2NTU to 39.2 NTU (mean= 14.9 NTU) 8.6mg/L to 32.6mg/L

(mean= 15.9mg/L) for temperature, pH, conductivity, turbidity and TDS respectively.

With the exception of conductivity (1038 µS/cm to 1381 µS/cm; mean= 1263 µS/cm) and pH (7.4 to 9.6; mean= 8.98), which were above the acceptable limits of WHO standards for drinking water, the rest of physical parameters recorded in the Lake Bosomtwi were also below the acceptable limits of WHO standards for drinking water. Coliforms contents of both water bodies; 505cfc/100mL to 2208cfc/100mL (mean=1078cfc/100mL) and 584cfc/100mL to 2603cfc/100mL (mean= 1248cfc/100mL) for Wli Waterfalls and

Lake Bosomtwi respectively were far above the acceptable limits for WHO standards for drinking water. Values recorded for peak periods (festive occasions when influx of

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tourists was high) were slightly higher than values recorded for the lean periods (non festive occasions when influx of tourists was very low). The differences were however not significant. While vegetation cover around Wli Waterfalls experienced a diversity of changes that of Lake Bosomtwi was a continuous decline. Grassland coverage and built up/bare areas on the other hand increased throughout the study period for the two study areas. While the improvement in the vegetation cover could partly be attributed to tourism development at Wli Waterfalls, the decline at Lake Bosomtwi could however not be attributed to tourism development alone. Anthropogenic activities such as farming and expansion in settlements could also be responsible. Social survey and observations made indicates that the residents in communities around Wli Waterfalls do perceive tourism development to be having more positive effects than negative ones on their environmental and economic activities. Residents from communities around Lake

Bosomtwi on the other hand perceive tourism development to be having more negative effects than positive ones on their environment. They also believed that economic benefits from tourism development are very minimal. The varied perceptions from the residents in two study areas may be due to the fact that tourism development at the Wli

Waterfalls is still at the euphoria stage of Doxey‟s Irridex Model while that of Lake

Bosomtwi is at the apathy stage. Responds from residents indicates that residents do not play any meaningful role in the management of tourism resource in their communities and that at best they are at the manipulation level on the ladder of citizen participation.

Despite the concerns raised by residents, especially those from Bosomtwi, on the perceived negative effects of tourism on their environment and economic activities,

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majority of them (especially the youth) still wants the development of tourism to go on in their communities.

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Table of Contents Title Page……………………………..………..…………………………………...... i Declaration………………….………….…………………………………...... ii Dedication…………………………………………………………………...... iii Acknowledgment…………………………………………………………...... iv ABSTRACT...... vi Table of Contents…………………………………………………………...... ix List of Figures……………………………………………………………...... xv List of Tables……………………………………………………………...... xvi List of Plates………………………………………………………………...... xix

List of Figures ...... xv CHAPTER ONE ...... 1 INTRODUCTION ...... 1 1.1 Background to the Study ...... 1 1.2 The Research Problem ...... 10 1.3 Aims and Objectives ...... 16 1.4 Hypotheses ...... 17 1.5 Research Questions ...... 18 1.6 Relevance of the Study ...... 18 1.7 Summary ...... 20 CHAPTER TWO ...... 21 LITERATURE REVIEW ...... 21 2.1 Introduction ...... 21 2.2 History of Tourism Development in Ghana ...... 21 2.3 Tourism in Perspective: Definitions and Concepts ...... 24 2.4 Concepts/Elements of Tourism Definitions ...... 26 2.5 Types/Forms of Tourism ...... 27 2.6 Impacts of Tourism ...... 28 2.7 Economic Impacts ...... 29 2.7.1 Economic Characteristics of the Tourism Industry ...... 29 2.7.2 Positive Impacts ...... 32

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2.7.2.1 Balance of Payments ...... 32 2.7.2.2 Employment ...... 34 2.7.2.3 Revenue to the Government ...... 37 2.7.2.4 Income ...... 39 2.7.2.5 Investments ...... 40 2.7.3 Negative Impacts ...... 41 2.7.3.1 Opportunity Cost ...... 41 2.7.3.2 Over-Dependency on Tourism ...... 42 2.7.3.3. Inflation ...... 43 2.7.3.4 Seasonality ...... 44 2.7.3.5 Leakages ...... 45 2.8 Environmental Effects ...... 46 2.8.1 Positive Impacts ...... 48 2.8.2 Negative Impacts ...... 49 2.8.2.1 Tourism and the Vegetation ...... 50 2.8.2.2 Tourism and Wildlife ...... 51 2.8.2.3 Tourism and Water Pollution ...... 52 2.8.2.4 Tourism and Man–Made Environment ...... 53 2.8.3 Reducing the Negative Environmental Impacts of Tourism ...... 54 2.9 Concepts and Theories of Participation ...... 56 2.9.1 A Ladder of Citizen Participation ...... 57 2.9.1.1 Characteristics of the Illustrations ...... 58 2.9.1.2 Limitations of the Typology...... 62 2.9.2 A New Ladder of Citizen Participation...... 63 2.9.2.1 Characteristics of the Illustration ...... 64 2.9.3 Social Learning as a New Policy Paradigm ...... 69 2.10 Conceptual Framework for the Study ...... 72 2.11 Summary ...... 75 CHAPTER THREE ...... 76 THE STUDY AREA AND METHODOLOGY ...... 76 3.1 Introduction ...... 76 3.2 The Study Area ...... 76

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3.2.1 Bosomtwi District ...... 76 3.2.1.1 Geology and Soil ...... 77 3.2.1.2 Vegetation ...... 78 3.2.1.3 Climate ...... 79 3.2.1.4 Population and Socio-economic Characteristics ...... 82 3.2.2 Hohoe Municipality ...... 85 3.2.2.1 Geology and Soil ...... 85 3.2.2.2 Vegetation ...... 87 3.2.2.3 Climate ...... 88 3.2.2.4 Population and Socio-economic Characteristics ...... 91 3.3 Rationale for Selecting Study Areas ...... 94 3.4 Data Collection ...... 95 3.5 Data Source ...... 95 3.6 The Sampling Sites ...... 95 3.7 Water Sampling and Analysis ...... 100 3.7.1 Physical Parameters ...... 101 3.7.2 Bacteriological Analysis ...... 101 3.8 Land Use and Cover Analysis ...... 102 3.9 Social Survey ...... 103 3.9.1 Target Population ...... 103 3.9.2 Sample Frame and Sample Size ...... 104 3.9.3 Sampling Procedure ...... 105 3.10 Sample Validation and Pilot Survey (Pre–Testing) ...... 106 3.11 Study Instruments ...... 107 3.11 Participant Observations ...... 109 3.12 Ethical Considerations...... 110 3.13 Summary ...... 111 CHAPTER FOUR ...... 112 STUDY RESULTS ...... 112 4.1 Introduction ...... 112 4.2 Physico–Chemical Parameters ...... 112 4.2.1 Temperature ...... 112 4.2.2 pH ...... 114

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4.2.3 Conductivity ...... 116 4.2.4 Turbidity ...... 118 4.2.5 Total Dissolved Solids (TDS) ...... 120

4.2.6 Nitrate (NO3) ...... 122

4.2.7 Nitrite (NO2) ...... 124

4.2.8 Phosphate (PO4)...... 126 4.2.9 Calcium (Ca) ...... 128 4.2.10 Magnesium (Mg) ...... 130 4.2.11 Potassium (K)...... 131 4.2.12 Chlorine (Cl) ...... 133 4.2.13 Sodium (Na) ...... 135 4.2.14 Fluoride (F-) ...... 137 4.2.15 Alkalinity ...... 139 4.2.16 Total Hardness ...... 141

4.2.17 Ammonium (NH3) ...... 143 4.3 Trace Metals Analysis ...... 143 4.3.1 Manganese (Mn) ...... 143 4.3.2 Iron (Fe) ...... 144 4.3.3 Copper (Cu), Lead (Pb), Cadmium (Cd) and Zinc (Zn) ...... 146 4.4 Bacteriological Analysis ...... 147 4.4.1 Total Coliforms ...... 147 4.4.2 Fecal Coliforms ...... 149 4.5 Multivariate Statistical Analysis ...... 152 4.6 Land Use Analysis ...... 156 4.8 Social Survey ...... 163 4.8.1 Bio Data of Respondents ...... 163 4.8.2 Perceived Environmental Impacts ...... 168 4.8.3 Perceived Economic Impacts ...... 172 4.8.4 Participation in Management of Tourism Facilities...... 177 4.9 Summary ...... 183 CHAPTER FIVE ...... 184 DISCUSSION ...... 184 5.1 Introduction ...... 184

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5.2 Water Quality Parameters ...... 184 5.2.1 Temperature ...... 184 5.2.2 pH ...... 185 5.2.3 Conductivity, Turbidity, TDS/TSS ...... 186

5.2.4 NO3/NO2 ...... 189

5.2.5 PO4 ...... 190 5.2.6 Calcium (Ca) and Magnesium (Mg) ...... 191 5.2.7 Chloride (CL) and Sodium (NA) ...... 192 5.2.8 Potassium (K)...... 193 5.2.9 Alkalinity ...... 194 5.2.10 Trace Metals Analysis ...... 195 5.2.11 Bacteriological Analysis ...... 196 5.3 Land Use Analysis ...... 197 5.4 Perceived Impacts of Tourism ...... 199 5.4.1 Perceived Environmental Impacts ...... 199 5.4.2 Perceived Economic Impacts ...... 205 5.5 Level of Participation in the Management of the Attractions by Local Residents ...... 210 5.6 Relationship between Environmental Impacts and Economic Activities in Study Area . 213 5.7 Relationship between Respondents Socio-Demographic Data and Perception about Effects of Tourism ...... 215 5.8 Summary ...... 230 CHAPTER SIX ...... 231 SUMMARY, CONCLUSION AND RECOMMENDATIONS ...... 231 6.1 Introduction ...... 231 6.2 Summary of Key Findings ...... 231 6.2.1 Water Quality Analysis ...... 232 6.3 Land Use Analysis ...... 235 6.4 Social Survey ...... 235 6.4.1 Perceived Environmental Effects ...... 235 6.4.2 Perceived Economic Effects ...... 236 6.5 Conclusion ...... 237 6.6 Contribution to Knowledge ...... 241 6.7 Recommendations ...... 242

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6.7.1 Recommendations for Sustainable Development of Tourism ...... 242 6.7.2 Recommendations for Further Studies ...... 246 REFERENCES ...... 248

Appendix 1: Questionnaires to Residents…………………………….……………...…265

Appendix 2a-b: Monthly Mean Rainfall for Kumasi and Hohoe ……...…………...….270

Appendix 3a-b: Monthly Minimum and Maximum Temperature for Kumasi and Hohoe …………………………………………………………………………………………..271

Appendix 4a –b: Monthly Minimum and Maximum Relative Humidity for Kumasi and Hohoe…………………………………………………………………………………...272

Appendix 5: Values, Periodic and Site Means for Physical Parameters …………...…..275

Appendix 6: Values, Periodic and Site Means for Nutrients Parameters ……...…....…276

Appendix 7: Values, Periodic and Site Means for Chemical Parameters …………...…278

Appendix 8: Values, Periodic and Site Means for Trace Metals Parameters ….…...….282

Appendix 9: Values, Periodic and Site Means for Bacteriological Parameters ………..285

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List of Figures Figure 2.1: The Eight Rungs Ladder of Citizen Participation...... 63

Figure 2.2: The New Ladder of Citizen Participation...... 69

Figure 2.3: Stages of Tourism in Development in Doxey‟s Irridex Model...... 75

Figure 3.1a-c: Monthly Maximum, Minimum and Mean for Temperature (a), Rainfall (b) and Humidity (c) in the Bosomtwi District between 2008 and 2012……………………80

Figure 3.2a-c: Monthly Maximum, Minimum and Mean for Temperature (a), Rainfall (b) and Humidity (c) in the Hohoe Municipality between 2008 and 2012………………….88

Figure 3.3: Map of Wli Waterfalls Showing Sampling Sites...... 95

Figure 3.4: Map of Lake Bosomtwi Showing Sampling Sites...... 97

Figure 4.1: Score Plot Illustrating the differentiation of Parameters Associated with Water Quality Parameters of Lake Bosomtwi and Wli Waterfalls during the study. A Three- Components System (PC1-PC3) Explaining 71.05% of Total Variance ...... 153

Figure 4.2: Dendogram showing Clustering of Water Quality Parameters of Wli Waterfalls and Lake Bosomtwi. Two Clusters were Distinctively Identified and they were Made Up of Three Sub-Groups...... 154 Figure 4.3: Land Use Map of Wli Waterfalls and Agumatsa Wildlife Sanctuary...... 163 Figure 4.4: Land Use Map of the Two Kilometer Buffer Zone Around Lake Bosomtwi...... 165

Figure. 5.1: Percentage Coverage of Closed Forest Vegetation around Lake Bosomtwi and Wli Waterfalls between 1990 and 2010...... 201

Figure 5.2: Percentage Coverage of Grass Vegetation around Lake Bosomtwi and Wli Waterfalls between 1990 and 2010...... 202

Figure 5.3: Percentage Coverage of Built Up/Bare Area around Lake Bosomtwi and Wli Waterfalls between 1990 and 2010...... 202

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List of Tables

Table 3.1: Tourist Arrivals and Receipts for Wli Waterfalls between 2006 and 2013.... 94 Table 3.2: GPS Positions of Sampling Sites at Wli Waterfalls...... 96 Table 3.3: GPS Positions of Sampling Sites at Lake Bosomtwi...... 98 Table 3.4: Number of Respondents from Each Community in the Study Area..………107 Table 4.1: Mean, Range and Periodic Means for Temperature...... 113 Table 4.2: Mean, Range and Periodic Means for pH...... 115 Table 4.3: Mean, Range and Periodic Means for Conductivity...... 117 Table 4.4: Mean, Range and Periodic Means for Turbidity...... 119 Table 4.5: Mean, Range and Periodic Means for TDS...... 121

Table 4.6: Mean, Range and Periodic Means for NO3...... 123

Table 4.7: Mean, Range and Periodic Means for NO2...... 125

Table 4.8: Mean, Range and Periodic Means for PO4 ...... 127 Table 4.9: Mean, Range and Periodic Means for Ca...... 129 Table 4.10: Mean, Range and Periodic Means for Mg...... 131 Table 4.11: Mean, Range and Periodic Means for K...... 132 Table 4.12: Mean, Range and Periodic Means for Cl...... 134 Table 4.13: Mean, Range and Periodic Means for Na...... 136 Table 4.15: Mean, Range and Periodic Means for Alkalinity...... 135 Table 4.14: Mean, Range and Periodic Means for F-...... 140 Table 4.16: Mean, Range and Periodic Means for Total Hardness...... 142 Table 4.17: Mean, Range and Periodic Means for Mn…………………………………144 Table 4.18: Mean, Range and Periodic Means for Fe...... 145 Table 4.19: Mean, Range and Periodic Means for Total Coliforms...... 148 Table 4.20: Mean, Range and Periodic Means for Fecal Coliforms...... 151 Table 4.21: Rotated Component Matrix of Water Quality Parameters ...... 155

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Table 4.22: Matrix of Land Cover by Class Values for the Years 1990, 2000 and 2010 around Wli Waterfalls.……………………………………………………………….....157

Table 4.23: Matrix of Land Cover by Class Values for the Years 1990, 2000 and 2010 around Lake Bosomtwi...... 129

Table 4.24: Gender of Respondents …………………………………………………....163 Table 4.25: Age of Respondents …………………………………………………….…164 Table 4.26: Educational Level of Respondents……………………………………..….164 Table 4.27: Religion of Respondents ……………………………………………..…...165 Table 4.28: Marital Status of Respondents ……………………………………………166 Table 4.29: Number of Children per Household……………………………………….166 Table 4.30: Occupation of Respondents …………………………………………….....167 Table 4.31: Number of Years Respondents has Lived in Community ………………...168 Table 4.32: Critical Environmental Problems in the Community ………………….….169 Table 4.33: Respondents Views on Causes of Environmental Problems …………...…170 Table 4.34: Types of Vegetation Found around the Attractions ……………………...171 Table 4.35: Respondents Views on Changes in Environment ………………………...172 Table 4.36: Respondents Views on Whether Tourism brings Benefits……………...... 172 Table 4.37: Types of Benefits Respondents get from Tourists ……………………….173 Table 4.38: Respondents Views on Seasonality Nature of Tourism Benefits………...173 Table 4.39: Respondents who have Worked in the Tourism Industry Before………….174 Table 4.40: Respondents who have Family Members Working in the Tourism Industry……………………………………………………………………………..…..175 Table 4.41: Respondents Views on the Effects of Tourism on Farming Activities……177 Table 4.42: Level of Participation in the Management of Tourism Industry………….178 Table 4.43: Reasons for Not Participation in the Management of Tourism Industry…178 Table 4.44: Consultations Before Tourism Development Decisions Are Taken……....179 Table 4.45: Respondents Know How Much is Earned from Tourism Industry……….180 Table 4.46: Knows What Money Earned from Tourism Industry is Used For………..180

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Table 4.47: TMC Renders Accounts on Earnings from Tourism to Community……...181 Table 5.1: Likert Scale Table on Perceived Environmental Impacts ...... 200 Table 5.2: Likert Scale Table on Perceived Economic Impacts ...... 205 Table 5.3a: Chi-Square Relationship between Age and Perceived Environmental Impacts ...... 216 Table 5.3b: Chi-Square Relationship between Sex and Perceived Environmental Impacts ……………………………………………………………………………………….....217

Table 5.3c: Chi-Square Relationship between Educational Level and Perceived Environmental Impacts……………………………………...………………………….218 Table 5.3d: Chi-Square Relationship between Occupation and Perceived Environmental Impacts …………………………………..……………………………………………..219 Table 5.3e: Chi-Square Relationship between Marital Status and Perceived Environmental Impacts: ………………………………………………………………..220 Table 5.3f: Chi-Square Relationship between Religion and Perceived Environmental Impacts …..…………………………………………..…………………………………221 Table 5.4a: Chi-Square Relationship between Age and Perceived Economic Impacts …………………………………………………………………………………………..223 Table 5.4b: Chi-Square Relationship between Sex and Perceived Economic Impacts…..……………………………………………………………………………...224 Table 5.4c: Chi-Square Relationship between Educational Level and Perceived Economic Impacts………………………………………………………………...…...... 225 Table 5.4d: Chi-Square Relationship between Occupation and Perceived Economic Impacts ………………………………………………………………………….……...226 Table 5.4e: Chi-Square Relationship between Marital Status and Perceived Economic Impacts ………………………………………………………………………………....227 Table 5.4f: Chi-Square Relationship between Religion and Perceived Economic Impacts …...…...... 228

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List of Plates Plate 1: Sign Board Directing Visitors to the Information Center...... 84 Plate 2: Sign Board Welcoming Visitors to the Bosomtwi Lake...... 93 Plate 3: Researcher Fetching Water in Lake Bosomtwi for Analysis in the Laboratory...... 231 Plate 4: Researcher Taking in–situ Measurement of Some Parameters at Wli Waterfalls ...... 231 Plate 5: Tourist Swimming in Lake Bosomtwi...... 232 Plate 6: Traders Selling their Wares on a Festive Occasion at the Shores of Lake Bosomtwi ...... 232 Plate 7: Tourists Swimming in the Wli Waterfalls...... 233 Pate 8: Tourists Waiting to Crouse on Lake Bosomtwi …………………………..……233 Plate 9: Wli Waterfalls Cascading Down at the Lower Falls...... 234 Plate 10: The Pool at Wli Waterfalls where Tourists Swim……………………………234

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CHAPTER ONE

INTRODUCTION

1.1 Background to the Study The importance of tourism as a tool for socio-economic development at the global, regional and national levels has attained the recognition of most governments and academic researchers. There is now the realization of the potential of tourism to contribute to the socio-economic and social development of countries and most developing countries have come to acknowledge that tourism is a key area for socio- economic development, employment generation and positive contributor to balance of payments. Thus, most developing countries regard the development of tourism as a panacea to their socio-economic problems (Cooper, 2012).

Tourism is a service industry which involves people moving to an “alien” environment for the purpose of sightseeing, recreation, business etc. for a period of not less than twenty-four hours but not more than a year, without engaging themselves in any income earning activity at this destination (Cooper et al, 1998).

World Tourism Organization (UNWTO) in one of its conferences defined tourism as “the activities of person travelling to and staying in places outside their usual environment for not more than one conservative year for leisure, business and other activities” (UNWTO,

1993).

Goeldner et al (2000) also defined tourism as “the phenomena and relationships arising from the interactions of tourists, business supplies, host government and host communities in the process of attracting and hosting these tourists and other visitors”.

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The different definitions given above indicate that different groups and institutions see it from different angles. A developing country may see it as the provision of goods and services at the destinations for consumption and satisfaction of non-residents for the accrued residual benefits to the providers of the goods and services. They therefore see it as a tool for solving their developmental problems. Developed countries on the other hand undertake tourism primarily for leisure, recreations, intellect etc with the socio- economic aspect being a secondary issue. From this perspective it is clear that tourism would not benefit developed and developing countries to the same extent, since each has it own reason for developing it (Pearce, 1987).

Many developing countries have placed greater weight on tourism in their attempt to develop their economies and as a result have put in place policies, strategies and activities to promote its growth (Milne, 1990). It is believed that as the tourist travels to consume the tourism product, income will accrue to the destination areas, leading to acceleration in the socio-economic development of these areas. Some of the benefits that destination areas receive from developing the tourism sector are:

First, as a result of the increased visitor expenditure, foreign exchange becomes available for the host country to help improve their balance of payment situations. According to

UNWTO, tourism is the fastest growing industry in the world and it has been growing steadily at about 4% annually (UNWTO, 2014).

According to the World Travel and Tourism Council (WTTC), tourism generated about

$1,158.5 billion to the world economy in 2008. It rose to about $1, 70.6 billion in 2011 and then $2,364.8 billion (3.1% of total world GDP) in 2014 (WTTC, 2015). It is

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expected to increase by 3.7% in 2015 and then an annual increment of about 3.9% for the next decade (WTTC, 2015). In most countries, tourism is the largest or among the top 3 in terms of commodity in international trade. For example, tourism was the leading provider of foreign exchange for Fiji Islands with estimated earnings of about $137.4 million in 2013 (WTTC, 2015). This was followed by sugar, with estimated earnings of about $99 million. It is also the leading source of foreign exchange for Kenya providing it with $149.5 million in 2013 and is expected to grow by about 6.4% in 2015 (WTTC,

2015).

Second, the labor intensive nature of the tourism industry serves as a great potential for a wide range of employment opportunities for the indigenes of the host country (Milne,

1990). Studies by WTTC indicate that tourism is one of the largest industries and a generator of quality jobs. In 2014, it created about 105.5 million direct jobs representing about 3.6% of all jobs in the world. It is expected to rise to about 107.6 million direct jobs representing an increase of about 2.1% in 2015 and estimated to rise by 2.0% per annum to create about 130.7 million direct jobs by 2025 (WTTC, 2015).

Total contribution of jobs (direct and indirect) by the tourism industry in 2014 was about

276.8 million jobs representing about 9.4% of all jobs in the world. The number of jobs created is expected to rise to about 284 million jobs representing an increase of about

2.6% in 2015 and estimated to rise by 2.3% per annum to create about 356.9 million jobs by 2025 (WTTC, 2015). In fact it is believed that for every 2.5 seconds, a new job is created in the tourism industry (UNWTO, 1993). In Mexico for instance, an investment of $80,000 in the tourism industry is believed to have created about 42 jobs but the same amount in the petroleum industry created only 16 jobs in 2000 (Altintas, 2006).

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Third, the ability of tourism to generate income is enormous. Eight percent (8%) of all worldwide income earners are people who work in the tourism industry. It is estimated that the tourism will generate over ten percent (10.3%) of global wages in 2015 (WTTC,

2015). In Bahamas where tourism is well developed, forty percent (40%) of Bahamian income is derived from tourism (Page & Connell, 2006).

Fourth, another area that the impact of tourism is also felt is with capital investments. The tourism industry is a sector that needs the injection of foreign capital to be able to provide the goods and services that help the industry to thrive. In 2008 alone, about $800 billion was pumped into the tourism industry worldwide. Even though it declined slightly to

$770 billion in 2012, it still represented about 5% of total investments worldwide. It started rising again in 2013 and by 2014, it has risen to $814.4 billion. It is expected to rise by about 4.8% in 2015 and then by an annual increment of about 4.6% over the next decade to over $1,336.4 billion in 2025, representing a total of 5.1% of all investments worldwide (WTTC, 2015).

Fifth, tourism also helps to increase government revenue through the imposition of taxes such as hotel bed tax, sales tax, personal income taxes, property taxes, corporate taxes, tolls, entry fees, entertainment levies etc. In 2010, over $928 billion was collected as taxes, representing about 10.6% of total tax collected worldwide that year (WTTC, 2012).

This figure rose to about $1,052 billion in 2012, (3.8% increment) and then $1,124 billion in 2014. With 5.7%, the Americas recorded the highest percentage increase. This was followed by Europe, Asia and with 5.2%, 4.3% and 2.2% respectively. Only the

Middle East has been recording negative growth for the past five years or so due the political instability going on in the area (UNWTO, 2015).

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Other benefits that can be derived from tourism include diversification of the economic structure, spread in regional development, catalyst for the expansion of other sectors of the economy, broadening of educational and cultural horizons, protecting and preserving heritage as well as justifying the protection and improvement of environmental quality.

As a result of the above benefits, attempts are being made by some countries, especially developing countries to expand the tourism sector in their economies. Tourist arrivals have been increasing steadily and with it, tourist receipts. Arrivals worldwide rose from about 1.05 billion in 2012 to about 1.15 billion in 2014 and it is forecast to rise to about

1.8 billion by 2025. Out of the above stated figures, about 62.3 million and 64.2 million were for Africa in 2012 and 2014 respectively (WTTC, 2015).

Receipts also increased from a meager $523.6 billion in 2000 to $1,383.8 billion in 2014 and it is expected to increase by 2.8% to $1,172.7 billion in 2015. About $16.8 billion and $51.5 billion of the above figures for 2000 and 2014 respectively were for Africa.

Despite the fact that Africa‟s share of the arrival and receipts are meager, it is the continent with the fastest growing rates. Though the growth rates for the world was 3.0% and 2.3% for arrivals and receipts respectively that of Africa, which was the highest, was

9.2% and 4.5% for arrivals and receipts respectively (WTTC, 2015).

Since the late 1980‟s, Ghana has been very responsive to the development of tourism as a tool in the socio-economic development of the country. Currently it is the third largest foreign exchange earner for the country after cocoa and gold (ISSER, 2014). Tourism has become one of the fastest growing sectors of the Ghanaian economy. By the year 2000, tourism in Ghana was projected to have been growing at a rate only second to that of

South Africa on the African continent. Tourism in Ghana was estimated to be growing at

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about 10.5% annually within the last decade of the twentieth century (GTA, 1999). In the year 2008, an estimated number of 698,069 tourist arrived in the country. It rose to about

1,080,220 and then 1,191,038 in 2011 and 2014 respectively (WTTC, 2015; GTA, 2014).

Receipts have also been increasing steadily since the early 1990‟s. It rose from a low receipt figure of $1,403.1 million in 2008 to about $2,179.0 and then $2,376.2 million in

2011 and 2014 respectively (WTTC, 2015; GTA, 2014).

The impact of tourism on the economy is such that without it the economy may not have been what it is today. In the year 2005, tourism contributed over 5.7% to the country‟s

Gross Domestic Product (GDP). The figure declined to about 4.3% and then 2.9% in

2011 and 2014 respectively. Even though there were some declines in the percentage rate, actual figures in terms of money into the economy increased. The decline was due to the expansion in the Ghanaian economy (WTTC, 2015; UNWTO, 2014). In 2012, Gross

Foreign Exchange Earnings (GFEE) from tourism in Ghana was $916.9 million and its multiplier effects on employment and income were 3.5% and 3.4% respectively. This figure is expected to increase by about 5.1% in 2015 (WTTC, 2015; ISSER, 2013).

Another area that the is benefiting from tourism is in the employment sector. By the year 2011, over 106,000 people were directly employed in the tourism sector whilst about 259,000 were indirectly employed in it. This rose steadily over the years to 122,000 and 298,500 (representing 2.2% and 5.5% of all jobs in the country) for direct and indirect employment respectively by 2014. This is expected to rise to 4.7% and

2.4% per annum for direct and indirect employment respectively in 2015 (WTTC, 2015;

GTA, 2014).

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The tourism sector has also helped in the development of infrastructure in terms of capital investments in the country. Capital investment rose from GH¢ 493 million in 2011 (4.6% of total investment) to GH¢ 674.5 million (2.7% of total investment) in 2014. It is expected to decline marginally in 2015 and then increase again by an average of about

2.9% annually for the next decade (WTTC, 2015).

Tourist receipts which covers all spending in the country by international tourists for both business and leisure trips increased from GH¢1,115 million in 2011 to a high of

GH¢2,292.2 million in 2014. This is expected to increase by about 5.1% in 2015 and an annual increase of about 3.5% for the next decade (WTTC, 2015; GTA, 2014).

In an attempt to develop the tourism sector, other sectors like transport and communication, energy, manufacturing as well as agriculture are always improved upon

(Poon, 1993: Butler, 1998). Places like Kakum in the and Boti in the

Easter Region, two villages which hitherto had no electricity can now boast of electric power. Roads have also been constructed to some of these attraction sites, which hitherto were not accessible (BOG, 2007). This is as a result of the fact that contemporary tourists are targeting the rural areas of developing countries due to the fact that, it offers them an unusual opportunity for participatory forms of tourism as well as changes in conventional product offerings (Amoah & Baum, 1997)).

The country (Ghana) therefore used the benefits from tourism to revive its‟ dwindling economy over the years. As a result of this, a 15-year Integrated National Tourism

Development Programme was launched in 1996 to serve as a guide to help develop the country as a popular destination for tourist and investors looking for destinations with

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guaranteed market. According to ISSER (2010) the expected end result was that by the year 2010, tourism was expected to have created more jobs, thus reducing employment, increase government revenue and develop an infrastructure that will also help stimulate local commerce and diversify the economy amongst other benefits.

Despite all the above-discussed benefits, tourism has some negative impacts on host communities. These include conflict with the needs and wishes of local residents, increase in cost of labor, land, goods and services, contamination of the values of local communities, increasing social vices such as prostitution, low–paid seasonal and gender– based jobs and degradation of the bio–physical environment (Milne, 1990).

As tourism gathers momentum in its stride in the 21st century, the major players in the industry have started to give the bio-physical environment a priority attention (Mathieson

& Wall, 1982). This is due to the fact that the core of tourism product and profitability in the industry depends on maintaining the attractiveness of the destination that the tourists come to see and experience. It has been said that tourism has the capacity to enhance the bio–physical environment by providing funds for conservation, preserving cultural and historical objects and protecting natural attractions. It can however, affect it negatively if not well planned. It is with these environmental problems in mind that the UNWTO met in 1993 to deliberate on development. They came out with a communiqué that, as far as tourism is concerned, the causes of environmental problems are much debated, and that their effects cannot yet be predicted with any certainty. There are those who even doubt the existence of such problems. Nonetheless, it is clear that anthropogenic activities by way of the local residents, tourists and developers are altering the world‟s environment and without any remedial action, the result may be catastrophic.

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Tourism should be one of the medium through which these problems can be tackled

(UNWTO, 1993).

The environment has variously been defined to include not only land, air, water, flora and fauna, but also encompasses people, their creations and the social, socio-economic and cultural conditions that affect their lives (Lerner, 1977). This discussion however adopts a more narrow focus by restricting it to the physical environment which includes both the natural and man-made environment. The environment being natural or man-made is one of the basic resources for tourism growth and development.

Perception is the process by which people translate sensory impressions into a coherent and unified view of the world around them (Mischel & Shoda, 1995). Even though perception is based on incomplete and unverified information, it is equated with reality for most practical purposes and guides human behavior in general. It is therefore used as a psychological phenomenon that provides an insight into how individuals perceive things or how an individual‟s brain process and interpret information. (Davis, 1993)It therefore has direct bearing on how residents of communities around the Lake Bosomtwi and Wli Waterfalls view or perceive tourism development and its impact on them as individuals and the community as a whole. The fundamental element of perception are the perceiver, the target and the situation (Mischel & Shoda, 1995; Davis, 1993; Bargh, et al., 1992).

Some studies on tourism impacts have hypothesized that perceptions of residents on these impacts may differ among the types or experiences of local residents (Yoon, 2000). Other works have looked at the impact of tourism on the perception of residents and have

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concluded that the perception of residents may be affected by other external factors in addition the impact of tourism development in their communities. Some of these external factors are the level of tourism development, site and time of research, extent of involvement in the management of the tourist attractions and demographic characteristics

(Perdue et al., 1995; Ap, 1992; Milman and Pizam, 1987; Allen & Gibson, 1987).

1.2 The Research Problem Ghana, like most developing countries, is doing everything possible to develop its tourism potentials which are mostly nature–based (Amuquandoh, 2010; Teye et al, 2002;

Cater, 1994; Brandon, 1993). As a result, tourism in Ghana has been growing at a steady pace of about seven percent (7%) per annum for the past two decades or so. This is due to the fact that tourism can encourage clean environment, conservation of the environment, preservation of historical and cultural heritage as well as the enhancement of social and economic benefits (Amuquandoh, 2010; Remeril, 1998; Hunter & Green, 1995;

Crampton & Moore, 1990; Mathieson & Wall, 1982).

Mathieson and Wall (1982) suggested conceptually that impacts of tourism development can conveniently be grouped under the broad headings socio-economic, physical

(environment) and social impacts. Liu et al. (1987) stated that cultural impacts should be added to the environmental, socio-economic and social impacts. The environmental and economic impacts will be the focus of this study so as to enable the researcher to establish a relationship between perceived impacts and results obtained from laboratory analysis

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A lot of questions have been asked concerning the environmental desirability of encouraging further expansion in the tourism industry in Ghana. Numerous studies have also indicated that tourism may have negative impacts on the environment and that most growth rates in tourism development were achieved partly at the expense of environmental sustainability (Pickering & Mount, 2010; Gursory et al., 2002; Puczko &

Ratz, 2000; Buhalis, 2000; Archer & Cooper, 1994). Buhalis (2000) has further postulated that consistent visits to natural areas do have some negative impacts on the environment such as erosion along trail paths, disruption of wild life through forced migration and, depletion of natural resources from illegal hunting and unauthorized plant collection. Gursory et al. (2002) argued that unplanned tourism development in developing countries often results in increased stress at the destination areas leading to negative changes in the environment in these areas. In Ghana for example, trees are felled to boost the carving industry to meet the ever increasing needs of tourists. Vegetation are also cleared to provide access routes and other social amenities at tourist‟s attraction sites, as well as littering of the tourist sites by the tourists among a host of other problems

(Amoah & Baum, 1997).

At the other side of the coin are the pro–conservationists who believe that tourism is an industry that can protect the environment of destination areas (Amuquandoh, 2010;

Masters, 1998; Remeril, 1998; Doswell, 1997; Hunter & Green, 1995). Issues of clean environment, biodiversity conservation, protection of endangered species, preservation and restoration of cultural and historical sites as well as the environment are all done due to tourism. Masters (1998), for example, argued that tourism is often used to provide a socio-economic rationale for the preservation of natural areas rather than develop them

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into alternative socio-economic ventures. In the case of Ghana for example, tourism offered the justification for the creation of new nature reserves and the protection of existing ones in the country. Examples here include Agumatsa Wildlife Sanctuary in the

Volta Region, in the Central Region, in the

Northern Region and Boabeng–Fiema Wildlife Santuary in the Brong Ahafo Region.

One of the critical benefits and costs of tourism development often discussed by tourism scholars is the economic impacts (Akis et al., 1996; Nelson, 1995; Husband, 1989;

Ritchie, 1988; Liu et al., 1987; Milman & Pizam, 1987; Sheldon et al., 1984). According to Fleming and Toepper (1990), recognition of the potential economic benefits of increased travel has led many nations, states, and local communities to intensify their tourism development. The most prominent benefits of tourism discussed in literature are tied to employment opportunities with increase in inflation as the most discussed cost

(Davis et al., 1988).

While a considerable amount of research work has been associated with the impact of tourism on the environment and the economic growth at destination areas in Ghana

(Aboagye et al, 2013; Anim et al., 2013; Havi & Enu, 2013; Bormann, 2012;

Amuquandoh, 2010; Kofigah,2008; Amuquandoh & Dei, 2007; BOG, 2007; Amoah &

Baum, 1997), these studies suffer from shortcomings which include the following;

First, most of the studies on environmental impacts were based on perception studies without the corresponding laboratory analysis studies to corroborate these findings.

Therefore a strong and reliable scientific baseline data and evidence cannot be established from such studies. The necessity of this approach is also based on the fact that real world

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situations of environmental impacts obtained through laboratory analysis and perception of residents may be different. Most of the studies were based on perceptions without laboratory analysis to see if the perceptions and the real world situations are linked.

Second, research has shown that relationships exist between environmental impacts and economic impacts. However, most of these impact studies were carried out distinctively without trying to establish the relationship that exists between the two.

Third, even though some of the economic studies have been directed at the district and local levels, they are not many and there is the need for more of such studies to help expand the frontiers for broadening the knowledge base and also help in the continuous assessment to see if the economic needs of the residents at the destination areas are being met (Amuquandoh, 2006).

Fourth, most of the studies have not determined the specific roles that residents play in the formulation of management policies (level of participation) for the attractions developed in their communities and this has affected decision making in the management of attractions (Choguill, 1986).

Based on these isolated shortcomings, this study attempts to; i. Conduct a study on the laboratory analysis of water quality of the water bodies that serve as attractions to the tourism industry in the study areas. The study areas have attractions that have the potential to be developed into world class tourism destinations. If these developments take place without a coherent and comprehensive planning strategies and appropriate tourism policies, the environment of the destination area may suffer, leading to a decline or even collapse of the industry (Amquandoh, 2006; Butler, 1980). In

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order for authorities to be able to develop appropriate policies and strategies to reduce the expected impacts as much as possible they will need a baseline data on the impacts of tourism at the destination areas. ii. The study is also to find out if real world situations and perceptions on environmental impacts at the study areas are the same. A significant number of the environmental impact studies in the study areas do not consider the link between residents perceived impacts of tourism on the physical environment and the real world situations as obtained through laboratory analysis. Other external factors sometimes influence resident‟s perceived environmental impacts of tourism rather than the real world situations on the ground. Some of these factors are types and extent of interactions between host and guest, birth place and community attachment, length of residency, educational level and level of knowledge about tourism, level of management participation by residents of host community and level of community and tourism development (Amuquandoh, 2006;

Gursoy & Rutherford, 2004; Teye et al., 2002; Jurowski et al., 1997; Williams et al.,

1995; Lankford et al., 1994; McCool & Martin, 1994; Davis et al.1988; Madrigal, 1993;

Long et al., 1990; Keogh, 1990; Perdue et al., 1990; Allen et al., 1988; Allen & Gibson,

1987; Liu et al., 1987; Um & Crompton, 1987; Milman & Pizam, 1987; Sheldon &

Var,1986;). There is therefore the need for researchers to compare perception to realities on the ground to find out if there is any link. iii. Again, the study attempts to establish the link between environmental impacts and economic impacts. The studies that have been done on the environmental and economic impacts were done distinctively of each other with very little attempt by the researchers to find out if the environmental impacts of tourism do affect the economic growth of

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destination areas in any way. Since research works have established that there is a relationship between the environment and economic development, there is the need to determine the relationships that link environmental impacts of tourism to the economic development of the study areas. iv. As tourism develops, the local economic structure of the community may also change.

Associated with this is a change in needs and aspirations. This fact, coupled with the fact that most of the economic impact studies have been directed at international and national levels rather than district and local levels (BOG, 2007; Amoah & Baum, 1997), there is the need for continuous studies on the economic impact of tourism in the study areas.

This will also put to rest the constant debate of whether the residents of the host communities who put up with the perceived negative impacts directly reap any of the benefits from tourism. v. Finally, the study was to help identify the role that local residents play in the management (level of participation) of the tourism attractions in their communities.

Studies have shown that wholesale acceptance of tourism development by operators and state authorities without critically assessing it and involving members of the communities in the policy formulation and management of the industry eventually affect its smooth development. This study will help to establish the level of participation of the citizens in the management of the tourism facilities and make recommendation for improvement where necessary.

To this end, while all attempts are being made to develop tourism for its accrued benefits, there is the need to identify both the positive and negative impacts on the environment as

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well as its economic cost and benefits on resident of the host communities. Again, there is the need to establish relationships existing between the environment and socio- economic impacts. There is also the need for the development of an integrated tourism management plan, which will seek to take full advantage of the economic benefits of tourism development in the study areas whilst at the same time protecting the bio- physical environment upon which it depends.

1.3 Aims and Objectives This study aims to identify both the positive and negative impacts of tourism on the environment in some communities with tourist attractions at its initial stages of development in Ghana. It is also to assess the relationship between environmental effects and the economic activities in the host communities. To this end, the specific objectives of the study are to ;

1. Assess the effects of tourism on the quality of water that serve as tourist attractions

within the selected tourism destination areas.

2. Assess the effects of tourism on the economic activities of residents in these

destination areas.

3. Assess the relationship between perceived environmental effects and the real world

situations as obtained from laboratory analysis.

4. Identify the extent of linkages that exists between environmental effects and

economic activities in the study areas.

5. Determine the level of participation by community members in the management of

tourism in their communities.

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1.4 Hypotheses A number of studies have indicated that other extraneous factors usually affect residents‟ perception about the impacts of tourism (Long, 2006; Teye et al, 2002; Williams &

Lawson, 2001; Allen et al, 1993). For the purpose of this study, socio-demographic characteristics of the residents in the host community were used as the main variable to test for relations with their perceptions on environmental and economic impacts of tourism. Socio–demographic characteristics of residents of host communities were chosen because in communities that tourism development is at the early developmental stages, demographic characteristics such as age, sex, marital status and religions do not affect their responses to issues on tourism impacts (Wang et al, 2006). Based on the above, the following null hypotheses were tested.

 HO: Demographic characteristic of residents in communities around Wli Waterfalls do affect their perception on environmental impacts of tourism in their communities.

 HO: Demographic characteristics of residents in communities around Lake Bosomtwi do affect their perception on environmental impacts of tourism in their communities.

 HO: Demographic characteristics of residents in communities around Wli Waterfalls do affect their perception on economic impacts of tourism in their communities.

 HO: Demographic characteristics of residents in communities around Lake Bosomtwi do affect their perceptions on economic impact of tourism in their communities.

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1.5 Research Questions Despite the fact that steps are being taken to increase development of tourism in Ghana, very little has been done to ensure that destination communities do benefit from the industry. Based on this, the following should have been answered at the end of the study;

1. Does tourism have any impact on the bio-physical environment in the host communities? 2. Does tourism have any impact on the economic activities of the host communities? 3. Are perceived environmental impacts by residents and the realities on the ground from laboratory analysis the same? 4. What relationship exists between the environmental impacts and economic activities in the communities? 5. Is the level of participation in the management of tourism by residents of the host communities enough to encourage them to support its development? 6. Do the residents of the host communities perceive tourism as an industry that can

help better their economic livelihood?

1.6 Relevance of the Study The study has helped in generating more discussions among community members and stakeholders in the industry on tourism impacts through the identification of potential environmental and economic benefits and cost from tourism development. As a result, it may lead to the development of measures for mitigating tourism development challenges in these destination areas.

Again, it is the environment that serves as the attraction to boost the development of nature based tourism in developing countries like Ghana. However, if this same tourism development is not planned, executed and managed very well, it will turn round to

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destroy the very environment that is supporting it (Gartner, 1996; McCool & Martin

1994; Var & Kim 1989; Milman & Pizam, 1987; Liu et al., 1987;) The study therefore may help in establishing the relationship between environmental resources in these communities and tourism development and, how they can be managed to reduce the negative impact on the environment if any.

The water bodies used for the study serve as source of water for use by the residents in the destination areas as well as the tourists. With the increasing problem of shortage of water for rural communities, the study findings can support the search for collective effort to safeguard the quality of the water bodies available to these communities and the incoming tourists. In addition to ensuring the efficient use of natural resources (water) by different groups, the health status of these users would be protected. It may also help to reduce potential conflicts between the community members and the visiting tourists as have been observed in other destinations in the world.

Finally, the outcome of the study may also serve as a reference document to tourism operators, Metropolitan/Municipal/District Assemblies, and government agencies involved in the development of the tourism industry to help them put in place efficient and sustainable tourism policy that will take into consideration the needs and aspirations of the host communities as well as tourists. It is also to help managers of tourism facilities find ways of mitigating the negative effects of tourism whilst at the same time conserving the bio- physical environment so as to facilitate the sustainable development of the tourism industry in these destination communities.

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1.7 Summary The chapter, which is an introductory chapter focused on the background information to the study, the problem statement, aims and objectives, of the study, hypothesis, research questions and relevance of the study. The next chapter, which is Chapter Two, is on literature review.

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CHAPTER TWO

LITERATURE REVIEW

2.1 Introduction The chapter provides background information to the relevant theoretical and empirical literature used as well as the conceptual framework for the study. Researchers have focused considerable amount of research efforts and time to study on the positive and negative impacts of tourism on the environment and economy of host communities. This is attributable to the contributions that have characterized discussions on these impacts.

Most of the early studies were focused on the positive impacts of tourism and this made countries (especially developing countries) adopt it without serious assessment. Later on, studies have however have proven that the impacts of tourism are not as rosy as earlier studies have painted it and this has called for additional studies to help unravel the net impact of tourism within the destination areas.

This chapter is in two parts. The first section covered concepts in tourism as well as the impacts. This review has discussed some critiques on various view points on the concepts and impacts on tourism development in especially developing countries. The second section looked at theories on citizen‟s participation as they relate to tourism development and management as well as the conceptual framework for the study.

2.2 History of Tourism Development in Ghana Tourism as an industry in Ghana went through four developmental phases (Asiedu,

1998). The first phase preceded independence to about two decades after independence. It marked the beginning of direct government involvement in developing the sector. It was during this same time that the world chose the tourism industry as a vehicle for the

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development of third world economies in particular (Asiedu, 1998). It was characterized by expansion and enhancement of tourism facilities, especially hotels to accommodate foreign dignitaries who were coming for the country‟s independence celebrations.

Development of institutional capacities to manage the goals set for the period was among the greatest achievements of the era. This part ended about a decade after independence

(Asiedu, 1998; Teye, 1988).

It was followed by the second part of the first phase which spanned the period between

1972 and 1978. This era was characterized by numerous studies on the sector (Asiedu,

1998; Teye, 1988). According to Asiedu (1998), it formed the first major step in formal development of tourism in Ghana. It started with an evaluation of the country‟s tourism resources by the Obuam Committee in 1972. Its main objective was to catalogue and classify the potentials of tourism resources for a five–year development plan which will cover the period of 1972–1976. The then issued a white paper on it after which investment areas for foreign participation and incentives for investors were identified (Asiedu, 1998; Teye, 1988).

Others studies were on the socio-economic impact assessment of tourism by ISSER in

1973 (Bormann, 2012); tourism planning and development in Ghana by UNDP in 1973

(Singh, 1978); and review of human resource requirements for the tourism sector by

USAID 1973 (Stewart, 1973). The local component mainly dealt with foreign exchange earnings from tourism (Ghosh & Kotey, 1973); multiplier effects of tourism earnings

(Ayittey, 1975) and the socio–cultural impacts of tourism (Addo et al., 1975). Based on the above studies, it was concluded that Ghana had a potential to develop tourism and

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there was therefore the need to formulate a policy to guide a long – term sustainable development of tourism (Teye, 1998).

The above served as the basis for the development of the first National Long–Term

Master Plan of 1975–1990 which formed the beginning of the second phase (Asiedu,

1998). This plan was developed by the Hoff and Overgaad Consultancy Firm in 1974 with financial and technical support from DANIDA. With an annual projected growth rate of 12.5% for fifteen years, the plan laid emphasis on tourist assets and facilities in the country and human resource needs. It evaluated the potential of the country to develop its physical, cultural and historical resources for tourism development and proposed the development of beach resorts and the Dodi Island alongside national parks and historical heritage attractions which give the country a comparative advantage over other West

African countries. The plan divided the country into three tourism regions and suggested that development of tourism should systematically follow in that order. The regions are; i. Aflao – / coastal territory ii. The territory iii. Ashanti to the North territory

The implementation of this wonderful plan failed due to political and socio-economic instabilities encountered by the country. The rampant coup d‟ tats impacted negatively on the functioning of public institutions managing tourism as well as the in–flow of tourist into the country (Teye, 1988).

The third phase which spanned the period between 1990 and 2010 consisted of a fifteen- year tourism development plan was aimed at making the country a middle–income

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economy and the gateway to . Government adopted and implemented various policies that sought to portray the sector as one of the main engines of socio-economic growth (GOG, 1996). According to Asiedu (1998), it also positioned the tourism sector as a major driver of growth and development as evidenced by increases in public and private sector investments in tourism facilities which led to increase in employment and contributions to Gross Domestic Product (GDP). It was funded by the Government of

Ghana and UNDP in 1990 with technical assistance from UNWTO and the Ministry of

Tourism as the implementation agency.

The final phase which is also a fifteen-year development plan was to be implemented between 2013 and 2027. The plan mainly tries to assess how tourism can contribute to national, regional and local economic development. It is also to enhance the role of tourism as a leading sector for job creation, generation of revenue, protection and conservation of the environment as well as achieving national cohesion. Finally, it was to help achieve the core objectives of the Ghana Shared Growth and Development Agenda

(GSGDA) and Millennium Development Goals (MDGs). The plan was therefore prepared with the aim of positioning tourism very high in the national development agenda (GOG, 2012).

2.3 Tourism in Perspective: Definitions and Concepts Travelling has been part of man since creation and has been characteristic feature of the human society and lifestyle. The sporadic travels by the nomads in the earlier days have now turned into the world‟s most flourishing industry. Little did the nomads then know that their sporadic travelling will become such an important industry. Travelling at that time was rare and restricted to within a geographic area (Pran & Sushma, 2003). This

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however started to change a little over ten thousand years ago when man invented the wheel and fixed it to his carts and chariots. With animals pulling the carts and chariots and giving him speed and comfort, men began to travel long distances. This was however, restricted to the rich and powerful in society (Pran & Sushma, 2003).

A lot of reasons have been given for people travelling but the most important one as far as tourism is concerned is to seek excitement (Ghosh, 2000). The level of satisfaction derived from travelling however, depends on factors such as age, health, education and status in society. The younger and more educated travel more than the elderly and less educated. In the same way the rich travel more than the poor (Ghosh, 2000).

The nature of tourism makes its definition very difficult. Tourism is a phenomena that involve so many products and services that complement each other. Pran and Sushma

(2003) defined tourism as “people travelling for pleasure or on business, staying in hotels and spending their hard–earned money at places where they do not normally reside or make a living”. This definition did not take into consideration those who will stay at the place for less than twenty–four hours and as a result may not sleep in a hotel. Wahab

(1975) on the other hand gave tourism a generic definition by saying “it is a purposeful human activity that serves as a link between people either within the same country or beyond the geographical limits of a state” This definition involves the satisfaction of varied needs other than exercising and remunerated functions.

Kamra and Chand (2006) citing Hunziker and Krapf (1942) offered a more technical definition of tourism as “the totality of the relationships and phenomena arising from travel and stay of non–residents, provided the stay does not imply the establishment of a

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permanent residence and is not connected with a remunerated activity". It is clear that this definition rest on the assumption that it ought to incorporate both travel and stay, thus excluding day tours and excursions. Another issue of importance in this definition is the proposition that tourism should not lead to permanent residence in the country/area of destination visited. This makes tourism a different entity from migration and rule out business travels on the count that tourism is not expected to relate to any earning opportunity at the destination area.

While there has been some sort of general consensus on the technical definitions of tourism or tourist, the general and/or wider concept of tourism still remains elusive or rather is vague and lacks clarity. Tourism as such does not have real objectives, precise and independent existence that is waiting to be discovered and described. To some extent, tourism can be seen as what the individual describing it wants it to be. The definitions above stress on moving away from one‟s normal place of residence. The problem has been whether the emphasis should be on the distance or purpose of movement. For the purpose of this study, tourism will cover the phenomena that arise from the travel of non– residents (including day tours and excursions) to areas of interest provided the stay does not imply the establishment of a permanent residence and is not connected with a remunerated activity.

2.4 Concepts/Elements of Tourism Definitions Based on the analysis of the definitions given above, the following elements of tourism can be identified: i. Movement– Tourism arises from the movement of people from one place to another.

This movement should be temporal and voluntary.

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ii. Stay/Time– Tourism involves the tourist staying at the destination for some time.

The duration should be more than 24 hours but less than 1 year. iii. Purpose– The purpose for the travel should be for educational, cultural, heritage,

business, health and recreational/leisure. iv. No Income Generation– There should not be any remuneration or income earning at

the destination. All money spent at the destination must be earned at the originating

country (Ghosh, 2000).

2.5 Types/Forms of Tourism According to Kamra and Chand (2006), there are two main types of tourism These are domestic tourism which involves the movement of people from one place to another within the same country and still satisfies the elements in the definitions above; and international tourism which involves the movement of people from one country to another (crossing of international boundary) and still satisfies the elements in the definition above. From the above, six forms of tourism may be identified. These are;

1. Recreational/Leisure Tourism: It is sometimes referred to as sun-sea-sand tourism.

The main aim of the type is pleasure. The tourist mainly seeks for change in

environment and rest. It is the type that a lot of people have in mind when tourism is

mentioned and it is most of the time organized on large scale. The

recreational/leisure tourist goes to experience things like the sea, sun and sporting

activities (Kamra and Chand, 2006). For example, moving from Europe to Ghana

during winter to enjoy sea and sunshine.

2. Cultural Tourism: This type of tourism is mainly to experience forms of cultural

activities. The tourists move from his permanent residence to another place to

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experience or take part in a new cultural activity such as music, drama, folklore

(Kamra and Chand, 2006). An example is the Blacks in the Diaspora coming to

Ghana to take part in our festivals.

3. Ethnic Tourism: This is the type that deals mainly with ethnic related issues. The

tourist travels from his/her usual place of abode to another place so as to come into

contact with unusual or quaint customs in mostly remote areas (Kamra and Chand,

2006). An example is the Blacks in the Diaspora coming to Ghana to visit the castles

or ancestral homes.

4. Historical Tourism: This type of tourism deals with the visiting of places of

historical importance to some people. These include places such as temples, churches,

mosques, museums and other locations of heritage (Kamra and Chand, 2006). An

example is a tourist moving from Ghana to St. Peter‟s Church in the Vatican.

5. Entrepreneurial/Eco Tourism: This type of tourism deals with the visiting of place

of ecological or environmental sites of interest. It is mostly practiced by the high

income groups in society. An example is the visit to Kakum National Park by people

residing outside Cape Coast (Kamra and Chand, 2006).

6. Adventure Tourism: This type deals with moving to another place for the purpose of

taking some adventurous activities such as mountaineering, trekking, paragliding etc.

It is mostly taken by the youth (Kamra and Chand, 2006). For example, the annual

Easter Paragliding at Atibie in the Eastern Region of Ghana.

2.6 Impacts of Tourism Impacts are a major element of tourism activities. The scope, effect and duration are complex and vary in terms of intensity. The variability of the impacts depends on the

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location, the level of its development and the environment in which the tourism activity operates. Impacts of tourism are mostly classified into economic, environmental and social/cultural effects (Page & Connell, 2006; Mathieson & Wall, 1982)

2.7 Economic Impacts According to Mathieson and Wall (1982), even though there are quite a number of research work on the economic impact of tourism, majority of them have been directed at the international and national levels. Peters, (1969), Gray (1970), Thuens (1976),

Vaughan (1977) and recent annual publications of WTTC and UNWTO all focuses on international and at best national levels. For years, planners and consultants had been predicting that tourism would grow to become the largest industry in the twenty–first century (Papson, 1979). By 1986, these predictions have been fulfilled with the world wide receipts of tourism estimated to be over $1.80 trillion. It has been growing at an average rate of above seven percent (7%) from then on. This has made it one of the largest sectors contributing over ten percent (10%) of the world‟s GDP (Hall, 2007;

Sharpley, 2000).

2.7.1 Economic Characteristics of the Tourism Industry According to Deliveli (2012), though tourism has been touted as the industry “without a chimney” that brings in the desperately needed foreign exchange, employment and other benefits to the destination areas (especially in developing countries). However some researchers have questioned the rational for regarding it as a single industry and comparing it with other industries (Wall & Mathieson, 2006; Leiper, 1979; Schmoll,

1977; Schneider, 1976). They argued that there are a number of unusual and unifying

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features of tourism which make it distinguishable from other single industries. Some of these features are; i. Tourism is an invisible export industry since no tangible product is shipped from

one place to another. It is among the very few industries in which the consumer

collects and consumes the services personally at where the product is produced.

Due to this, the exporting destination does not incur any cost in terms of freight

outside its boundaries unless the transportation facility used by the tourist is

owned by the destination which is very rare in developing countries (Leiper,

1979). ii. Goods & services that support the industry such as transportation facilities,

telecommunication systems, water supplies and sewerage systems, retail services

and many more are required by tourists at the destination area. This has to be

created, expanded or exported based on their availability and the nature and

magnitude of the tourist demand (Leiper, 1979).. iii. Tourism is a fragmented product, integrated with and directly affecting many

other sectors of the economy. Tourists in general use and consume a spectrum of

components which sometimes come from firms that are specialized in tourism

business and some from non-tourism specialized business firms (Wall &

Mathieson, 2006). iv. Tourism is a highly unstable product. This is due to the fact that it is strongly

affected by seasonal variations, pronounced and unpredictable influences from

external forces as well as heterogeneous nature of the tourist‟s motivation and

expectations. It is also highly elastic with regards to price & income. These

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factors combined promote low level of customer loyalty with respect to

destinations, modes of travel, accommodation units and travel intermediaries

(Wall & Mathieson, 2006).

Statistics from UNWTO (1991) indicates that tourism provides over ten percent (10%) of the world‟s income and employment. Many authors have emphasized on the positive aspects of tourism and refer to it as the “industry without chimney” that provides manna from heaven (Page & Dowling, 2002; Lundberg et al, 1995; Boo, 1990). As a result of the above, the tourism–development nexus has attracted the attention of researchers within the last three decades and the focus has always been on the positive impacts.

However, there are also a number of negative impacts of tourism to the destination areas which are not always considered by the pro-tourism advocates. However, de Kadt‟s work titled” Tourism: Passport to Development” shaped the thoughts to cover both positive and negative impacts on national and local economic development (Godwin, 2008; Harrison,

2008).

Wall and Mathieson (2006), also argued that the magnitude of the impacts of tourism on the economy of the host community is influenced by five factors. These are; a. The type of tourism facility and attractions for tourist b. The level and volume of spending c. The level of socio-economic development in the host community or country. d. The extent to which tourist spending is maintained and re – circulated in the host

community or country. e. The extent of seasonality of tourist visit to the host community or country.

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2.7.2 Positive Impacts Tourism has been identified as one of the largest and continuously developing sectors of most economies in the world. Benefits such as high growth and development rates, high volumes of foreign inflows, infrastructural development favorable balance of payments, revenue to the government, income generation and employment actively promotes economic growth of host communities and a country as a whole. Most highly developed countries such as Austria, France, Switzerland and some of the Caribbean states accumulated a big deal of their social and economic development on profits from tourism

(Lundberg et al, 1995).

2.7.2.1 Balance of Payments The balance of payments accounts for a country reflects the transactions of that country during a period of time between the residents of that country and the rest of the world.

Services such as tourism which is part of the invisible account aspect of the balance of payments are probably the most significant justification used by governments to promote tourism (Lickorish & Jenkins, 1997). Tourism‟s balance of payments of a country is the difference between the amount spent by foreign visitors and those spent by residents in foreign country and the result may either be a net surplus or deficient on the tourism account. The effects of tourism on balance of payment can be viewed from three angles.

These are primary, secondary and tertiary (Induced Secondary Effects) effects (Wall &

Mathieson, 2006; Airey, 1978).

Primary Effects: It refers to the actual tourist expenditures made by both foreign visitors within the country and residents of that country outside the country. They result in direct inflows and outflows of currency respectively. Primary effects only occur when tourist

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cross international boundaries. It is easy to measure because whatever the expenditure is on is recorded and reported separately (Wall & Mathieson, 2006).

Secondary Effects: A secondary effect which is more difficult to measure refers to the effects on the balance of payment on the direct tourist expenditure as they percolate through the economy. It therefore does not require the initial visitor expenditure to have taken place in another country. Secondary effects may be apparent in three different ways. These are;

Direct Secondary Effects – which covers expenditures on overseas marketing, visible imports, commissions to travel agents, outflows in the form of interest and dividend payments to overseas investors and airline operator disbursements on their crew overseas expenses (Wall & Mathieson, 2006).

Indirect Secondary Effects – covers earnings from initial tourist services which is passed on to other suppliers of goods and services whose production depends upon a supply of imported goods. The purchase of these goods requires an outflow of currency from the home country (Wall & Mathieson, 2006).

Induced Secondary Effects – which is the third type, covers wages, salaries and rents that are used on or remitted abroad by a labor force that are of foreign origin. (Mathieson

& Wall, 1982)

In most developing and some developed countries, earnings from tourism help reduce and occasionally eradicate balance of payments deficits. This has been the case for countries such as Italy, Spain, France and the USA in the developed world and Bahamas,

Fiji Islands, Thailand, Kenya and South Africa in the developing world (Page & Connell,

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2006). For example, the USA, Spain, Italy and France had a net surplus of 37.2, 19.7,

14.3, and 12.1 billion dollars respectively on their tourism accounts whilst Germany,

China and Japan had a net deficit of 45.5, 24.1 and 11.9 billion dollars respectively in

2011 (UNWTO, 2012).

2.7.2.2 Employment Even though, there has been a considerable debate as to the role of tourism in employment generation, some authors are of the view that tourism helps in the generation of employment in the host communities. According to Elkan (1975), employments generated at tourism destination areas do have some common features. A few of these are;

i. Even though not perfectly related, employment and income generation in the

tourism industry are casually related they are not necessarily of equal size or

created at the same time. Income and employment multipliers are not the same and

the maximization of income does not necessarily mean there will be a

correspondent maximization of employment in the industry at the destination area. ii. The effects of tourism on employment are influenced by the type of tourist activity

taking place at the destination region. Activities like provision of accommodation

facilities and other services such as hotels, quest houses, bars, cafeterias and

restaurants provides more employment opportunities than other sectors of the

tourism activity. Elkan (1975) noted that for every hotel bed in East Africa, 0.8

persons are employed. He elaborated this by saying that within a span 10 years,

whilst employment in the hotel industry increased by 111% and that of cafes, bars

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and restaurants increased by 147%, increases in the attractions and transportation

sector were only 52% and 31% respectively. iii. Another feature of tourism on employment which is sometimes used by critics of

tourism against it is the type of skills needed for the job and the ratio of the labor

force. The tourism sector requires large number of workers with minimal skills. It

creates few jobs at the managerial and professional levels and these are often filled

by people from outside the destination area. Again, due to the fact that a large

chunk of the jobs created by tourism are seasonal and involves janitorial work,

housekeeping, food and beverage preparation and serving in bars and restaurants,

majority of employees are women. It is estimated that about 75% of all employees

in the tourism sector in the Caribbean are women with remaining 25% being men

with most of the managerial positions going to them (Yang, 2005)

iv. Another feature is that a considerable number of employments in the tourism

industry are disguised. As a result, it is very difficult to calculate the real impact

of tourism on employment. In creating employment, tourism sometimes take

people from other sectors of the economy or employ people who are not

considered as part of the labor force. Impact of tourism usually goes beyond the

destination area. As a result, employment may be created outside the destination

areas, but most of the time, these are not included when discussing employment

in the sector. Some of the positions are filled also by part time workers so it is

very difficult to place them in the equation when statistics on employment are

being calculated.

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v. Finally, a high percentage of jobs in the tourism sector are seasonal and normally

contributes to the high levels of fluctuations in employment at the local and

regional areas. The seasonality therefore attracts only part time job seekers such as

students and house wives. Archer (1978) cited an example of Anglesey where

additional 800 workers are recruited every summer to meet the demands of tourist

in the accommodation, services and attractions sectors of the industry.

Page and Connell (2006), describing the benefits of tourism postulated that tourism generates three (3) types of employment. These are;

 Direct employment – jobs created as a result of visitor expenditure and direct result

of tourism activities eg. Hotel staff and tour guides.

 Indirect employment – jobs created within the tourism supply sector but not as a

result of direct tourism activities eg. Construction workers building a hotel.

 Induced employment – jobs created as a result of tourism expenditure as local

residents spend money earned from tourism eg. traders

Tourism is said to be the largest employer in some tourism developed countries such as

Bahamas. Though it is very difficult to estimate the number of employments in the industry due to its multi–sectorial nature, research has proven that tourism generates quite a number of employments. Jones and Pizman (1993) estimated that tourism employed over 16 million people directly and indirectly in Western Europe alone in 1992. By 1992, over 84000 people in United Kingdom were directly or indirectly employed by tourism.

By 1996 this figure has increased by about fifteen percent (Lickorish & Jenkins, 1997;

Brooke, 1996). An attempt by UNWTO in 1993 to quantify the future growth

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employment by the tourism industry between 2004 and 2014 estimated that over 11500,

4200 and 4000 job will be created in China, Indonesia and Mexico respectively in 2012 alone. According to Gosh (2000), in 1998, an estimated investment of one million rupee into the tourism sector created an average of 89 jobs in the hotel and restaurant sector alone, as against 45 jobs in agriculture and 13 jobs in the manufacturing sector. The ratio obviously increases when some ancillary services associated with hotels and restaurants are taken into account.

Several factors influence the patterns of tourism related employment at the destination areas.. While some forms of tourism such as farm tourism creates little or no new employments, resort development may create a variety of new jobs. Also, the number of locals employed in the tourism industry in an area depends on the local skills base. In most cases, the managerial positions are few and given to outsiders. The locals are mostly given the jobs that require minimal skills with low pay or little reward.

2.7.2.3 Revenue to the Government Revenue to government from tourism usually comes from both direct and indirect taxations. Direct taxation covers taxes on income from direct tourism employment, tourism and transportation companies as well as fees and charges on other services to the tourists. The indirect taxations covers taxes on custom duties and other charges levied on goods and services supplied by tourists, loan repayments and revenue from government owned or financed tourist enterprises.

Major sources of revenue to the government from the tourism sector are from direct taxation and customs duties. The basis for government to raise revenue through taxes from the tourism sector is rooted in the fact that, governments all over the world provide

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general services which benefit the tourism sector as well. For example communication, health, transportation and, water and sewage facilities, policing and other security services are all hidden investments which governments provide. They are termed hidden because, the facilities although benefiting tourism may not have been provided for the tourism sector but rather for general development purposes (Wall & Mathieson, 2006).

Lickorish and Jenkins (1997) however argued that over emphasis on direct taxation by countries on the tourism sector will affect price and drive away potential tourist and investors alike. Government should rather find alternative ways of raising revenue from tourism and this is usually through indirect taxes such as airport taxes, bed taxes and levies imposed on imported materials for the tourism sector.

Even though tourism can contribute substantial amount of money to government revenue, measuring it has always been a problem. One difficulty for example is defining the scope of tourism. Though many revenue contributions such as import duties can be derived from tourism induced transactions, they can as well be generated by other non – tourism transaction. Another difficulty is trying to identify the flow of revenue from the tourism sector. This may be due to the fact that, an increase in tourism activities may generate other economic activities which may also generate revenue to the government. Total revenue generated by the tourism sector to some countries exceeds 50% of the total revenue of that country. For example tourism alone contributed over 64 % of the customs duties for Bahamas in 1976 (Archer 1977) as well as about 15.5% of GDP to Cape Verde

(WTTC, 2013). It is estimated that tourism contributed about 1,972.8 billion US dollars

(2.8%) as revenue to the GDP of world economy in 2011. It was expected to rise by 2.8%

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in 2012 and then 4.2% per annum for the next decade to an estimated value of about

3,056.2 billion US dollars (WTTC, 2012).

2.7.2.4 Income The concept of multiplier effects has always been the basis for the discussion of the income effects of tourism. It has been very difficult to make any significant comparison between incomes arising from tourism related activities and those from other sectors. It is however, a fact that tourism related activities most of the time generate income in situ more than most sectors of the economy. This is because tourism which most of the time takes place in rural areas makes use of locations such as , jungles, beaches and other areas which have limited attractive economic use to the locals (Lickorish & Jenkins,

1997; Lundberg et al, 1995).

Johnston and Thomas (1992) noted that in many development countries, tourism generated incomes are often higher than average income levels. This may lead to a labor drift from the land or other sectors of the economy to the tourism sector. To control this, there is the need to increase wages in other sectors to prevent labor drift. For example, in some remote areas of Scotland such as the Hebridean Island, tourism helped to diversify rural incomes, thus sustaining these communities. Again, in the Lothian Region, out of

18.2 million pounds sterling tourist‟s expenditure in 1980, approximately 5.1 million pound sterling ended up with the local residents as income. The amount of tourist‟s expenditure that remains as income to locals increase as the area of measurement is extended (Matheson & Wall, 1982).

Employment and income effects of tourism are interlinked. One major importance of the two combined is that, they trigger multiplier effects. Income from tourism to local

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residents most often comes from wages and salaries paid to them as a result of employment they gain from tourism related activities. Employment in hotels, restaurants, attraction sites and travel and tour agencies are few of the areas that local residents get their income from (Archer, 1998).

2.7.2.5 Investments The scale of growth of tourism and its accompanied high infrastructure demands requires massive capital investments. The rapidly constructive vast resort areas with its corresponding growth in ancillary services in the Mediterranean, Caribbean and the warm–climate developing countries of Africa needed huge amounts of local and foreign capital investments. Governments, especially in developing countries encouraged investors to invest in the tourism sectors to reap some of the perceived benefits (Lickorish

& Jenkins, 1997). In 2011 alone, about 743 billion US dollars representing about 5% at all investment went into the tourism sector worldwide. It was expected to rise by 3.5% to about 769 billion U.S dollars in 2012. Out of this, about 26 billion U.S dollars representing about 3.5% of total world investment came to Africa (WTTC, 2013).

Wall and Matheson (2006), however, pointed out that massive capital investment in the tourism sector does not favor developing economies. This is because foreigners dominate the investments and owned most of tourism structures in most developing countries. This has resulted in high leakages in the economy of these developing countries, thus contributing to the disappointing economic performance of the tourism sector in these countries. Perez (1974) also gave two reasons why the capital investments of tourism in most developing countries are dominated by foreigners.

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a. The encouragement of foreign investment in the early stages of tourism development

due to high capital requirements of infrastructural and service facilities. b. The emergence of multinational corporations such as chain of international hotel and

restaurants, and tour operators which has the tendency to integrate the industry

towards both horizontal and vertical lines.

2.7.3 Negative Impacts A high percentage of studies that have been conducted on the economic dimensions of tourism places emphasis on the benefits rather than the cost of tourism. The little available literature on the cost also focuses on the direct cost of tourism, thus ignoring the indirect cost. Opperman and Chon (1997) and Martin De Holan and Phillips (1997) however argue that tourism has many hidden cost which can have unfavorable economic impacts on the host community or country. They listed opportunity cost, overdependence on tourism/lack of diversity, inflation, seasonality, leakages, high cost of infrastructural projects and little or no trickle–down effects of tourism earnings on the host community‟s economy as some of the ways through which tourism is a cost to the economy of destination areas (Cooper, 2012; Lickorish & Jenkins ,2006; Wall & Mathieson, 2006).

2.7.3.1 Opportunity Cost It relates to the time, efforts and money used in developing tourism at the expense of other developmental activities and/or investments. That is money used to develop tourism may not be available for other uses. This is a key issue for poorer countries justifying tourism development as a means of poverty alleviation because research have proven that sometimes it is detrimental to the poor in that community. This explains why some

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researchers have always proposed the integration of tourism into other social and economic strategies for development (Cooper, 2012; Lickorish & Jenkins, 1997)

Opportunity cost is extremely difficult to measure. It is the major reason why they are often ignored, resulting in the over emphasis on the positive impacts of tourism. To be able to measure opportunity cost in tourism accurately, it is necessary to describe and evaluate the opportunities which are to be forgone. Wall and Mathieson (2006) citing

Parks Canada (1997) noted that the establishment of a park in Newfoundland led to the curtailment of all forestry opportunities to produce fuel wood, pulp wood and sawn timber at the initial stages. From the national perspective, this was not a problem because they got the timber from other parts of the city. Local residents had serious problem since the establishment of the park resulted in a net loss of about 109,456 U.S dollars to the local community through replacement of fuel wood.

2.7.3.2 Over-Dependency on Tourism Heavy reliance on any single industry in any country (especially less developed) is a recipe for disaster in the long term and economic dependency on tourism is no exemption. Tourism as an industry is very volatile, price elastic and prone to changes in fashion and taste, seasonal in demand and political situations. Many tourists avoid destinations which are politically unstable, but do not cancel their holidays. They simply go for alternative locations and this always leads to a reduction in the patronage at these destination areas. Seasonality of the industry also leads to seasonal jobs and loss of income during the off or lean season (C ooper, 2012).

The economic downturn of some countries also affects the number of tourists that patronize some attractions and this affects earnings. In 2009 for example, Hawaii suffered

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a drastic downturn in tourist numbers due to the world‟s financial meltdown and this impacted negatively on the Island‟s economy and public services in terms of funding, tax revenue and employment. Again, the religious confrontations in Ireland were cited as responsible for the reduction in tourist arrivals in the 1980s. Another example is Arab-

Israeli wars of 1973 which also greatly affected tourist arrival in Israel. For example,

Israel recorded 74000 frontier arrivals in September of 1973 but this reduced to around

20000 in the following month with the advent of the war (Cooper, 2012; Page & Connell,

2006; Wall & Mathieson, 1996). Again, arrivals declined by more than 7% and 8% in

2009 and 2011 respectively due to the Arab Spring (Gordon, 2011).

2.7.3.3. Inflation Tourism development mostly creates inflation effects on local economies in relation to land, properties and goods due to high demand for these properties, goods and services

(Cooper, 2012). The spending power of tourist most of the time exceeds that of local residents. Retailers react to this by increasing their prices to make more profit or shift to the sale of goods that are highly demanded by tourist. This will eventually lead to the local community being unable to afford local housing or purchasing of local goods.

Inflation in destination areas can also be caused by increasing land values. Increased tourism activities usually create additional demand for land. Competition from investors in the tourism industry usually forces the prices of these lands to rise. When that happens, it increases the sources of income to operators in the industry such as owners of hotels, vacation homes and other tourist facilities (Lickorish & Jenkins, 1997).

Local residents are however, forced to pay more for their homes and larger taxes because of the increased land value. The end result is that it may lead to "enclave tourism" in

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which goods and services provided are too expensive for the local residents, or these goods and services may not be those that the residents need. This has been a big problem in the English Lake District and Snowdonia National Parks where externalities of tourism as an activity has become evident as residents suffer from additional traffic queues for services and competition for local goods (Cooper, 2012; Wall & Mathieson, 2006;

Lickorish & Jenkins, 1997; Page & Connell, 2006).

2.7.3.4 Seasonality Seasonality is one of the major disadvantages of tourism as an economic activity on the destination area. Even though the peak season may bring the opportunity to generate enough revenue, it is for a short period. The revenue must therefore be sufficient enough to allow an income which will support individuals and the economy throughout the year.

It also means that the investments made in tourism business is idle for some part of the year. The seasonality of the industry in most tourism regions is manifested in hotel occupancy rate. In these areas, some hotels actually close down during the off season while those who still operate experience reduced revenue. Since the investments are not fully utilized during the off season, returns on capital are often low. This makes tourism less attractive to invest in than other sectors of the economy which most of the time experiences steady production (Page & Connell, 2006, Lickorish & Jenkins, 1997; Wall

& Mathieson, 1996; Archer, 1978).

The problems faced by tour operators are almost the same those faced by hoteliers. This has resulted in foreign investors not willing to invest in the marketing of tourism in many developing countries. The locals who do so also do it at a greater risk than those in the other sectors of the economy which may offer more attractive returns. The best way to

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solve this problem is for the public authorities in these developing countries to take over the running of such investments (Wall & Mathieson, 2006).

2.7.3.5 Leakages Tourists are short term-stay visitors who come along with certain expectations relating to the good and services provided them. Very few developing countries have the capital and human resources and means to supply and satisfy these needs. These developing countries therefore resort to the importation of goods and services, and the payment for these imported goods are referred to as leakages (Page and Conwell, 2006). The end result is that, residents of destination areas do not benefit from the foreign exchange generated by tourist‟s activities in most developing countries. It is the foreign investors in the shape of multinational corporations which control these tourist facilities that receive substantial proportions of tourist spending. Page and Conwell (2006) and Lickorish and

Jenkins (1997) postulated that leakages may occur through;

. Repatriation of profits generated from foreign capital investments . Not sourcing goods and services locally . Payment of holidays made in generated countries . Foreign ownership of transport services such as airlines.

According to Lickorish and Jenkins (1997), least developed countries and more open economies have a greater propensity to experience high leakages in tourism activities.

Less developed countries lack majority of supporting industries needed to make tourism more viable and therefore imports more of goods and services needed to improve upon the available facilities.

Martin De Holan and Phillips (1997) recorded that almost 90% of tourist facility development in the coastal areas of Belize is in the hands of foreign investors and that 45

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about 75% of earnings on tourism from Cuba is leaked out. Opperman and Chon (1997) also found leakage rates of between 27 and 38% in Singapore. Fletcher and Snee (1989) also noted that for every dollar that is spent in the Pacific Island of Palau, 53% of it leaks out of the Island‟s economy.

In areas where the leakages rate is high, the multiplier effects of tourism cannot develop to the full potential as most of the tourist revenue filters out of the destination region. It is therefore necessary for destination areas to try and limit their imports and to substitute it by domestic production. Encouragement of domestic production will not only reduce the leakages but also generate revenue and income to residents of destination areas.

2.8 Environmental Effects According to Wall and Wright, (1977), even though research on environmental impacts of tourism have been going on for some time now, concrete literature does not exist on it because it is very difficult to ascertain these impacts. This difficulty has come about as a result of the following reasons;

In the first place, man has been living on and modifying the earth for a longtime. It is therefore very difficult to reconstruct the destroyed part so as to get a baseline against which a measurement can be compared to.

The second difficulty arises from the inability of researchers to differentiate between changes induced by pre-existing process and those induced by influx of tourist (Hunter &

Green, 1995; Wall & Wright, 1977). There is no doubt that the provision of tourism development projects such as resort landscapes, construction of access roads, tourist attractions and other facilities such as hotels, hospitals, telecommunications and many

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others may lead to a change in the environment. The problem is that the local community may also be using these same facilities. It is therefore very difficult to attribute these changes to tourism alone.

The third difficulty comes from the complex interactions of the tourism phenomena, making total impacts almost impossible to measure. Many of the impacts of tourism are manifested in subtle ways with primary impacts for example given rise to secondary and tertiary impacts which may generate a myriad of successive repercussions that are partially impossible to trace and monitor.

The fourth difficulty stems from the spatial and temporal discontinuities between causes and effects. For instance, erosion in one location may result in deposition elsewhere and destruction of key elements of an animal‟s habitat may lead to population decline throughout its range. A considerable time may elapse before the full implications of an activity are apparent. This makes it very difficult to establish both temporal and spatial constraints for proper undertaking of environmental impacts studies. (Wall & Mathieson

2006; Wall & Wright 1977).

The fifth problem arises from the fact that the most studies on environmental impacts of tourism concentrate on one particular component of the environment. The components of natural environment are however, closely interrelated and highly interdependent. As the activities of tourism are likely to affect more than one environmental component at a time, it is imperative to examine the environment as a whole and not individual component in isolation. In practice, this is extremely difficult to do.

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Finally, research on the impacts of tourism on the environment is topically uneven and is particularly sparse on air, soil, and water quality.

The environment has variously been defined to include not only land, air, water, flora and fauna, but also encompasses people, their creations and the social, economic and cultural conditions that affect their lives (Lerner, 1977). This discussion however adopts a more narrow focus by restricting it to the physical impacts which includes both the natural and man-made environment. The environment being natural or man-made is one of the basic resources for tourism growth. However, the growth of tourism leads, inevitably to changes in the environment.

The history of tourism growth and development indicates that the environment of destination areas has been the major element in this growth and development. Majority forms of tourism depend upon the environment and its quality for their resource base and attractions. Scenic sites, amendable climate, and unique landscape features have served as attractions that exert some form of influence upon the patronage of specific communities

(Cooper, 2012, Wall & Mathieson, 2006). There are however, some positive and negative effects of this patronage on the environment. Some of the positive effects of tourism on the environment are discussed below.

2.8.1 Positive Impacts Most literature on environmental impacts of tourism captures the „hotspots‟ of conflict between tourism and the environment. However there is clear evidence that tourism if well planned and controlled can help maintain and improve upon the environment in many ways (Cooper, 2012). Cooper (2012) and, Lickerish and Jenkins (1997) listed the following as a few of the positive environmental impacts

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i. Conservation of Important Natural Areas: Some natural areas such as forest,

wetlands etc. that might have deteriorated naturally or as a result of anthropogenic

activities are conserved and justifiably paid for by tourism ii. Conservation of Archaeological and Historical Site: Tourism growth and

development provides incentives for the conservation of some archaeological and

historical sites such as castles and tombs which might have naturally deteriorate

or disappear. iii. Improvements of Environmental Quality: Tourism most often provide the

incentives for “cleaning up” the overall environment through the control of air,

water, land and noise pollution, as well as improving environmental aesthetics

through landscaping programs, appropriate building design and better

maintenance. iv. Improvements of Infrastructure: Infrastructure such as airports, roads, water

and sewage system, telecommunication and health facilities of host communities

are often improved upon for the smooth development and growth of tourism. This

provides both environmental and economic benefits.

2.8.2 Negative Impacts However, there is current and growing concern about the impact that some forms of tourism development are having on the environment. There are examples from almost every corner of the world, where tourism development has been identified as being the main cause for environmental degradation in that area (Lickorish & Jenkins 1997).

Destruction of flora and fauna, water and air pollution, destruction of geologic and photographic features as well as negative impacts on other ecosystems (coastlines,

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inlands and mountains) and man-made environments are a few of the negative effects of tourism on the environment.

2.8.2.1 Tourism and the Vegetation Vegetation is one of the attractions tourists go to visit. Even though there are numerous documented impacts of tourism on vegetation, the dominant consequences of tourism on the vegetation is through a process of trampling while visitors walking in the forest or brushing past vegetation crush and damage it (Cooper, 2012, Wall & Mathieson, 2006).

In the first place, trampling compacts soils and this make it difficult for new seeds to germinate. This may lead to extinction of fragile plants. Again, trampling may lead to the death of soil organism and flooding, resulting in decline of soil fertility. This may affect the growth and development of sensitive plants leading to a decline of species diversity.

Trampling also makes it difficult for replacement plants to grow and establish well.

People passing by accidentally knock off flower heads and buds to exacerbate the process. Re-establishment is particularly more difficult in harsh environments such as the mountains, and sand dunes and coastal areas.

Other activities of tourism that affect the vegetation include changes in species composition as a result of plants, flowers and fungi collection by tourists; careless use of camp fires in parks leading to fire outbreaks in forested regions such as California in

USA and Tasmania in Australia and the deliberate chopping of trees for carving, tents poles and firewood during camping leading to deforestation. This has removed especially younger trees from forests which alter the age structure of the plant community. Again, excessive dumping of garbage in parks and attraction sites is not only unsightly but also

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changes the nutrient status of the soil, thus affecting the growth and development of some plant species.

2.8.2.2 Tourism and Wildlife Wildlife has become a major resource for tourism, not only on land but also in aquatic environment. The hunting, viewing and photographing of wildlife, scuba diving on reef as well as swimming with dolphins and visiting loggerhead turtle nesting sites are a few of tourism activities that affect wildlife. Tourism activities may have intentional (direct) or unintentional (indirect) effects. Tourism activities such as poaching and hunting do have direct effects on wildlife while other activities such as observation may have indirect effects (Cooper, 2012; Lickorish & Jenkins, 1997; Mathieson & Wall, 1982).

Direct Effects: The direct effects of tourism activities on wildlife depends largely on the level of tourism development, resilience of the species involved, the ease with which they are able to adapt to the change and the presence of tourists. It must be noted however that the ability of wildlife to withstand an influx of tourists varies from species to species and region to region. Disruption of feeding and breeding patterns of animals as a result of tourists trying to photograph the critical point of preying and mating also affect wildlife.

Myers et al (2000) claimed that the close shadowing of lions by tourists in the Safaris of

Africa leads to many missed kills with the result that many lion cubs were being starved.

Killing of wildlife through indiscriminate hunting and fishing, as well as accidental killing of animals also affect the feeding and breeding habits of wildlife

Indirect Effects: In most cases tourists do not intend to harm wildlife with their activities. These activities are however those that affect wildlife most. This includes the changing of existing habits of animals like bears that now prefer to feed on garbage

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around campsites instead of moving into the wild, demand for animal souvenirs which leads to the capture and killing of animals as well as disruption of migrating, breeding and feeding patterns due to the development of tourist infrastructure. Martuka (1974), noted that both grizzly and brown bears in the Glacier National Park have been attracted to camp sites to feed leftovers by tourists. This has led to an increase in the frequency of human interactions with bears resulting in increase injuries to tourist by the bears.

2.8.2.3 Tourism and Water Pollution Good and quality water is one of the basic resources that tourism needs in its development. Activities such as swimming, fishing and boating as well as usage of water by tourists which require the availability of high quality water also pollute the water bodies. In areas where proper sewage disposal systems have not been installed for tourists to use, pollution of ground water from the sewage may occur. Also, the presence of cruise ships in the Caribbean is known to have led to the deposit of large amounts of waste into the ocean annually. Many water bodies are also getting polluted with oil due to the presence of outboard motors on canoes and other forms of boats being used by tourist for water sports (Cooper, 2012). Wall and Wright (2006), also listed the following as the major effect of tourism on the quality of water. i. Pathogens are introduced into the aquatic environment in raw or inadequately

treated sewage. This pollutes the water body and becomes a potential health

hazards to both the tourist and residents of local communities. ii. The addition of nutrients to the water bodies from sewage may hasten the process

of eutrophication which will lead to a reduction in the availability of dissolved

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oxygen in the water body. It is the dissolved oxygen that governs fish numbers,

species composition and growth rates. iii. The presence of oil in water from recreational vehicles, cruise ships and boats

reduces the availability of oxygen in the affected water body. This has detrimental

effects on aquatic plant and animal life. iv. Lead compounds from petroleum products used by vehicles and outboard motors

as well as other trace elements from decomposing tins and bottles left behind by

tourist all affect the quality of water bodies.

Tangi (1977) postulated that accumulated impacts of the tourist‟s activities may pollute the water body so much that it will reduce tourist satisfaction in the use of the water bodies as well as disturb the life style of local community. He noted that occurrence of diseases such as cholera, typhoid; viral hepatitis and dysentery have increased in some rural communities of Thailand due to the presence of tourists.

2.8.2.4 Tourism and Man–Made Environment Most researches erroneously assume that the basic resources of tourism are predominantly natural attractions and that environmental impacts are basically due to excessive patronage of the resources. However, without the development of other tourist facilities and infrastructure such as resorts, hotels, roads and health facilities, tourist would not be sufficiently satisfied to continuously patronize the attraction. One of the most obvious environmental effects of tourism is the development of these facilities and infrastructures. The failure to integrate resort infrastructure with aesthetic character of the natural environment (architectural pollution), sprawl development of coastal resorts and hotels along beaches (ribbon development and sprawl); overcrowding of infrastructural

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facilities and traffic congestion, the clearance of vegetation for roads and other constructional activities that disrupts wildlife and reduces soil fertility and pollution of rivers and lakes are few of the environment problems associated with resort and hotel facilities. Some physical environmental impacts induced by tourist facilities and infrastructural development include encroachment on residential and farm lands, destruction of historical structures due to excessive patronage of the structure and destruction of the natural topography of the land (Cooper, 2012; Lickorish & Jenkins,

1997; Wall & Mathieson, 1982).

2.8.3 Reducing the Negative Environmental Impacts of Tourism According to Lickorish and Jenkins (2006) as well as Gunn (1988), using the environmental planning approach, before development is one of the best ways to reduce, if not eliminate some negative impacts of tourism on the environment. The planning which must take place at all levels – national, regional and site specific should be in a comprehensive manner and be integrated with the overall planning of the area.

Inskeep (1991) and Jenkins (1991), state that the environmental planning approach follows almost the same process which is used for development planning. Emphasis is however, placed on the construction of physical events, economic, social and cultural requirements. Jenkins (1991), went on to list establishing development objectives; survey of existing situations; analysis or synthesis; plan formulation; recommendation and implementation as the procedural steps for developing an environmental planning approach . i. Establishing Development Objective: The basis for the planning approach

should be the general objectives for developing tourism at the destination area.

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Such objectives are considered as temporal until they are integrated with others

and are observed to be compatible with them. For example, an environmentally

oriented objective often include developing tourism in such a manner that no

serious negative impact results, and using tourism as a means of achieving

conservation objectives. ii. Survey of Existing Situations – This involves a survey to collect data on existing

characteristics of the area chosen for the project. For a beach resort for example,

data would be collected on climatic condition of the area, land and under water

topography of the area, extent and quality of the beach, near–shore current flows

and erosion. Anthropogenic features such as historical and existing land use,

settlement and infrastructural patterns, cultural and archeological sites, land

tenure systems, existing development plans for the area as well as other socio-

economic characteristics of the residents of the community. iii. Analysis or Synthesis – This involves the interrelated analysis of several issues

such as market analysis and alternative projections of number and types of tourist

expected, accommodation and other tourist facilities needed, types of tourist

attractions to be developed, and the type of transportation and services required.

Environmental characteristics are also analyzed to determine the carrying capacity

of the area, environmental impacts of alternative types of tourism development

and how best the development project fits into the area‟s overall environmental

policy. iv. Plan Formulation – This involves the process of formulating alternative plans

and evaluating these plans to determine how well they meet the development

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objectives. The best plan or combination of alternative plans is then selected and

refined to become the final plan. A detailed environmental impact assessment

should be made of the final plan. v. Recommendations – Recommendations or mitigation measures are prepared and

put in place for all aspects of the planning program. vi. Implementation – Implementation based on the already formulated plan then

starts, making use of the various techniques such as organizational, marketing,

legal and financial (Jenkins, 1991).

In some countries, environmental auditing is increasingly becoming one of the procedural steps even though it is by no means a general practice. This may be due to the fact that most governments have not made it mandatory. Governments all over the world are however, becoming more concerned for the environment and it is expected that legislation will be used to enforce the performance of environmental auditing.

2.9 Concepts and Theories of Participation “Citizen Participation” or “Citizen Control” has been a topic that has been involved in heated debates for decades. Everybody seems to think that it is good but defining and practicing it is what creates the problem. According to Arnstein (1969) the idea of citizen participation is like eating spinach: no one is against it in principle because technically it is good for you. After all participation of the governed in their government (in this case, management of resources), in theory is a revered idea that is vigorously applauded by virtually everyone. Support for it however reduces to polite hand claps when this principle is asked for by the poor owners of the resource. Connor (1988) also said that citizen participation is a splendored thing with a price to pay. The problem arises when its

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many and diverse practitioners start to discuss alternative approaches to the issue. "The result sometimes resembles the Tower of Babel, with all the busy builders quite unable to communicate with one another".

Participation has become a key consideration in the discourse and practice of environmental policy–making at local, regional through to international levels (Collins &

Ison, 2006). Although impetus for participation and stakeholder movement has increased over the years, the desire and capacity for critically engaging with the methods and the grounds of knowledge of participation has perhaps lagged. Research now is focused on developing better techniques, tools, and mechanisms for participation (OECD, 2001).

Researchers such as Shier (2009), Tritter and McCallum (2006), Bishop and Davis (2002) have all done some work on participation For the purpose of this work however, “A

Ladder of Citizen Participation” (Arnestein, 1969), “A New Ladder of Citizen

Participation” (Connor, 1988) and “Dare We Jump Off Arnstein‟s Ladder? Social

Learning as a New Policy Paradigm” (Collins & Ison, 2006) would be reviewed.

2.9.1 A Ladder of Citizen Participation Sherry Arnstein was the first to come out with elaborate document on participation in

1969 with the title “A Ladder of Citizen Participation”. She used three federal social programs: urban renewal, anti-poverty campaign and model cities as examples to throw more light on that “heated controversial topic”. Even though citizens participation have variously been buried in phrases like “self –help”, “citizen involvement" and "absolute control"; she classified it as “citizen power”. That is, the redistribution of power that enables the "have not" citizens, presently excluded from the political and socio-economic processes to be deliberately included in the future. She went on to state that it is the

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strategy by which the "have not" do join in determining how information is shared, goals and policies are set, tax resources are allocated, programs are operated and benefits like contracts and patronage are parceled out (Arnstein,1969).

The typology which was designed by her to be provocative is arranged in a ladder pattern with each rung corresponding to the extent of citizens‟ power in determining the role that the citizens play in the plan and/or program (Connor, 1985). The eight rung ladder starts from manipulation through therapy, informing, consultation, placation, partnership, delegated power to the apex which is citizen control. She argued that the first two rungs on the ladder represent non participation, the third, fourth and fifth rungs on the ladder represent some degrees of tokenism, with the remaining three representing degrees of citizen power.

2.9.1.1 Characteristics of the Illustrations Manipulation– Under this rung of the ladder, people in the name of citizen participation are placed on rubberstamp advisory committees/boards for the purpose of educating them or engineering their support. The bottom rung of the ladder signifies the distortion of participation into public relations vehicle by power holders instead of genuine participation. The major function of the advisory committee/board is to educate, persuade and advice the citizens not to kick against or reverse official programs or policies. They do not have any legitimate power or function. They are only used to prove that the “grass root people” are involved in decision making, even though the decision may not have been discussed with the people.

Therapy– Within this rung is a form of group therapy often masked as citizen participation. It is both dishonest and arrogant. At this stage of the ladder, powerlessness

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is viewed as synonymous with some form of insanity. Officials therefore subject these citizens to clinical group therapy under the umbrella of involving them in decision making. Some researchers see this form of participation as very detrimental to reputation of the citizens because even though they are engaged extensively in activities in the community, the focus of these activities is on curing them of their “pathology” rather than tackling the root cause of the problem.

Informing– The first and most important step towards legitimizing citizen participation is informing citizens about their rights, responsibilities and options. The problem with this is that most often the emphasis is placed on a one-way flow of information. That is from officials to poor citizens without a channel for feedback information and power of negotiations. The most commonly used tool for the spreading of the information are news media, pamphlets and posters. Most of the time, the information is provided at the late stage in the planning and the citizens therefore have little opportunity to influence the program for their benefit. Sometimes, meetings are also turned into vehicles for the one way communication by the simple device of providing superficial information, discouraging questions or giving irrelevant answers.

Consultation– Inviting opinions and ideas from citizens just like informing them can be a very good step towards full participation of citizens. If it is however not combined with other modes of participation, it is more of a sham than reality since it does not offer any assurance that concerns and ideas raised by citizens will be taken into account. The most common methods used within this rung of the ladder are neighborhood meetings, public hearings and attitude surveys. Attitude survey which is most commonly used is not a valid indicator of community opinion when not used with other inputs from citizens.

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When the decision makers restrict the ideas of citizens at this level, participation remains just a window dressing process. Participation is only measured by how many poor citizens come to meeting, take brochures home or answer questionnaires. The end results is that citizens are deemed to have “participated in participation” while officials or power holders also achieve the evidence that they have gone through the required methods of involving the “poor citizens”.

Placation– It is the level at which citizens begin to have some degree of influences though it is still at the tokenism level. A major strategy used here is to handpick a few of the “worthy” poor citizens and place them on boards. The problem with this rung is that if the selected few are not accountable to a constituency in the community or if the traditional power holders retains majority of the seats, the representatives of the "have not" can easily be out-voted. In some cases too, they allow the citizens to advice or plan ad infinitum but the power to judge the legitimacy or feasibility of the advice given is retained by the power holders. The degree to which citizens are actually placated depends largely on two factors. These factors are;

1. The quality of technical assistance they may have in articulating their priorities.

2. The extent to which the community has been organized to press for those priorities.

It is worthy to note that most policies and programs of citizens participation is developing countries are at this level (Bishop & Davis, 2002).

Partnership - It is at this level of the rung that power is actually redistributed through negotiations between citizens and power holders. Here, power is shared through planning and decision-making. Structures such as joint policy boards, planning committees and

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mechanisms for resolving impasses are used. Ground rules that are established through some form of give and take are not subjected to unilateral change. Partnership works most effectively when there is an organized power base in the community to which the citizens‟ leaders are accountable to or when the citizen group has the financial muscles to pay its leaders reasonable honoraria as well as having the resources to hire and fire its own technicians, lawyers and community organizers. With these ingredients, citizens have some genuine bargaining influence over the outcome of the plan. That is, as long as both parties find it useful to maintain the partnership. It is worthy to note that in most cases where powers have been shared, it was not given by the power holder but rather wrestled from them by the poor citizen (Wilcox, 1994).

Delegated Power– This usually comes about from intensive negotiations between citizens and public official. The result is the citizens achieving dominant decision making power over policies and programs. At this point the ladder has been scaled to the point where citizens hold significant cards to assure accountability from officials. Power holders therefore need to start the bargaining process to resolve differences, but not the other way round. Another way of achieving delegated power is to create separate and parallel groups of citizens and power holders with the provision for the citizens group to veto if differences in opinions are not resolved through negotiations.

Citizen Control – It is when the have-not citizens obtain the majority of decision making seats or full managerial power. Though no one in a nation (not even the president) has absolute control, it is very important that the rhetoric is not confused with intent. Here people simply demand for that degree of power (control) which guarantees that citizens can govern a program or an institution, be in full charge of policy and managerial aspects

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and be able to negotiate for the conditions under which “outsiders” may change them. A neighborhood corporation with no intermediaries between it and the source of control is a very good example.

2.9.1.2 Limitations of the Typology i. In order to highlight the basic divisions between the powerless citizens and the

power holder, the ladder simply juxtaposes them. The truth however, is that

neither the power holders nor the poor citizens are homogenous blocks. Each

group contains a host of divergent points of view, competing vested interest

splintered subgroups (Yang, 2005; Wilcox, 1994). ii. The typology ignored the analysis of the most significant road blocks to achieving

genuine levels of participations. Those road blocks affect both sides and should

not be ignored that easily (Yang, 2005; Connor, 1988). iii. The eight rungs on the ladder are only theoretical and that in the real world, it

could be more than 150 with less sharp and pure distinctions among them. Again,

the characteristics used to illustrate each of the rungs could be used for the other

rungs. For example employment of the poor citizens in a program could occur at

any of the eight rungs on the ladder. (Yang, 2005; Choguill, 1986).

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Figure 2.1: The Eight Rungs Ladder of Citizen Participation

8 Citizen control

7 Delegated power Degree of citizen power

6 Partnership

5 Placation

4 Consultation Degree of tokenism

3 Informing

2 Therapy

Non Participation 1 Manipulation

Source: Arnstein (1967)

2.9.2 A New Ladder of Citizen Participation Connor (1988) in reviewing “the ladder of citizen participation” by Arnstein (1969) listed some problems (listed above) among others as the weakness against the theory. He went to propose a new theory known as “A New Ladder of Citizen Participation”. The typology used by Conner was also designed in the form of a ladder just as that of

Arnstein. The new ladder which was to provide a systematic approach to preventing and resolving public controversy over some specific policies and programs in both urban and rural settings was in seven rungs. Only one of the levels (consultation) appeared in the

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ladders of both Connor and Arnstein‟s theory. The seven rungs on the ladder of Conner‟s theory are education, information feedback, consultation, joint planning, mediation, litigation and resolution/prevention.

2.9.2.1 Characteristics of the Illustration Education - The foundation of any program to prevent or resolve conflict among the public is education. Proponents (power holders) cannot afford to have large chunk of their constituents being ignorant about the objectives, activities and effects of their proposed project or program. Most often, existing educational resources such as schools and public affairs media are often used because education actually calls for a long-term, low-profile and relatively low-cost program. The essence of education is to provide people with sound knowledge base before issues arises because once the anxieties and hostilities reach “fever” levels, educating those affected becomes impossible. In education, mutual understanding is essential. That is the proponents need to have a systematic appreciation of their various constituents just as the latter need knowledge of the proponent. Most often, when sound education is developed before the policy or project starts, it is accepted with open hand and this always leads to “prevention” (Lake,

1980).

Information Feedback – It is dissemination of information about proposal and at the same time solicits people‟s views on the proposals and its alternatives. This happens when the constituents affected by the proposal indicate that they do not understand and yet accept it. Formal and informal media channels such as reply-paid postcards and telephone hotlines may be used in collating the feedback information. Other techniques such as sample surveys and community and organizational profiles may also be used for

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the dissemination. This will help in acquiring accurate appraisal of what each party knows and believes about the proposal. Responds from such information–feedback may provide a clear and feasible solution to the issue which may result in reaching the resolution rung on the ladder straight away. Failure may force us to the comprehensive and powerful strategy of consulting with those that are affected (Conner, 1985; Hollings,

1998).

Consultation – It is applied when the first two rungs on the ladder fail to produce acceptable results and the gap between the current knowledge about a proposal as well as its acceptance seems to be too wide to be bridged by education and information feedback.

Consultation involves finding; i. Additional solutions to the issues than originally envisaged by the proponent. ii. Further potential evaluation criteria than initially contemplated. iii. Views of interested and informed people on the evaluation criteria. iv Technically sound and socio-economically acceptable alternative solutions.

Consultation is basically an advisory process because the power holder may accept or reject the views expressed by the public (citizens). The advantage however is that the issues have been brought to the fore and solutions to them may be found later.

Techniques mostly used for consultation include responsive publications, open houses, planning workshops, advisory groups and reference centers. Most often, more than one technique is used to achieve effective consultation. Effective consultation often leads to the resolution stage of the ladder. If that does not happen then we move on to joint planning.

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Joint Planning – When a party involved with a proposal has legal jurisdiction over some aspects of the affected area that party should go beyond mere advisory role to a partner in joint planning. Whenever the organizations involved are many, then it is better to work with them in the “one –window” approach. Involving highly-placed representatives of the various agencies in planning workshop and work through shared definitions of the situation brings about opportunities to maximizes creative solutions and minimize inter- organizational game playing. Most public programs and policies usually work at the three levels of information, feedback, consultation and joint planning process with relevant jurisdiction. The cumulative effect of the fore going approaches, may well accomplish resolution. If not then it means quite a number of issues have not been settled and therefore there will be the need to move to mediation.

Mediation – Even though it is based on the long traditions of labor-management applications, it has recently been used in resolving environmental and land use problems.

It is always considered the best option as compared to lengthy and costly legal actions. A neutral third party leads the two groups through conflict resolving processes, often resulting in compromise solutions. Mediation becomes inevitable when the conflict is mature and power is balanced between the two parties, and negotiation is seen by both parties as the obvious choice as well as the ability to reverse agreements later if it becomes necessary. In most environmental disputes however, all these conditions are always present. There are two types of mediators. They are;

(a). The Technical Expects who argued on the specifics of alternative solutions (b). The Behavioral leader who focuses on mutual acceptance and understanding among those involved.

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Mediation if properly done may lead to resolution which is at the apex of the rungs. If this does not happen then, there is recourse to the law.

Litigation – Despite the fact that this method has been criticized severally for its delay, cost and divisive nature, it still has a place in the management of citizen participation conflicts. The opportunity for legal solutions depends greatly on the jurisprudence operating in that community. The adversarial relationship inherent in a legal action often leaves both parties feeling antagonistic towards each other. Some kind of bridge building is done before resolution stage is reached.

Resolution/Prevention – Prevention may not only be accomplished by education alone but also by the public affairs technique of issue management or the application of consumer oriented marketing program. A major advantage of prevention in citizen participation is savings in time and cost of implementation. Others are as a result of better public consultation, better technical proposals; avoidance of negative image; and better relationship between the power holders and the poor citizens.

Resolution on the other hand implies an acceptance of the policy or project by most of the parties involved. Acceptance does not necessary mean full support. It may simply mean that it is the “least most” costly alternative available. Even though, it may be more costly and restrictive to power holders with a number of unwanted features in it, generally, it is accepted to be the better option than others which include the “do nothing” options. One basic requisite for effective resolution is the sense of equity among both parties.

Otherwise the agreement is likely to fall apart during or after implementation.

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In conclusion, The Ladder of Citizen Participation provides the power holders the numerous approaches available to them in resolving conflicts on resource utilization. The implication is that; i. There is no single best way of managing citizen participation programs and that the

given situation decides which one to use. ii. There is a cumulative relationship between the rungs on the ladder and that each

successive rung builds upon the previous one. iii. Depending on the issue at hand, several approaches will be used simultaneously to

satisfy both parties. iv. Finally, complex environmental, socio-economic an socio-cultural issues will not be

resolved by mere news release or public meetings, but rather, a systematic process

appropriate for the situation (Conner, 1988).

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Figure 2.2: The New Ladder of Citizen Participation

RESOLUTION/PREVENTION

LITIGATION

MEDIATION LEADERS

JOINT PLANNING

CONSULTATION

INFORMATION FEEDBACK GENERAL PUBLIC

EDUCATION

Source: Connor (1988)

2.9.3 Social Learning as a New Policy Paradigm Collins and Ison (2006) in reviewing Arnstein (1969) suggested that due to the numerous problems with the “Ladder of Citizen Participation”, a new theory, the “Social Learning

Theory” should be adopted as a new policy paradigm to form the basis for citizen participation.

Even though the communities do have representatives on the committees that manage the tourism resources, they seem not to be happy with that arrangement and are demanding

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for some degree of power which guarantees them the authority to take full charge of policy and managerial aspects of tourism activities in the communities. In cases where the livelihood of the residents of communities such as that of the study areas depends largely on the same resource that serve as attractions to the tourist or the development of tourism may lead to the losses of economic activities, then the issue of management of the resource become relevant. If the community members are not allowed to participate in the management of the resource or their level of participation is not acceptable to them, then their level of support for the development of the tourism industry may be very low or not existing at all. An eloquent testimony of this is the low support for tourism in the

Cape Coast – Elmina area which was linked to the failure of the project implementer to involve the chiefs and people of the area in the early stages of tourism development in the area (Teye et al., 2002).

The social learning concept has widely been used within the last decade in the study and management of complex and multiple stakeholder resources such as water catchments.

The European Union in the early part of the 21st established the Simpler Legislation for

Internal Markets (SLIM) Project which set out to explore the extent to which social learning could be used to promote concerted action among users seeking to manage water catchments in a more sustainable manner. This was done through a series of case studies in several European Union countries (Environmental Science and Policy, 2007; Collins &

Ison, 2006). The social learning approach for managing water catchments is based on the idea that sustainable and regenerated water catchment are emergent property of social process. That is, the things that are considered as desirable water catchment properties arise out of interaction and constructing issues such as sharing problem definitions,

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negotiations, conflict resolutions, learning, agreement, confronting power asymmetries and, concerted actions among multiple and interdependent stakeholders (Finger &

Verlan, 1995).

Social learning has some advantages that make it a preferred option over the other models. Among these are; i. Strategic reasoning for concerted action, a hallmark of social learning is a

requirement for sustainable management or regeneration of water catchments that

requires changes in behaviors of stakeholders in the catchment area. This is

because water catchments are messy situations and therefore focusing on social

learning rather than participation might open up new insight into the kinds of

roles, relationships and sense of purpose leading to accommodations between all

stakeholders (SLIM, 2004a). ii. A social learning approach provides a context for a dynamic local decentralized

process, and to some extent, a concerted parallel local process in the case of large

watersheds. It is therefore a complementary policy approach but is somehow

significantly different in its epistemological assumptions from existing

mechanisms (Blackmore, 2007). iii. The social learning approach points towards an appreciation of participation as

more complex than those suggested by the metaphor of ladder type of

participation. Tritter and McCallum (2006) argued that by using the metaphor of

ladder, a wider context of snakes as well as a number of rungs may be missed. iv. The other forms of participation depict it as a power struggle between citizens

trying to move up the ladder, and organizations/institutions trying to limit their

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ascent to the top and barring them from claiming control or power for them.

Inability to achieve this implies automatic failure of the participatory process. It is

however, possible that those involved may be satisfied with whatever level that

they may have achieved (Hayward et al, 2005). v. It has the ability to bring meaning into natural resources management which is

characterized by complexity, uncertainty and multiple stakeholders (SLIM,

2004b).

Despite the above advantages, social learning has the short coming of not having the ability to reveal in clear pictorial form the power agendas implicit in many institutionalized structures and the differences in the forms and strategies of participation(Collins & Ison, 2006).

2.10 Conceptual Framework for the Study Going through and assessing the strengths and weaknesses of various models such as

"Social Exchange Process" (Ap 1992); “Butler‟s Tourism Destination Life Cycle Model”

(1980) and “Social Learning Theory” (Collins & Ison, 2006), the “Doxey‟s Irridex

Model” by Doxey (1975) was considered and adopted as the most appropriate framework for developing an understanding and analyzing the level of participation of residents in the management of tourism in the communities as well as their perception on environmental and economic effects of tourism on their communities and the realities on the ground.

The Doxey‟s Irridex Model (DIM) developed by Doxey in 1975 is a theoretical model which states that resident‟s reaction to tourism will change in a predictable manner. The

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model states that an increase in the numbers of tourist and a more developed tourism industry at the destination always results in irritation in the host communities. This irritation can take the form of unfriendly behavior personified as resentment from the local community towards the tourist (Cordero, 2008). Doxey argued that the reaction of the host community goes through four stages. These stages are Euphoria, Apathy,

Annoyance and Antagonism. The model was slightly modified to fit with objectives of the study. The DIM by Doxey has come to be considered as one of the most important contribution to tourism literature, even though it is among the most heavily criticized by researchers in the tourism industry. Some of the criticisms against it are;

The model overlooks the situation whereby increase in visitor numbers may not necessarily lead to antagonism (Garland, 1984).

 The model does not fore see the possibility of the reactions reversing if effective

management strategies are put in place.

 The model is not based on detailed empirical research but mainly on conjecture

(Keyser, 2002).

 The model assumes that it is the whole community that becomes hostile to tourist, but

often communities are heterogeneous and different section of the community have

different reactions (Ivanovic, 2009)

 The homogeneity characteristics of communities adopted by the model have also

been questioned (Brougham & Butler, 1981).

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Even though DIM is most often criticized by researchers, it still remains the most popular model used by researchers in the tourism industry (Lawson et al, 1998. This may be due to the numerous advantages it possesses. These include;

 The simplistic nature of the model makes it indicate a telling factor in tourism

development.

 The model suggests that communities pass through a sequence of reactions as the

impact of an evolving tourism industry in their area becomes more pronounced.

 Justifies residents‟ attitudes at different growth stages of a tourist destination.

 Assess the host-guest interaction and relationships

 Makes the comparing of residents‟ reaction at two different attractions easier.

 The Model postulates that the more common an identity is felt by a community, the

more likely it is able to make a constructive response about what levels and types of

tourism it wishes to host.

 Finally the stages in the model parallels the more generally applicable product life

cycle and they are implicitly accompanied by increasingly adverse effects on the local

community as the nature of tourism in the area becomes progressively mass–tourism

oriented (Altintas, 2009).

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Figure 2.3: Stages of Tourism Development in Doxey’s Irridex Model

Tourism development is at initial stages. A feeling of EUPHORIA happiness or comfort whereby visitors are welcome and there is little planning.

When locals‟ starts losing interest in tourism and visitors APATHY are taken for granted and contact becomes more formal. Managers are more concerned with increasing visitations

When the numbers and the unfavourable impacts have increased and saturation point is being approached. Locals ANNOYANCE have misgivings. Planners attempt to control it through increased infrastructure rather than limiting growth.

Generation of hostile reactions towards tourist with open ANTAGONISM expressions of irritation. Planning is remedial yet promotion is increased to offset deteriorating reputation of the resort. sssssssss Source: Page and Dowling, 2002 (modified)

2.11 Summary The chapter focused on the discussion of relevant literature in tourism development.

Issues like definitions, concepts and types of tourism as well as tourism development in

Ghana. Environmental and economic impacts of tourism on the host communities were also discussed. Finally, theories on citizen‟s participation by Arnstein (1967), Conner

(1988) and Collins and Ison (2006) as well as the adopted conceptual framework for the study were also discussed.

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CHAPTER THREE

THE STUDY AREA AND METHODOLOGY

3.1 Introduction The chapter provides background information on the municipality and district selected for the study including its geology and soils, climatic conditions, vegetative cover, population and socio-economic activities that take place there. It also discusses the main methodologies used in collecting data for the research. Three (3) major approaches were used to achieve the objectives of the study. The first approach involved an assessment of water quality to determine the extent of environmental impacts of tourism on the quality of water in the study area. The second covered analysis of satellite images of the study areas from 1990 to 2010 to determine possible changes in land use with the development of tourism in the communities. The third involved a social survey within the communities to determine the perceived environmental and economic impacts of tourism on the economic livelihoods of residents.

3.2 The Study Area Two under developed but well-patronized tourist attraction sites were selected for the study. These are the Lake Bosomtwi located in the of Bosomtwi and Bosome-Freho

Districts of the Ashanti Region and Wli Waterfalls located in Hohoe Municipality of the

Volta Region.

3.2.1 Bosomtwi District The Bosomtwi District which lies within latitudes 60241 and 60431 N and longitudes 10461 and 10681 W is located in the central part of the Ashanti Region (NDC, 2010). It is bounded on the north by Kumasi Metropolis, the east by Ejusu-Juaben Municipality and

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Bosome-Freho, the west by Atwima-Kwanwoma District and the south by Bekwai

Municipality as its southern boundary. The district covers an area of about 500 sq. km and this forms about one percent (1%) of the total land area of the Ashanti Region. The

District is made up of 3 area councils: Kuntanase, Boneso and Jachie with Kuntunase serving as its district capital (NDC, 2010).

3.2.1.1 Geology and Soil The Bosomtwi District is underlain mainly by the Birrimian formation. Associated with the Birrimian formation is an extensive intrusion of granites masses (Dickson & Benneh,

1990). The Birrimian formation is divided into Lower Birrimian and the Upper Birrimian.

The Lower Birrimian consists of metamorphosed sediments such as phyllites and schists.

The Upper Birrimian is made up of both metamorphosed lava and rocks of the Lower

Birrimian (Dickson & Benneh, 1990). So far, the Birrimian formation has been the most important geological formation in Ghana, since it contains almost all the minerals exported from the country (Dickson & Benneh, 1990). The extensive masses of granite found in the area are formed from the cooling of magma which rose from the interior of the earth and reached the surface probably through deep-soiled cracks and zones of weakness in the Birrimian formation (Dickson & Benneh, 1990; Buchanan, 1983).

According to Dickson & Benneh (1990) on a broad scale of soil classification, Forest

Ochrosol interspersed with the Forest Ochrosol–Oxysol Intergrades, are the dominant soils found in the district. The Forest Ochrosols, the dominant soil types found in the area is highly coloured with the colours ranging from brown to orange. The Forest Ochrosols are porous, well-drained and generally loamy (Monkhouse, 1998). They were developed over a wide range of highly weathered parent materials such as granite, Tarkwaian and

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Birrimian rocks (Adu, 1992). The soils are not highly leached as found in Forest Oxysols of the rain forest. As a result, it contains greater quantities of nutrients that is generally alkaline and therefore supports tree crops such as cocoa (Dickson & Benneh, 1990;

Monkhouse, 1998).

The Forest Ochrosols–Oxysols intergrades have almost similar characteristics as the

Forest Ochrosols. The only difference is that, it also has some characteristics of the Forest

Oxysols found in the rain forest belt (Monkhouse, 1998). In terms of nutrients, this type of soil is not well endowed like the Forest Ochrosols but is well supplied than the Forest

Oxysols. It is therefore mildly alkaline to mildly acidic and can support tree crops to some extent (Adu, 1992; (Dickson & Benneh, 1990).

According to Obeng (2000), the most commonest components of this broad scale classification are the Kumasi–Offin Compound Association and Bomso–Offin

Compound Association which are well drained and made up of quartz gravels and iron- stone module and are mostly found in the western and middle belt of the district; the

Bekwai–Oda Compound Association, Bekwai–Akomadan–Oda Compound Association and Kobeda–Bechem–Webenso–Oda which are mostly found in north-eastern and eastern parts of the district; and Atukrom–Asikuma Association which is well drained and is found in the eastern part of the lake.

3.2.1.2 Vegetation The major vegetation found in the Bosomtwi district is the semi–deciduous forest characterized by plant species of the celtis-triplochetol association (Taylor, 1952) The appearance of this vegetation is almost like that of the evergreen forest, even though it is less luxuriant and more open and has fewer species (Dickson & Benneh 1990;

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Monkhouse 1998). Again, most of the trees in the middle and upper layers exhibit deciduous characteristics of shedding their leaves during the dry season (November to

March) when the influence of the harmattan is greatly felt (Walker, 1962). A marked feature about the shedding of leaves is that, trees here do not shed all their leaves at the same time nor are the trees of the same species leafless together (Buchanan, 1983). Trees of the lower layer, however, stay green during the dry season due to the moist conditions experienced there ((Dickson & Benneh, 1990) The major tree species are Torminalias,

Funtumia, Bombax, Ficus, Ceiba pentandra, Meltis, Mildrebraedii, Triplochilon scleroxylan and Elaesisguineesis, and. Human activities such as farming and logging have completely modified the originally dense vegetation, making it loose its pristine status. Only patches of the original vegetation exist in the most inaccessible areas such as the hilly areas. This has reduced the nature of the vegetation belt, especially around urban settlements (Monkhouse 1998; Dickson & Benneh, 1990)

3.2.1.3 Climate The Bosomtwi District falls within the wet semi-equatorial climatic zone. Temperatures are relatively high and uniform throughout the year (Walker, 1962). The annual mean is around 250C with the high mean temperature of around 320C occurring just before the major wet season in February. The minimum mean temperature of around 220 C as indicated in Fig. 3.1a is usually recorded during the minor wet season (NDC, 2010). The district experiences the double maxima type of rainfall which is slowly emerging into one. The main season occurs from March to July with June being the peak as indicated in

Fig 3.1b The minor season starts from September to November with October being the peak. August which used to be cool and dry is experiencing an unpredictable rainfall

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pattern. The main dry season occurs between December and March during which time the desiccating harmattan wind blows over the district (Dickson and Benneh, 1990).

Relative humidity is generally high throughout the year with the highest recorded in the cool and dry month of August and the beginning of the minor wet season as indicated in

Fig 3.1c. The lowest figures of around 50% are usually recorded in the month of January in the dry season.

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(a)

40

30 C 0 20

10 Jul Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar MONTHMay TEMPERATURE./

MAX MIN T. MEAN

(b)

60.0

40.0

20.0

0.0 Jul RAINFALL/cm Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar MONTHMay

MAX MIN T. MEAN

(c)

100 80 60

40 20 0 Jul HUMIDITY/% Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar MONTHMay

MAX MIN T. MEAN

Source: Ghana Meteorological Service, 2013

Figure 3.1a-c: Monthly Maximum, Minimum and Mean for Temperature (a), Rainfall (b) and Humidity (c) in the Bosomtwi District between 2008 and 2012,

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3.2.1.4 Population and Socio-economic Characteristics According to the population census of 2000, the population of the Bosomtwi–Kwanwoma

District was 146, 028, representing over 4.1% of the regions‟ share of the national population. In 1984, the district had a population of 87,325 which indicates that there was a 60% increase in population between the two censuses with a growth rate of about 3.0%

(NDC, 2010). In the 2000 census, 71,904 of the population representing 48.5% were males with the remaining 74,124 representing 51.5% were females. The district also had a population density of 236 persons per square kilometer (GSS, 2012). Over 85% and

4.7% of the population are Christians and Muslims respectively with the remaining being traditional religion practitioners and other religions. About 35% of the population in the district has not attended school at all and about 62% of those above 18 years gainfully employed. Eighteen percent (18%) of that population is not working at all with the remaining 20% being either apprentice or doing some menial jobs for the family. Of those gainfully employed, 72.6% of them are self-employed, 9.3% of them with government agencies and the remaining 18% of them working for others (GSS, 2012).

The major occupation in the district is agriculture with 52.3% engaged in it. Over thirteen percent (13.3%) of them are into trading and 11.3% engaged in white color jobs. The main sources of water for domestic use are wells and boreholes. These two together supplies about 77.6% with pipe water supplying them with 8.6%. Others like streams and rivers supplying the communities with the remaining 13.7%. Only 0.6% of residents in the district have access to water closet toilet facilities (NDC, 2010) . It is estimated that about 66.5% of the population in the district uses public toilets and pit latrines, with 6% uses the bush and surrounding areas as their places of convenience. Only 0.4% of the

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households have their solid waste collected by contractors. About 7.5% either burns or buries their waste with the remaining 86.7% dumping them at public bumps or any convenient place (NDC, 2010).

Apart from the Lake Bosomtwi, the district has a number of tourist attractions scattered around the Lake (Kofigah, 2008). Notably among these are the butterfly sanctuary (a valley full of butterflies) at Obo to the west of Abono. There is also the large volume of bird nest with beautifully colored birds in them at Hantase, to the west of Obo. To the east of Hantase is Banso where the beautiful Old Catholic Church that serve as an attraction to the religious minded tourists. In Abrodwum and Atafram respectively to the east of Abono are the Sacred Abrodwum Stone – the fetish grove representing the spiritual activity center of the Lake communities and the Holy Rock of Atafrom where people go to worship (Kofigah, 2008).

Inhabitants of the communities around the Lake are very hospitable and more than willing to help numerous tourists who visit the area. The district is therefore one of the most attractive destination for tourists, holiday makers and sight seers (GHA, 2013).

There are quite a number of hotels and guest houses, restaurants and bars that serve the needs of tourists. Some of these are the Lake Bosomtwi Tourist Lodge at Kuntunase,

Twum Barima Hotel at Patiensa, Lake Bosomtwi Paradise Resort at Abono, Bosomtwi

Gardens at Abono, Lake Point Guest House at Obo and the Rainbow Gardens Village at

Anyinatiase (GHA, 2014).

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Plate 1: Sign Board Welcoming Visitors to the Lake Bosomtwi

The Lake Bosomtwi lies about 20 kilometres to the south–east of Kumasi and 15 km south of Kuntunase, the capital of the Bosomtwi District (NDC, 2010). The Lake is about

11 km in width and 75 meters deep. The water is surprisingly salty but rich in freshwater fish, crabs and fish–catching birds that the inhabitants fish and hunt for commercial and domestic use. Its formation is shrouded in mystery with some scientists claiming that it is a crater lake formed from a meteorite that fell into the surrounding mountains some millions of years ago (NDC, 2010). The Lake Bosomtwi is surrounded by twenty–eight towns and villages and the inhabitants are mostly farmers with fishing as a major pastime. Population in the villages are quite small with Abono having the largest of about

2000 (GSS, 2012).

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Data on tourist arrivals at the Lake is scanty and may not be accurate due to bad management strategies and poor record keeping by the Tourism Management Committee

(TMC). It is however, estimated that over 75,000 tourists with about 26% of them being foreigners visit the Lake Bosomtwi and its surrounding attractions annually (NDC, 2010)

3.2.2 Hohoe Municipality

The Hohoe Municipality which is one of the eighteen districts in Volta Region was carved out of both Jasikan and Kpando District Councils in 1979. It has a total land area of 1,172 km2 and lies within latitude 60 45I N and 70 15I N, and longitude 00 15I E and 00

45I E (National Development Commission, 2010). It covers about 5.6% of the total land mass of the Volta Region and shares boundaries with the Republic of Togo to the East,

Jasikan District to the north, Ho Municipal Assembly and the Kpando Municipality to the south-east and south-west respectively, and South Dayi District to the west. The district with Hohoe as its capital has eight zonal councils namely Weto, Ve, Lolobi, Logba/Tafi,

Likpe, Liati/Afadjato, Leklebi and Have/Nyagbo (NDC, 2010).

3.2.2.1 Geology and Soil

The district is a mountainous region with the Akwapim-Togo ranges forming a major part of the district. This has resulted in the district having a number of hills and mountains, including the highest one in Ghana- Afadja (Mountain Afadjato). The major rock formations found in the district are the Togo series and the Buem formation

(Dickson & Benneh, 1990). Both the Togo series and Buem rocks were formed from eroded materials that were deposited in Basins. The Togo series is made up of sedimentary rocks and its metamorphosed version such as quarzite, schist, shale and phyllite. These rocks were those that were folded to form the Akwapim-Togo ranges

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(Adu & Asiamah, 1992). The Buem rocks, on the other hand, are made from materials that had been eroded from the Togo series and deposited in the low lying areas around the

Akwapim-Togo ranges. Some volcanic materials deposited in the low lying areas around the Akwapim-Togo ranges also form part of the rocks found in the district (Adu &

Asiamah, 1992; Junner & Hurst, 1946).

Soils in the district generally tend to be sandy over-lying iron pans. Soils found in both the moist semi-deciduous forest and interior wooded savanna are found in the district

(Asiamah, 1995). The main soils found in the area are the Forest Ochrosols and the

Groundwater Lateritic soils. The Forest Ochrosols is highly coloured with the colours ranging from brown to orange. The Forest Ochrosols is porous, well-drained and generally loamy (Buchanan, 1983). They were developed over a wide range of highly weathered parent materials such as granite, Tarkwaian and Birrimian rocks. The soil is not highly leached such as Forest Oxysols found in the rain forest. As a result, it contains greater quantities of nutrients that is generally alkaline (Monkhouse, 1998; Dickson &

Benneh, 1990).

The Groundwater Lateritic soils, the dominant soil type found in the Municipality developed over both the Voltaian shale and granites. The major characteristic is the presence of „iron pan” (a cemented layer of ironstone) at generally a shallow depth below the surface of the soil (NDC, 2010). It is very difficult for rain water to penetrate the iron pans and thus renders the soil water logged during the rainy season. The soils, however, dry up very quickly during the dry season to form hard cakes. In color, the soils range from a combination of yellow and brown to yellow and grey (Asiamah, 1995).

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3.2.2.2 Vegetation

The Municipality falls within the transitional zone of both the moist semi deciduous and the interior wooded savanna belts of Ghana. While the eastern section such as the

Alavanyo area is forested, the western section covering areas such as Kpeve and Have are covered by woodland savannah and tall grasses (Taylor, 1952).

The appearance of semi-deciduous forest is almost like that of the evergreen forest, even though it is less luxuriant and more open and has fewer trees (Monkhouse, 1998; Dickson

& Benneh, 1990). Again, most of the trees in the middle and upper layers exhibit deciduous characteristics of shedding their leaves during the dry season (November–

March) when the influence of the harmattan is greatly felt (Dickson & Benneh, 1990). A marked feature about the shedding of leaves is that, trees here do not shed all their leaves at the same time nor are the trees of the same species leafless together. Trees of the lower layer, however, stay green during the dry season due to the moist conditions experience there ((Dickson & Benneh, 1990). However, human activities such as farming and logging have completely modified the originally dense vegetation, making it loose its pristine status. Only patches of the original vegetation exist in the most inaccessible areas such as the hilly areas. This has reduced number of species in the vegetation belt especially, around urban settlement ((NDC, 2010; Monkhouse, 1998; Dickson & Benneh,

1990).

Trees found in the area are widely scattered. However, as one moves to the south which is close to the boundary with the moist deciduous forest, they become a bit dense. The trees are not as tall and gigantic as those found in the moist deciduous forest. Tufted

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grasses grow rapidly to a height of over three (3) meters in the form of a stiff straw-grass crowned with silvery spikes (Monkhouse, 1998; Dickson & Benneh, 1990).

There are marked changes in plants in this vegetation belt during the different seasons of the year. During the rainy season, trees blossom and grasses shoot up rapidly making the area look green with life. Soon after the rains, however, leaves begin to change color from green to yellow and trees begin to shed their leaves. Grasses dry up and the land looks parched and desolate. This type of vegetation is largely man made (Dickson &

Benneh 1990).

3.2.2.3 Climate

The Hohoe municipality falls within the wet semi-equatorial climatic zone.

Temperatures as indicated in Fig 3.2a are high and almost uniform throughout the year, departing very little form 270C. Average peaks of between 340 C and 35.50 C experienced between February and April with the lowest of between 210 C - 230C being experienced in August and the harmattan month of December (Dickson & Benneh,1990;

Monkhouse,1999). The rainfall pattern experienced in the Municipality used to be the double maxima type. As indicated in Fig 3.2b, the first one is between April and July and the second one between September and October. Annual rainfall is between 125cm and

200cm (Dickson & Benneh, 1990). However, anthropogenic activities have led to a highly unpredictable pattern of rainy season in the district. The hitherto well defined two peaks as explained by Dickson and Benneh (1990) and Monkhouse (1998) have almost merged into one with the rains starting from mid-April and ending in October (NDC,

2010).

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Dry season in the Municipality has also become quite sharp and pronounced lasting from between four to five months. Average relative humidity as shown in Fig 3.2c is high throughout the year with the highest range of between 75% - 90% experienced in the months of June and July with the lowest of between 55% - 65% experienced in December and January (NDC, 2010)

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(a)

40

C 30 0 20

10 Jul Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar May TEMPERATURE/ MONTH

MAX MIN T. MEAN

(b)

40 30

20 10 0 Jul Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar May RAINFALL/cm MONTH

MAX MIN T. MEAN

(c)

90 70 50

HUMIDITY/% 30 Jul Jan Jun Oct Apr Feb Sep Dec Aug Nov Mar May MONTH

MAX MIN T. MEAN

Source: Ghana Meteorological Service Figure 3.2a-c Monthly Maximum, Minimum and Mean for Temperature (a), Rainfall (b) and Humidity (c) in the Hohoe Municipality between 2008 and 2012,

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3.2.2.4 Population and Socio-economic Characteristics

The population figure for the Hohoe Municipality based on the 2000 population and housing census was 153,047 representing about 6.3% of the region‟s share of the country‟s population. This is a rise of about 54 % of the 1984 population and housing census figure of 85,706. The gender breakdown of the population of the Municipality after the 2000 population and housing census were 74,137 and 78,910 representing 48% and 52% for males and females respectively. A population density of 130 persons per square kilometer for the Municipality is higher than that of the region and the country.

Majority of residents (87.9%) are Christians with 5.3% and 1.6% of the rest of the population being Muslims and Traditionalist respectively (NDC, 2010).

The Municipality has a high illiteracy rate with about 41.5% of the population being illiterate. Of those who are educated, 74.2% of them have had up to Middle or Junior

Secondary School level, 15.4% had up to Secondary/Vocational/Technical level and

8.6% having gone up to the tertiary level. 90.3% of the 65,678 who fall within the working age group of 15 years and above are actively engaged in one form of employment or the other. Of those who are actively employed, 53.6% of them are engaged in agricultural activities, 29.7% are employed by the formal sector and the remaining 15.7% engaged in trading or other forms of employment. About 42.1% of water for domestic use in the Municipality comes from rivers/streams. Pipe and boreholes/wells contribute 31.1% and 20.5% respectively of the water used for domestic purposes. Only 1.8% of residents in the Municipality use water closet facilities with

24.7% and 38.1% using pit latrine and public toilets respectively. The remaining 7.1% of the use the surrounding bushes for their place of convenience (NDC, 2010).

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There are quite a number of tourist attractions in the Hohoe Municipality including the

Wli Waterfalls. Others are the lofty mountains blending with low green plains such as

Mountain Afadjato (the highest peak in Ghana located between Liati Wote and Gbledi communities); spectacular waterfalls such as the Tsatsadu, the Tagbo and the Wadjakli

Waterfalls located at Alavanyo, Liate Wote and Likpe Todome respectively; sanctuaries such as sacred Mona Monkey sanctuary at Tafi Atome; and ancient caves and sites such as the ancient iron mines at Akpafu Todzi and the four ancestral caves and the stalactite and stalagmite caves at Likpe Todome and Logba Toa respectively (GHA, 2014; Degbor,

2002).

The people in the communities near the attractions are more than willing to express their hospitality to all visitors. The Municipality is therefore a destination for tourists, holiday makers and sight seers. There are hotels and guest houses restaurants/bars such as Hotel

De Monk, Matvin Hotel, Geduld Hotel, Taste Lodge Hotel, Evergreen Lodge, Galaxy lodge and Water Heights Guest House dotted in almost all the communities where the attractions are located (GHA, 2013).

The Wli Waterfall is located within the 3 km sq. Agumatsa Wildlife Sanctuary at Wli–

Afegame in the Hohoe Municipality in the Volta Region. Water descends from the

Agumatsa Mountains which is 834m high. With a total height of over 400m, this waterfall is reputed to be the highest waterfall in West Africa (Degbor, 2002).

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Plate 2: Sign Board Directing Visitors to the Information Center at Wli Afagame

The waterfall is about 45 minutes‟ walk from the town of Wli–Afegame. The community which is about 15 kilometres from the Municipal capital Hohoe is a quiet and homogenous society. It has population of about 1,500 (GSS, 2012) and farming is the major occupation of residents (NDC, 2010).

Tourist arrivals at the Wli Waterfalls rose from 14,345 in 2006 to 69,872 in 2013 with a percentage increment of about 487%. In 2013, about 44,860 (64.20%) of the arrivals were Ghanaians with the remaining 25,012 (35.80%) being foreigners (GTA, 2014).

Receipts also rose from GH¢25,031.40 in 2006 to GH¢268,657.00 with a percentage increment of over 1000% (GTA, 2014).

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Table 3.1: Tourist Arrivals and Receipts for Wli Waterfalls between 2006 and 2013

YEAR R' DENTS N. R'DENTS T. A'VALS R' NUE (GH¢) 2006 8,989 5,356 14,345 25,031.40 2007 12,201 5,592 17,793 41,729.50 2008 11,262 5,608 16,870 33,185.90 2009 - - - - 2010 9,346 3,386 12,732 4,600.00 2011 21,474 8,751 30,225 134,450.00 2012 25,448 15,805 41,253 157,110.00 2013 44,860 25,012 69,872 268,657.00 Grand Total 133,580 69,510 203,090 664,763.80 Source: Ghana Tourism Authority, 2014

R'DENTS : RESIDENTS

N. R'DENTS : NON RESIDENTS

T. A'VALS : TOTAL ARRIVALS

R'NUE (GH¢) : REVENUE

3.3 Rationale for Selecting Study Areas The major reason for selecting the areas listed above for the study is the potential of these areas for tourism development. The tourist attractions in the study areas such as, the hilly nature of the land (topography), flora and fauna (ecological), as well as the ever presence of water, if well developed, will lead to a boom in nature–based and out–door tourism in the study area.

Again, development of tourism at the study areas is still at initial stages and in rural settings. It is therefore characterised by rural economy which will make it easy for the impacts of tourism to be assessed. Amuquandoh and Dei (2007) buttressing this point made by Kokkranikal (2003) stated that tourism in destination areas that are very small lend itself to detailed analysis than those in large urban destinations with urban economy.

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Finally, with tourism at its initial stages of development, it will be easier to formulate sustainable tourism development plans for these areas so as to protect the water bodies and the fragile ecosystems surrounding them from degradation (Prideaux, 2000).

3.4 Data Collection In order to achieve the objectives of the study, there was the need for enough data to be used. Three different approaches were therefore used to achieve that objective. These included water quality analysis of water from the water bodies that serve as the attraction.

Land use analysis on the vegetative cover around the water bodies as well as a social survey of residents in the communities around the water bodies.

3.5 Data Source The study made use of data from both primary and secondary sources. The primary data included results of water quality analysis, satellite images of the study areas, questionnaires, participant and observations whilst the secondary data were from textbooks, journals (Brunt & Courtney, 1999; Butler, 1999; Cohen, 1998); project reports

(Bryden, 1973) and other documents relevant to the study.

3.6 The Sampling Sites The selection of sampling sites began with a reconnaissance survey of the two tourists attraction sites mentioned above. This was based on the high number of tourist who patronize these sites as well as the importance of the water bodies found in the study areas to the social and economic activities of the communities in which the attractions are located. In order to get the impact of tourism on the water bodies, water samples from the

Lake and Waterfalls were taken in such a way that, some of the water samples were taken from areas where tourist activities are very minimal through to the areas where the

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tourist‟s activities are always high. Water samples were also taken at areas where the communities fetch water for domestic use. Based on this criterion, five (5) sites were selected in the Wli Waterfalls area. The sites selected were the Upper Falls (WUF),

Lower Falls (WLF), Pool Site (WPS), Ninth Bridge (WBR) and Drinking Spot (WDR) as indicated in Table 4.1 and Fig. 4.1

Table 3.2: GPS Positions of Sampling Sites at Wli Waterfalls

SITES LOCATION FROM DISTANCE N 070 06I 30.7II WUF (Site 1) E 0000 36I 51.1II – – N 070 06I 27.0II WLF (Site 2) W 0000 36I 49.1II Site 1 to Site 2 0.25 km N 070 06I 26.4II WPS (Site 3) W 0000 36I 48.6II Site 2 to Site 3 0.05 km N 070 06I 35.6II WBR (Site 4) E 0000 36I 44.7II Site 3 to Site 4 0.15 km N 070 06I 28.0II WDR (Site 5) E 0000 35I 57.8II Site 4 to Site 5 0.35 km

WUF: Wli Upper Falls

WLF: Wli Lower Falls

WPS: Wli Pool Site

WBR: Wli Ninth Bridge

WDR: Wli Drinking Spot

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Figure 3.3 Map of Wli Waterfalls Showing Sampling Sites

Source: CERGIS of University of Ghana

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Lake Bosomtwi is surrounded by small towns and villages with Abono being the town where a large chunk of the tourism activities on the Lake takes place. It was therefore selected as one of the sampling sites. To be able to assess the impact of tourism on the water body of the Lake, water samples of the Lake were taken from four other towns apart from Abono. With Abono being the focal point, two towns to the east (second and fourth towns) and two towns to the west (second and fourth towns) were selected as sampling sites. Based on the above, samples were taken at Abono as the focal point,

Abrodwum and Nyinatiase to the east of Abono as well as Obo and Nkowie to the west of Abono as indicated in Table 4.3 and Fig. 4.2.

Table 3.3 GPS Positions of Sampling Sites at Lake Bosomtwi

SITE LOCATION FROM DISTANCE N 060 31I 49.4.II 0 I II BAB (Site 1) W 001 25 27.6 – – N 060 31I 31.7II 0 I II BAM (Site 2) W 001 26 33.0 Site 1 to Site 2 1.55 km N 060 30I 39.5II 0 I II BNY (Site 3) W 001 26 49.6 Site 2 to Site 3 1.84 km N 060 32I 20.4II 0 I II BOB (Site 4) W 001 24 40.0 Site 3 to Site 4 1.60 km N 060 32I 42.1II 0 I II BNK (Site 5) W 001 24 26.3 Site 4 to Site 5 1.25 km

BAB: Bosomtwi - Abono

BAM: Bosomtwi - Abrodwum

BNY: Bosomtwi - Nyinatiase

BOB: Bosomtwi - Obo

BNK: Bosomtwi - Nkowie

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Figure 3.4: Map of Lake Bosomtwi Showing Sampling Sites

Source: CERGIS of University of Ghana

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3.7 Water Sampling and Analysis Water samples for physico–chemical and bacteriological analysis were taken from the

Wli Waterfalls and Lake Bosomtwi. Twelve (12) samples were taken at a month‟s interval from July 2012 to June 2013. In all, twenty–eight (28) parameters were selected for analysis to check the effects of tourism on the quality of water in the study areas. The parameters were grouped into physical, chemical and bacteriological.

Physical Parameters: Temperature, pH, Turbidity, Conductivity. Total Dissolved Solids

(TDS), Total Suspended Solids (TSS), Total Hardness, Alkalinity.

Chemical Parameters: Bicarbonate (HCO3), Chloride (Cl), Fluoride (F-), Calcium (Ca),

Sodium (Na), Magnesium (Mg), Potassium (K).

Nutrients Parameters: Nitrate (NO3), Nitrite (NO2-), Phosphate (PO4), Ammonia (NH3)

Bacteriological Parameters: Total Coliforms, Fecal Coliforms.

Heavy Metals: Zinc (Zn), Copper (Cu), Cadmium (Cd), Lead (Pb), Manganese (Mn),

Total Iron (Fe).

At each sampling site, a clean plastic bucket was used to fetch water manually at depths of between eight (8) and ten (10) centimeters below the water surface for in-situ measurements of some parameters. A clean 1.5 liter plastic bottle was filled and sent to the laboratory for physico-chemical analysis. An already sterilized 0.5 liter bottle was also filled for bacteriological analysis. The water samples were then immediately placed in an ice chest with ice cubes and transported to the laboratory within 24 hours of collection and placed in a refrigerator with a temperature of about 4oC. This was to help

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prevent loss of certain parameters and also to maintain the actual values of the parameters

(De Zuane, 1997). All analyses were carried out in the laboratory within seven (7) days of sample collection. All the physico–chemical analysis were carried out at the laboratories of the Environmental Chemistry Division of the Water Research Institute in

Accra. The bacteriological analyses were also carried out at the laboratories of the

Environmental Biology and Health Division of the Water Research Institute in Accra.

3.7.1 Physical Parameters Temperature, pH, conductivity and total dissolved solids were measured in-situ, using a

Horiba Digital Water Quality Checker (Model V.10). This type of equipment allows fast and accurate readings to be taken, thus eliminating errors due to changes in time.

Temperature, pH, conductivity and total dissolved solids/suspended solids were measured in 0C, pH unit, uS/cm and mg/L respectively.

The APHA (1998) standards were used to analyze the remaining physico–chemical parameters. Whilst turbidity was measured in NTU, the remaining physico–chemical and heavy metal parameters were measured in mg/L.

3.7.2 Bacteriological Analysis The Standard Membrane Filter technique, which is faster, requires fewer steps and media, less expensive, more portable and could process larger quantities of water samples at the same time was used (Talaro & Talaro, 1993). Autoclavable bottles were used for sampling. Before each sampling trip got started, sampling bottles and all other kits were sterilized by autoclaving at a temperature of 120oC for fifteen (15) minutes. At each sampling site, a sterilized 0.5 liter-bottle was filled with water sample for bacteriological

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analysis in the laboratory. The sterilized bottles, held at the base, were submerged before opening the bottle to reduce bacterial contamination (APHA, 1998).

The technique involved the use of a special sterilized membrane filters made up of nitrocellulose acetate and polycarbonate and is 150μm thick and has a 0.45μm diameter pores (Harley & Prescott, 1990). 20ml and 50ml water samples were filtered through a membrane filter for total and fecal coliforms, respectively. The membrane filters were then carefully removed from the filtration kit with sterilized forceps and placed in a Petri

Dish containing a media prepared from McConkey Agar. The Petri Dish was then covered and placed in an oven for incubation. Samples were incubated at 37oC and 44oC for total coliform and fecal coliform, respectively, for 16 to18 hours. After the incubation period, the growth on the membrane filters were identified and counted under magnifying glass in coliform units of cfu/100mL.

3.8 Land Use and Cover Analysis This analysis was to help identify, if any, the effects of tourism on land use in the study areas. To be able to identify and analyze this effectively, satellite images were used.

Satellite imagery data used for the study spanned a period of twenty years (from 1990 to

2010). Satellite imageries of 30m resolution with less than 30% cloud cover for three different years (1990, 2000 and 2010) were acquired from Centre for Remote Sensing and Geographic Information Systems (CERGIS) of the University of Ghana, Legon, for the study.

The process started by assigning coordinates to the image, using 1:50000 Ghana topographic data of the same area. This was followed by rectification which is the

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process of projecting the data onto a plane and making it conform to the map projection.

Classification of images, using Erdas Imagine Software was then performed. The unsupervised classification method which has the advantage of eliminating individual biases was used in the classification of images. This is because it is computer –based and allows the specification of parameters that the computer uses as guidelines to uncover statistical patterns in the data (Stow, 2010). Assigning a new class value to all classes, known as recoding, then followed. This was to create a new thematic raster layer using a new class number. Some of the classes too were combined through this process. The area of various classes in the raster attributed table was then generated and exported as .dat.

The table was then opened in excel, copied and added to the already composed map.

Finally the various time series maps were composed in ArcMap showing the changes in the cover types with statistics indicating the changes from 1990, 2000 and 2010 (Mas,

1999).

3.9 Social Survey This was to find out the perception of residents on the environmental effects of the tourism and how these effects affect economic activities in the study areas. It was also to find out the perception of the local inhabitants on the activities of tourists in the study areas. To be able to get a broad spectrum of information, multiple data collection methods were used. These included distribution of structured questionnaires and observations.

3.9.1 Target Population The target populations for the social survey were made up of heads or representatives (a member of a household who is above 18 years) of households found in the communities selected for the study. The Ghana Statistical Service (GSS) has defined a household as;

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"A person or group of persons related or unrelated and who live together in the same house or compound, and share the same housekeeping arrangements and are catered for as one unit".

Based on the above definition, there is the possibility that there could be more than one household in one house. However, for the purpose of this study, each house found in the study areas was considered as a household. This is due to the fact that the communities selected for the study are the indigenous and almost homogenous types of society where almost all members of the communities live in family owned houses and so do a lot of things together.

3.9.2 Sample Frame and Sample Size The list of houses compiled by the GSS for the 2000/2010 population census served as the frame for the sample that was used for selecting respondents.

The sample frame for the study was so huge that it was practically impossible to contact all of them. This was as a result of factors such as availability of time and resources. In choosing the sample size, researcher was mindful of the fact that care must be taken to make the sample for the research quite representative. The Yamane (1967) formula for calculating population sample size was therefore adopted and used in calculating the sample size. It is of importance to note that even though other factors such as residential patterns and family structures were considered, population was the basic factor used in determining the sample size.

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N n  1 Ne2

Where; n = sample size to be calculated N = actual population size e = standard error which depends on the required confidence level set by the researcher. In this case, the confidence level was 95 percent. The value of “e” therefore was 0.05.

3.9.3 Sampling Procedure It is the sampling scheme that was used in selecting respondents for the study. Care was taken in choosing a sampling procedure so that the study will be able to represent on a large scale, the characteristics of the entire population, so that the results can be generalized to the whole population. The nature of the study required that both probability and non–probability sampling procedures were used. To be able to get a broad spectrum of respondents from the local residents, both systematic and simple random sampling technique which is a probability technique was also used.

The social survey began with the listing of all houses in the communities selected for the study. This was followed by moving to the field to give identification marks to the various houses with all the houses in each community being given numbers from 1 to the

Nth number which is the last of the houses. The sample sizes for each community was then calculated based on the Yamane formula (1967) for determining sampling sizes for social surveys. The sample size was then used to divide the number of houses in each community to get the sampling fraction (Kumekpor, 2002). A simple random sampling system was then used to pick from 1 to the Nth number of houses till the sampling fraction is derived. Respondents for the study were then picked from the houses that have

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been picked to form the sampling fraction. Respondents were heads of the houses selected or any member of the house who is above 18 years and members of the house agree that he/she should answer the questions

3.10 Sample Validation and Pilot Survey (Pre –Testing) The importance of validity and reliability in a study is critical to the usefulness of the study and can be approached through careful attention to a study‟s conceptualization and the way in which the data is collected, analyzed, interpreted and the presentation of results (Shadish et al., 2002). Zikmund and Babin (2009) defined validity as the degree to which correct inferences can be made based on results from an instrument.

To ensure validity and reliability, questionnaires were pre–tested on twenty (20) respondents in the Bosomtwi district in order to assess their suitability for achieving the objectives of the study. Four (4) respondents were purposively selected from each of the five communities to form the sample for the pre-test survey. Pre–testing refers to a procedure that involves a trial run with a group of residents to iron out fundamental problems associated with the questionnaire (Zikmund & Babin, 2009). Pre–testing therefore helps to identify problems with questionnaires, such as ambiguity, unclear instructions and irrelevant questions (Roberts–Lombard, 2006). After pre–testing, the necessary modifications to the questionnaires were made before actual survey work took place. The pre–testing also enlightened the researcher to some problems that he is likely to encounter during actual survey. Mechanisms were therefore put in place to rectify them.

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Some of the information from pre-testing such as that of the bio–data were compared with the figures from the 2000 population census for reliability. Reliability may be fundamentally concerned with issues of consistency of measures (Bryman & Bell, 2003).

3.11 Study Instruments In gathering the data, a semi–structured questionnaires containing a mixture of close– ended, open–ended and Likert scale questions were used. Items in the questionnaires include questions on environmental effects, economic effects and perception on the development of tourism in the communities. There were some questions on bio–data as well, since factors such as age, sex, educational level, occupation, marital status and religion affect people‟s perception about tourism development. While some of the questions were close–ended because the researcher believes that they demand a "yes" or

"no" answers, others sought the opinion on or interpretation of issues so were left open– ended. In soliciting information to measure issues relating to impacts and whether to support tourism development, a five–point Likert scale type of questions were asked.

Some of the opened and closed ended questions were framed based on that of Akis et al.

(1996). They were, however, modified to suit the conditions within the study areas.

The Likert scale questions on the other hand were adopted from the impact statements developed by Yoon (2000) of the Virginia Polytechnic and State University. The scale of

Yoon was modified slightly by replacing the term “moderate” with “neutral” to reflect and capture the mood of the respondents in the study areas. The final version of the instrument was also grouped into three components under environmental, economic and level of participation categories so as to achieve the objectives of the study. The items

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from this section of the questionnaires were responded to on a 5-point Likert scale with 1 representing strongly disagree to 5 representing strongly agree. Based on the above, the researcher adopted the scale range below to help in the interpretation of the results;

0.00 – 1.00 = “Strongly Disagree” 1.01 – 2.00 = “Disagree” 2.01 – 3.00 = “Neutral/Not Sure” 3.01 – 4.00 = “Agree” 4.0 – 5.00 = “Strongly Agree”

The questionnaires were administered in both English and local dialects (Akan and Ewe).

Six Research Assistants were mostly Master of Philosophy students or National Service

Personnel from University of Ghana and University of Professional Studies were recruited and trained to help in administering the questionnaires. This is because majority of the residents has had little or no formal education. Literate respondents, however, filled the questionnaires themselves. The questionnaires were given to opinion leaders and residents of the communities in the study area for information on the environmental impacts of tourism as well as its effects on their economic livelihood. Residents‟ perception on tourism development and their role in the management of the attractions were also sought.

In selecting houses using the Yamane formula elucidated upon earlier on, care was taken not to give more than one questionnaire to each household. This is due to the fact that most of the residents live in family owned houses. One is likely to get the same answers if more than one questionnaire is given to a household.

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Purposive sampling technique was also used in the case of the opinion leaders because specific individuals were needed to provide answers to specific questions. Stratification was used to lower known variations in the population. It was used to ensure that all the characteristics in the study were represented in the sample (Twumasi, 1986).

As indicated in Table 25 below, 585 questionnaires were administered to the residents of the two study areas out of which 493 questionnaires were considered valid for use. While

333 questionnaires were given to seven communities around the Lake Bosomtwi (Abono,

Obo, Nkowie, Abrodwum, Nyinatiase, Abaase and Adwafo), 252 questionnaires were administered to four communities around the Wli Waterfalls (Agoviefe, Afegame, Tadzi and Dzogbega).

Table 3.4: No of Respondents from Each Community in the Study Areas

LAKE BOSOMTWI WLI WATERFALLS Community No. of Resp. Valid No Used Community No. of Resp. Valid No Used Abono 85 74 Agoviefe 85 75 Obo 58 48 Afegame 65 56 Nkowie 47 39 Tadzi 55 48 Abrowum 40 31 Dzogbega 47 41 Nyinatiase 38 30 Abaase 35 29 Adwafo 30 22 G. TOTAL 333 273 G. TOTAL 252 220 Source: Field Data (2014)

3.11 Participant Observations Many hours were also spent in the communities observing and participating in almost all the anthropogenic activities practiced by the tourist and the residents that are related to tourism. Activities such as the disposal of wastewater and other waste products, swimming and bathing in water bodies, spending habits, interactions between tourists and

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residents, protection and/or destruction of vegetation and many others were observed critically during the field trips. Other social and economic activities, apart from tourism, were also observed and noted. This helped in getting first-hand information on how tourists and residents interact with the environment and also get acquainted with the residents before actual data collection started.

3.12 Ethical Considerations

Ethical considerations in research is an accumulation of values and principles that addresses questions of what is good or bad in dealing with human beings. Ethics simply searches for reasons for acting or refraining from acting (AHEC, 2003). Issues that researchers take into consideration when dealing with ethical considerations are varied.

The most frequently considered ones are informed consent, voluntary participation, do no harm, confidentiality, anonymity and assessing only relevant components (Trochim,

2006).

From the onset of the study, the researcher recognized the need for public engagement and wide spread consultations involving the community as well as experts and interest groups. Letters were therefore sent to the chiefs, assembly men/women and other opinion leaders in the various communities to get the people informed about the study, its scope and purpose before work started. Care was also taken not to coerce members of the community to be part of the study. This was done by informing them that the study is for academic and policy formulation purposes and that no harm will befall them in the process of participation. Again they were assured that strict confidentiality and anonymity will be adhered to. They were made to understand that should any of them feel

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uncomfortable with the process, that individual had the right to withdraw from the data collection exercise. Finally, before each questionnaire was given out, the respondent was reminded of the above ethical considerations.

3.13 Summary

The chapter covered the environmental and economic characteristics of the municipality and district selected for the study. Soils found in moist semi–deciduous forest as well as interior wooded savanna are found in the study areas. The moist semi–deciduous forest and the interior wooded savanna are the major vegetative cover found in the study areas.

Both study areas fall within the semi–equatorial climatic zone. Population densities within the study areas are quite high with farming being the major occupation. Again, it provided information on the methodology used in conducting the study. This included the source of data, study areas and rational for selecting them, water sampling and analysis, land cover analysis and methods as well as the ethical considerations employed in collecting the social data.

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CHAPTER FOUR

STUDY RESULTS

4.1 Introduction This chapter is in four (4) sections. The first part deals with analysis and interpretation of the physico–chemical as well as the nutrients, heavy metals and bacteriological parameters used in the water quality analysis. The second part deals with the interpretation of the principal component analysis of water quality parameters within sites as well as between sites. The third sections deals with the interpretation of the satellite images of land use patterns in the study area. The final section covered the interpretation of social survey results.

4.2 Physico–Chemical Parameters

Analysis for the water quality was carried out on seasonal basis. The seasons were grouped into two. These are the; i. Lean Periods: refers to the period during which tourism activities are very minimal ii. Peak Periods: refers to the period during which tourism activities are very high.

4.2.1 Temperature Temperature ranged from 23.600C recorded at WUF in August to 27.90 0C also recorded at WUF in July. The highest annual mean value of 25.740C was recorded at WPS with

WUF recording the lowest of 25.330C. The highest value of 27.900C was recorded in July which is in the peak period with the lowest of 23.600C recorded in August which falls under the lean period. The means for the peak periods were higher than that of the lean periods with figures ranging from, 25.620C recorded at WDR to 26.150C at WUF, and

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24.510C at WUF to 25.330C at WDR for the peak and lean periods respectively. Monthly means ranged from the lowest of 24.620C recorded in February to a high of 26.140C recorded in January as shown in Table 4.1 below.

The results indicate that all the temperature values recorded at the Wli Waterfalls were within the natural background range of 26.500C to 28.500C. Generally, values recorded for the peak periods were slightly higher than that of the lean periods. Variability between the peak and lean periods were minimal for all the sites with WPS showing the highest variability and WDR showing the lowest variability. With the exception of WPS which was significant (ANOVA p>0.05) with a standard deviation and standard error mean of 1.382 and 0.56436 respectively, variability between the periods of the other sites were insignificant.

Table 4.1: Mean, Range and Periodic Means for Temperature Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 23.6 - 27.9 25.33 1.38 26.15 24.51 WLF 23.7 - 26.9 25.59 0.64 25.88 25.31 WPS 24.7 - 26.4 25.74 0.38 25.93 25.55 WBR 24.7 - 26.2 25.47 0.76 25.70 25.23 TEMP WDR 24.4 - 25.4 25.48 0.81 25.62 25.33 (0C) BAB 28.2 - 31.8 30.20 1.91 29.67 30.57 BOB 28.1 - 31.9 29.97 0.91 29.28 30.63 BNK 28.2 - 31.1 29.89 1.24 29.67 30.12 BAM 28.2 - 29.6 28.76 1.81 28.71 28.82 BNY 28.2 - 31.1 29.90 1.75 29.82 30.02

Temperature values at Lake Bosomtwi as indicated in Table 4.1 above ranged from

28.100C recorded in August to 31.900C recorded in March. The highest and the lowest values were all recorded at BOB. Annual mean temperature for the various sites at Lake

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Bosomtwi ranged from 28.760C recorded at BAM to 30.200C recorded of BAB. The mean values for the lean periods ranged from 28.710C recorded at BAM to a high of

29.820C recorded at BOB. The mean values for the peak periods ranged from 28.200C recorded at BAM to 30.630C recorded at BOB. Monthly mean values also ranged from

28.700C recorded in December to 30.600C recorded in February.

Even though the mean values recorded for the lean periods were slightly higher than that of peak periods, the values recorded did not follow any specific pattern. Variations between the periods as well as the sampling sites were minimal. Difference between the periods were also minimal with only that of BOB being significant (ANOVA p>0.05) with a standard deviation and standard error mean of 0.90037 and 0.36757 respectively.

Most of the values recorded were above the acceptable limit for drinking water (WHO,

1993).

4.2.2 pH Table 4.2 below indicates that pH values at Wli Waterfalls range from 6.10 recorded at

WBR to 8.70 recorded at WDR. The highest pH value of 8.70 was recorded in July and the lowest recorded in May with both of them being recorded in the peak period.

Generally the mean values for the lean period were greater than that of the peak period with values ranging from 6.83 recorded at WBR to 7.45 recorded WDR and 6.65 recorded at WPS to 7.05 recorded at WDR for lean and peak periods respectively. Annual mean value ranged from 6.78 recorded at WBR to 7.25 recorded at WDR. Monthly means ranged from a low of 6.94 recorded in September to the highest of 7.44 recorded in January. Apart from the value recorded at WDR in May which was slightly alkaline

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(8.70), all the remaining values fall within the natural background range of between 6.50 and 8.50.

Again, values recorded for the lean periods were slightly higher than those recorded for the peak periods. pH values recorded for the sites did not follow any specific pattern with the exception of December which recorded values of above 7.10 for all the sites.

Variability was very minimal for the periods in all sites apart from that of WDR and

WLF which were a bit more pronounced. With a standard deviation of 0.24014 and a standard error mean of 0.09804, only WUF has a significant variation (ANOVA p>0.05) with the rest showing insignificant variations.

Table 4.2: Mean, Range and Periodic Means for pH Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 6.7 - 7.6 7.19 0.24 7.03 7.35 WLF 6.5 - 8.1 6.99 0.46 6.78 7.20 WPS 6.3 - 7.5 6.86 0.41 6.65 7.07 WBR 6.1 - 7.4 6.78 0.31 6.72 6.83

PH WDR 6.5 - 8.7 7.25 0.75 7.05 7.45 (pH units) BAB 8.8 - 9.5 9.07 0.40 9.01 9.13 BOB 8.7 - 9.6 9.08 0.50 9.02 9.13 BNK 8.6 - 9.5 9.06 0.47 8.98 9.13 BAM 7.4 - 9.6 8.92 1.77 8.77 9.07 BNY 8.6 - 9.5 9.10 0.55 9.05 9.13

pH values for the Lake Bosomtwi as shown in Table 4.2 above ranged from 7.40 recorded in January at BAM to 9.60 recorded on two different occasions at BOB and

BAM with both of them being recorded in April. Annual values ranged from 8.92 recorded at BAM to 9.10 recorded at BNY. The lean periods had mean values ranging

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from 8.77 recorded at BAM to 9.02 recorded at BOB. Mean values for the peak periods also ranged from 9.07 recorded at BAM to 9.13 recorded at the four remaining sites of

BAB, BOB BNK and BNY. Monthly means were from 8.50 recorded in December to

9.50 recorded in June.

Generally the mean values recorded for the lean periods were slightly higher than those recorded for the peak periods. Variations between the sites as well as the periods were very minimal. Differences between the periods were insignificant for all the sites

(ANOVA p>0.05). With the exception of BAM which had a value of 7.40 in January, the remaining values were above acceptable limit for drinking water (WHO, 1993).

4.2.3 Conductivity As indicated in Table 4.3 below, conductivity values range from a low of 2.2µS/cm recorded at WUF during the lean period to a high of 101.1µS/cm recorded at WPS during the peak period. While the lowest value was recorded in October the highest was recorded in September .The annual mean values for the various sites ranged from a low of 23.95µS/cm to 70.42µS/cm recorded at WBR and WPS respectively.

Generally the values recorded at Wli Waterfalls during the peak periods were slightly higher than those of the lean periods. The difference between the peak and lean periods for WPS was a bit larger than that of the rest. The mean values for the lean periods ranged from 20.20µS/cm recorded at WBR to 56.18µS/cm recorded a WPS and that of the peak periods was from 26.92µS/cm to 84.65µS/cm recorded at WBR and WPS respectively. Monthly average was from 23.76µS/cm to 49.90µS/cm recorded in

November and July respectively.

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Even though the values did not show any specific pattern, the highest values for the various sites were recorded in September, probably due to the heavy down pour a day before the sampling date. All the values also fall below the natural background level of

700µS/cm for domestic use (UNESCO, 1987). Variability between the periods for some of the sites was not much with the difference between them not being significant. The difference between the periods at WPS and WBR were however significant (ANOVA p>0.05) with standard deviations of 13.72395 and 4.18505, and a standard error mean of

5.6078 and 1.70854 respectively for WPS and WBR.

Table 4.3: Mean, Range and Periodic Means for Conductivity Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 2.2 - 39.4 24.52 13.72 27.43 21.60 WLF 19.5 - 38.6 24.52 12.38 27.43 21.60 WPS 42.6 - 101.1 70.42 8.04 84.65 56.18 WBR 16.5 - 30.8 23.95 4.19 26.92 20.98 COND WDR 12.9 - 39.6 26.38 11.39 28.05 24.70 (µS/cm) BAB 1148 - 1381 1301.25 105.46 1335.17 1267.33 BOB 1048 - 1374 1264.99 124.75 1282.83 1247.17 BNK 1058 - 1376 1264.50 118.93 1281.50 1247.50 BAM 1038 - 1376 1281.50 385.18 1237.17 1199.33 BNY 1058 - 1375 1264.42 118.72 1281.50 1247.33

Conductivity values in the Lake Bosomtwi as indicated by Table 4.3 range from

1038µS/cm recorded in July at BAM to 1381µS/cm recorded in March at BAB. Annual means for the various site at Bosomtwi ranged from 1264.42µS/cm recorded at BNY to

1301.25µS/cm recorded at BAB.

The mean peak periods on the other hand had values ranging between 1237.17µS/cm recorded at BAM to 1335.17µS/cm recorded at BAB with the periodic means for the lean

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periods for the various sites ranged between 1199.33µS/cm recorded at BAM to

1267.37µS/cm recorded at BAB. Monthly means range from 1144.20µS/cm recorded in

August to 1375.24µS/cm recorded in April.

Values recorded for the peak periods were slightly higher than those recorded for the lean period. Again the values at BAB were slightly higher than those recorded at other sites.

This may be due to the fact that tourist congregate at that place more than the other sites.

Variability between the periods as well as among the sites was minimal. As a result differences between the periods at the various sites were insignificant (ANOVA p>0.05).

All the values recorded were far above the acceptable limit for drinking water (WHO,

1993).

4.2.4 Turbidity Turbidity values recorded at Wli Waterfalls ranged from a low of 5.12NTU recorded in

April at WPS to a high of 39.20NTU recorded in September at WLF as shown in Table

4.4 below. While the lowest was recorded during the lean period the highest was recorded during the peak period. The annual means for the various sites ranged from 13.69 recorded at WUF to a high of 20.57NTU recorded at the WPS. With the exception of

WPS which had a huge difference between the mean for the peak and lean periods, the differences in the mean periods of the other sites were minimal. The mean values for the peak periods ranged from a low of 15.38NTU recorded at WUF to a high of 28.31NTU recorded at WPS. The leans periods also recorded values ranging from 10.69NTU recorded at WLF to 12.83NTU recorded at WPS. Monthly means ranged from a low of

7.35NTU recorded in February to a high of 21.75NTU recorded in September.

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Generally the turbidity values did not show any specific pattern with the exception of

February which recorded very low values for all the sites. The peak periods also recorded the slightly higher values than those recorded for the lean periods for all the sites.

Variability between the lean and peak periods and among the site was minimal with the exception of the values recorded at WPS. The differences between the periods were all insignificant with the exception of WBR which was significant (ANOVA p>0.05) with a standard deviation and standard error mean of 1.63512 and 0.66754 respectively. All the values recorded were above the natural background level of 5NTU for drinking water

(WHO, 1993). Only the values recorded in February were very close to it.

Table 4.4: Mean, Range and Periodic Means for Turbidity Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 7.3- 17.5 13.69 45.33 15.38 11.99 WLF 5.5 - 39.2 14.74 9.20 18.78 10.69 WPS 5.1 - 29.5 20.57 4.52 28.31 12.83 WBR 7.1 - 17.9 14.05 1.64 15.63 12.46 TURB WDR 5.2 - 24.2 14.54 7.59 16.19 12.09 (NTU) BAB 3.3 - 18.1 7.26 2.91 8.80 5.71 BOB 3.9 - 9.2 6.29 6.13 7.46 5.11 BNK 3.1 - 12.0 6.38 3.30 7.35 5.38 BAM 2.9 - 9.0 6.05 2.92 6.55 5.55 BNY 3.0 - 12.0 6.36 3.29 7.34 5.38

Table 4.4 above indicates that turbidity values recorded for Lake Bosomtwi ranged between 2.9NTU recorded at BAM in April to 18.1NTU recorded at BAB in June.

Values recorded for the peak periods were slightly higher than that of the lean periods.

The periodic means for the various sites during the lean periods ranged from 5.11NTU recorded at BOB to 5.71NTU recorded at BAB. The peak periods had values ranging

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between 6.55NTU recorded at BAM to 8.80NTU recorded at BAB as the means for the various sites with monthly values ranging between 4.03NTU recorded in May at BAB to

18.08NTU recorded in June at BAB. Monthly means ranged from 3.14NTU recorded in

April to 9.38NTU recorded in June.

Values that were recorded at BAB were slightly higher than those recorded at the other sites. The values further decrease as one moves away from the tourist center at BAB.

Difference between the periods at the various sites were all insignificant (ANOVA p>0.05). Variability among the sites as well as between the periods was very minimal.

Almost all the values recorded were above the natural background level 5NTU acceptable for drinking water (WHO, 1993). The only exceptions are the values for April and May at

BAM and, April and June at BNY.

4.2.5 Total Dissolved Solids (TDS) The values for TDS at Wli Waterfalls as indicated in Table 4.5 below ranged from

8.60mg/L to 32.60mg/L all recorded at WPS. The lowest value was recorded in February during lean periods and the highest value was recorded in September during the peak periods. Annual mean values for the various sites ranged from 13.75mg/L recorded at

WBR to 15.28mg/L recorded at WDR. Means for the periods also ranged from

12.47mg/L recorded at WBR to 13.68mg/L recorded at WDR, and 14.55mg/L recorded at

WLF to 17.13mg/L recorded at WPS for lean and peak periods respectively. Monthly mean ranged from 11.96mg/L recorded in August to 20.96mg/L recorded in July.

Generally the values recorded for the peak periods were slightly higher than those recorded for the lean periods. Variations between the periods were very minimal with

WPS showing the greatest variation among sites. The difference between the periods 120

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were insignificant for all the sites with the exception of WDR (ANOVA p>0.05) with standard deviation of 2.96108 and standard error mean of 1.20886.

The values did not follow any specific pattern even though WDR recorded values higher than the others which may be attributed to the large number of the residents that converge at the place to fetch water at all time. All the values were however well below the natural background level of 1000mg/L for domestic use (WHO, 1993).

Table 4.5: Mean, Range and Periodic Means for TDS Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 10.6 - 18.4 15.03 4.44 15.53 13.10 WLF 10.3 - 18.4 13.96 3.41 14.55 13.42 WPS 8.6 - 32.6 15.03 3.52 17.13 12.93 WBR 10.2 - 17.6 13.75 3.01 15.02 12.47 TDS WDR 10.8 - 19.2 15.28 2.96 16.88 13.68 (mg/L) BAB 668 – 790 723.25 28.72 744.50 702.17 BOB 658 – 788 715.50 63.78 729.50 701.50 BNK 668 – 765 714.92 48.72 727.83 702.00 BAM 499 – 736 671.92 87.09 709.50 634.33 BNY 678 – 766 721.92 54.10 736.17 704.33

Even though TDS values recorded in the Lake Bosomtwi were high, they all fall below the WHO acceptable limit of 1000mg/L for drinking water. Even though the values recorded did not follow any specific pattern, all the values recorded in the months of

August, October and November was below 700mg/L for all the sites.

Again, even though the values recorded for the peak periods were slightly higher than that of the lean periods, variations between them as well as among the sites were minimal. As a result differences between the lean and peak periods for the various sites were all insignificant (ANOVA p>0.05) 121

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As indicated in Table 4.5 above, periodic means for TDS ranged from 634.37mg/L to

704.33mg/L recorded at BAM and BNY respectively for the lean periods and

709.50mg/L to 744.50mg/L recorded at BAM and BAB respectively for the peak periods.

Annual means for the various sites ranged from a low of 671.90mg/L to 723.25mg/L recorded at BAM and BAB respectively. Monthly means for the sites ranged from

636.22mg/L recorded in January to 746.40mg/L recorded in December.

4.2.6 Nitrate (NO3) Table 4.6 below indicates that nitrate values recorded at Wli Waterfalls ranged from

0.01mg/L recorded in five different months at WBR to 0.82mg/L recorded in November at WPS. The highest values of 0.82mg/L, as well as all the 0.10mg/L values were all recorded during the lean period. The lowest annual mean value of 0.03mg/L was recorded at WBR with the highest of 0.34mg/L recorded at WDR. This may be due to the presence of high number of locals in the area to fetch water for domestic use, leading to the contamination of the water body through washing and other and anthropogenic activities.

While the means for the lean periods ranges from a low of 0.02mg/L recorded at WBR, to a high of 0.28mg/L recorded at WLF, that of the peak periods ranged from 0.03mg/L also recorded at WBR to 0.41mg/L recorded at WDR. Monthly means ranged from 0.10mg/L recorded in February to 0.34mg/L recorded in December.

The values recorded did not follow any specific pattern with exception of WBR which recorded values lower than 0.05mg/L throughout the study period. This may be due to the very little human activities taking place there. Again the values recorded for the peak periods were slightly higher than those recorded for lean periods for all the sites.

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Table 4.6: Mean, Range and Periodic Means for NO3 Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.12 - 0.32 0.26 0.07 0.28 0.23 WLF 0.14 - 0.53 0.32 0.14 0.36 0.28 WPS 0.12 - 0.82 0.30 0.29 0.32 0.27 WBR 0.01 - 0.08 0.03 0.03 0.03 0.02

NO3 WDR 0.11 - 0.52 0.34 0.14 0.41 0.26 (mg/L) BAB 0.12 - 0.32 0.20 0.07 0.18 0.21 BOB 0.12 - 0.31 0.18 0.10 0.17 0.19 BNK 0.11 - 0.33 0.19 0.05 0.17 0.21 BAM 0.01 - 0.41 0.17 0.16 0.14 0.19 BNY 0.08 - 0.31 0.16 0.09 0.15 0.09

Variability between the peak and lean periods as well as among the sites was very minimal. The differences between the periods for the various site were all not significant with exception of WDR which was significant (ANOVA p>0.05) with a standard deviation and standard error mean of 0.13703 and 0.05594 respectively. All the values recorded were for below the acceptable limit of 10.0mg/L for drinking water (WHO,

1993).

Nitrate values for Lake Bosomtwi as shown in Table 4.6 range between 0.01mg/L recorded in March at BAM to 0.41mg/L also recorded at BAM in September. The lean periods with values ranging between 0.08mg/L recorded in June at BNY to 0.33mg/L recorded in August at BNK had mean values for the various sites ranging between

0.09mg/L recorded at BNY to 0.21mg/L recorded on two different occasions at BAB and

BNK. The peak periods also had values ranging between 0.01mg/L to 0.41mg/L, all recorded at BAM in March and September respectively. The mean values for the various sites during the peak periods ranged from 0.14mg/L recorded at BAM to 0.18mg/L

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recorded at BNK. Monthly means for the sampling period was from a low of 0.09mg/L recorded in March to 0.25 recorded in September. Annual means ranged from 0.16 recorded at BNY to 0.20 recorded at BAB.

Even though the values for March and May were slightly lower than those recorded for the other months, the values recorded for nitrate did not show any specific pattern. High and low values were recorded in both the lean and peak periods. However, all the values recorded were far below the acceptable limits for drinking water (WHO, 1993).

Variations among the values for the various sites as well as between the lean and peak periods were quite minimal with differences between the periods at the various sites all being insignificant (ANOVA p> 0.05).

4.2.7 Nitrite (NO2) The lowest values of 0.001mg/L were recorded on two different occasions at WUF and

WLF sites. The highest value of 0.081mg/L was also recorded in December at WDR. As indicated in the Table 4.7 below, the annual mean values for the various site ranged from

0.020mg/L recorded at WUF to 0.035mg/L recorded at WDR. There were very little differences between the values of the lean periods and the peak periods.

Periodic means ranged from 0.02mg/L recorded at four sites to 0.03mg/L recorded at

WDR for the lean periods. The peak periods on the other hand, had values of 0.02mg/L recorded at WUF to 0.04mg/L recorded on two different occasions at WBR and WDR.

Monthly mean ranged from 0.01mg/L to 0.05mg/L recorded in June and December respectively.

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All the values recorded fall within the natural background level of 10.0mg/L for drinking water (WHO, 1993). Variability between the periods and among the sites were however very minimal. The differences in the periods were all insignificant except that of WUF which was significant (ANOVA p>0.05) a standard deviation and standard error mean of

0.00866 and 0.00354 respectively.

Table 4.7: Mean, Range and Periodic Means for NO2 Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.001 - 0.027 0.020 0.01 0.02 0.02 WLF 0.001 - 0.039 0.025 0.01 0.03 0.02 WPS 0.011 - 0.054 0.025 0.02 0.03 0.02 WBR 0.011 - 0.061 0.030 0.03 0.04 0.02

NO2 WDR 0.022 - 0.081 0.035 0.01 0.04 0.03 (mg/L) BAB 0.013 - 0.068 0.035 0.01 0.04 0.03 BOB 0.016 - 0.039 0.025 0.01 0.03 0.02 BNK 0.012 - 0.072 0.025 0.01 0.03 0.02 BAM 0.011 - 0.035 0.020 0.03 0.02 0.02 BNY 0.011 - 0.055 0.025 0.01 0.03 0.02

The lowest values recorded for nitrite in the Lake Bosomtwi as shown in Table 4.7 above was 0.011mg/L recorded on two occasions in January and February at BNY and BAM respectively. The highest value on the other hand is 0.072mg/L recorded in October at

BNK. The highest values were recorded during peak periods and that of the lowest values were recorded at both periods. Annual means ranged from 0.020mg/L recorded at BAM to 0.035mg/L recorded at BAB. With values ranging between 0.011mg/L recorded at

BAM to 0.072mg/L recorded at BNK, the lean periods had means for the various sites ranging between 0.02mg/L recorded at four different sites 0.03mg/L recorded at BAB.

With the exception of BAB and BAM which recorded 0.04mg/L and 0.02mg/L as the

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highest and lowest mean for the peak periods respectively, the remaining three sites recorded 0.03mg/L as their means with values ranging between 0.011mg/L recorded at

BNY in January to 0.68mg/L recorded at BAB in July. Monthly means for the various sites ranged from 0.013mg/L recorded in February to 0.036mg/L recorded in October.

All the values recorded were far below the acceptable limit of 10.0mg/L for drinking water (WHO, 1993). Values recorded did not follow any specific pattern with both high and low values being recorded in both periods. Variations between the values were minimal among the sites and the periods. The difference between the periods of the various sites were therefore insignificant (ANOVA p>0.05).

4.2.8 Phosphate (PO4) Generally, most of the values recorded for phosphate at Wli Waterfalls, especially those at WDR and WDR were above the acceptable background level of 0.30mg/L. Even though there was no clear cut pattern with the values recorded, the peak periods recorded mean values that are slightly higher than that of the lean periods. Variability between the periods and among the sites was very minimal. The differences between periods at WPS was significant (ANOVA p>0.05) with the standard deviation and standard error mean of

0.8385 and 0.03423 respectively. The differences between the periods of the remaining sites were all insignificant.

Phosphate values from the Wli waterfalls as indicated in Table 4.8 below shows that it ranged from 0.05mg/L recorded in July at WLF to a high of 0.88mg/L recorded at WPS in December. Annual mean values ranged from 0.30mg/L recorded on two occasions at

WLF and WBR to a high of 0.38mg/L recorded at WPS.

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The values recorded for the peak periods were slightly higher than that of the lean periods with values ranging between 0.03mg/L recorded at WUF to 0.88mg/L record at WPS, and 0.14mg/L recorded at WPS to 0.48mg/L recorded at WDR for the peak and lean periods respectively. The mean values for the periods also ranged from 0.31mg/L recorded at WLF to 0.48mg/L recorded at WPS for the peak periods and 0.26mg/L recorded at WUF to 0.34mg/L recorded at WDR for lean periods. The monthly mean values ranged from 0.24mg/L recorded in September to 0.56mg/L recorded in October.

Table 4.8: Mean, Range and Periodic Means for PO4 Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.14 - 0.80 0.31 0.08 0.36 0.26 WLF 0.05 - 0.45 0.30 0.16 0.31 0.29 WPS 0.06 – 0.88 0.38 0.32 0.48 0.28 WBR 0.14 - 0.63 0.30 0.30 0.33 0.27

PO4 WDR 0.14 - 0.49 0.36 0.17 0.38 0.34 (mg/L) BAB 0.26 - 0.85 0.43 0.11 0.38 0.48 BOB 0.23 - 0.64 0.41 0.12 0.38 0.43 BNK 0.18 - 0.82 0.37 0.20 0.33 0.41 BAM 0.11 - 0.71 0.91 0.28 0.39 0.42 BNY 0.16 - 0.82 0.38 0.20 0.34 0.42

Phosphate values recorded for Lake Bosomtwi as indicated by Table 4.8 ranges between a low of 0.11mg/L recorded in July at BAM to a high of 0.85mg/L recorded in February at BAB. The lean periods had values ranging between 0.23mg/L recorded in June at BOB to 0.85mg/L recorded in February at BAB with means ranging between 0.41mg/L recorded at BNK to 0.48mg/L recorded at BAB. The peak periods had means ranging between 0.33mg/L recorded at BNK to 0.39mg/L recorded at BAM with values ranging between 0.11mg/L to 0.71mg/L with both of them recorded at BAM in May and March

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respectively. The monthly means ranged between 0.23mg/L to 0.62mg/L for May and

November respectively with annual means ranging between 0.37mg/L recorded at BMK to 0.91mg/L recorded at BAM.

Generally the values did not follow any specific pattern apart from the fact that all the values recorded in May for all the sites fell below the acceptable limit of 0.3mg/L for drinking water (WHO, 1993). Other months that recorded values below the acceptable limits are January at BNY, February at BNK, April at BNK and BNY, and July at BOB and BNK. Variations between the periods and among the sites were minimal making the difference between the periods at the various sites insignificant (ANOVA p>0.05).

4.2.9 Calcium (Ca) Generally variations between the periods at Wli Waterfalls were minimal with the peak periods recording values slightly higher than that of the lean periods. Mean values ranging between 1.63mg/L to 2.53mg/L were recorded at WLF and WDR respectively for lean periods as indicated in Table 4.9 below. The peak periods had mean values ranging from 2.03mg/L recorded at WUF to 2.60mg/L recorded at WR. All the values recorded were well below the acceptable natural background level for drinking water of

200mg/L (WHO, 1993). The difference between the periods for the various site were insignificant apart from that of WLF which was significant (ANOVA p>0.05) with a standard deviation of 0.53666 and standard error mean of 0.21909.

Whilst the lowest values were recorded in the lean periods, the highest value was recorded during the peak period. Annual means for all the sites ranged from low of

1.86mg/L recorded at WUF to 2.57mg/L recorded at WDR. Monthly means for calcium

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ranged from 1.52mg/L recorded in February to 2.88mg/L recorded in October. The highest value of 3.40mg/L was recorded in July with the lowest recorded on two different occasions in June and November. The highest was recorded in July probably due to the fact that there was flooding during that month which may have triggered weathering, thus allowing calcium in the rocks to be released.

Table 4.9: Mean, Range and Periodic Means for Ca Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 1.4 - 2.4 1.86 0.48 2.03 1.68 WLF 0.8 - 2.6 1.93 0.54 2.23 1.63 WPS 1.6 - 3.2 2.41 1.15 2.50 2.30 WBR 1.4 - 3.4 2.33 0.90 2.52 2.13 Ca WDR 1.6 - 3.2 2.57 0.73 2.60 2.53 (mg/L) BAB 6.4 - 44.1 20.73 11.39 22.95 18.50 BOB 6.2 - 43.1 20.22 11.01 22.17 18.27 BNK 6.2 - 40.4 17.23 5.47 19.53 14.90 BAM 2.8 - 40.4 19.94 8.05 24.90 14.97 BNY 6.3 - 40.4 17.27 5.47 19.58 14.95

Calcium values recorded in the Lake Bosomtwi as shown in Table 4.9 starts from

2.80mgvalues/L recorded in November at BAM to 44.10mg/L recorded in October at

BAB. Annual means for the various sites range from 17.20mg/L recorded at BNY to

20.73mg/L recorded at BAB. Monthly means also ranged from a low of 6.50mg/L recorded in March to 40.80mg/L recorded in September. With values ranging between

2.80mg/L and 44.10mg/L recorded in November and October respectively at BAM the lean periods had means for the various site ranging between 14.90 mg/L recorded at

BNK to 18.50mg/L recorded at BAB. The peak periods had values ranging between 6.20 mg/L recorded at BNK in March to 42.40mg/L recorded in July at BAB with periodic

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means values for the various sites ranging between 19.53mg/L to 24.90mg/L recorded at

BNK and BAM respectively.

Generally the values recorded did not follow any specific pattern with the exception of

July which recorded values above 40.30mg/L for all the sites. High and low values were recorded for both periods. Even though variations between them were quite large, differences between the periodic and annual means were quite minimal. The difference between the periods at BAM was however, significant (ANOVA p>0.05) with standard deviation and standard error mean of 8.05299 and 3.28762 respectively.

4.2.10 Magnesium (Mg) Magnesium values for Wli Waterfalls as shown in Table 4.10 ranged from 0.50mg/L recorded at two different locations at WUF and WLF all in July to 4.80mg/L recorded in

October at WPS. The minimum values were recorded in the lean periods and the highest values were recorded during the peak period. Annual means for the various sites ranged from 1.17mg/L recorded at WBR to 2.94mg/L recorded at WPS. With values ranging between 0.60mg/L recorded in October at WLF to 4.80mg/L also recorded in October at

WPS, the peak periods had values ranging between 1.28mg/L recorded at WPR to

3.37mg/L recorded at WPS as means for the various sites. The lean periods also had mean values ranging between 1.02mg/L recorded at WUF to 2.50mg/L recorded in

March at WPS. Monthly means ranged from 1.04mg/L recorded May to 2.02mg/L recorded in November.

Table 4.10 below shows that all the Magnesium values recorded in the Lake Bosomtwi were far below the acceptable limit for drinking water (WHO, 1993). Generally values recorded for Magnesium in the Lake Bosomtwi did not follow any specific pattern with

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high and low values being recorded during both periods and sites. The values recorded for the peak periods were however, slightly higher than those recorded for the lean periods. Variations between the periods and the sites as well as among the values recorded were very minimal. Difference between the periods for the various sites were therefore insignificant (ANOVA p>0.05)

Table 4.10: Mean, Range and Periodic Means for Mg Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.5 - 1.8 1.26 0.49 1.50 1.02 WLF 0.5 - 1.5 1.28 0.65 1.33 1.23 WPS 2.1 - 4.8 2.94 0.89 3.37 2.5 WBR 0.6 - 1.8 1.17 0.52 1.28 1.05 Mg WDR 1.2 - 1.6 1.55 0.23 1.63 1.47 (mg/L) BAB 12.4 - 38.9 19.09 2.09 21.17 17.01 BOB 12.6 - 24.3 17.08 4.07 17.72 16.43 BNK 12.6 - 20.6 14.87 10.07 15.47 14.27 BAM 10.1 - 41.3 17.49 11.06 19.53 15.45 BNY 10.7 - 43.7 18.99 14.58 20.21 17.77

With values ranging between 10.10mg/L recorded in December at BAM to 43.70mg/L recorded in January at BNY, annual means for the various sites ranged between

14.87mg/L recorded at BNK to 19.09mg/L recorded at BAM. Monthly means ranged from a low of 12.60mg/L recorded in September to 32.96mg/L recorded in January.

Monthly values ranging between 10.10mg/L recorded at BAM in December to

31.60mg/L recorded in July also at BAM.

4.2.11 Potassium (K) At Wli Waterfalls, potassium values as indicated in Table 4.11 ranged between 0.30mg/L and 1.70mg/L were recorded at WUF and WLF respectively. The lean periods had values

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ranging from 0.50mg/L recorded on two different occasions to 1.60mg/L. The highest was recorded in December at WDR and the lowest were all recorded in August at WUF and WLF.

Table 4.11: Mean, Range and Periodic Means for K Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.3 - 1.3 0.75 0.31 0.82 0.68 WLF 0.4 - 1.7 0.94 0.72 1.02 0.85 WPS 0.7 - 1.4 0.98 0.35 1.03 0.93 WBR 0.6 - 1.3 0.88 0.21 0.93 0.82 K WDR 0.9 - 1.6 1.06 0.26 1.10 1.02 (mg/L) BAB 20.6 - 26.2 22.93 2.69 23.10 22.75 BOB 10.1 - 25.5 22.49 5.88 23.47 21.50 BNK 6.3 - 25.4 18.82 7.39 19.10 18.53 BAM 6.2 - 24.8 18.95 6.36 19.34 18.55 BNY 4.3 - 25.4 18.65 7.95 19.52 17.77

The peak periods on the other hand had values ranging between 0.30mg/L recorded in

September at WUF to 1.70mg/L also recorded in September at WLF. The means for the periods also ranged from 0.82mg/L recorded at WUF and WBR to 1.10mg/L recorded at

WDR, and 0.68mg/L recorded at WUF to 1.02mg/L recorded at WDR for the peak and lean periods respectively. Annual means ranged from0.75mg/L recorded at WUF to

1.06mg/L recorded at WDR. Monthly means were from 0.80mg/L recorded in June to

1.10mg/L recorded in July.

Potassium values recorded did not show any specific pattern. Variations between the sites and periods were very minimal. Difference between the periods of the various sites were all insignificant (ANOVA p>0.05). All the values recorded were far below the acceptable

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limit of 200mg/L for drinking water (WHO, 1993). The peak periods had values slightly higher than those of the lean periods.

All the values recoded for Potassium in the Lake Bosomtwi as shown in Table 4.11 falls below the acceptable limit of 200mg/L for drinking water (WHO, 1993). The values did not follow any specific pattern with both high and low values being recorded in the two periods.

The values for the peak periods were slightly higher than those recorded for the lean periods. Variations between the values, the periodic means, as well as the annual means were very minimal resulting in the differences between the periodic means of all the sites being insignificant (ANOVA p>0.05).

Potassium values for Lake Bosomtwi ranged from 4.30mg/L to 26.20mg/L all recorded in

May at BNY and BAB respectively. The peak periods recorded mean values ranging between 19.10mg/L and 23.47mg/L recorded at BNK and BOB respectively. These were higher than the values ranging between 17.77mg/L to 22.75mg/L recorded at BNK and

BAB respectively for the lean periods. Monthly means ranged from 10.60mg/L to

24.20mg/L recorded in April and October respectively with annual means also ranging between 18.70mg/L recorded at BNY to 22.90mg/L recorded at BAB.

4.2.12 Chlorine (C l) As shown in Table 4.12, chloride values recorded at Wli Waterfalls were low with very little minimal variations between them. The lowest of 2mg/L was recorded at all the sites during both periods and every month except October and November. The highest value of

5mg/L was recorded on three different occasions with two of them being recorded in

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November at WPS with the remaining one in May at WDR. Annual means for the various sites ranged from 2.66mg/L recorded at WBR to 3.32mg/L recorded at WPS. Monthly means ranged from 2.4mg/L recorded in both March and September to4.40mg/ L recorded in November.

Differences between the periods of the various sites were very minimal with all of them being insignificant (ANOVA p>0.05). The values for the peak periods were between

2mg/L recorded at all the sites to 5mg/L recorded in November at WPS and WDR with its periodic means ranging between 2.83mg/L recorded at WBR to 3.33mg/L recorded at

WPS. The lean periods also had values ranging between 2mg/L recorded at all the sites to

5mg/L recorded in May at WPS with its periodic means ranging between 2.52mg/L recorded at WBR to 3.33mg/L recorded at WPS. All the values recorded were far below the acceptable limit of 200mg/L above which the salty taste of the water may be affected

(WHO, 1993)

Table 4.12: Mean, Range and Periodic Means for Cl Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 2.0 - 4.0 2.84 0.82 3.01 2.67 WLF 2.0 - 4.0 2.92 0.98 3.01 2.83 WPS 2.0 - 5.0 3.32 0.82 3.33 3.33 WBR 2.0 - 5.0 2.67 1.03 2.83 2.52 Cl WDR 2.0 – 4.5 2.66 1.27 3.01 2.33 (mg/L) BAB 101 – 164 116.58 31.23 121.33 111.83 B OB 108 – 152 117.75 15.26 122.50 113.01 BNK 101 – 144 119.34 23.87 125.01 113.50 BAM 100 – 149 114.10 20.79 117.01 111.01 BNY 102 – 154 123.50 20.73 126.83 120.17

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Chloride values for the Lake Bosomtwi ranged between 101mg/L recorded in May at

BAM to 164mg/L recorded in November at BAB as shown in Table 4.12. Annual means range from a low of 114mg/L recorded at BAM to 123mg/L recorded at BNY. Monthly means ranged from 107mg/L recorded in April to 139mg/L recorded in January. Values recorded for the peak periods, ranging between 117mg/L recorded at BAM to 126mg/L recorded at BNY slightly higher than those recorded for the lean periods ranged between

111mg/L recorded at BAM to 120mg/L recorded in BNY.

Generally the chloride values recorded at the Lake Bosomtwi did not follow any specific pattern with both high and low values being recorded in both the lean and peak periods.

The values though high fall below the acceptable limit of 200mg/L for drinking water

(WHO, 1993). Variations between the values among the sites and between the periods were minimal even though the difference between the highest and the lowest values was quite huge. The difference between the periods for the various sites were not significant

(ANOVA p>0.05).

4.2.13 Sodium (Na) Sodium values recorded at Wli Waterfalls as shown in Table 4.13 ranged from 0.50mg/L recorded at WBR in March to 3.80mg/L recorded at WLF in May with both of them being recorded during the peak periods. Annual means for the various sites ranged from

2.01mg/L recorded at WUF to 2.40mg/L recorded at WLF. Monthly means also ranged from a low of 1.12mg/L recorded in March to 3.20mg/L recorded in October. The p eak periods had values ranging between 1.10mg/L recorded in June at WDR to 3.70mg/L recorded at two different locations in December at WLF and WPS with the peak periods mean values ranging from 2.13mg/L recorded at WBR to 2.85mg/L recorded WLF.

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With values ranging between 0.30mg/L recorded at WBR in March to 3.80mg/L recorded at WLF in May, the lean periods had means for the various sites ranging between

1.72mg/L recorded at WUF to 2.17mg/L recorded at WPS. Generally, sodium values recorded for the waterfalls did not follow any specific pattern even though the values recorded during the peak periods were slightly higher than that of the lean periods.

Variations between the periods and sites as well as among the values recorded were very minimal.

Table 4.13: Mean, Range and Periodic Means for Na Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 1.2 - 2.8 2.01 0.37 2.28 1.72 WLF 0.8 - 3.8 2.40 1.28 2.85 1.95 WPS 0.8 - 3.7 2.24 1.54 2.30 2.17 WBR 0.5 - 3.5 2.08 1.28 2.13 2.02 Na WDR 1.1 - 3.3 2.18 1.04 2.33 2.02 (mg/L) BAB 171 – 292 198.92 44.90 202.67 195.17 BOB 110 – 263 181.17 17.46 183.00 179.33 BNK 106 – 271 166.67 57.25 172.67 160.67 BAM 121 – 267 173.59 28.53 178.00 169.17 BNY 105 – 272 163.34 55.04 170.10 156.67

Difference between the periods were however significant (ANOVA p>0.05) only at WUF with standard deviation of 0.36697 and a standard error mean of 0.14981. All the values recorded during the sampling period were far below the acceptable limit of 200mg/L for drinking water (WHO, 1993).

Sodium values recorded in Lake Bosomtwi as indicated in Table 4.13 ranged from

105.01mg/L recorded in April at BNY to 292.10mg/L recorded in October at BAM. Both

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values were recorded during the lean period. Values ranging between 105.01mg/L at

BNY to 292.11mg/L BAM were recorded for the peak periods with its means values for the various sites ranging between 170.10mg/L recorded at BNY to 202.7mg/L recorded at

BAM. The lean periods had values ranging between 10.10mg/L recorded at BNK in

March to 288.11 recorded at BAM in December with its periodic means ranging between

156.67mg/L recorded at BNY to 195.17mg/L recorded at BAM. Monthly means ranged from 118.40mg/L recorded in March to 273.01mg/L recorded in November. Annual means ranged from a low of 163.34mg/L recorded at BNY to 198.92mg/L recorded at

BAM.

Values recorded did not follow any specific pattern with both high and low values recorded at both periods and at all the sites. Even though the values recorded were quite high, most of them fell below the acceptable limit for drinking water (WHO, 1993).

Again variations among the values are quite high but this did not reflect in the variations between periods and among the sites. As a result the differences between the periods were all insignificant (ANOVA p>0.05).

4.2.14 Fluoride (F-) As indicated in Table 4.14, fluoride values at Wli Waterfalls ranged between 0.01mg/L recorded at WUF in July to 0.82mg/L recorded WLF in April. The highest value was recorded during the lean periods and the lowest during the peak periods. The lean periods had values ranging between 0.01mg/L recorded at WUF to 0.82mg/L recorded at WLF with its periodic means ranging between 0.17mg/L recorded at WDR to 0.37mg/L recorded at WUF. The peak periods also had values between 0.01mg/L recorded at WUF to 0.68mg/L recorded at WBR with its periodic means ranging between 0.13mg/L

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recorded at WDR to 0.23mg/L recorded at WBR. Annual means for fluoride ranged from

0.15mg/L recorded at WDR to 0.27mg/L recorded at WUF. Monthly means ranged from a low 0.01mg/L recorded in January, July, October, November and December to high at

0.74mg/L recorded in June. February, March, April and May recorded high value at above 0.35mg/L for all the sites with the remaining months recording very low marks of

0.01mg/L and below. As a result of the above variations between the months were very high. The variations between the periods as well as between the sites were minimal.

Differences between the periods were all insignificant (ANOVA p>0.05). Values recorded for the lean periods were slightly higher than that of the peak periods. However the difference at WUF and WLF were quite higher than that of WPS, WBR, and WDR.

Table 4.14: Mean, Range and Periodic Means for F- Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.01 - 0.73 0.27 0.20 0.17 037 WLF 0.01 - 0.82 0.24 0.20 0.31 0.16 WPS 0.01 - 0.79 0.20 0.09 0.22 0.17 WBR 0.01 - 0.78 0.24 0.05 0.25 0.23 F- WDR 0.01 - 0.60 0.15 0.08 0.13 0.17 (mg/L) BAB 0.07 - 0.67 0.37 0.27 0.38 0.36 BOB 0.10 - 0.79 0.34 0.38 0.41 0.27 BNK 0.10 - 0.80 0.35 0.41 0.37 0.32 BAM 0.05 - 0.64 0.32 0.18 0.32 0.31 BNY 0.07 - 0.63 0.37 0.22 0.39 0.34

Values for fluoride in the Lake Bosomtwi ranged from a low of 0.05mg/L recorded in

October at BAM to a high of 0.80mg/L recorded in March at BOB as shown in Table

4.14. Annual mean values for the various sites range from 0.32mg/L recorded at BAM to

0.37mg/L recorded at BAB and BNY. The lean period had values ranging between

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0.05mg/L recorded in October at BAM to 0.67mg/L recorded in August at BAB with periodic means for the various sites ranging between 0.27mg/L recorded at BOB to

0.36mg/L recorded at BAB.

With values ranging between 0.07mg/L recorded in December at BAM to 0.80mg/L recorded in March at BOB, the peak periods had means ranging between 0.32mg/L and

0.41mg/L recorded at BAM and BOB respectively. The monthly means also ranged between 0.24mg/L to 0.55mg/L recorded in October and December respectively.

Generally the values recorded for fluoride did not follow any specific pattern with both the lean and peak periods recording high and low values. However values lower than

0.10mg/L were recorded at BAM and BNY in October and BAB in November. Even though variations between values were quite substantial, the variations between periods were very minimal leading to the differences between the periods of all the sites being insignificant (ANOVA p>0.05).

4.2.15 Alkalinity Alkalinity values recorded at Wli Waterfalls ranged from a low of 7.20mg/L recorded in

July at WPS to a high of 14.50mg/L recorded in November at WUF. The highest value was recorded in a peak periods whilst that of the lowest value was recorded in the lean periods. Annual mean values for the sites ranged from 8.84mg/L recorded at WBR to

10.88mg/L recorded at WUF. With the exception of WBR, the mean values recorded during lean periods were slightly higher than that of the peak periods with values ranging from 8.93mg/L to 11.50mg/L and 8.75mg/L to 10.25mg/L being the means for peak and lean periods respectively as shown in Table 4.15 below

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With the exception of August which recorded the lowest values for all the sites, the values for alkalinity did not follow any specific pattern for the entire periods of sampling.

Monthly mean for all the sites ranged from a low of 8.84mg/L recorded in August to

10.92mg/L recorded January. All the values and its mean fell below the acceptable limit of 20mg/L for drinking water (WHO, 1993). Variability between the values was very minimal with the difference between the periods for all the sites being insignificant.

Table 4.15: Mean, Range and Periodic Means for Alkalinity Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 8.4 - 14.5 10.88 2.52 11.5 10.25 WLF 8.1 - 10.2 9.09 0.78 9.33 8.85 WPS 7.2 - 10.4 9.18 1.10 9.43 8.93 WBR 8.2 - 9.2 8.84 0.70 8.75 8.93 Alkalinity WDR 8.2 - 10.4 9.40 1.26 9.82 8.97 (mg/L) BAB 346 – 450 399.50 42.25 409.67 389.33

BOB 319 – 450 385.06 65.01 404.67 365.50 BNK 322 – 450 382.42 68.89 397.17 367.67 BAM 322 – 532 396.50 76.20 423.33 369.67 BNY 312 – 448 378.92 62.89 398.50 359.33

Alkalinity values from Lake Bosomtwi ranged from 312mg/L recorded in January at

BNY to 532mg/L recorded in November at BAM as shown in Table 4.15 above. The highest was recorded during the lean periods and lowest on the other hand was recorded during the peak period. With values ranging between 340mg/L and 532mg/L all recorded at BAM in August and November respectively, the lean periods had values that were slightly higher than those recorded during the peak periods. The peak periods also had values ranging between 322mg/L recorded in January at BNY to 424mg/L recorded in

December at BAB.

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The mean values for the periods were also from 359.30mg/L to 389.20mg/L and

397.20mg/L to 423.30mg/L for the peak and lean periods respectively. Monthly means also ranged from 344.40mg/L recorded in December to 448.10mg/L recorded in June.

Values ranging between 378.90mg/L to 399.30mg/L were also recorded at BNY and

BAM respectively as annual means.

Even though values recorded for the months of June, August and October all fall below the 400mg/L for all the sites, there was no clear cut pattern in the values recorded for alkalinity in the Lake Bosomtwi. All the values recorded at all the sites were far above the acceptable limit of 20mg/L for drinking water (WHO, 1993). Variability among the value of the various sites as well as between the periods was minimal with both high and low values being recorded during both periods. The differences between the periods were insignificant at all the sites (ANOVA p> 0.05).

4.2.16 Total Hardness Total hardness values at Wli Waterfalls as indicated in Table 4.16 ranged from 4.20mg/L recorded in October at WLF to 20.30mg/L recorded in September at WUF. Annual mean values for the various sites ranged from a low of 10.10mg/L recorded at WLF to a high of

12.80mg/L recorded at WDR. Most of the values recorded in the peak periods were slightly higher than those recorded for lean periods. Values ranging from 4.20mg/L recorded in October at WLF to 14.3mg/L recorded in August at WDR, and 6.2mg/L recorded in July at WLF to 20.30mg/L recorded in September at WUF were for the lean and peak periods respectively.

Periodic means ranging from 9.82mg/L at WLF to 12.33mg/L at WDR and 10.22mg/L at

WLF to 14.45mg/L at WUF were recorded for lean and peak periods respectively at the 141

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various sites. Monthly means are from a low of 8.70mg/L in August to a high of

15.40mg/L in December.

Generally the values recorded for total hardness did not follow any specific pattern except that August recorded the lowest values for all the sites. Also variability between the periods and among the sites were minimal with WUF showing the highest variability.

Differences between the periods for all the sites were insignificant except the WUF which was significant at (ANOVA p>0.05) with standard deviation and standard error mean of 1.92709 and 0.78673 respectively. All the values recorded fall far below the acceptable limit of 500mg/L for drinking water (WHO, 1993).

Table 4.16: Mean, Range and Periodic Means for Total Hardness Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 6.1 - 20.3 12.36 1.93 14.45 10.27 WLF 4.2 - 14.6 10.02 4.32 10.22 9.82 WPS 10.1 - 18.1 12.04 4.16 12.42 11.65 WBR 8.2 - 19.1 11.76 3.12 12.52 11.01 T. HARD WDR 10.1 - 18.5 12.80 3.25 13.27 12.33 (mg/L) BAB 74.6 - 270.1 134.91 47.32 149.27 120.55 BOB 72.1 - 166.3 120.07 23.41 126.58 113.55 BNK 70.4 - 190.1 122.73 15.63 127.88 117.58 BAM 70.2 - 220.2 129.03 58.39 141.53 116.52 BNY 72.5 - 170.4 125.84 30.07 131.62 120.05

Total hardness values from the Lake Bosomtwi were from 70.20mg/L recorded in March at BAM to 270.07mg/L recorded in December at BAB as indicated in Table 4.16 above.

Annual means for the various sites ranged from 120.10mg/L recorded at BOB to

134.91mg/L recorded at BAB. Monthly means also ranged from 72.80mg/L recorded in

March to 180.20mg/L recorded in December. The lean periods had values ranging

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between 72.10mg/L recorded in April at BOB to 190.10mg/L recorded in July at BAM with its periodic mean values for the various sites ranging between 113.55mg/L to

120.55mg/L recorded at BOB and BAB respectively. The peak periods on the other hand had values ranging between 70.20mg/L recorded in March at BAM to 270.10mg/L recorded in December at BAB with its periodic means ranging between 126.56mg/L and

149.27mg/L recorded at BOB and BAM respectively.

Even though all the values recorded were below the acceptable limit of 500mg/L for drinking water (WHO, 1993), a large number of them were above 100mg/L. With values ranging between 70.20mg/L and 270.10mg/L, variations between the values were quite higher. The variations between the periodic as well as among the annual means were however very minimal leading to all the differences between the means of the periods being insignificant (ANOVA p>0.05).

4.2.17 Ammonium (NH3) Ammonium had values less than 0.001mg/L recorded for all the sites at Wli Waterfalls and Lake Bosomtwi throughout the sampling period. It was therefore impossible to analyze for the significance level of the difference between the periods with all means being the same.

4.3 Trace Metals Analysis 4.3.1 Manganese (Mn) Even though 0.06mg/L and 0.07mg/L were recorded for manganese at WUF and WLF in

February, majority of the values recorded at Wli Waterfalls were below the acceptable limit of 0.05 mg/L. As SHOWN in Table 4.17 below, all the annual, monthly and

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periodic means were below the acceptable limit for drinking water (WHO, 1993) with none of the differences between the periods being significant (ANOVA p>0.05).

Table 4.17: Mean, Range and Periodic Means for Manganese Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEAN DEV'TION PEAK LEAN W. UF 0.02 - 0.06 0.05 0.02 0.05 0.04 W. LF 0.01 - 0.07 0.04 0.02 0.04 0.04 W. PS 0.01 - 0.05 0.03 0.02 0.03 0.03 W. BR 0.01 - 0.04 0.03 0.01 0.03 0.03 Mn W. DR 0.01 - 0.05 0.03 0.03 0.03 0.02 B. AB 0.01 - 0.02 0.01 0.01 0.01 0.01 B. OB 0.01 - 0.02 0.02 0.01 0.02 0.01 B. NK 0.01 - 0.02 0.01 0.00 0.01 0.01 B. AM 0.01 - 0.03 0.02 0.01 0.02 0.01 B. NY 0.01 - 0.02 0.01 0.01 0.01 0.01

As indicated in Table 4.17 above, manganese levels recorded in the Lake Bosomtwi were very low with the highest value being 0.03mg/L. Most of the values fell below 0.01mg/L, and this made the variations among them very minimal. Mean values for the periods were the same for most of the sites. The difference between those that were not the same were so minimal that the differences between the periods for the various sites were all insignificant (ANOVA p>0.05)

4.3.2 Iron (Fe) Iron values recorded for the various sites at Wli Waterfalls as indicated in the Table 4.18 below ranged from 0.10mg/L to 6.20mg/L. Whilst the highest was recorded only once at

WPS in February that of the lowest was recorded on five different occasions with two each at WLF and WPS and the remaining one at WUF with three of them having been recorded in November and the other two recorded in December. Monthly mean also

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ranged from 1.60mg/L recorded at WLF to 2.90mg/L recorded at WDR. Values ranging from 0.10mg/L to 6.20mg/L were recorded for the lean periods with a mean range of between 1.10mg/L to 2.88mg/L recorded for the various sites. The lowest was recorded at

WLF and the highest at WDR. The peak periods had values ranging between 0.1mg/L to

5.80mg/L with a mean range of between 1.70mg/L to 3.10mg/L. The highest was recorded at WDR and the lowest at WUF. Differences between the monthly means for all sites were quite high ranging from 0.82 mg/L recorded in January to 4.50mg/L recorded in March.

All the values recorded were above the acceptable limit of 0.03mg/L for drinking water.

Even though the values recorded did not follow any particular pattern, values recorded for WDR and WPS were a bit higher than the rest. This may be as a result high weathering due to high attrition at the place as a result of high anthropogenic activities by tourist and local residents alike at both WDR and WPS. The differences between the periods for the various sites were insignificant. This may be due to the minimal nature of the difference between them.

Table 4.18: Mean, Range and Periodic Means for Fe Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 0.1 - 4.2 1.72 1.26 1.97 1.47 WLF 0.1 - 5.2 1.64 2.43 2.18 1.10 WPS 0.1 - 6.2 2.57 2.01 2.93 1.97 WBR 0.3 - 4.8 1.87 1.31 2.6 1.13 Fe WDR 1.6 - 5.2 2.97 1.95 3.05 2.88 (mg/L) BAB 0.1 - 0.3 0.21 0.02 0.25 0.17 BOB 0.1 - 0.2 0.12 0.02 0.13 0.10 BNK 0.1 - 0.2 0.13 0.02 0.13 0.12 BAM 0.1 - 0.3 0.12 0.03 0.13 0.10 BNY 0.1 - 0.4 0.15 0.05 0.17 0.13

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Iron value for the Lake Bosomtwi as indicated in Table 4.18 ranged between 0.1mg/L recorded on two different occasions (April and May) at all the sites to 0.40mg/L recorded in March at BAB. Annual means for the various sites at Bosomtwi ranged from 0.12mg/L recorded at BAM and BOB to 0.21mg/L recorded at BAB. The lean periods had an average range of between 0.10mg/L recorded at BAM and BOB to 0.17mg/L recorded at

BAB. The peak periods also means ranging between 0.13mg/L recorded at BOB, BNK and BAM to 0.25mg/L recorded at BAM. Monthly means ranged from 0.09mg/L recorded in September to 0.23mg/L recorded in February.

Even though values recorded for iron in the Lake Bosomtwi did not follow any specific pattern, the values for the peak periods were slightly higher than those recorded for the lean periods. Variety between the periods at the various sites as well as between the sites were minimal with the differences between the periods being insignificant (ANOVA p>0.05) for all the sites. With the exception of the values recorded in March, April, and

May at BAM, all the remaining values recorded during the sampling period were below the acceptable limit of 0.3mg/L for drinking water (WHO, 1993).

4.3.3 Copper (Cu), Lead (Pb), Cadmium (Cd) and Zinc (Zn) Values recorded for copper, lead and cadmium at Wli Waterfalls were all below the

WHO natural background levels of 1.00mg/L, 0.05mg/L and 0.003mg/L respectively.

Values recorded for the various sites were also the same throughout the sampling period.

Whilst 0.020mg/L was recorded for Copper, 0.005mg/L and 0.002mg/L were recorded for lead and cadmium respectively. As a result differences between the periodic means

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could not be calculated. In the case of Zinc even though there were little variations between the values recorded for the various sites the differences were very minimal with almost all the values falling below 0.01mg/L. The differences between the periods were so minimal that none of them were significant (ANOVA p>0.05).

Values recorded for copper, lead and cadmium in the Lake Bosomtwi were all below the acceptable limit of 1.00mg/L, 0.05mg/L and 0.003mg/L respectively for drinking water

(WHO, 1993). Values recorded for the various sites were also the same throughout the sampling period. Whilst 0.020mg/L was recorded for Copper, 0.005mg/L and 0.002mg/L were recorded for lead and cadmium respectively. As a result differences between the periodic means could not be calculated. Values recorded for zinc on the other hand even though had, some variations among them, they were so minimal that the periodic means were either the same or almost the same for all the sites. The differences between them were therefore insignificant (ANOVA p>0.05).

4.4 Bacteriological Analysis 4.4.1 Total Coliforms As indicated in Table 4.19 below, total coliforms values from Wli Waterfalls ranged from 505cfu/100mL recorded in April at WUF to 2418cfu/100mL recorded in July at

WPS. The lowest was recorded during the lean periods and the highest was recorded during the peak periods. Annual mean for the various site ranged from a low of

895cfu/100mL to 1602cfu/100mL recorded at WUF and WBR respectively.

Values recorded for the various periods ranged from 505cfu/100mL recorded in April at

WUF to 1642cfu/100mL recorded in January and 605cfu/100mL recorded in May to

2418cfu/100mL recorded in September for the lean and peak periods respectively. The

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periodic means also ranged from 835cfu/100mL recorded at the WUF to 1285 recorded at

WBR for the lean periods and 949cfu/100mL to 1920cfu/100mL recorded at WBR for the peak periods. Monthly means for the various sites were from 709cfu/100mL to

1657cfu/100mL recorded in February and July respectively.

Table 4.19: Mean, Range and Periodic Means for Total Coliforms Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 505 – 1345 895 53.25 949 835 WLF 642 – 1555 1014 374.98 1132 895 WPS 742 – 2418 1489 1012.59 1692 1287 WBR 898 – 2208 1602 370.14 1920 1285 T. COLI WDR 792 – 1886 1225 773.74 1388 1063 (cfu/100mL) BAB 998 – 2046 1489 399.15 1550 1428 BOB 559 – 2603 1266 612.29 1288 1243 BNK 554 – 1962 1116 555.18 1205 1027 BAM 588 – 1876 1248 437.71 1299 1197 BNY 558 – 2594 1242 728.01 1402 1083

Even though the total coliforms values did not follow any specific pattern, values recorded on sampling days that fell on or immediately after heavy down pours were quite high. Again values recorded for the peak periods were slightly higher than those recorded for the lean periods. Variations between the periods were minimal with the exception of

WPS which may be due to the presence of large number of tourist on public holidays.

Differences between the periods were not significant at WLF, WBR and WDR. There were however, highly significant at WUF and WPS with standard deviation of 53.24534 and 370.14290 respectively. The standard error means were 21.73732 and 151.11021 respectively for WUF and WPS. All the values recorded were above the WHO acceptable limit of 0cfu/100mL.

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Total coliforms values recorded for the Lake Bosomtwi ranged from a low of

554cfu/100mL recorded in February at BNK to a high of 2603cfu/100mL recorded in

September at BOB as indicated in Table 4.19. Annual means for the various sites ranged from 1116cfu/100mL recorded at BNK to 1489cfu/100mL recorded at BAB. The lean periods had means ranging between 1027cfu/100mL recorded at BNK to 1428cfu/100mL recorded at BAB. Means values for the various sites ranged from 1205cfu/100mL recorded at BNK to 1550cfu/100mL recorded at BAB. Monthly means ranged from

763cfu/100mL recorded in February to 1980cfu/100mL recorded September.

Even though high and low figures were recorded in both the lean and peak periods, values for the peak periods were slightly higher than those recorded for the lean periods.

This may be attributed to the increase in anthropogenic activities by both tourist an residents in and around the Lake Bosomtwi during the peak periods. The variations between the values for the periods as well as among the sites were not very much. This resulted in the differences between the periods for all the sites being insignificant

(ANOVA p>0.05). Values recorded for all the sites during both periods were far above the acceptable level of 0cfu/100mL for drinking water (WHO, 1993).

4.4.2 Fecal Coliforms Generally, fecal coliforms values recorded at all the sites at Wli Waterfalls were above acceptable limit of 0cfu/100mL for drinking water (WHO, 1993). Values recorded did not follow any specific pattern. Values for the peak periods were however slightly higher than those recorded for the lean periods. Again WPS recorded values higher than the other sites. This may probably be due to the high presence of tourist at the site as

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compared to the other sites. The vice versa may be true for WUF which recorded low values as compared to the other sites throughout the sampling period. Difference between the periods were also very minimal with only WUF being significant (ANOVA p>0.05).

The standard deviation and standard error mean for WUF were 25.18465 and 10.28159 respectively

As shown in the Table 4.20 below fecal coliforms values recorded for all the sites ranged from 108cfu/100mL recorded at WLF in December to 1488cfu/100mL recorded at WPS in December. Annual means for the various sites was from a low of 270cfu/100mL recorded at WUF to a high of 654cfu/100mL recorded at WPS. Differences between monthly means were quite high with February recording the lowest of 155cfu/100mL to the highest of 730cfu/100mL recorded in May. Means for the lean periods were slightly lower than that of the peak periods with values ranging between 236cfu/100mL to

590cfu/100mL and 304cfu/100mL to 718cfu/100mL for the lean and peak periods respectively..

Fecal coliforms values recorded for Lake Bosomtwi at various sites were far above the acceptable limit of 0cfu/100mL for drinking water (WHO, 1993). This may be attributed to the high anthropogenic activities by tourist and residents around the Lake Bosomtwi especially during the peak periods. The values for the peak periods were slightly higher than those recorded for the lean periods, even though the values recorded did not follow a specific pattern.

Again high and low values were recorded for both the lean and peak periods. This resulted in the variations between the periods and among the sites being very minimal.

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With the exception of BOB which was significant (ANOVA p>0.05) with standard deviation and standard error mean of 44.21048 and 18.04885 respectively, the difference between the periods of the remaining sites were all insignificant.

Table 4.20: Mean, Range and Periodic Means for Fecal Coliforms Values

ANNUAL STD. PERIODIC MEAN

PARAMETER SITE RANGE MEANS DEV'TION PEAK LEAN WUF 125 – 425 270 25.19 304 236 WLF 108 – 1209 463 306.69 578 350 WPS 117 – 1488 654 518.28 718 590 WBR 208 – 986 555 275.01 636 473 F. COLI WDR 190 – 742 479 244.93 524 433 (cfu/100mL) BAB 476 – 848 614 138.76 660 569 BOB 376 – 672 572 44.21 590 555 BNK 126 – 704 357 264.31 426 288 BAM 111 – 744 368 324.55 420 317 BNY 110 – 704 370 350.44 464 276

Again high and low values were recorded for both the lean and peak periods. This resulted in the variations between the periods and among the sites being very minimal.

With the exception of BOB which was significant (ANOVA p>0.05) with standard deviation and standard error mean of 44.21048 and 18.04885 respectively, the difference between the periods of the remaining sites were all insignificant.

Fecal coliforms values recorded for Lake Bosomtwi as indicated in Table 4.20 above ranged between 110cfu/100mL recorded in December at BNY to 848cfu/100mL recorded in May at BAM. Annual means for the various sites ranged from 357cfu/100mL recorded at BNK to 614cfu/100mL recorded at BAB with periodic means also ranging between

276cfu/100mL recorded at BNY to 569cfu/100mL recorded at BAB, and 420cfu/100mL recorded at BAM to 660cfu/100mL recorded at BAB, for the lean and peak periods 151

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respectively. The monthly means ranged from 249cfu/100mL recorded in February to

708cfu/100mL recorded in September.

4.5 Multivariate Statistical Analysis In order to further identify and characterize water quality parameters, as well as to determine the similarities between them, the Principal Component Analysis (PCA) and

Cluster Analysis (CA) were also applied. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called Principal Components https://www.google.com/search?sourceid=navclient. CA on the other hand is the task of grouping a set of objects in such a way that objects in the same group (cluster) are more similar to each other than to those in other groups https://www.google.com/search?sourceid=navclient&aq.

PCA was used in the reduction of the size of the data by forming a few linear combinations of the original data. It provided a better understanding of data interpretation as correlated variables were grouped together. Correlation coefficients that is greater than

0.70 were considered highly correlated. The Kaiser-Meyer-Olkin (KMO) measure of sample adequacy was used and the results indicated that it was > 0.5, suggesting that the sample size was adequate (Todd, 1999).

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Table 4.21: Rotated Component Matrix of Water Quality Parameters

C O M P O N E N T S PARAMETERS PC1 PC2 PC3 Total Dissolved Solids 0.981 -0.017 -0.048 Chloride 0.980 -0.028 -0.028 Bicarbonate 0.976 0.017 -0.007 Alkalinity 0.971 -0.048 -0.015 Conductivity 0.970 -0.046 -0.036 Potassium 0.962 -0.027 -0.004 Sodium 0.955 0.083 0.031 Temperature 0.932 0.040 0.089 pH 0.917 -0.157 0.057 Total Hardness 0.900 -0.016 -0.081 Magnesium 0.858 -0.148 -0.062 Calcium 0.775 0.245 0.013 Iron -0.719 -0.081 -0.071 Manganese -0.688 0.011 -0.216 Fluoride 0.499 -0.053 -0.063 Turbidity -0.490 0.146 0.155 Total Coliforms 0.060 0.890 0.076 Fecal Coliforms 0.000 0.848 -0.125 Nitrite 0.127 0.004 0.751 Phosphate 0.237 -0.017 0.717 Total Suspended Solids -0.299 0.447 0.462 Eigen Value 12.15 1.87 1.62 Percentage of Variance 55.22 8.48 7.36 Cumulative Percentage 55.22 63.69 71.05

The results of the PCA, based on the correlation matrix of water quality parameters of

Lake Bosomtwi and Wli Waterfalls are presented in Table 4.21 and Figure 4.1. As shown in Table 4.21 above, three components with Eigen values greater than 1 were extracted. This accounted for 71.05% of total variance. The first component (PC1), which generally explained the majority of total variance (55.22%), had high loadings on TDS,

Cl, HCO3, Alkalinity, conductivity, K, Na, temperature, pH, total hardness, Mg, Ca and

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Fe. This represented the first distinction in the profiles of water quality of Lake

Bosomtwi and Wli Waterfalls measured during the study period. PC2 accounted for

8.48% of total variance and was made up of the total and fecal coliform bacteria. This suggests that the water quality of both Lake Bosomtwi Wli Waterfalls is also influenced by the presence of both total and fecal coliform bacteria.

The third component (PC3) depicted the influence of nutrients such as NO2 and PO4 on water quality. This accounted for 7.36% of total variance. As indicated in Table 4.21 there was a strong associations observed between TDS, Cl, K, Alkalinity and HCO3 in

PC1. There were also some moderate associations observed between temperature and

Ca, as well as pH and Na.

Figure 4.1: Score Plot Illustrating the Differentiation of Parameters Associated with Water Quality Parameters of Lake Bosomtwi and Wli Waterfalls during the Study. A Three-Component System (PC1-PC3) explaining 71.05% of Total Variance. 154

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The CA was used to determine similarities between water quality parameters as well as to classify homogenous groups that commonly correlate with the data matrix and dendogram in the Wli Waterfalls and Lake Bosomtwi. As shown in Figure 4.2, two main clusters (A and B) were observed with four subgroups showing the relationships between the water quality parameters of both the Lake Bosomtwi and Wli Waterfalls. Cluster A corresponded with the associations between Coliforms, TDS and conductivity in both water bodies. Cluster B depicts the influence of HCO3, Alkalinity, Na, Cl, Total

Hardness, NO3, K, Mg, Ca, F, pH, Turbidity and Temperature. In the case of the subgroups, the first one showed the influence of Coliforms TDS and Conductivity on the water quality of the Lake and the Waterfalls. The second subgroup also showed the influences of HCO3 and Alkalinity, with the third subgroup showing Na, Cl and Total

Hardness on the quality of water in the two water bodies. The final (fourth) group showed the influence of NO3, Mg, F, Turbidity, Temperature, pH, Ca and K on the quality of water in the Lake and Waterfalls.

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Figure 4.2: Dendogram Showing Clustering of Water Quality Parameters of the Wli Waterfalls and Lake Bosomtwi. Two Clusters were Distinctively Identified and they were Made Up of Four Sub-Groups

4.6 Land Use Analysis Generally, the results of land use analysis around the Wli Waterfalls showed that there has been some improvement in the protection of vegetation in and around the Agumatsa

Wildlife Sanctuary. In all about, 47.13 sq. km of land covering the Agumatsa Wildlife

Sanctuary and the immediate surroundings of the waterfalls was used for the analysis.

About 19.69 sq. km (41.79%) of the total land area was made up of closed forest vegetation in 1990. By the year 2000, the coverage has reduced drastically to 10.04 sq km

(21.30%). This figure then rose to 14.58 sq. km (30.94%) by 2010. Opened forest vegetation on the other hand covered 24.69 sq km (52.40%) of the total land area by

1990. It reduced to 22.65 sq km (48.06%) in 2000 and rose sharply to 26.55 sq km

(56.33%) in 2010. Dense shrub coverage increased from 2.47 sq km (5.24%) in 1990 to

13.53 sq. km (28.71%) in 2000. It then reduced to 4.48 sq. km (9.51%) in 2010.

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Grassland and built up/bare areas increased gradually over the years. Whiles grassland coverage was 0.12 sq. km (0.25%), 0.61 sq. km (1.29%) and 1.06 sq. km (2.25%) for

1990, 2000, and 2010 respectively, that of built up/bare area was 0.15 sq. km (0.32%),

0.30 sq. km (0.64%) and 0.46 sq. km (0.98%) for 1990, 2000 and 2010 respectively.

Table 4.22: Matrix of Land Cover by Class Values for the Years 1990, 2000 and 2010 around Wli Waterfalls CLASSES 1990 % 2000 % 2010 % Closed vegetation very active bushes 19.69 41.79 10.04 21.30 14.58 30.94 Open vegetation very active bushes 24.69 52.40 22.65 48.06 26.55 56.33 Dense shrub/herbaceous 2.47 5.24 13.53 28.71 4.48 9.51 Grass/herbaceous 0.12 0.25 0.61 1.29 1.06 2.25 Built up/bare area 0.15 0.32 0.30 0.64 0.46 0.98 GRAND TOTAL 47.13 100 47.13 100 47.13 100 Source: CERGIS (2014) As shown in Table 4.22 the closed forest vegetation lost close to about 50% of its coverage to the other classes such as opened forest vegetation, which in itself also lost about 40% of its coverage to other classes such as dense shrubs, grassland and built up/bare areas in the ten-year period of 1990 and 2000. Dense shrub, grassland and built up/bare areas on the other hand gained coverage. While dense shrubs and grassland coverage increased by over 500% each, that of built up/bare areas increased by about

100%. The level of increase and decrease between 2000 and 2010 even though high, was not as drastic as it was for period between 1990 and 2000. Closed forest vegetation and opened forest vegetation increased in coverage by about 50% and 20% respectively.

Grassland and built up/bare areas coverage also increased by about 75% and 54% respectively. Dense shrub was the only class that had its coverage reduced by about 33%.

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Figure 4.3: Land Use Map of Wli Waterfalls and Agumatsa Wildlife Sanctuary

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Using two kilometer buffer zone around the Lake Bosomtwi, a total of 117.51 sq. km of land area was used. As shown in Table 4.23, the forest cover for the area under study reduced drastically over the years. Closed forest vegetation coverage of 44.67 sq. km

(38.00%) in 1990 reduced to 41.29 sq. km (35.60%) in 2000 and a further decline to

30.92 sq. km (26.30%) in 2010. Open forest vegetation coverage also reduced from 18.78 sq. km (16.00%) in 1990 to 18.05 sq. km (15.40%) in 2000. It then increased to 20.38

(17.34%) in 2010. Dense shrub, grassland and built up/bare area coverage however, increased over the years. Built up/bare area coverage increased drastically from 0.09 sq. km (0.08%) in 1990 to 3.11 sq. km (2.65%) in 2000 and then 3.98 sq. km (3.4%) in 2010.

Grassland coverage also increased from 0.41 sq. km (0.35%) to 0.54 sq. km (0.46%) and then to 0.69 sq. km (0.60%) in 1990, 2000 and 2010 respectively. Dense shrub coverage on the other hand also increased from 4.75 sq. km (4.00%) to 6.19 sq. km (5.30%) and then, to 15.72 sq. km (13.40%) for 1990, 2000 and 2010 respectively. As expected, the area covered by water bodies (the lake mainly) reduced over the years. It reduced from

48.80 sq. km (41.50%) in 1990 to 47.83 sq. km (40.70%) in 2000. It then reduced further to 45.81 sq. km (39.00%) in 2010.

Table 4.23: Matrix of Land Cover by Class Values for the Years 1990, 2000 and 2010 around the Lake Bosomtwi CLASSES 1990 % 2000 % 2010 % Closed vegetation very active bushes 44.67 38.02 41.79 35.56 30.92 26.31 Open vegetation very active bushes 18.78 15.98 18.05 15.36 20.38 17.34 Dense shrub/herbaceous 4.75 4.04 6.19 5.27 15.72 13.38 Grass/herbaceous 0.41 0.35 0.54 0.46 0.69 0.59 Built up/bare area 0.09 0.08 3.11 2.65 3.98 3.39 Water body 48.8 41.53 47.83 40.70 45.81 38.99 GRAND TOTAL 117.51 100 117.51 100 117.51 100 Source: CERGIS (2014)

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Figure 4.4: Land Use Map of the Two Kilometer Buffer Zone Around Lake Bosomtwi

The closed forest vegetation around the Lake Bosomtwi lost about 8% of its coverage to other classes such as opened forest vegetation within the ten-year period of between 1990 and 2000. The opened forest vegetation in itself lost just a little over 4% of this coverage to the other classes such as dense shrub, grassland and built up/bare area. It was therefore not surprising that dense shrub coverage increased by about 35% whilst that of grassland increased by about 77%. Built up/bare area coverage was the highest gainer from the

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reduction in the coverage of both forest vegetations with an increase of about 2500% in coverage area.

The reduction and the increases that took place between the ten-year period of 2000 and

2010 were even more drastic than those that took place between 1990 and 2000. Closed forest vegetation was the only class that lost coverage of about 27%. Opened forest vegetation, dense shrub and grassland, and built up/bare area coverage areas on the other hand increased by about 15%, 152%, 20% and 30% respectively. Water body (mainly the lake) reduced continuously for the entire period of the study.

45

30 1990 2000 15 2010 % Coverageof in Sq Km

0 BOSOMTWI WLI SITE

Figure 4.5: Percentage Coverage of Closed Forest Vegetation around Lake Bosomtwi and Wli Waterfalls between 1990 and 2010

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3

2 1990 2000 1 2010 of Coverage in Sq. Km

%

0 BOSOMTWI WLI SITE

Figure 4.6: Percentage Coverage of Grass Vegetation around Lake Bosomtwi and

Wli Waterfalls between 1990 and 2010

4.00

3.00

1990 2.00 2000 2010 1.00 % Coverageof in Sq. Km 0.00 BOSOMTWI WLI SITE

Figure 4.7: Percentage Coverage of Built Up/Bare Area around Lake Bosomtwi and

Wli Waterfalls between 1990 and 2010

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4.8 Social Survey 4.8.1 Bio Data of Respondents

In all 219 (49.1%) of the respondents randomly selected as shown in Table 4.24 below were females with the remaining 227 (50.9%) being males. However respondents from the communities around the Lake Bosomtwi had about 57.9% of its respondents being females and the remaining 42.1% were males. Communities around the Wli Waterfalls on the other hand had more males with 61.3% and 38.7% of them being males and females respectively.

Table 4.24: Gender of Respondents

Gender of Respondents Bosomtwi Wli Total (%) Male 102 125 50.9 Female 140 79 49.1 GRAND TOTAL 242 204 100.0 Source: Field Data (2014)

Majority of the respondents were in their youthful ages with as many as 270 (55%) of them falling between the 20-39 age bracket. The age bracket groups of 20-30yrs, 30-

39yrs, 40-49yrs, 50-59yrs, 60-69yrs and 70 and above had values of 178(37.7%),

112(23.7%), 76(16.1%), 54(11.4%), 27(5.7%) and 25(5.3%) respectively. One hundred and seventy-one (66.0%) and 119 (55.9%) of the respondents in the communities around the Lake Bosomtwi and Wli Waterfalls respectively were between the youthful ages of

20-39 years as indicated in Table. 4.25 below. The mid age bracket of between 40 and

49 had 16.6% and 15.5% for respondents around the Lake Bosomtwi and the Wli

Waterfalls respectively. Communities around the Wli Waterfalls however, had more respondents aged 50 and above (28.6%) than those of the Lake Bosomtwi area (17.4%).

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Table 4.25: Age of Respondents

Age of Respondents Bosomtwi Wli Total (%) 20-29 108 70 37.7 30-39 63 49 23.7 40-49 43 30 16.1 50-59 29 25 11.4 60-69 10 17 5.8 70+ 6 19 5.3 GRAND TOTAL 259 213 100.0 Source: Field Data (2014)

Table 4.26: Educational Level of Respondents

Educational Level Bosomtwi Wli Total (%) None 27 9 7.8 Primary 44 17 13.2 JSS/Middle School 136 102 51.5 Secondary/Vocational/Technical 23 56 17.1 Tertiary 19 29 10.4 GRAND TOTAL 249 213 100 Source: Field Data (2014)

Generally the level of education among the respondents as shown in Table 4.26 above was low. Thirty-six (7.8%) of the respondents have had no education at all with as many as 299 (64.7%) having had up to either primary or JSS/Middle School education.

Seventy-nine (17.1%) and 48 (10.4%) have either had education to the Sec/Voc/Tech or tertiary level. Respondents of the communities around the Wli Waterfalls are however, highly educated in percentage wise than those in the communities around the Lake

Bosomtwi. This is a confirmation of data from the 2010 population and household census by Ghana Statistical Service. While only 4.2% of respondents have had no education in the communities around the Wli Waterfalls, 10.8% of those around the Lake Bosomtwi were not educated at all. Communities around the Wli Waterfalls had 39.9% of its

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respondents having been educated to that level Secondary/Vocational/Technical or tertiary education level with those around the Lake Bosomtwi having only 16.8% of its respondents educated to that level.

A large number of respondents as shown in Table 4.27 below were Christians. Four hundred and one (84.6%) of the total number of respondents were Christians. While

17(3.6%) were Traditionalist, 10(2.1%) were either Muslims or were of other religion. As much as 46(9.7%) refused to indicate their religious inclination. The communities around both the Lake Bosomtwi and the Wli Waterfalls had high percentages of respondents being Christians with values of 88.4% and 80.0% respectively. Respondents from around the Lake Bosomtwi and Wli Waterfalls had 1.9% each of their respondents being

Muslims with 4.6% and 2.3% respectively being Traditionalist. About 15.8% and of

4.1% of the respondents did not indicate their religious inclination for the communities around the Wli Waterfalls and the Lake Bosomtwi respectively.

Table 4.27: Religion of Respondents

Religion Bosomtwi Wli Total (%) Christian 229 172 84.6 Moslem 5 4 2.1 Traditionalist 12 5 3.6 Others 1 0 0.2 None 12 34 9.5 GRAND TOTAL 249 213 100 Source: Field Data (2014)

As indicated in Table 4.28 below, as many as 248 (53.4%) of the respondents are married with 163 (35.7%) being single. Only 30 (6.6%) were either divorced or separated with the remaining 20 (4.4%) being widowed. A high percentage of the respondents at both study

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areas were married. High percentages of the respondents at Lake Bosomtwi (54.5%) and

Wli Waterfalls (52.1%) respectively were married with 38.6% and 32.2% respectively not married. Respondents in the communities around the Lake Bosomtwi had 3.7% and

3.3% either divorce/separated or widowed. Around the Wli Waterfalls, 10.0% and 5.7% of the respondents were either divorced/separated or widowed.

Table 4.28: Marital Status of Respondents

Marital Status Bosomtwi Wli Total (%) Single 95 68 35.6 Married 134 110 53.4 Divorced/Separated 21 21 6.6 Widowed 12 12 4.4 GRAND TOTAL 246 211 100 Source: Field Data (2014)

Generally, children and household sizes were quite large. As many as 134 (29.1%) of the respondents had children of between four and nine with 16 (3.5%) of them having more than 10 children. Whiles 174 (37.8%) of the respondents had between 1 and 3 children,

136 (29.6%) of them had no children at all as indicated Table 4.29 below.

Table 4.29: Number of Children per a Household

No of Children Bosomtwi Wli Total (%) None 68 68 29.6 1 to 3 88 86 37.8 4 to 6 64 47 24.1 7 to 9 16 7 5.0 10 and above 11 5 3.5 GRAND TOTAL 247 213 100.0 Source: Field Data (2014)

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Respondents at Lake Bosomtwi had more large household sizes of more than 6 children

(11%) as compared to that of Wli Waterfalls (5.5%). About twenty percent (27.5%) of the respondents at Lake Bosomtwi had no children with 61.5% of them having between 1 and 6 children. At Wli Waterfalls, 31.9% of the respondents do not have children at all with 62.5% of them having between 1 and 6 children.

Table 4.30: Occupation of Respondents

Occupation Bosomtwi Wli Total (%) Unemployed 41 7 10.5 Farmer 105 66 37.4 Trader 34 73 23.4 Tourism Industry 23 28 11.2 Public Servant 14 20 7.4 Pensioner 2 10 2.6 Fishing 18 6 5.3 Others 10 0 2.2 GRAND TOTAL 247 210 100.0 Source: Field Data (2014)

As shown in Table 4.30 above the farming is the major occupation that most of the respondents are engaged in. As many as 171 (37.4%) of the respondents are farmers and this was followed by trading with 107 (23.4%) and then those who are directly or indirectly employed in the tourism industry such as tour guide, employees of hotels, restaurants, chop bars and other entertainment centers 51 (11.2%). Public/civil servants, pensioners, fishing and others follow in that order with values of 34 (7.4%), 12 (2.6%),

10 (2.2%) and 24 (5.3%) respectively. About 48 (10.5%) of the respondents claimed that they are unemployed. 16.6% of its respondents at the Lake Bosomtwi said they were unemployed with only 3% of respondents at Wli Waterfalls stating that they are unemployed. Fourteen percent (14% ) of respondents at Wli Waterfalls said they are

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either working directly or indirectly in the tourism industry as against 7.3% of the respondents at the Lake Bosomtwi. Both study areas had farming as the major occupation engaged in by respondents. As many as 51.0% of the respondents at the Lake Bosomtwi are engaged in farming with Wli Waterfalls having 34.7% of its respondents engaged in farming. Again, while 4.0% of respondents at Lake Bosomtwi were engaged in fishing, none of the respondents at Wli Waterfalls are engaged in Fishing.

4.8.2 Perceived Environmental Impacts

Majority of the respondents, 128 (27.4%) of them have lived in the study areas for more than 30 years as shown in Table 4.31. This is because most of them are natives of the area and were born there. Those who have lived in the area up to 5 years 81 (17.3%) follows those who have lived there for more than 30 years. This was followed by respondents who have lived in there between 6 and 10 years, 16 and 20 years, 26 and 30 years, and 21 to 25 years with values of 69 (14.7%), 53 (11.3%), 50 (10.7%), and 46

(9.8%) respectively. The age bracket of 11 to 15 years recorded the least respondents of

41 (8.8%).

Table 4.31: Number of Years Respondents have Lived in Community

Years Bosomtwi (%) Wli (%) Total (%) 0-5 12.9 22.6 17.3 6-10 11.3 18.9 14.7 11-15 8.6 9.0 8.8 16-20 11.7 10.8 11.3 21-25 11.7 7.5 9.8 26-30 10.5 10.8 10.7 30+ 33.2 20.3 27.4 GRAND TOTAL 100.0 Source: Field Data (2014)

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Table 4.31 also indicates that, communities around the Lake Bosomtwi had more respondents living in the area for more than 30 years (33.2%) as compared to that of Wli

Waterfalls with (20.3%). Communities around Wli Waterfalls however, had more people living in the area for up to 10 years (41.5%) than that of Lake Bosomtwi (24.2%). Those who have lived in the area between 16 and 25 years were slightly higher in the communities around Lake Bosomtwi (23.4%) than that of Wli Waterfalls (22.6%).

Table 4.32: Critical Environmental Problems in the Community

Critical Environmental Issue Bosomtwi (%) Wli (%) Total (%) Loss of Soil Fertility 2.0 8.0 5.0 Pollution 26.0 16.1 21.1 Poor Sanitation 27.0 15.6 21.3 Soil Erosion 19.6 6.0 11.0 Inadequate Toilet Facilities 6.4 31.2 18.7 Poor Drainage Systems 2.0 6.5 4.2 Deforestation 12.7 10.1 11.4 Improper Fishing/farming Methods 4.4 6.5 5.5 GRAND TOTAL 100.0 Source: Field Data (2014)

As Table 4.32 above, most respondents listed poor sanitation 86 (21.3%) and pollution of water bodies 85 (21.1%) as the most critical environmental issues in their communities as the major environmental problems. This was followed by inadequate toilet facilities 75

(18.7%), erosion 52 (11.0%) and deforestation 46 (11.4%). Improper fishing /farming 23

(5.5%), loss of soil fertility 20(5.0%) and poor drainage systems 17 (4.2) were the least mentioned environmental issues. Whiles respondents around the Lake Bosomtwi had poor sanitation (27.0%), pollution (26.0%) and erosion (19.6%) as their critical environmental issues, Wli Waterfalls had inadequate toilet facilities (31.2%), pollution

(16.1%) and poor sanitation (15.6%) as the major environmental problems. Respondents

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in both communities listed poor drainage systems and improper farming and fishing methods as the least critical environmental issues.

As many as 254 (53.6%) of the respondents were emphatic that the environmental issues mentioned above had nothing to do with tourism, with 176 (37.1%) of them saying the environmental problems were related to tourism. Forty-four (9.3%) of them however, were not sure whether the environmental problems were related to tourism or not. About thirty-two percent (31.6%) of respondents at Wli Waterfalls agreed that the critical environmental issues in the area are related to tourism with as many as 68.4% saying the environmental issues are not related to tourism in anyway. Majority of the people around the Lake Bosomtwi (52.0%) however, think that the environmental issues are related to tourism as shown in Table 4.33 below.

Table 4.33: Respondents Views on Causes of the Environmental Problems

Causes Related to Tourism Bosomtwi (%) Wli (%) Total (%) Yes 29.4 51.0 37.1 No 65.1 45.4 53.6 Not Sure 5.7 3.6 9.3 GRAND TOTAL 100.0 Source: Field Data (2014)

Provision of infrastructural projects (45.5%), improving sanitation (18.8%), enforcement of laws (14.0%) and provision of toilet facilities (10.9%) were the factors that in the opinion of the respondents could be used to solve the critical environmental issues listed by the respondents. To the respondents around the Lake Bosomtwi, improving sanitation

(29.2%), provision of infrastructure (25.0%), enforcement of laws (20.5) and afforestation (12.5%) were the major factors that could solve the environmental problems

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with provision of toilet facilities being the least (3.2%)among them. Respondents around the Wli Waterfalls however, cited provisions of infrastructure (46.3%) as the major factor to solving environmental problems. This was followed by provision of toilet facilities

(20.3%) and creation of jobs (8.5%) with enforcements of laws as the least (5.6%) among of them.

As shown in Table 4.34 below, as many as 259 (65.9%), 58 (14.8%), 42 (10.7%) and 34

(8.7%) of the respondents listed rain forest, secondary forest, grass/shrubs and farms as the vegetation found in the area with 273 (67.2%) of them saying the vegetation has always been so with the remaining 133 (32.8%) saying there has been some changes.

About eighty-four percent (83.8%) of the respondents around the Lake Bosomtwi as compared to 48.0% around Wli Waterfalls stated rain forest as the main vegetative cover found the areas. This is followed by grass/shrubs (8.6%) at the Lake Bosomtwi and secondary forest (26.0%) at Wli Waterfalls.

Table 4.34: Types of Vegetation Found around the Attractions

Types of Vegetation Bosomtwi (%) Wli (%) Total (%) Rain Forest 83.8 48.0 65.9 Grass/Shrub 8.6 12.8 10.7 Farms 4.3 13.3 8.7 Secondary Forest 2.7 26.0 14.8 GRAND TOTAL 100.0 Source: Field Data (2014)

As much as 64.8% and 69.6% of respondents around the Lake Bosomtwi and Wli

Waterfalls respectively agreed that the vegetation has not changed. Of those who argued that there has been some change in the vegetative cover in the study areas, only 28.6% of these respondents around Wli Waterfalls and 45.5% around the Lake Bosomtwi agreed

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that the growth of the tourism industry is the cause of the change as indicated in Table

4.35 below.

Table 4.35: Respondents Views on Changes in Vegetation

Any Changes in Vegetation Bosomtwi (%) Wli (%) Total (%) Yes 64.8 69.6 67.2 No 35.2 30.4 32.8 GRAND TOTAL 100.0 Source: Field Data (2014)

4.8.3 Perceived Economic Impacts

On the issue of economic impacts, as much as 326 (71.6%) of the respondents disagreed that growth in the tourism industry has brought any economic benefit to them with only

129 (28.4%) agreeing that tourism has affected them economically within the last three months. A high percentage of respondents around Lake Bosomtwi (71.6%) and Wli

Waterfalls (71.7%) disagreed that tourism is having any influence on their economic life as shown in Table 4.36 below.

Table 4.36: Respondents Views on Whether Tourism Brings Benefits

Benefits of Tourism to You Bosomtwi (%) Wli (%) Total (%) Yes 28.4 28.3 28.4 No 71.6 71.7 71.6 GRAND TOTAL 100.0 Source: Field Data (2014)

Of the 129 (28.4%) that agreed tourism has influenced their economic life within the last three months as indicated in Table 4.37 many as 79 (61.7%) of the valid respondents listed revenue from more sales from their farm produce and other products as the major economic benefit they get from tourism. This was followed by job creation 20 (15.6%),

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provision of social amenities 14 (10.9%), gift from tourist 9 (7.1%) and revenue from ticket sales for the community 6 (4.7%). Respondents around both the Lake Bosomtwi

(64.8%) and the Wli Waterfalls (57.9%) had revenue from more sales their farm produce and other products as the major economic benefit derived from the tourism industry. This was followed by job creation and provision of social amenities at both study areas.

Table 4.37: Types of Benefits Respondents Get from Tourists

Types of Economic Benefits Bosomtwi (%) Wli (%) Total (%) Job Creation 16.9 14.0 15.6 Revenue from More Sales 64.8 57.9 61.7 Revenue from Tickets Sold 3.4 5.3 4.7 Gifts from Tourists 3.6 12.3 7.1 Provision of Social Amenities 11.3 10.5 10.9 GRAND TOTAL 100.0 Source: Field Data (2014)

Table 4.38: Respondents Views on Seasonality Nature of Tourism Benefits

Value of Benefits All Year Round Bosomtwi (%) Wli (%) Total (%) Yes 19.1 34.4 26.8 No 80.9 65.6 75.2 GRAND TOTAL 100 Source: Field Data (2014)

As indicated in Table 4.38 above, all the respondents who agreed that they get some benefits from tourism said that the benefit is not the same throughout the year. One hundred and thirty-five (69.2%) cited festive occasions as the period within which the benefits are high. This was followed by summer holidays 52 (26.7%) and other occasions

8 (4.1%). Respondents around the Lake Bosomtwi (67.7%) and the Wli Waterfalls

(72.6%) had festive occasions as the most important period within which earnings from

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the tourism industry are high. This was followed by summer holidays with 29.3% and

21.0% for the Lake Bosomtwi and the Wli Waterfalls respectively.

Table 4.39: Respondents Who Have Worked in the Tourism Industry Before

Ever Worked in Tourism Industry Bosomtwi (%) Wli (%) Total (%) Yes 18.3 14.9 16.8 No 81.7 85.1 83.2 GRAND TOTAL 100 Source: Field Data (2014)

As indicated in Table 4.39 above, only seventy-six (16.8%) of respondents said they are working or had ever worked in the tourism industry before. Only 36 (44.4% of the valid figure) of them said they had worked in the industry for a long time. As many as 377

(83.2%) have never worked in the tourism industry before. About eighty one percent

(81.3%) and 85.1% of the respondents around the Lake Bosomtwi and the Wli Waterfalls respectively have never worked in the tourism industry before. Seasonality nature of jobs

(29.4%) low remuneration (25.5%), more respectable jobs (21.6%) and rotational system of recruitment (11.8%) were given as the main reasons by the 56% of valid respondents who said that their family members are working or had ever worked in the tourism industry and have changed jobs. Valid respondents around the Lake Bosomtwi however, listed seasonality nature of jobs (30.4%), low remuneration (30.4%), insincerity of mangers (21.7%) and more respectable jobs (17.4%) were listed as the reasons for the change. Those around the Wli Waterfalls on the other hand listed seasonality nature of jobs (46.42%), low remuneration (28.6%), rotational systems of recruitment (14.3%) and more respectable jobs (7.1%) as the major reasons for the change.

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A large percentage of respondents (78.3%) claimed none of their relations had ever worked in the tourism industry directly with only 21.7% agreeing that some family member had ever worked in the tourism industry. Those who have had relations ever working in the tourism industry, only one (49.0%) or two (36.5%) of their family members have worked in the tourism industry. The remaining 15.0% is shared among those who have three or more relations working in the tourism industry as indicated in

Table 4.40 below.

Table 4.40: Respondents who’s Family Members Had Ever Worked/Working in

the Tourism Industry

Family Member Working in Tourism Bosomtwi (%) Wli (%) Total (%) Yes 18.8 25.3 21.7 No 81.2 74.7 78.3 GRAND TOTAL 100 Source: Field Data (2014)

As shown in Table 4.40 above, just about nineteen percent (18.8%) of respondents around the Lake Bosomtwi as compared to 25.3% at Wli Waterfalls agreed that they have relations who had ever worked in the tourism industry within the last three months. Over eighty percent (80%) respondents in communities around both the Lake Bosomtwi and

Wli Waterfalls who had relations working or had ever worked in the tourism industry said only one or two family members were involved in this. Only eighty-four (18.82%) of valid respondents agreed that any family member of theirs are employed or ever employed indirectly in the tourism industry with about 70.0% of these valid respondents saying between one and two members of their family member are indirectly employed by the tourism industry. Only a few, 18.1% and 19.6% of valid respondents for Lake

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Bosomtwi and Wli Waterfalls respectively agreed that any member of their family is indirectly employed in the tourism industry. While 56.5% of the valid respondents around the Lake Bosomtwi said that only one or two family members are indirectly employed by tourism those around the Wli Waterfalls is 84.6% with the remaining 43.5% and 15.4% shared by three and above at the Lake Bosomtwi and Wli Waterfalls respectively.

Malaria/fever was listed as the most prevalent disease in the study areas by 267 (63.4%) of the respondents. This was followed by cholera/diarrhea, cardio vascular diseases, skin rashes, bilharzias and HIV/AIDS with values of 45 (10.7%), 43 (10.2%), 32 (7.6%), 14

(3.3%) and 13 (3.1%) respectively. Respondents around the Lake Bosomtwi as well as

Wli Waterfalls listed malaria/fever as the most prevalent disease in the study area with

62.9% and 64.1% respectively. This was followed by cholera/diarrhea (16.5%), skin disease (10.2%) and bilharzias (5.9%) in the communities around the Lake Bosomtwi, with Cardio vascular (19.0%), HIV/AIDS (7.1%), skin diseases (4.4%) and cholera/diarrhea (3.3%) following in the communities around Wli Waterfalls. Even though most of the diseases listed are water borne diseases or may be influenced by the in- flow of tourist, only 27.6% and 7.3% of the valid respondents around the Lake

Bosomtwi and the Wli Waterfalls respectively agreed that the diseases prevalent in the communities were related to the pollution of water bodies by tourist.

Farming, trading and fishing were mostly listed by respondents as other economic activities taking place in the communities apart from tourism. Lake Bosomtwi and Wli

Waterfalls had only 24.4% and 20.8% of the valid respondents respectively stating that some of the other economic activities (especially farming) in the communities have been affected by tourism. In the communities around the Lake Bosomtwi, 40.7% and 35.6%

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respondents listed reserving farmlands for tourism related development projects and the youth neglecting farming to join tourism as the major problems of farming as far as tourism is concerned. Those around Wli Waterfalls on the other hand had 54.8% and

23.8% respectively of the valid respondents listing reserving farmlands for tourism related development projects and the youth neglecting farming to join tourism as the major problems of farming as far as tourism is concerned. About twenty-one percent

(21.4%) and 23.7% of valid respondents around the Lake Bosomtwi and Wli Waterfalls respectively said farming has been affected positively by tourism through the expansion of farms by farmers due to increase in demand of farm produce by tourist as shown in

Table 4.41 below.

Table 4.41: Respondents Views on How Tourism Affects Farming Activities

How Tourism Affects Farming Bosomtwi (%) Wli (%) Total (%) Farming Neglected by Youth 35.6 23.8 29.7 Farm Lands Reserved for Farming 40.7 54.8 47.7 Expansion of Farms to Feed Tourists 23.7 21.4 22.6 GRAND TOTAL 100 Source: Field Data (2014)

4.8.4 Participation in Management of Tourism Facilities.

As shown in Table 4.42, participation in the management of the tourism industry is very low in all the communities. Only 99 (22.2%) of the total respondents agreed that they have ever participated in taken decisions on the management of tourism in their communities with 347 (77.8%) saying they have never taken part in the decision making.

As many as 79.9% of respondents in the communities around the Wli Waterfalls say they had never participated in decision making as far as tourism is concern with 76.0% around the Lake Bosomtwi also saying they have never participated in the decision making.

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Table 4.42: Level of Participation in the Management of Tourism Industry

Participation in Meeting of Industry Bosomtwi (%) Wli (%) Total (%) Yes 24.0 20.1 22.1 No 76.0 79.9 77.8 GRAND TOTAL 100.0 Source: Field Data (2014)

Table 4.43: Reasons for Not Participation in the Management of Tourism Industry

Reasons for Not Participating Bosomtwi (%) Wli (%) Total (%) Not Invited 52.8 31.2 42.0 Not a Member of Committee 26.8 33.4 30.1 Other Reasons 20.4 35.4 27.9 GRAND TOTAL 100.0 Source: Field Data (2014)

As shown in Table 4.43 above, 133 (42%) of the valid respondents said they had never participated in decision making process in tourism development in their communities before because they have been invited to any of the forums on tourism. This was followed by 117 (30.1%) of the valid respondents saying they are not members of the

Tourism Management Committees (TMC). About fourteen percent (13.9%) of the valid respondents who have participated did so because they are members of the TMC with

6.9% participating because they were also invited as opinion leaders. Only twenty-four percent and twenty percent of respondents around the Lake Bosomtwi and the Wli

Waterfalls respectively agreed that they had ever participated in decision making on tourism development in their community. "I am not invited" and "not a member of the

TMC" were the most listed reasons for not taking part in the decisions making process on tourism development in their communities.

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Table 4.44: Consultations Before Tourism Development Decisions Are Taken

TMC Consulting Before Meetings Bosomtwi (%) Wli (%) Total (%) Consulted Regularly 8.4 16.4 12.4 Consulted Once in a While 25.4 37.0 31.2 Never Consulted 66.2 46.6 56.4 GRAND TOTAL 100.0 Source: Field Data (2014)

As indicated in Table 4.44 above, only 12.4% of them agreed that they are consulted regularly by the TMC before major decisions concerning the management of the tourism development are concerned. This was followed by about thirty-one percent (31.2%) of the respondents who said they are consulted once in a while with the remaining 56.4% saying they are never been consulted. 63.2% of the valid respondents who agreed that they are consulted regularly or once in a while come from the communities around Wli

Waterfalls with the remaining 36.8% coming from the communities around the Lake

Bosomtwi. Again, majority (71.5%) of respondents disagreed that their representatives on the TMC do consult them before attending meetings or give them feedbacks on issues discussed at the meetings with only 28.5% of them agreeing that the representatives do consult them or give them feedbacks. A high percentage (66.3%) of those who disagreed that their representatives on the TMC consult them were from the communities around

Lake Bosomtwi with the remaining ones coming from the communities around Wli

Waterfalls. Majority of them, 52.8% and 67.5% of respondents around the Lake

Bosomtwi and the Wli Waterfalls respectively claim they are satisfied with the status quo, as far as management of tourism is concerned.

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As shown in Table 4.45 below, only (16.8%) of the respondents agreed that they have an idea as to how much accrues from gate proceeds from tourism with 33.2% agreeing that they know what the gate proceeds are used for.

Table 4.45: Know How Much is Earned from Tourism Industry

How Much Accrues From Tourism Bosomtwi (%) Wli (%) Total (%) Yes 12.3 21.3 16.8 No 87.7 78.7 83.2 GRAND TOTAL 100.0 Source: Field Data (2014)

Of the seventy-eight respondents who have an idea as to how much is earned from tourism, only 29.6% of them were from communities around the Lake Bosomtwi. Again, as much as 26.2% of those who claimed to know what the gate proceeds are used for were from communities around Lake Bosomtwi. As much as 78.3% and 59.4 % of respondents from the communities around the Lake Bosomtwi and Wli Waterfalls respectively disagreed that the TMC do render accounts on the gate proceeds that accrue from tourism development as shown in Tables 4.46 and 4.47 below.

Table 4.46: Knows What Accrued Money is Used For

Bosomtwi Wli Total What Accrued Money is Use For (%) (%) (%) Yes 28.8 18.8 33.2 No 71.2 62.4 66.8 GRAND TOTAL 100.0 Source: Field Data (2014)

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Table 4.47: TMC Renders Accounts on Earnings on Tourism to Community

Bosomtwi Wli Total TMC Render Accounts to Comm. (%) (%) (%) Yes 21.7 40.6 31.2 No 78.3 59.4 68.8 GRAND TOTAL 100.0 Source: Field Data (2014)

Respondents generally would like the tourist to come with 277 (61.6%) saying they like a lot of things about tourism with only 173% (38.4%) saying they don‟t like tourism development in their community. Sharing of ideas/gifts (28.7%), increasing revenue/income (27.2%), infrastructure development (21.1%), improved image (9.1%), environmental protection (7.5%) and creations of jobs (6.4%) were listed as the reasons for wanting tourism development in their communities. Unlike respondents around the

Lake Bosomtwi with only 42.9% who like tourism development, those around the Wli

Waterfalls had as much as 84.2% of its respondents liking the tourism development within their communities. Only sixteen percent (16%) of respondents around the Wli

Waterfalls as compared to 57.1% around the Lake Bosomtwi do not want tourism to develop in their communities. Sharing of ideas/gifts (30.6%), increasing revenue/income

(26.5%), infrastructure development (18.4%), improved image (9.2%) and creation of jobs (8.2%) were listed by the valid respondents as the reason why tourism development in the communities around the Lake Bosomtwi should be accelerated. That for Wli

Waterfalls followed the same pattern with sharing of ideas/gifts (27.5%), increasing revenue/income (27.5%), infrastructure development (22.8%), improved image (9.0%) and creation of jobs (5.4%) as the reasons for need for accelerated development of tourism in the community.

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Despite the fact that quite a high percentage of respondents were not happy with the development of tourism in their communities, only 82 (18.5%) did not want the tourist to come all year round with as much as 362 (81.5%) of the respondents saying all year- round tourism activities would be appreciated. Of the very few (18.5%) that do not want the tourists to come all year round, half of them do not want the tourist to come at all.

About twenty-four percent (23.8%) of the valid respondents want the tourists to come on public holidays and 15.0% expecting them only once a year. Communities around Wli

Waterfalls had as much as 98.0% of its respondents saying they want the tourist to come all year round with 68.2% of that of Lake Bosomtwi agreeing that the tourist should come all year round. Thirty-nine (51.2%) of the valid percentage that do not want the tourist to come year round also do not want them to come at all.

Of the forty respondents who do not want the tourist to come at all, 34 (85%) of them cited no benefit at all as their major reason. Increased in social vices and adulterations of culture were the other reasons listed by these respondents. All the 34 respondents who cited no benefits as the major reason for not wanting the tourism to develop were from the communities around Lake Bosomtwi. Of the nineteen respondents who cited increased social vices as the major reasons for the tourist not to come at all or on specific occasions only two were from the communities around the Wli Waterfalls with the remaining 17 (89.13%) coming from around the Lake Bosomtwi. Again 68.5% of the respondents around the Lake Bosomtwi believe that the tourists most often break the traditions of the communities and should be punished severely for breaking them. On the other hand, 49.8% of respondents around the Wli Waterfalls believed that tourists who break traditions should be punished for breaking them.

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4.9 Summary

The chapter analyzed the results obtained from the data collected. It is in three sections.

The first aspect dealt with the use of Analysis of Variance (ANOVA), Principal

Component Analysis (PCA) and correlation to establish relationships between water quality parameters within and between sites. Secondly, matrix of land cover was also used to assess the effects of tourism on vegetative cover (land use) in the study areas.

Finally, descriptive and inferential statistics were used to interpret data from the social survey.

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CHAPTER FIVE

DISCUSSION

5.1 Introduction This chapter discusses the results of the study under the broad sub-titles environmental impacts, economic impacts and general perceptions.

5.2 Water Quality Parameters 5.2.1 Temperature Temperature of water bodies are affected by the atmospheric temperature prevailing at the area at the time of sampling. Temperature values recorded at the Wli Waterfalls ranged from 23.60C to 27.90C. Temperature values recorded during peak periods were consistently higher than those recorded during the lean periods. This may be due to the fact that samplings on festive occasions (peak periods) were done in the late afternoon to make room for human activities to take place in the morning. WPS also had the highest annual mean probably due to the fact that most of sampling for both the peak and lean periods were done in the afternoons. Again, it is the only sampling site at the Wli

Waterfalls that had very little vegetative cover to protect the water from direct rays of the sunlight. A research work by Karikari (1998) in the environs of Jasikan which is close to

Hohoe recorded values ranging between 25.00C and 26.00C with a mean of 25.70C. The annual mean values recorded for all the sites were within the 25.0oC and 26.0oC recorded for Jasikan, an indication that.

Mean temperature values for the Lake Bosomtwi ranged from 28.20C recorded at BNK to

31.9oC recorded at BOB. Values recorded during the lean periods were slightly higher than that of peak periods with the exception of March which recorded high figures at all the sites. This may be due to the fact that sampling on lean periods were mostly done in 184

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the afternoon as compared to that of late at night and early mornings for the peak periods.

Even though the highest periodic means for the lean and peak periods were recorded at

BOB and BNY respectively, BAB recorded the highest annual mean. This may be due to the fact that even though sampling on peak periods takes place in the early part of the mornings, BAB was the last place to sample. It therefore always takes place in the early part of the afternoon. A similar work on near the WAF by Karikari (1998)

o o near the dam recorded values ranging between 27.6 C and 30.5 C. Another study by

Anim et al (2013) on the Lake Bosomtwi recorded a mean of 28.10C.

Temperature values recorded at Wli Waterfalls for both periods were therefore not far above the ones recorded by Karikari (1998) and Anim et al (2013). This is an indication that tourism is having little or no effects on temperature of the water body at Wli

Waterfalls. One possible effect of temperature increase in water is the increase in chemical reactions, which lead to a decrease in the solubility of gases such as O2 and CO2.

This results in the death of organism which serves as source of food for the fish stock in the Lake Bosomtwi. Again, fish are poikilothermic and for that matter cannot withstand drastic changes in temperature. This may have resulted in the complaint by fisherman that there has been a reduction in fish catch in the Lake Bosomtwi (Aniapam & Nyame,

2012).

5.2.2 pH In natural waters, the pH is primarily a function of carbonate system. This is made up of carbon dioxide, carbonic acid, bicarbonate and carbonate. Some of these elements occur naturally even though most are as a result of anthropogenic activities (Chapman 1992).

The pH content of a water body may therefore be affected naturally or through

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anthropogenic activities. Almost all the pH values recorded at Wli Waterfalls were more of basic to slightly alkaline (6.1-8.7). Differences between the periods were not much, with the peak periods recording slightly lower values than that of the lean periods. The highest of 8.7 was recorded WDR in July when the flow of water was high and human activities are high there. The above two reasons may have accounted for the high value recorded at that site during that month. Similar works by Osafo (1989) at Torzienu in the

Volta region recorded similar values of between 6.6 and 7.5 and these were not far from the values recorded at Wli Waterfalls. pH values recorded for the Lake Bosomtwi were more alkaline than acidic with values ranging between 7.4 to 9.6. Differences between the periods were minimal with BAM showing the greatest variation even though it was insignificant. A similar work by Anim et al (2013) recorded an average of 8.9 which was very close to the averages recorded for this work. She argued that naturally, high pH values have been recorded for the Lake

Bosomtwi. The alkaline nature of the water on the lake may not attributed to tourism in the strict sense.

5.2.3 Conductivity, Turbidity, TDS/TSS The conductivity of a water body is related to the ability of that water to conduct electric current and provides quick information on the variations in the dissolved minerals concentration of the water. All conductivity values recorded at Wli Waterfalls (2.2µS/cm to 101.1µS/cm) fall far below the natural background level of 450µS/cm for drinking water. WPS however, recorded the highest values of between 42.6µS/cm and

101.1µS/cm. This was followed by WDR (12.9µS/cm to 39.6µS/cm ). This may be due to the fact that they are the sites where human activities of bathing/swimming and fetching

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water for domestic purpose take place. The peak periods also recorded values slightly higher than that of the lean periods. The above explanations may be responsible for these results. The differences were however not significant enough to attribute to the effects of tourism. Values ranging between 80µS/cm and 780µS/cm, as well as 341µS/cm and

421µS/cm were recorded at Torzienu and Jasikan respectively by Osafo (1989) and

Karikari (1998). The vast difference between the results of the earlier work and this may be due to the fact that the Wli Waterfalls flow over hard bedrocks which reduces weathering.

The Bosomtwi on the other hand had conductivity values ranging between 103.8µS/cm recorded in July at BAM to 1381µS/cm recorded in March at BAB. This may be due to the fact that BAB is the main tourist center. There was also a heavy downpour a day before the sampling date in March. As a result all the sites recorded high values. The peak periods also recorded higher values than the lean periods. The presence of numerous tourists on such days may have accounted for the differences recorded between the values of the peak an lean periods. A similar work by Karikari (1998) on Lake Volta recorded a value of 87.4µS/cm as the mean for conductivity. Anim et al (2003) on the other hand recorded a mean value of above 1000µS/cm in Lake Bosomtwi. The difference between the values may be due to the fact that the Lake Bosomtwi does not have an outflow. All debris that flow into it stays in it.

As reported by Biney (1992) the occurrence of high TDS/SS concentration usually coincides with high turbidity values. This confirms the results of this study where the highest annual means at Wli Waterfalls for all the three parameters were recorded at

WPS. Without any exceptions, all the mean values recorded for the peak periods were

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higher than those recorded for the lean periods. The highest values for these parameters were recorded at WPS and the lowest at WUF. This is due to the fact that WPS has the highest concentration of anthropogenic activities due to high convergence of tourist there.

WUF due to its location (upper part of the falls) attracts the least number of tourists at

Wli Waterfalls. All the turbidity values recorded were above the natural background level

5 NTU for drinking water with September recording the highest monthly mean probably due to the heavy downpour a couple of days before the sampling day. The TDS/SS values were all far below the acceptable level. Higher values recorded for conductivity and turbidity during the peak periods is an indication that tourism may be having some effects on water quality at Wli, even though the effects are insignificant.

The highest annual means for the three parameters at Lake Bosomtwi just as it happened at Wli Waterfalls was recorded at a single site (BAB), which also happens to be the main tourist center at Bosomtwi and therefore attracts more tourist than the other sites. The value reduces as one moves away from BAB, due to the reduction of rippling effects on the water body. The peak period means were also slightly higher than those recorded for the lean periods even though they are not significant.

In water quality analysis, high volumes of suspended materials are not acceptable because they provide absorption site for biological and chemical agents. It may also be degraded biologically, resulting in objectionable by-products (De Zuan, 1997). Another major effect of high conductivity, turbidity and TDS/SS in water is that it increases the hardness of the water, thus making it unsuitable for domestic purposes such as washing

(Spellman and Drinan, 2000). More money is spent on extra soap so as to be able to use the water and this serves as the drain on the resources of the residents.

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5.2.4 NO3/NO2 Nitrate and Nitrite are elements when found in large quantities (more than 5mg/L) is an indication of human or animal waste pollution or pollution from fertilizer (Karikari,

1998; Chapman, 1992). All NO3 values recorded for Wli Waterfalls (0.1mg/L–0.8mg/L) were far below the acceptable limits of 10mg/L. This is an indication that the water has not been polluted much. However values of above 0.5 and 0.8 were recorded at WDR and

WPS respectively. These are the sites that anthropogenic activities are high due to the swimming and fetching of water for domestic use. Again, periodic variations were very minimal even though the peak periods were slightly higher than those recorded for the lean periods. This is an indication that anthropogenic activities, including that of tourism activities are affecting the quality of the water at Wli Waterfalls (Karikari, 1998;

Chapman, 1992) even though not enough to be significant. Studies by Karikari (1998) and Osafo (1989) in the Volta Region recorded means values of between 0.2mg/L–

0.22mg/L which were not different from the results of the study. Values ranging between

0.1mg/L–29.0mg/L were recorded by Adzalu (1998) in a study carried out in Western and Central Regions.

Values recorded at the Lake Bosomtwi though slightly lower were almost similar to those recorded at Wli Waterfalls. Also variations between the periods were very minimal with that of the peak periods slightly higher than those recorded during the lean periods. One of the reasons for the slightly lower values recorded in the Lake Bosomtwi than Wli

Waterfalls may be due to the presence of animals in the Agumatsa forest which increase animals waste into the Wli Waterfalls as compared to the Lake Bosomtwi (MBGnet,

2006). Studies conducted by Karikari in the Volta Lake recorded values between

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0.01mg/L to 0.08mg/L. Another one as indicated by Spellman and Drinan, (2000) as well as Tundisi and Straskraba (1999) also indicated that natural lakes and reservoirs usually have less than 2mg/L of NO3.

NO2 values in most cases depend on NO3 values recorded (Spellman & Drinan, 2000).

NO2 values recorded at both Wli Waterfalls and the Lake Bosomtwi did follow similar pattern as those recorded for NO3. Sites with high anthropogenic activities such as WPS and BAB recorded the highest means of between 0.03mg/L to 0.04mg/L. These figures are however, far below the acceptable limit. Variations between the periodic means were also insignificant. It is an indication that the effect of tourism on NO2 in the water body is not that much.

5.2.5 PO4 Phosphates are pollutants associated with the oxidation of organic matter in waste effluents, especially those containing detergents (Akuffo, 1998; Chapman, 1992). They are also strongly bonded to soils (Russell, 2009) and as a result, PO4 is actively taken up by plants (Spellman & Drinan, 2000). Higher concentrations are indication of pollutants which most often results in eutrophication. Most of the values recorded, especially those recorded at WDR and WPS were above the natural background level of 0.3mg/L. This may be due to the fact that washing is done around these sites is high. The differences between the periods were minimal leading to insignificant relationship except that of

WPS which was significant (ANOVA p>0.05). This is an indication that anthropogenic activities, including that of tourist are slightly affecting the water body at Wli Waterfalls.

Phosphate values for the Lake Bosomtwi also followed the same pattern as that of Wli

Waterfalls. They were all above the acceptable level, indicating that anthropogenic

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activities, including that of tourists are affecting the Lake Bosomtwi. Surprisingly however, the mean values for the lean periods were slightly higher than those recorded for the peak periods. Observations made by the researcher indicates that residents are not allowed to do washing along the banks of the Lake Bosomtwi on days that tourist flock to the area in large quantities.

5.2.6 Calcium (Ca) and Magnesium (Mg) Geology of a site affects the Calcium values of water bodies in that area. This is because

Ca ions is readily dissolved from rocks rich in Ca minerals such as carbonates and sulphates (Akpabli & Drah, 2001). Ca is therefore found in all water bodies and it combines with magnesium to cause hardness (Karikari, 1998). Ca values recorded for

Wli Waterfalls were from <1.0mg/L to 3.4omg/L. They were far below the WHO acceptable limits of 200mg/L in drinking water. Even though the mean values recorded for the peak periods were slightly higher than those recorded for the lean period, they cannot be attributed strictly to tourism. The Ca content in the water may come from the rocks found in the basin of the water body (Akpabli & Drah, 2001).

Even though Ca values recorded in the Lake Bosomtwi were all below the WHO acceptable level of 200mg/L they were higher than those recorded at Wli Waterfalls. The values ranged from 2.8mg/L to 44.1mg/L. Also, even though the mean values for the peak periods were slightly higher than those recorded for the lean periods, the variations were so minimal that they were all insignificant apart from the values at BAM. Tourism could therefore not be responsible for that in the strict sense. It must be noted however that the highest annual means for both sides were recorded at sites with high anthropogenic activities. This may be due to the fact that the presence of human being

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may lead to high attrition with rocks thus increasing weathering which may release the

Ca from the rocks in the water bodies (Oram,2014; LennTech,1998).

Magnesium is very common in most surface water bodies. Levels in water bodies are most often affected by types of rocks found in the basin of that water body. It combines with calcium to determine the hardness of water bodies (Karikari et al 2013). Value recorded at both Wli Waterfalls and Lake Bosomtwi were far below the WHO acceptable limit of 150mg/L. Values recorded at the Lake Bosomtwi were higher than those recorded at Wli Waterfalls. Again, values recorded during the peak periods were slightly higher than those recorded for the lean period. Differences between them were however minimal and as such were all insignificant. The Mg content of both Lake Bosomtwi and

Wli Waterfalls may be attributed to the rocks found in the basin of the two water bodies.

The slight differences between the periodic means may be due to the presence of high anthropogenic activities leading to high attritions on such occasions leading to increased weathering which releases the Mg in the rocks into the water bodies (Oram, 2014).

5.2.7 Chloride (CL) and Sodium (NA) Chloride is present in water bodies at various concentrations. High level can make it unpalatable and unfit for drinking. In combinations with sodium, it gives salty taste. High concentration of it in a non –saline water body may be an indication of pollution by industrial waste (Spellman and Drinan, 2000; Chapman, 1992). Cl values recorded at Wli

Waterfalls were very low with mean values of between 2..67mg/L and 3.30mg/L.

Observations by the researcher indicates that measures have been put in place by management of the site to protect the falls from industrial and sewage pollutants. Even

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though the peak periods were slightly higher than those recorded during the lean periods, they were all insignificant. It can therefore not be attributed to tourism.

Values recorded for the Lake Bosomtwi, though lower than the acceptable limit, were quite high. The values ranged from a 116.58mg/L recorded at BAB (the main tourist center) to 123.50mg/L recorded at BNY. Unlike the residents at BAB, those in the other towns dump waste close to the Lake Bosomtwi. Again, the researcher observed that some tourist facilities in these settlements also release their human excreta straight into the lake. The two factors above may have been responsible for the high Cl in the Lake

Bosomtwi.

Sodium values recorded in Wli Waterfalls followed the same pattern as that of Cl with all of them being very low (0.50mg/L to 3.80mg/L). The reasons for the above may be the same as that of Cl. The Na values for the Lake Bosomtwi also followed the same pattern as that of Cl. The annual mean values ranged between 163.34mg/L to 198.92mg/L.

Unlike Cl, the highest value was recorded at BAB. It could therefore be linked to anthropogenic activities by residents and tourists alike.

5.2.8 Potassium (K) Natural sources of potassium in water bodies are from the rocks in the basin of that water body. The contents are very low because potassium bearing rocks are relatively resistant to weathering. It was therefore not surprising that low values were recorded at both Wli

Waterfalls and Lake Bosomtwi. Values between 0.30mg/L and 1.70mg/L, and 4.30mg/L and 26.20mg/L which were far below the acceptable limit of 30mg/L were recorded for

Wli Waterfalls and Lake Bosomtwi respectively. The values for the peak periods were slightly higher than those recorded for the lean periods but all of them were insignificant

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due to the minimal nature of the differences. The differences in the values recorded at both sites may be due to the fact that the Lake Bosomtwi is a stagnant water body without any outlet. Potassium derived from the surrounding hills through farming activities and drains into it by run-offs accumulate in it.

5.2.9 Alkalinity Alkalinity of water is the measure of the water‟s ability to absorb hydrogen ions without significant changes to pH (Chapman, 1992). That is the level of ability of the water to neutralize acids. The major chemical compositions of alkalinity are bicarbonate, carbonate and hydroxyl ions. Alkalinity values at Wli Waterfalls ranged from 7.20mg/L to 14.50mg/L which were all below WHO acceptable limit of 400mg/L for drinking water. Values recorded for the peak periods were slightly higher than those recorded for lean periods. The highest annual mean as well as the periodic means were all recorded at

WUF. This may be due to the activities of residents who fetch water at that place for domestic purposes.

Alkalinity values for Lake Bosomtwi on the other hand were quite high ranging from

312mg/L to 532mg/L. Values for the lean periods were slightly lower than these recorded for peak periods. Even though the highest value was recorded at BAM, the highest values for both annual and periodic means were all recorded of BAB. Again, some values recorded during the peak periods were above the acceptable limit of 400mg/L. The high values could be attributed to tourism as well as other anthropogenic activities such as washing of cars and dishes a BAB and WDR respectively. It could also come from the rocks/soils that are beneath the water body (Spellman & Drinan, 2000).

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5.2.10 Trace Metals Analysis All heavy metals exist in surface waters in colloidal, particulate and dissolved forms,

Dissolved concentrations are however, generally very low. Living organisms require trace amounts of some heavy metals including Cu, Fe, Mn and Zn. Excessive levels of essential metals however, can be detrimental to the organism. Others like Pb and Cd are not essential to living organisms (Spellman & Drinan, 2000; De Zuane, 1997;

Tchobanoglous & Schroeder, 1987).

The same values were recorded for Cu, Pb and Cd throughout the sampling periods and they were all below the acceptable limits for WHO standards. Since both the lean and peak periods recorded the same values, it could not be attributed to the presence of tourist or anthropogenic activities by the residents.

The only heavy metal that had values were above acceptable limits of the WHO was iron.

The peak periods were also slightly higher than those recorded for the lean periods. This could not be strictly attributed to tourism activities. WDR and WPS recorded the highest values probably due to high weathering as a result of attrition at the place due to the fact that residents fetch water there for domestic use and swimming by tourists. This results in high weathering due to high attrition from residents and tourists alike.

Iron values recorded for Lake Bosomtwi ranged from 0.1mg/L to 0.4mg/L. Annual mean values ranged between 0.12mg/L and 0.21mg/L which were all above the acceptable limit of 0.03mg/L. The reasons for this may be due to the facts stated for that of Wli

Waterfalls.

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5.2.11 Bacteriological Analysis Coliforms refers to a large group of grain-negative rod-shaped non-spore forming bacteria that develop red colors with metallic sheen within 18 to 24 hours of incubation at

o o 37 C and 44 C for total and fecal coliforms respectively on an endo–type medium containing lactose. The group includes thermos-tolerant coliforms of fecal origin as well as some bacteria that may be isolated from other environmental sources. Thus the presence of total coliforms may or may not include fecal contamination (Bartram &

Balance, 1996).

Generally, high values were for total and fecal coliforms at all the sites at both Wli

Waterfalls and the Lake Bosomtwi. Total coliforms values ranged from 505cfu/100mL to

2418cfu/100mL and 554cfu/100mL to 2594cfu/100mL respectively for Wli Waterfalls and Lake Bosomtwi. Fecal coliforms also ranged from 108cfu/100mL to 1488cfu/100mL and 110cfu/100mL to 848cfu/100mL for Wli Waterfalls and the Lake Bosomtwi respectively. They were all above the WHO acceptable limit of drinking water

(0cfu/100ML).

Even though the salt content of Lake Bosomtwi was higher than that of Wli Waterfalls, the highest annual mean values for the coliforms were still recorded at Bosomtwi. This may be due to the fact that Wli Waterfalls is a flowing water body and as such the bacteria are swept downstream. The Lake Bosomtwi is stagnant without any outlet but receives high amount of water from surrounding hills. Differences between the periods are slightly higher at Wli Waterfalls than at the Lake Bosomtwi with the peak periods recording higher values than the lean periods at all sites. Differences between periods of some sites such as WPS, WUF and BOB were significant. It must be noted that the high

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difference between the periods is an indication that tourism may be having some impact on the water bodies. Proper sewage disposal systems have not been installed for tourists to use. Improper disposal by tourist may lead to pollution of ground water from the sewage.

5.3 Land Use Analysis Each land cover and land use over the years is associated with a number of environmental consequences and the interactions between the above two have been identified to be persistent because of the significant effects they have on the earth system functioning such as changes in the atmospheric composition and extensive modification of ecosystems (Lambin et al, 200). Land cover types in the basin of Wli Waterfalls have experienced a diversity of changes over the twenty-year period considered for the study.

Throughout the study period, opened forest vegetation and closed forest vegetation cover occupied a larger portion of the area under study around the Wli Waterfalls. Even though the closed forest vegetation is scattered all over the study area, it is more densely concentrated in the eastern and northern parts of the Wli Waterfalls than the other areas.

The opened forest vegetation on the other hand covers the southern and western portions of the study area mostly even though it is also wide spread.

There was a drastic reduction of the forest vegetation coverage from 94.14% of the study area in 1990 to 69.9% in 2000. The loss of the forest vegetation between 1990 and 2000 seems to be principally induced by anthropogenic activities through the conversion and utilization of natural vegetation around the waterfalls to other uses. This is especially so at areas where physical and economic factors forced the people to clear the land for farming and cutting of the trees for firewood.

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However, there was a drastic change in forest vegetation for the better between the period of 2000 and 2010. This improvement in the forest vegetation cover could be attributed to the effects of effective management practices that have been put in place to protect the forest around the waterfalls from deforestation and also to restore the lost vegetative cover in the area. This was done by banning the community members from farming around the waterfalls and the Agumatsa Wildlife Sanctuary was also created for reafforestation. This led to the prohibition of farming and cutting down of trees in the areas surrounding the waterfall and this law is strictly enforced. Again intensive education and sensitization programs have been going on in the area for some time now and this seems to be working at least for now.

The land cover types within a two kilometer buffer zone around the Lake Bosomtwi used for the study also experienced some diversity of changes over the period of study. Water bodies (mainly the lake), the closed forest and opened forest vegetation are classes that cover a large portion of the area under study around the Lake Bosomtwi. Even though the closed forest vegetation is scattered all over the study area, it had reduce drastically to the north east with the stretch between Nkowie and Pipie not having any closed vegetation by

2010. Opened forest vegetation on the other hand was dotted among the closed forest vegetation but started increasing slowly and by 2010 had covered large portion of western and north eastern parts of the study area with the space between Nkowie and

Pipie almost covered with the opened forest vegetation.

The changes that took place in the study area around the Lake Bosomtwi between 1990 and 2000 were as a result of anthropogenic activities. The forest vegetation coverage was reduced probably due to the fact that residents were turning parts of it into farms. Dense

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shrub, grassland and built up/bare areas coverage increased because the activities of the residents such as building and farming increased. There was however, a mixed type of changes at the study area between the ten-year period of 2000 and 2010. While closed forest vegetation coverage reduced, that of opened forest vegetation increased marginally.

Dense shrub, grassland and built up areas also increased drastically. There was a slight increase in opened vegetation because a one year Collaborative Ecosystems Conservation on Lake Bosomtwi was launched by ROCHA in 2014 with sponsorship from UICN.

Increase in residential properties as well as in tourism related facilities such as hotels have also increase. It was therefore not surprising that the coverage of water bodies such as rivers and streams and especially the lake reduced throughout the e twenty-year period considered for the study. This is due to the conversion of natural vegetation around the lake into other uses such as farming. Participant observation by the researcher indicated that dumping of waste into the lake in some communities as well as other anthropogenic activities have contributed to the drying up of the lake.

5.4 Perceived Impacts of Tourism 5.4.1 Perceived Environmental Impacts A major objective of the study was to assess the effects of tourism on the environment.

Table 5.1 below shows the dimensions of environmental effects of tourism in the two study areas as perceived by the respondents. Respondents in the communities around the

Lake Bosomtwi “ strongly agreed” (4.23) that the Lake Bosomtwi is highly polluted. They also “agreed” that problems such as congestion and increasing noise in the community due to tourism development (3.83) and deterioration in the natural environment due to the provision of tourist facilities (3.96) as well as increase in vandalism (3.98) is on the

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increase. They were however, not sure if deforestation is taking place because people are clearing the land to farm so as to produce food for the tourist (2.43). As to the positive environmental effects, they only agreed sparsely (3.06) to the fact the tourism development creates incentives for restoring other environmental resources. These same respondents were also “not sure” if tourism development has led to improved sanitation

(2.25) or has provided incentives for restoring of historic buildings (2.47).

Table 5.1: Likert Scale Table on Perceived Environmental Impacts

ITEM OF DESCRIPTION LAKE BOSOMTWI WLI WATERFALLS

No Mean St. Dev No Mean St. Dev

Deterioration in environment due to 255 3.96 1.48 210 1.92 1.40 construction of hotels Problems such as congestion and noise 253 3.83 1.33 210 2.01 1.36 Vegetation cleared to increase food 251 2.43 1.28 208 2.45 1.38 supply Water pollution increases due to tourism 251 4. 23 1.00 209 2.42 1.17 Vandalism increases due to tourism 251 3.98 1.40 210 1.82 1.34 Improved Sanitation 251 2.25 1.21 209 4.21 1.3 Incentives for restoring historic 250 2.47 1.26 210 4.01 1.04 buildings 210 4.62 1.28 Incentives for restoring other 250 3.06 1.42 environmental resources

Scale: 1="Strongly Disagree"; 2="Disagree"; 3="Neutral"; 4="Agree"; 5="Strongly Agree"

To the residents in the communities around Wli Waterfalls however, the positive effects of tourism development on the environment far exceed the negative effects. Respondents

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in the communities around Wli Waterfalls “strongly agreed” that tourism has led to improved sanitation (4.21), provided incentives for the restoration of other environmental resources (4.62) as well as incentives for restoring historic buildings (4.01). They however, out rightly disagreed or were not sure on the issue of negative effects. The respondents “disagreed” that tourism development has led to increase in vandalism in the community (1.82) or has led to deterioration in the environment due to the construction of facilities for tourist (1.92). They were also neutral (not sure) whether tourism development has led to problems such as increased congestion and noise in the community (2.01), pollution of the waterfall (2.42) and deforestation due to increase in farms to feed tourist (2.45).

Responds from respondents and personal observations indicates that effects of tourism are more severe on the Lake Bosomtwi than on the Wli Waterfalls. This may be attributed to the fact that tourism activities have been going on for a longer period at the

Lake Bosomtwi than at the Wli Waterfalls. Again the conditions that prevail at the two attractions are different. Boating, which takes place on the lake is likely to increase oil content in the lake (Mathieson & Wall, 1982). Unlike the river that flows, the lake is stagnant with a number of streams flowing into it with debris. It is very difficult however, to attribute the pollution of the lake to tourism alone. This is because the lake is surrounded by the settlements of the indigenes that also use the water as much as the tourist if not more. It is therefore difficult to differentiate between changes induced by pre-existing processes and those induced by the influx of tourist as buttressed by Wall and Wright (1997).

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On the issue of restoration of other environmental resources due to the flourishing of tourism, Wli Waterfalls recorded above average as compared to average for the Lake

Bosomtwi .The managers/operators at Wli Waterfalls have been able to create a forest reserve (Agumatsa Wildlife Sanctuary) leading to the preservation and conservation of both flora and fauna. Again, even though a couple of facilities have sprung up in the communities around the waterfalls, it cannot be compared to the numerous hotels and other facilities scattered in the communities around the lake. Environmental resources are therefore destroyed to pave way for the construction of these facilities (Cooper, 2012;

Lickerish & Jenkins, 1997; Uysal et al, 1992).

In areas with high concentration of tourist activities and appealing natural attractions, waste disposal is a problem and improper disposal can destroy natural environment such as water bodies (Suulu, 2003). Solid waste and litter made up of plastics and rubber, paper, cans and bottles are a common sight along the path to the Wli Waterfalls and most especially along the banks of the Lake Bosomtwi. Even though there are some few dust bins scattered along the foot path to the waterfalls and the banks of the lake, the high volume of tourist that have started visiting these places (most especially Bosomtwi) has contributed to the rapid garbage generation to an extent that it has exceeded the ability of the residents to manage them. Apart from Abono that has some few dust bins dotted along the banks of the lake, tourist hiking along the banks of the lake litter around by leaving behind garbage that they generate. This is compounded by the problem of inadequate waste management system in communities. This notion confirms the views of

Suulu (2003), who said that tourist leave behind about 70,000 tons of waste every year in the Caribbean and this affects the environment with all the detritus typical of remote

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areas that have few garbage collection or disposal facilities. Both study areas for example do have few places of convenience which do not even meet international standards.

With only four tourist facilities at Wli Waterfalls (three hotel/guesthouse and Tourist

Information Center), it was expected that respondents will not agree to the issue of environmental destruction due to construction of tourist facilities. Respondents around the Lake Bosomtwi however, agreed to it due to the fact that eight tourist facilities were counted between Anyinatiase and Nkowi (seven hotels /guest houses and a Tourist

Information Center). Some respondents in the communities around the Lake Bosomtwi claimed that their farm lands have been taken away from them and given to investors by the traditional authorities with little or no compensations.

Respondents in communities from both study areas were uncertain as to whether the destruction of vegetation was as a result of increase in agriculture activities. This is because crops such as bananas and apples that the tourists buy most are not produced in the area. It is only on festive occasions that when the local tourist comes that they do patronize the produce from the local farms. This confirms a postulation by Mbaiwa

(2003) that development of tourism do not necessary influence agricultural production in especially rural communities. He argued that even though tourism has developed rapidly within the last decade in the Okavenga Delta in Bostwana, most of the farm produce used in the area comes from Namibia, South Africa and Zimbabwe.

While respondents from the communities around the Wli Waterfalls were not sure as to whether there has been some increase in noise making, those around the Lake Bosomtwi agreed. Operators at Wli Waterfalls restrict the level of noise making claiming it disturbs

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the animals in the forest reserve. It is on some festive occasions that they allow the tourist to send music instruments to the falls. A similar work by Roodt (1998) confirmed that noise affected the hippopotamus population as well as nesting birds and other wild life species in the Xakanaxa area of the Moremi Game Reserve in Bostwana.

Observations in the communities around the Lake Bosomtwi proved otherwise. This is due to the fact that the attractions are in the midst of the communities, some amount of noise come from them. The problem becomes even worse on festive occasions (public holidays) when a lot of partying goes on along the banks of the lake deep into the night.

Respondents at Abono in particular also complained of congestion and it may be due to the fact that the tourism activities are concentrated at Abono at the expense of the other communities around the Lake Bosomtwi.

Even though respondents agreed that environmental problems have increased within the last couple of years in their communities with about 42.4% of them listing poor sanitation and water pollution as the major environmental problems in the study areas, majority of them expressed doubts as whether tourism development was responsible for that. This was found to be consistent with the views of Amuquandah (2010), that residents in the communities around the Lake Bosomtwi are not sure whether pollutions of the lake is as a result of tourist influx. This perception is however high among the residents at Wli

Waterfalls than those around Lake Bosomtwi. Informal discussions with some residents and operators of tourism facilities indicates that some of the hotels/guest houses release their waste directly into the lake and this might have influenced the results from respondents around Lake Bosomtwi to be more negative than those around Wli

Waterfalls.

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5.4.2 Perceived Economic Impacts Assessing the economic effects of tourism on the two communities was one of the major objectives of the study. Table 5.2 below shows the responses from residents from the communities on the perceived effects of tourism on the micro-economy of the communities. The Likert scale type of analysis was used.

Residents from communities around both Wli Waterfalls and Lake Bosomtwi to some extent were "not sure" (neutral) to the fact that tourism development has led to some improvement in infrastructural development such as roads. There was not much difference between the mean values for both Wli Waterfalls (2.90) and Lake Bosomtwi

(2.49). Residents of communities around Wli Waterfalls were however more positive on the above than those around the Lake Bosomtwi.

Table 5.2: Likert Scale Table on Perceived Economic Impacts

ITEM OF DESCRIPTION LAKE BOSOMTWI WLI WATERFALLS

No Mean St. Dev No Mean St. Dev

Improvement in road infrastructure 254 2.49 1.36 206 2.90 1.32 Creation of more jobs in community 251 3.06 1.49 194 4.45 1.16 Increased farming and fishing activities 249 3.14 1.34 197 3.16 1.28 More investment in community 249 3.14 1.34 197 4.42 1.28 Increase spending in community 250 3. 00 1.36 192 2.24 1.23 Improvement in standard of living 249 2.75 1.27 193 4.38 1.40

Increase in growth of local businesses 249 2.59 1.31 194 4.14 1.30

Tourism revenue more important than others 250 2.14 1.14 191 3.98 1.45

Tourist spending increases prices of products 250 3.57 1.37 190 3.87 1.05

Scale: 1="Strongly Disagree"; 2="Disagree"; 3="Neutral"; 4="Agree"; 5="Strongly Agree"

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Residents around the Wli Waterfalls were positive on the issue that tourism has led to an increase in investment and job creation in their communities than those around Lake

Bosomtwi. With means of 4.42 and 4.45 respectively, respondents in communities around Wli Waterfalls "strongly agreed” to the fact that, more investments and jobs creation has come into their communities. Respondents around Lake Bosomtwi on the other hand only „agreed‟ that there has been some increase in investments (3.14) and jobs creation (3.06) with the development of tourism. Again respondents from both study areas only "agreed" (3.16 and 3.14 for those around Wli Waterfalls and Lake Bosomtwi respectively) that tourism has led to an increase in farming and fishing activities in their communities. Respondents in both communities accepted that there has been some increase in spending, especially by tourist in their communities as well. Respondents in communities around Wli Waterfalls „not sure/neutral‟ (2.24) to a sharp increase in spending in the communities, while those around Lake Bosomtwi "not sure/neutral"

(3.00) that there has been some increase in spending by tourist in their communities.

Corresponding to this is the sharp increase in the prices of goods in their communities with means of 3.87 and 3.57 at Wli Waterfalls and Lake Bosomtwi respectively. Also respondents from Bosomtwi were "not sure" (2.59) whether tourism has led to the increase in the growth of local businesses with their counterparts around Wli Waterfalls strongly agreed (4.14) that tourism development has led to an increase in the growth of local businesses.

Furthermore, respondents in communities around Wli Waterfalls „strongly agreed‟ (4.38) that growth in small local business has led to an improvement in the standard of living in their communities with those from around the Lake Bosomtwi "not sure" (2.75) if the

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growth in small businesses has led to an improvement in the standard of living in the communities. Finally respondents from communities around Lake Bosomtwi "not sure/neutral" (2.14) that revenue from tourism is more important than other sources of revenue with those from around Wli Waterfalls on the other hand "agreeing" (3.98) that revenue from tourism is important than from other sources.

One major area through which tourism can influence the domestic economy of destination areas is through infrastructural development, especially that of roads

(Mbaiwa, 2003; Mings, 1979). The opposite however is the case for the communities in both study areas. In the Bosomtwi District, it is only the trunk road between Kuntunase, the district capital and Abono the major tourist center that is in motorable state. The roads from Abono to other communities such as from Abono through Obo to Nko wie and from

Abono through Adwafo, Abrodwum, Abease to Anyinatiase are so bad that it is only motorable during dry season. Similarly, the trunk road through Hohoe is the only road in a good shape. However the one from Hohoe to the waterfalls is in a deplorable state. The residents of the study areas rarely use the trunk roads. It is the access routes from the tourist sites to the district capital that they mostly use. The bad nature of these roads may have accounted for the responds from the residents.

According to Dickman (1992) the provision of food, equipment, furniture as well as constructions facilities and provisions of other goods and services in the host community are needed to make the tourist comfortable. This calls for investments in the host communities (Mings, 1979). This was confirmed with the study when respondents in the communities around Wli Waterfalls "strongly agreed" that investments have increased as compared to the "agreed" by respondents from communities around the Lake Bosomtwi.

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The difference may be due to the fact that a couple of hotels for tourist use had been commissioned not quite long ago at Wli Waterfalls with another one being under construction and the residents are fascinated about them. Even though there are more hotels around the Lake Bosomtwi than Wli Waterfalls, the expectations at Wli Waterfalls are high since they are new and this may have influenced the response. This seems to confirm Andereck and Vogt, (2000) and Liu and Var (1986) arguments that in economically depressed regions, local residents tend to over–estimate the economic gains of tourism. Even though the overall responds from residents around the Lake Bosomtwi agrees with the finding of Amuquandoh (2006), they are at the low side. This may be due to the fact that the residents around the Lake Bosomtwi have now begun to feel the true effects of tourism.

Closely related to investments is the issue of job creation. Conforming to Amuquandoh

(2006) arguments, respondents from communities at both study areas agreed that tourism development has led to an increase in job creation in their communities. It was however, higher among the residents around Wli Waterfalls with "strongly agree" to the "agreed" by those around Lake Bosomtwi which was also lower than that of Amuquandoh (2006).

The reasons for this may be the same as those for the increased investments. The rotational system of recruitment of tour guides from the various clans in the communities around Wli Waterfalls may be responsible for the respondents there being more positive than those around the Lake Bosomtwi. This was confirmed by the answers to the question on the number of respondents or their relations who are working or had ever worked in the tourism industry. Only 33.2% of the valid respondents from communities around

Lake Bosomtwi claimed that, they or their family members had ever worked in the

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tourism industry as compared to 48.2% of the valid respondents from the communities around Wli Waterfalls. One factor that may also have affected the responds of the residents on job creation is the type of jobs created. Most of them are lowly paid manual jobs such as cleaners, watchmen and cooks in the hotels/guest houses as well as tour guides (Mbaiwa, 2003). It was therefore not surprising that 33.4% of all respondents who had worked in the tourism but are no more working in the industry cited the above reasons for leaving the industry.

Respondents from communities in both study areas only agreed that farming and fishing

(the two major occupations in the study areas) activities have increased with the development of tourism. The mean for Wli Waterfalls was slightly higher than the one recorded for Lake Bosomtwi. This may be due to the fact that some respondents from communities around Wli Waterfalls claim that some fruits like orange and banana bought by the tourist are produced by them. Informal discussions with traders and operators of tourist facilities indicate the development of tourism in the study areas have not been able to influence agricultural production very much. The over reliance of the tourism industry in the study areas on agricultural produce from outside the study areas is an indications that it has not yet affected agricultural activities very much. This confirms the findings of

Mbaiwa (2003) and Frechtling, (1994) in a study at the Okavango Delta in Botswana.

Another reason that respondents cited as a possible cause for the under development in the agricultural sector in the study areas is the problem of taking over farm lands for tourism related projects. Some tourist facilities like hotels/guest houses in the Bosomtwi area as well as the Agumatsa Forest Reserve in the Wli Waterfalls area are all occupying lands that were previously farm lands.

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Finally, the issue of the youth moving from agriculture and fishing to the "quick–money– making" tourism industry is another reason for the not so impressive growth in agricultue and fishing activities. Decline in the output of major occupations such as farming and fishing in tourism destination areas most often force the youth in such communities to turn to tourism as an alternative source of livelihood (Amuquandoh, 2006). It was therefore not surprising that 23.8% and 35.6% of valid respondents from communities around Wli Waterfalls and Lake Bosomtwi respectively cited youth neglecting farming to join tourism as a cause for the decline in agricultural activities in the study areas.

5.5 Level of Participation in the Management of the Attractions by Local Residents The type of management strategies put in place by the managers of a tourist facility in consultation with the local residents determines the level of participation in the management of the resource by the residents (Brandon, 1993; Keogh, 1990). The management strategies at both places are almost similar though implementation is quite different.

The Wli Waterfall is located within the Agumatsa Wildlife Sanctuary which covers over three sq km of land belonging to the nine clans found in the four communities around the waterfall. The attraction is managed by a 13 member Tourism Management Committee

(TMC). They are made up of a representative each from the nine clans, representative each from Municipal Assembly and the town development association, the remaining two coming from the traditional council. They serve a four-year term and hand over to a new team. The clan members on the committee serve as the main tour guides with few others that they select from the communities. All routes to the attraction have been blocked with the exceptions of the footpath from Wli Afagame where the offices to the TMC are

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located. These same offices serve as Tourist Information Center. All tourists going to the attraction goes through that office to pay the gate fees. At the end of the year, all the total proceeds are shared among the stakeholders. The Municipal Assembly takes 20% of the gross. The remaining amount is converted to hundred percent and shared among the four communities of Agoviefe, Afegame,Todzi and Dzogbaga that produces the nine clans and the surrounding villages. 25%, 20%, 20%, 15% and 5% are given to the Tourism

Management Committees (TMC) of Agviefe, Afagame, Todzi, Dzogbaga and the surrounding villages respectively. The remaining 15% is then given to the land owners of

Agumatsa Wildlife Sanctuary. The TMC is supposed to meet the community members in a forum to agree on the development projects that the proceeds from gate fees should be used for.

However, residents indicated that the forums discussed above rarely takes place. When they do happen at all, only a selected few (mostly cronies of the committee members) are invited. On the few occasions that they are opened to the public, they are only informed about what the committee has done or are doing without allowing questions. Irrelevant answers are given questions asked at such forums. The above is an indication that residents around the Wli waterfalls are still at the non-participation stage (manipulation) at the lower rung on the ladder of citizen participation with some traces movement up to the information level at the lower rung of degree of tokenism stage (Arnstein, 1969). This is because a selected few have been put on the "rubber-stamped" advisory committees.

The main function for these "rubber-stamped" advisory committees members is to educate the residents to support for the programs of the managers. They do not have any

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legitimate powers to operate. They are only used to prove that the “grass root” people are also involved in the decision making process.

Even though Bosomtwi is also supposed to have a TMC in place to manage the resources, it is only in name. The management committee is suppose to be made up of representatives from the District Assembly, representatives from the traditional authorities and the rest from Abono (the major tourist center) and the other communities surrounding the lake. The representatives from the other towns surrounding the lake claims the residents of Abono do not allow them to benefit from the gate proceeds so they do not want to be part of the management committee. There is also no systematic way of collecting gate proceeds. The District Assembly on festive occasions mount roads blocks between Kuntunase, the district capital and Abono to collect money from all those going to Abono. The representatives from Abono at the Tourist Information Center also try to extract monies from the tourist as well. Should the tourist move to the other communities such as Obo, Abrodwum, Anyinatiase and the other communities, they also try to extract money from the tourist claiming that they do not get anything from the gate proceeds.

The residents claim that they are hardly invited to public forums organized by the TMC.

On the few occasions that such forums are organized, they are not invited. Some also say that even if they are invited, they will not attend. This is because on the few occasions that they have attended such forums, decisions agreed on are not implemented. Again, monies collected are not accounted for properly. The resources are controlled by the selected few who form the TMC and the government to some extent. This has therefore resulted in the lack of meaningful participation of the locals in the management of the tourism industry. Major decisions and policy issues in relation to tourism development

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therefore were taken without their full participation. Residents of the communities around the lake are therefore still on the non-participation stage of manipulation which is the lowest rung of the ladder on Arnsteins ladder of citizen participation. This is because the representatives from the other communities are only stooges for the representatives at

Abono and the District Assembly. Their major function is to educate their other colleagues not to kick against or reverse official decisions.

5.6 Relationship between Environmental Impacts and Economic Activities in Study Area Even though the water bodies serving as attractions (especially that of Wli Waterfalls) have not been polluted very much. The pollution that has taken place is affecting economic activities in the communities in the study areas. The communities around the

Lake Bosomtwi use the water for some domestic purposes and therefore at this level of pollution the raw water would have to be treated before use. Some residents around the

Wli Waterfalls also complain about the difficulty they are facing in drinking the water from the waterfalls without treating them since tourist including women who may be menstruating (taboo) swim at the pool site which flows down to where the residents fetch water for domestic use. The above problems coupled with the fact that water rarely flow through the few taps found in some of the communities have compelled the residents to resort to the use of sachet water for drinking, while they continue to use the waters in the

Lake and Waterfalls for other domestic purposes. This affects the well-being of the residents since the money used in purchasing the sachet water could have been used to take care of other pressing needs. Others, especially poor farmers who cannot afford to buy the sachet water from other sources still depend on the waterfalls for drinking and other domestic uses. This affects their health and the end result is that money is spent on

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the treatment of diseases that may emerge from using this water source. It was therefore not surprising that cholera/diarrhea and to some extent Malaria were listed as the most prevalent diseases in both study areas. Working hours are lost in the process and this affects economic productivity in the communities.

Related to the above is the problem of low fish catch in Lake Bosomtwi. A major effect of high conductivity, turbidity, and TDS/SS is that it affects the water balance in the cells of aquatic organisms which make it sink or float to a depth it is not adapted to (Spellman

& Drinan, 2000). This may lead to a change in temperature surrounding the organisms.

Most aquatic organisms are poikilothermic and the drastic change in temperature may affect fish and other micro-organisms that serve as food to the fish. The spawning process of the fish may also be disrupted. The sound of speeding boats may also affect the habitat of the fish. This may have resulted in the complaint by fishermen that there has been a reduction in fish catch with the increase in tourist activities such as swimming and boating on the lake. The implication is that it is going to make the fishermen poorer if the lost income from fishing is not compensated with tourism related earnings. Again in an attempt to protect the waterfalls, fishing in the river that serves as the source of water for the waterfalls has been banned. This has affected the economic well-being of those who would have been fishing for their livelihoods.

Personal discussions with residents indicate that agricultural activities have also been affected by the environmental effects of tourism. Even though the environmental effects are not negative, its effects on agriculture are more negative than positive. In an attempt to protect the Wli Waterfalls for example, the Agumatsa Wildlife Sanctuary was created.

The area that the forest reserve covers used to be farmlands and it was taken away from

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them with a promise of jobs and other benefits from tourism. This however did not materialize and has rendered the farmers poorer. Again residents (especially those from the communities around Lake Bosomtwi) claim that their farmlands are forcibly taken away from them by the traditional authorities and given to investors to build tourism facilitates such as hotels and restaurants without any compensation. At Wli Waterfalls also, the buffer zone between the town of Afegame and the forest reserve has been acquired by an investor for the constructions of hotels. This has prevented them from farming in the area and has also resulted in the increase in poverty in the study areas.

Hunting which used to be a pastime for most men in the communities around the Wli

Waterfalls has been banned in order to protect the animal population in the forest reserve.

This has resulted in the loss of income that they would have been derived from selling the game caught in the forest reserve. Again they spend their meager earnings to buy meat/fish that they would have gotten from the forest reserve or the water bodies.

5.7 Relationship between Respondents Socio-Demographic Data and Perception about Effects of Tourism Socio-demographic characteristics have been identified as one of the variables that influence perceptions on the effects of tourism. As a result, the socio-demographic characteristics of the residents in the communities around the Lake Bosomtwi and Wli

Waterfalls were tested against the perceived environmental and economic effects to establish the significant relationships between them. The Pearson Chi-square (PX2) was used to test for significant relationships between socio–demographic characteristics such as age, sex, educational level, occupation, marital status and religion against selected items in the questionnaires such as deterioration in environment due to provision of tourism infrastructure; increase in congestion and noise; vegetation cleared for farming

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activities; increase in pollution of the lake and waterfalls; increase in vandalism; improved sanitation; incentives for restoring historic building and incentives for restoring other environmental resources for perceived environmental effects and improvement in road infrastructure; creation of more jobs in community; increased spending in community; improvement in standard of living; increase in growth of local business; revenue from tourism very important and high spending by tourist increases prices of goods for perceived economic effects.

Table 5.3a: Relationship between Age and Perceived Environmental Impacts (X 2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Deterioration in environment due to construction of hotels 208 14.49 20 0.805 (ns) Problems such as congestion and noise 208 20.62 20 0.402 (ns) Vegetation cleared to increase food supply 207 14.82 20 0.786 (ns) Water pollution increases due to tourism 206 10.48 20 0.959 (ns) Vandalism increases due to tourism 208 29.99 20 0.070 (ns) Improved sanitation 208 16.38 15 0.358 (ns) Incentives for restoring historic buildings 208 18.12 20 0.529 (ns) Incentives for restoring other environmental resources 207 21.46 20 0.498 (ns) Summary of Analysis 0.551 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Deterioration in environment due to construction of hotels 252 21.25 20 0.383 (ns) Problems such as congestion and noise 253 30.40 20 0.064 (ns) Vegetation cleared to increase food supply 251 19.43 20 0.494 (ns) Water pollution increases due to tourism 251 23.12 20 0.003 (s) Vandalism increases due to tourism 251 34.29 20 0.024 (ns) Improved sanitation 251 30.32 20 0.065 (ns) Incentives for restoring historic buildings 250 9.56 20 0.926 (ns) Incentives for restoring other environmental resources 252 22.42 20 0.286 (ns) Summary of Analysis 0.316 (ns)

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Table 5.3b: Relationship between Gender and Perceived Environmental Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value df P-value Deterioration in environment due to construction of hotels 199 7.02 4 0.851 (ns) Problems such as congestion and noise 199 3.55 4 0.420 (ns) Vegetation cleared to increase food supply 199 1.65 4 0.799 (ns) Water pollution increases due to tourism 197 5.32 4 0.256 (ns) Vandalism increases due to tourism 199 2.91 4 0.574 (ns) Improved sanitation 199 9.33 3 0.025 (ns) Incentives for restoring historic buildings 199 1.54 4 0.819 (ns) Incentives for restoring other environmental resources 199 3.62 4 0.528 (ns) Summary of Analysis 0.534 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value df P-value Deterioration in environment due to construction of hotels 238 1.36 4 0.851 (ns) Problems such as congestion and noise 237 8.26 4 0.082 (ns) Vegetation cleared to increase food supply 235 2.77 4 0.597 (ns) Water pollution increases due to tourism 235 5.65 4 0.277 (ns) Vandalism increases due to tourism 235 2.95 4 0.566 (ns) Improved sanitation 235 4.17 4 0.382 (ns) Incentives for restoring historic buildings 234 7.91 4 0.095 (ns) Incentives for restoring other environmental resources 236 5.48 4 0.123 (ns) Summary of Analysis 0.372 (ns)

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Table 5.3c: Relationship between Education and Perceived Environmental Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Deterioration in environment due to construction of hotels 208 11.69 16 0.765 (ns) Problems such as congestion and noise 208 13.68 16 0.011 (ns) Vegetation cleared to increase food supply 207 31.12 16 0.010(ns) Water pollution increases due to tourism 206 33.87 16 0.005 (s) Vandalism increases due to tourism 208 34.15 16 0.006 (ns) Improved sanitation 208 41.36 12 0.000 (s) Incentives for restoring historic buildings 208 20.99 16 0.179 (ns) Incentives for restoring other environmental resources 208 26.32 16 0.186 (ns) Summary of Analysis 0.156 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Deterioration in environment due to construction of hotels 242 13.28 16 0.653 (ns) Problems such as congestion and noise 243 15.50 16 0.489 (ns) Vegetation cleared to increase food supply 241 8.95 16 0.916 (ns) Water pollution increases due to tourism 241 26.3 16 0.050 (ns) Vandalism increases due to tourism 241 24.82 16 0.073 (ns) Improved sanitation 241 15.89 16 0.454 (ns) Incentives for restoring historic buildings 241 20.21 16 0.211 (ns) Incentives for restoring other environmental resources 241 24.62 16 0.003 (s) Summary of Analysis 0.361 (ns)

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Table 5.3d: Relationship between Occupation and Perceived Environmental Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Deterioration in environment due to construction of hotels 206 23.62 24 0.484 (ns) Problems such as congestion and noise 206 33.51 24 0.094 (ns) Vegetation cleared to increase food supply 205 15.86 24 0.893 (ns) Water pollution increases due to tourism 204 33.43 24 0.095 (ns) Vandalism increases due to tourism 206 34.46 24 0.077 (ns) Improved sanitation 206 37.25 18 0.005 (s) Incentives for restoring historic buildings 206 17.24 24 0.838 (ns) Incentives for restoring other environmental resources 206 32.36 18 0.004 (s) Summary of Analysis 0.311 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Deterioration in environment due to construction of hotels 241 38.03 28 0.098 (ns) Problems such as congestion and noise 242 29.85 28 0.002 (s) Vegetation cleared to increase food supply 240 18.04 28 0.925 (ns) Water pollution increases due to tourism 240 36.58 28 0.001 (s) Vandalism increases due to tourism 240 47.65 28 0.012 (ns) Improved sanitation 240 29.36 28 0.394 (ns) Incentives for restoring historic buildings 239 32.23 28 0.265 (ns) Incentives for restoring other environmental resources 240 24.26 28 0.452 (ns) Summary of Analysis 0.269 (ns)

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Table 5.3e: Relationship between Marital Status and Perceived Environmental Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Deterioration in environment due to construction of hotels 206 17.51 12 0.131 (ns) Problems such as congestion and noise 206 18.87 12 0.092 (ns) Vegetation cleared to increase food supply 205 15.78 12 0.201 (ns) Water pollution increases due to tourism 204 8.35 12 0.757 (ns) Vandalism increases due to tourism 206 13.55 12 0.331 (ns) Improved sanitation 206 11.17 9 0.264 (ns) Incentives for restoring historic buildings 206 4.76 12 0.965 (ns) Incentives for restoring other environmental resources 206 9.78 12 0.498 (ns) Summary of Analysis 0.405 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Deterioration in environment due to construction of hotels 239 13.36 12 0.343 (ns) Problems such as congestion and noise 240 16.79 12 0.157 (ns) Vegetation cleared to increase food supply 238 25.8 12 0.011 (ns) Water pollution increases due to tourism 238 14.4 12 0.276 (ns) Vandalism increases due to tourism 238 10.19 12 0.599 (ns) Improved sanitation 238 15.33 12 0.224 (ns) Incentives for restoring historic buildings 237 8.83 12 0.718 (ns) Incentives for restoring other environmental resources 238 26.45 12 0.146 (ns) Summary of Analysis 0.309 (ns)

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Table 5.3f: Relationship between Religion and Perceived Environmental Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Deterioration in environment due to construction of hotels 178 1.69 8 0.989 (ns) Problems such as congestion and noise 178 8.16 8 0.418 (ns) Vegetation cleared to increase food supply 178 4.05 8 0.852 (ns) Water pollution increases due to tourism 176 5.74 8 0.677 (ns) Vandalism increases due to tourism 178 3.83 8 0.872 (ns) Improved sanitation 178 4.89 6 0.558 (ns) Incentives for restoring historic buildings 178 1.67 6 0.947 (ns) Incentives for restoring other environmental resources 178 2.84 6 0.666 (ns) Summary of Analysis 0.747 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Deterioration in environment due to construction of hotels 242 29.67 12 0.003 (s) Problems such as congestion and noise 241 19.38 12 0.080 (ns) Vegetation cleared to increase food supply 239 9.99 12 0.617 (ns) Water pollution increases due to tourism 239 20.03 12 0.066 (ns) Vandalism increases due to tourism 239 12.26 12 0.425 (ns) Improved sanitation 239 6.91 12 0.864 (ns) Incentives for restoring historic buildings 238 10.22 12 0.596 (ns) Incentives for restoring other environmental resources 239 12.82 12 0.526 (ns) Summary of Analysis 0.397 (ns)

Tables 5a to 5f represent the results from the analysis of the socio-demographic characteristics and the selected items in the questionnaire. Summary of analysis for significant relationships between perceived environmental effects and age (P-values:

0.551 and 0.316); Sex (P-values: 0.534 and 0.331); educational levels (P-values: 0.156 and 0.361); occupation (P-values: 0.311 and 0.331); marital status (P-values: 0.405 and

0.309) and religion (P-values: 0.747 and 0.397) respectively for Wli Waterfalls and Lake

Bosomtwi (for the two values in each bracket) were all above the 0.005 significant level

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used for the analysis. This is an indication that none of them was significant and were therefore all rejected.

Despite the non-significant nature of the relationships, some specific items in the questionnaires were significant with some characteristics of the socio-demographics features. Educational level of respondents at Wli Waterfalls for example had significant relationships with increase in water pollution (P-value: 0.005); increase in vandalism (P- value: 0.005) and improved sanitation (P-value: 0.000). Again, occupation of respondents at Wli Waterfalls also had significant relationships with improved sanitation (P-value:

0.005) and incentives for restoring other environmental resources (P-value: 0.004).

Finally, religions had a significant relationship with deterioration in vegetation due to provision of tourism facilities at Lake Bosomtwi (Pv - alue: 0.003).

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Table 5.4a: Relationship between Age and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 192 17.85 20 0.396 (ns) Creation of more jobs in community 194 20.03 20 0.456 (ns) High increase in farming and fishing activities 194 31.79 20 0.046 (ns) More investments in community 192 20.66 20 0.417 (ns) Increased spending in the community 193 24.11 20 0.238 (ns) Increase in standard of living in community 192 21.79 20 0.352 (ns) Increase in growth of local businesses 194 10.75 20 0.952 (ns) Tourism revenue more important than other sources 191 22.02 20 0.34 (ns) High spending by tourist increases prices of products 190 18.64 20 0.545 (ns) Summary of Analysis 0.416

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 248 15.62 20 0.456 (ns) Creation of more jobs in community 249 17.34 20 0.631 (ns) High increase in farming and fishing activities 247 22.59 20 0.309 (ns) More investments in community 248 28.30 20 0.102 (ns) Increased spending in the community 247 11.96 20 0.916 (ns) Increase in standard of living in community 248 14.30 20 0.815 (ns) Increase in growth of local businesses 247 22.18 20 0.331 (ns) Tourism revenue more important than other sources 248 19.54 20 0.487 (ns) High spending by tourist increases prices of products 247 23.04 20 0.287 (ns) Summary of Analysis 0.482 (ns)

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Table 5.4b: Relationship between Gender and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 185 6.17 4 0.068 (ns) Creation of more jobs in community 185 2.45 4 0.563 (ns) High increase in farming and fishing activities 185 3.20 4 0.525 (ns) More investments in community 183 2.93 4 0.570 (ns) Increased spending in the community 184 10.87 4 0.028 (ns) Increase in standard of living in community 183 11.28 4 0.024 (ns) Increase in growth of local businesses 185 11.68 4 0.020 (ns) Tourism revenue more important than other sources 182 3.43 4 0.488 (ns) High spending by tourist increases prices of products 181 4.65 4 0.325 (ns) Summary of Analysis 0.290 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 233 10.36 4 0.075 (ns) Creation of more jobs in community 233 4.73 4 0.316 (ns) High increase in farming and fishing activities 232 4.44 4 0.350 (ns) More investments in community 232 10.92 4 0.027 (ns) Increased spending in the community 231 10.84 4 0.028 (ns) Increase in standard of living in community 232 8.19 4 0.085 (ns) Increase in growth of local businesses 232 7.74 4 0.101 (ns) Tourism revenue more important than other sources 232 10.22 4 0.037 (ns) High spending by tourist increases prices of products 237 8.37 4 0.079 (ns) Summary of Analysis 0.122 (ns)

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Table 5.4c: Relationship between Education and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 194 39.96 16 0.004 (s) Creation of more jobs in community 194 46.97 16 0.000 (ns) High increase in farming and fishing activities 194 32.42 16 0.009 (ns) More investments in community 192 20.02 16 0.219 (ns) Increased spending in the community 193 15.44 16 0.492 (ns) Increase in standard of living in community 192 22.18 16 0.137 (ns) Increase in growth of local businesses 194 33.48 16 0.006 (ns) Tourism revenue more important than other sources 191 31.80 16 0.011 (ns) High spending by tourist increases prices of products 190 26.72 16 0.045 (ns) Summary of Analysis 0.103 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 240 22.24 16 0.098 (ns) Creation of more jobs in community 241 24.86 16 0.072 (ns) High increase in farming and fishing activities 239 28.39 16 0.028 (ns) More investments in community 240 19.39 16 0.249 (ns) Increased spending in the community 239 19.19 16 0.259 (ns) Increase in standard of living in community 240 20.92 16 0.181(ns) Increase in growth of local businesses 239 19.16 16 0.260 (ns) Tourism revenue more important than other sources 240 25.95 16 0.055 (ns) High spending by tourist increases prices of products 239 20.55 16 0.197 (ns) Summary of Analysis 0.152 (ns)

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Table 5.4d: Relationship between Occupation and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 194 30.35 24 0.962 (ns) Creation of more jobs in community 194 28.82 24 0.363 (ns) High increase in farming and fishing activities 194 28.12 24 0.255 (ns) More investments in community 192 19.74 24 0.712 (ns) Increased spending in the community 194 34.39 24 0.078 (ns) Increase in standard of living in community 192 25.08 24 0.401 (ns) Increase in growth of local businesses 194 36.99 24 0.044 (ns) Tourism revenue more important than other sources 191 39.38 24 0.025 (ns) High spending by tourist increases prices of products 190 42.69 24 0.011 (ns) Summary of Analysis 0.317 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 239 42.22 28 0.003 (s) Creation of more jobs in community 240 32.47 28 0.256 (ns) High increase in farming and fishing activities 238 56.91 28 0.001 (s) More investments in community 239 42.47 28 0.039 (ns) Increased spending in the community 239 47.01 28 0.014 (ns) Increase in standard of living in community 239 42.58 28 0.038 (ns) Increase in growth of local businesses 238 47.92 28 0.011 (ns) Tourism revenue more important than other sources 239 21.9 28 0.786 (ns) High spending by tourist increases prices of products 238 38.71 28 0.086 (ns) Summary of Analysis 0.137 (ns)

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Table 5.4e: Relationship between Marital Status and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 194 20.12 12 0.092 (ns) Creation of more jobs in community 194 14.85 12 0.250 (ns) High increase in farming and fishing activities 194 7.96 12 0.788 (ns) More investments in community 192 22.58 12 0.031 (ns) Increased spending in the community 193 16.41 12 0.173 (ns) Increase in standard of living in community 192 5.55 12 0.937 (ns) Increase in growth of local businesses 194 11.84 12 0.458 (ns) Tourism revenue more important than other sources 191 15.66 12 0.207 (ns) High spending by tourist increases prices of products 193 12.93 12 0.374 (ns) Summary of Analysis 0.368 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 236 11.33 12 0.412 (ns) Creation of more jobs in community 238 10.23 12 0.595 (ns) High increase in farming and fishing activities 236 9.26 12 0.681 (ns) More investments in community 237 16.46 12 0.171 (ns) Increased spending in the community 236 9.37 12 0.671 (ns) Increase in standard of living in community 237 10.54 12 0.569 (ns) Increase in growth of local businesses 236 8.64 12 0.733 (ns) Tourism revenue more important than other sources 237 14.76 12 0.255 (ns) High spending by tourist increases prices of products 236 12.93 12 0.374 (ns) Summary of Analysis 0.496 (ns)

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Table 5.4f: Relationship between Religion and Perceived Economic Impacts (X2)

DESCRIPTION OF ITEMS (Wli Waterfalls) No Value Df P-value Improvement in road infrastructure 165 4.66 8 0.784 (ns) Creation of more jobs in community 167 5.03 8 0.754 (ns) High increase in farming and fishing activities 167 4.88 8 0.770 (ns) More investments in community 166 1.28 8 0.996 (ns) Increased spending in the community 166 5.05 8 0.752 (ns) Increase in standard of living in community 165 3.13 8 0.926 (ns) Increase in growth of local businesses 167 2.87 8 0.942 (ns) Tourism revenue more important than other sources 164 3.97 8 0.860 (ns) High spending by tourist increases prices of products 163 4.61 8 0.798 (ns) Summary of Analysis 0.842 (ns)

DESCRIPTION OF ITEMS (Lake Bosomtwi) No Value Df P-value Improvement in road infrastructure 238 7.48 12 0.732 (ns) Creation of more jobs in community 239 5.71 12 0.930 (ns) High increase in farming and fishing activities 237 6.62 12 0.882 (ns) More investments in community 238 9.70 12 0.642 (ns) Increased spending in the community 238 11.8 12 0.462 (ns) Increase in standard of living in community 238 12.88 12 0.378 (ns) Increase in growth of local businesses 237 10.31 12 0.589 (ns) Tourism revenue more important than other sources 238 18.55 12 0.100 (ns) High spending by tourist increases prices of products 237 6.12 12 0.910 (ns) Summary of Analysis 0.625 (ns)

Tables 5.4a to 5.4f represent the summary of analysis for significant relationships between perceived economic effects and age (P-Values: 0.416 and 0.482); Sex (P-Values:

290 and 0.122); educational level (P-Value: 0.103 and 0.152); Occupation( P-Values:

0.317 and 0.317); Marital status (P-Values: 0.368 and 0.496) and religion (P-Values:

0.842 and 0.625) respectively for Wli Waterfalls and Lake Bosomtwi ( for the two values in each of the brackets) were all above the 0.005 significant level used for the analysis. It is an indication that none of them was significant and all of them were therefore rejected.

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A few of the items in the questionnaires were however significant with some of the characteristics of the socio-demographic features. Educational levels of respondents at

Wli Waterfalls for example were significant with improvement in road infrastructure (P-

Values: 0.004) and creation of more jobs (P-Values: 0.000). Occupation of respondents at

Lake Bosomtwi was also significant with improvement in infrastructure (P-Values:

0.003) and increasing in farming and fishing activities (P-Values: 0.001).

There was very little significant relationship between the perception of respondents on the effects of tourism and their demographic characteristic. This may be attributed to the fact that tourism developments in the communities are still at the euphoria stage, confirming the findings of Wang et al (2006) and Dogan (1989). Dogan (1989) went on to explain that in communities where the level of tourism is low there is very little difference between demographic characteristics of respondents and their attitudes towards tourism development.

Even though there were some few significant relationships between demographic characteristic of respondents and their attitudes towards tourism, that from communities around Lake Bosomtwi had more significant relationships than those from around Wli

Waterfalls. This may also be attributed to the level of tourism development in the two communities (Butler, 1999). Even though tourism developments in the two study areas are still at an early stages, tourism development around Lake Bosomtwi is well developed than those around Wli Waterfalls. Therefore whilst tourism development at Wli

Waterfalls is still at the euphoria stage, that of Lake Bosomtwi may be in the apathy or heading to the apathy stage (Page & Dowlings, 2002). It has been argued that there is a relationship between the attitudes of residents and the level of tourism development in

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their community (Dogan, 1989) and this may be what is happening in the two study areas.

5.8 Summary This chapter discussed the results of the analysis done in the previous chapter and arrived at the conclusion that the water bodies that serve as the attractions in the study areas have not been polluted much. The little pollution that has taken place cannot be attributed to tourism activities alone. On the issue of land use, vegetative cover around the Wli

Waterfalls is receiving better attention than that of the Lake Bosomtwi. Finally, the residents in communities around the Wli Waterfalls perceive tourism in a more positive manner than those from around the Lake Bosomtwi.

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CHAPTER SIX

SUMMARY, CONCLUSION AND RECOMMENDATIONS

6.1 Introduction The main aim of the study was to assess environmental and economic impacts of tourism on the residents around the Wli Waterfalls and Lake Bosomtwi. It was to help understand the relationship between perceived impacts by residents and the actual situation on the ground and its implication on sustainable tourism development in the study areas. The chapter also summarizes the key findings of the study, draw conclusions and come out with recommendations for policy formulations and for further studies.

6.2 Summary of Key Findings Tourism has rapidly grown to become one of the largest industries in the world.

Accompanying the growth is the rapid increase in environmental and economic impacts at the destination areas in most cases (Mathieson & Wall, 1982). These impacts become pronounced with changes in the volume of tourists, characteristics of the tourists as well as the development status of the destination area (Madrigal, 1993; Perdue et al, 1990;

Allen et al, 1988; Lankford & Howard, 1994).

To be able to collect information from a broad spectrum for extensive analysis, a three tier dimensional techniques were employed. This included water quality analysis of Lake

Bosomtwi and Wli Waterfalls that serve the dual purpose of being the resources for the tourist‟s attraction as well as source of water for domestic use to the residents of the communities around the attractions. The others are an analysis of satellite images of the immediate environs of the attractions to determine changes in land use with the

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development of tourism as well as a social survey to determine the perceived environmental and economic impacts of tourism on the residents.

A major objective of the study was to assess the significant impacts of tourism on the bio- physical environment. In achieving this objective analysis of the quality of the water bodies in the Lake Bosomtwi and Wli Waterfalls were done. The results obtained were then compared with the WHO standards for drinking water to see if tourism has affected the quality of these water bodies in anyway. Again sampling periods were divided into two; peak periods (during festive occasions when large numbers of tourists visit the attractions) and lean periods (ordinary days when the number of tourists to the site is very few or no visitors). This was to enable the researcher compare the two periods to analyze for significant differences between them.

Satellite images of the study areas spanning a period of twenty years were analyzed to assess the impacts of tourism development on land use (vegetation cover) through activities such as destruction of vegetation to construct facilities such hotels and cutting down of trees to provide souvenirs to tourist.

6.2.1 Water Quality Analysis Values recorded for most of the physical parameters at the Wli Waterfalls were far below the acceptable limits for WHO standards for drinking water. Values recorded for the peak periods were slightly higher than the values recorded for the lean periods. The differences between the periods at the various sites were however, very minimal leading to a few of them being significant at ANOVA p>0.05. Again results indicated that sampling sites such as WPS and WDR with high anthropogenic activities (tourism related) were the

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sites where the highest values were recorded and the differences between the periods were significant.

Physical parameters recorded in Lake Bosomtwi followed almost the same pattern as those recorded for Wli Waterfalls with the values for the peak periods being higher than those for the lean periods. Again, both Wli Waterfalls and Lake Bosomtwi had the highest values for conductivity, turbidity and TDS/TSS recorded at places with highest anthropogenic activities (tourism related). A major difference between the two areas is that with the exception of turbidity, all values recorded for physical parameter in Lake

Bosomtwi were higher than those recorded at Wli Waterfalls with some of the values from Lake Bosomtwi being above the acceptable limits of WHO standards for drinking water. This is due to the fact that tourism activities have been going on for a longer period at Bosomtwi than at Wli.

Generally, the nutrient content of the waters in both the Lake and Waterfalls were within the acceptable limits of WHO standard for drinking water. However, values recorded at

Wli Waterfalls were slightly higher than values recorded at Lake Bosomtwi. Again, values recorded at sites such as WPS, WDR and BAB with high anthropogenic activities

(tourism related) though below the acceptable limits of WHO standards were still higher than values recorded at the other sites of the study areas. As a result, even though differences between the periods were very minimal, it was still significant (ANOVA p>0.05) at these sites. PO4 values especially those recorded from the Lake Bosomtwi were high and above the acceptable limits of WHO standards. Again sites such as WDR and BAB with high anthropogenic activities (tourism related) recorded very high values.

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Almost all the values recorded for chemical parameters at Wli Waterfalls were below the acceptable limits of WHO standards for drinking water. Again values recorded for the peak periods were slightly higher than those recorded for the lean periods. Only Ca and

Na were significant (ANOVA p > 0.05) at WUF and WLF respectively. The two sites are hilly areas where the flow of the water is very swift. It will therefore lead to high erosion and those found in the bed rock would be released.

Even though values recorded for chemical parameters recorded in Lake Bosomtwi were far higher than the values recorded for the Wli Waterfalls, almost all of them fall below the acceptable limits of WHO standards for drinking water. Only the values recorded for

Na and Alkalinity were above the acceptable limit for WHO standards for drinking water.

Values recorded for the peak periods higher than those for the lean periods. The differences are so minimal that they are all insignificant apart from the periodic differences of Ca at BAM which was significant (ANOVA p> 0.05).

Only Fe had major differences in values recorded for trace metal parameters at both Lake

Bosomtwi and Wli Waterfalls. Values for the rest of the parameters were the same throughout the sampling period and were far below the acceptable limits for WHO standards for drinking water. The presence of such trace metals in the water bodies could not be attributed to tourism activities.

Coliforms (total and fecal) values that were recorded for both the Wli Waterfalls and

Lake Bosomtwi were very high and followed the same pattern. All the values were above the acceptable limits for WHO standards for drinking water. Values recorded for the peak periods were slightly higher than those recorded for the lean periods. The differences

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were minimal and therefore insignificant with the exception of WPS and BAB which are the main tourist centers for Wli Waterfalls and Lake Bosomtwi respectively. This is an indication that tourism activities affect the coliform content of the water bodies.

6.3 Land Use Analysis Land cover types around the Wli Waterfalls have experienced a diversity of changes over the years. Forest vegetation declined during the first decade but the coverage increased again over the next decade. This is due to the fact that part of the vegetative cover around waterfalls was turned into a forest reserve and the rules governing its protection were strictly enforced. Built up/bare surface coverage on the other hand increased throughout the study period. Forest vegetation cover around the Lake Bosomtwi on the other hand declined throughout the study period. As expected, built up/bare surface coverage also increased throughout the study period. Unlike the improvement around the Wli

Waterfalls, the decline around the Lake Bosomtwi cannot be attributed solely to the effects of tourism. This is due to the other anthropogenic activities like farming that take place around the lake.

6.4 Social Survey 6.4.1 Perceived Environmental Effects The Likert scale was used to access the perceived level of environmental impacts of tourism. It came out that views from the two study areas were different. Generally, residents around the Wli Waterfalls were full of praise for tourism having positive impacts on environment, those from around Lake Bosomtwi was not so sure about that.

Whilst respondents from the communities around the Wli Waterfalls strongly agreeing to the fact that tourism is having some positive impact on the environment, those around the

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Lake Bosomtwi on the other hand, only agreed that tourism is helping in the protection of the environment. Respondents from communities around the Lake Bosomtwi felt that tourism is not helping in protection of the local environment. They were also not sure whether clearing land for increase farming activities was related to tourism.

6.4.2 Perceived Economic Effects A large chunk of respondents disagreed that they have benefited economically from the tourism industry within the last three months. More respondents at Bosomtwi disagreed to this issue on benefiting economically from tourism than respondents from Wli.

Revenue from sales of farm produce and artifacts, creation of jobs and revenue from ticket sales as well as gifts from tourists were listed as the major economic benefits derived from tourism industry within the last three months. A large percentage of the valid respondents who claimed they had benefited from tourism say that the benefits are seasonal with festive occasions as the most important periods during which the benefits derived are high. Residents in the communities around Wli Waterfalls were more positive about the economic impacts of tourism than those around Lake Bosomtwi,

The attitudes of respondents in the communities around the Lake Bosomtwi to the economic impacts may be due to the fact that tourism development has been going on in the area for longer periods and as such have been exposed to the realities on the ground for longer period. Again even though more business in the form of hotels in the communities around Lake Bosomtwi outnumbers those around the Wli Waterfalls, most of them are owned by non-natives and the number of locals that are employed is very small. This means that tourism in the Lake Bosomtwi area does not have substantial and meaningful economic benefits to the residents, hence its sustainability in terms of

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economic benefits becomes questionable. Again the findings indicate that farming and fishing have not been influenced much due to the fact that almost all the products that the tourists consume at the destination areas are either procured from other parts of the country or imported from outside the country.

6.5 Conclusion There is an indication that the quality of water in both Wli Waterfalls and Lake

Bosomtwi have been polluted to some extent and that the values recorded for some of the physical parameters were above acceptable limits of WHO standards for drinking water.

It is however very difficult to fully attribute this pollution to the development of tourism alone in the communities. This is because the local residents as well as the tourists all use the tourism resources and it will be very difficult to distinguish between the effects that result from anthropogenic activities of the tourists and that of the local residents. Again, even though both water bodies have been polluted to some extent the pollution is more severe in the Lake Bosomtwi than in the Wli Waterfalls. Some residents around Lake

Bosomtwi have therefore started using more resources to get better quality water such as buying sachet water for drinking.

The low level of NO2 and NO3 may be attributed to restrictions placed on residents from throwing solid waste into the water bodies especially at Wli Waterfalls. Most of the PO4 values are however higher than the acceptable limits for WHO because some level of washing is allowed in both water bodies especially during the lean periods. This is more so in the Lake Bosomtwi than the Wli Waterfalls. The nutrient contents of both the Wli

Waterfalls and Lake Bosomtwi is an indication that the pollution that has taken place in

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the water bodies may be attributed to the activities of both tourist and residents in the communities surrounding the water bodies.

Using chemical parameters alone indicates that the Wli Waterfalls is not polluted and that the differences between the periodic values could be attributed to the natural causes of erosion and weathering as well as other anthropogenic activities such as washing and bathing in the water body rather than tourism related activities. The case of the Lake

Bosomtwi is slightly different from that of Wli Waterfalls. Apart from the fact that natural causes and other anthropogenic activities such as washing and bathing in the water bodies is responsible for the high values recorded, tourism activities can also be cited as a cause. Waste from tourists facilities along the banks of the lake are released into it. The large influx of tourist also resulted in the highest means being recorded at places with high anthropogenic activities such as BAB and BOB.

The coliforms content of the two water bodies is an indication that they are polluted. The pollution is from activities of tourist as well as residents of the communities. It is the reason for the significant differences between the periods at the main tourist centers of both study areas.

It can therefore be concluded that environmental impacts of tourism development (real and perceived) are more severe on the Lake Bosomtwi and the communities around it than on the Wli Waterfalls and the communities around it. This is due to the fact that the levels of tourism development in the two study areas are not the same. Tourism has been going on at Lake Bosomtwi for longer period than at Wli Waterfalls. Interviews with residents indicate that while serious tourism at Wli Waterfalls started in the last decade of

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the twentieth century, it has been going on at Lake Bosomtwi since the last quarter of the twentieth century. The number of tourism related facilities in the two areas is a clear demonstration of the level and extent of tourism development. While communities around the Wli Waterfalls have only three hotels/guest houses, those around the Lake

Bosomtwi have as many as eight of such facilities. As already alluded to, the number of tourists who also patronizes the facilities at the Lake Bosomtwi far exceeds that of Wli

Waterfalls.

Again, it is clear that economic benefits of tourism development in the communities around the Wli Waterfalls far outweigh those in the communities around the Lake

Bosomtwi. They all agreed however that despite these positive impacts, there are some negative impacts as well. Respondents in communities around Wli Waterfalls support the development of tourism because they are still at the euphoria stage on Doxey‟s Irridex

Model of resident‟s attitudes towards tourism development. This is because tourism development at Wli Waterfalls is still at the early stage of development and they have a favorable attitude towards its development. The attitude of respondents in the communities around the Wli Waterfalls towards development tourism can also be explained by the Social Exchange Theory which says that the attitude of host community is always favorable to the development of tourism when they believe perceived benefits outweigh the perceived cost (Amuquandoh, 2006; Butler, 1998).

Biodata characteristics such as age, gender, level of education and marital status did not affect the results of perceived economic effects much due to the level of tourism development in that study area. This conforms to Dogan (1998) assertion that attitudes

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towards tourism development in a third world environment with newly developed attractions are usually uniform.

As a result of the fact that tourism development especially at Wli Waterfalls is still at its early stage, issues of sustainability are not given much attention. Sustainability in the tourism industry is hanged on three main locks of social equity, economic efficiency and ecological sustainability (Angelson et al, 1994). Social equity seeks to ensure equity in the distribution of cost, benefits, decisions making and management. This most often leads to the eradication of poverty in these poor communities. This however seems to be the opposite as the study indications that residents of these communities have limited access and control over the income from tourism development in their communities.

Participation by the residents in the management of the tourism resources is very low.

Residents at both study areas are still at the manipulation level which is at the lower section of non-participation stage. Even though they have representatives on the management committees, they are not accountable to the people and as such do the biddings of the operators and the municipal/district assemblies. Residents are however on the verge of moving to the information stage.

Finally, the analysis indicated that environmental impacts, both positive and negative do affect economic activities in both study areas. Swimming and bathing in water bodies at both places have forced residents in the communities around the water bodies to resort to the buying of sachet water for drinking at extra cost. Again, in an attempt to protect the water bodies or develop tourism related projects, farming lands have been taken forcefully from the residents. This has affected their farming activities and for that matter

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income. Youth in these communities are also moving away from farming to tourism for

„quick money‟.

6.6 Contribution to Knowledge This study has made a number of original contributions to knowledge as well as expanding the horizon of others. These contributions include;

In the first place, the study established a relationship between perceived impacts and realities on the ground. Most studies on such as Amquandoh (2010) at

Bosomtwi in Ghana, Teye et al (2002) at Cape Coast and Elmina in Ghana and Husband

(1989) in Zambia all looked at perception without assessing the physical impacts on the ground. Since these scholars listed above and others such as Jurowski et al (1997),

Lankford & Howard (1994), McCool and Martin (1994) and Allen et al (1993) have postulated that other factors such as biographic characteristics, level of tourism development, length of residency and community attachment affects people‟s perception and attitudes towards tourism development, there was the need to establish a link between realities and perceptions.

Secondly this study has been able to establish that environmental impacts sometimes do have a direct bearing on economic activities at the destination areas. Even though there have been some quite extensive work done on the environmental and economic impacts, they have been done distinctively without trying to establish the linkages between them.

Studies by Tosun (2002), Wahab and Pigram (1997) and McIntosh et al (1995) have all looked at both the positive and negative impacts of tourism on economies of host communities without linking them to other sectors. In the same way studies by Puczko and Ratz (2000), Ceballos-Lascurain (1996), Glasson et al (1995), Prosser (1994) and

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Carter (1991) have also looked at the positive and negative environmental impacts without linking them to for example to economic impacts. Even though works by

Mbaiwa (1999) and Mathieson and Wall (1982) looked at both environmental and economic effects, they looked at the two separated. This work has succeeded in combining the two.

Finally, this study has expanded the frontiers of existing knowledge on environmental and economic impacts on destination areas that are yet to develop their attractions to the maximum. Development of tourism at Wli Waterfalls for example is at the euphoria stage and therefore, here is the need to gather data to serve as baseline data for future studies.

This is because most of the existing studies on destination areas were done when tourism development was at its peak, making it difficult to distinguish between impacts that predate the development of tourism and the impacts that are directly linked to tourism development.

6.7 Recommendations Based on the results of the study, the researcher is recommending the following measures to help develop sustainable tourism as well as improve upon the economic well-being of the residents in the two study areas.

6.7.1 Recommendations for Sustainable Development of Tourism In the first place, the level of participation in the management of tourism facilities by the members of the host communities should be improved upon. Participation in the tourism industry is essentially about making sure that large or greater proportions of the key constituents (indigenes) are not ignorant about the objectives, activities, benefits and cost of tourism development on the community. Participation can be at two levels. These are;

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i. Participation in terms of policy formulation, planning and implementation. ii. Participation in terms of monitoring and evaluation as well as sharing of benefits accruing from project implementation.

It is important to note that to be able to make tourism development sustainable in the study areas, policy formulation should take into consideration the level of participation of the residents of the host communities. Consultation, consensus building and empowerment of the local people in planning, designing and implementation of tourism programs can facilitate the sustainability of tourism in the two study areas (especially that of Lake Bosomtwi). Since the core attractions in the study areas are communal properties, it is essential that the views of all members of the communities around the attractions are taken into consideration. For a start, public forums with community members to discuss policy formulations, design and implementation will be better than dealing with a selected few. This will make all of them support the development of the tourism industry. After all, eco–tourism advocates for a locally controlled tourism industry to ensure benefits to the local people and the sustainable use of resources.

Again, to be able to take full advantage of the benefits that tourism brings to a host community, the local residents should be well educated so as to be able to participate fully in the tourism industry. Personnel that are needed to fill positions in the tourism industry such as hotel managers, tour guides and so on requires special skills and capabilities which can be provided by highly literate personnel. However, illiteracy rates among residents around the Wli Waterfalls and the Lake Bosomtwi are also high that authorities will have to improve upon the very poor educational infrastructure especially those found in the communities around Lake Bosomtwi so that accessibility to education

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will be improved. Again some of the revenue from tourism should be channeled into

scholarship funds to enable the citizens attain higher and specialized education to procure

jobs in tourism and be able to reap the benefits of tourism.

Also, managers of the attractions should adopt pro-poor tourism policies to help the

locals also benefit from the “goodies” derived from tourism development. The pro-poor

approach tends to devise strategies that will ensure that benefits accruing to residents of

destination areas are maximized. A number of approaches can be adopted for this. They

include:

i. Direct effects: Insisting that items like food stuffs used in the tourism industry must

come from local farmers if they can produce them.

ii. Indirect effects: Trying to increase the selling of goods and services from the

destination areas. iii. Induced effects: Trying to increase benefits like in local wages and investments into

the economy of the destination areas.

Fourth, managers and operators in the tourism industry are in the habit of over

emphasizing the potential benefits at the expense of potential cost. Under estimating the

potential negative impacts are likely to generate intense hostility from the host towards

the tourist, especially when they move from the euphoria stage through the apathy,

annoyance to the antagonism stage. It is therefore imperative that the government through

the Ministry of Tourism and Creative Arts (MOTCA) and the Municipal and District

Assemblies in collaboration with the managers and operators in the tourism industry

intensify education and come out clean on the potential benefits as well as potential cost

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of tourism to the residents of the destination communities so as to reduce if not eliminate any antagonism or hostile attitudes in future.

Furthermore, both the tourist and the residents of the destination communities complained about the lack of basic infrastructure projects to make their stay and living conditions respectively more comfortable. Fortunately however, most of the needs of the tourists are intertwined with the needs of the residents in the destination communities.

Government should therefore make it a point to provide new ones and or improve upon existing infrastructures such as roads, health facilities, security posts, potable water and sanitation facilities. This will help to increase the number of tourists to the destination areas to increase revenue to the residents of the destination. It will at the same time make the residents be content with the development of tourism, because it was through it that the infrastructure projects were developed.

Another area that has generated a lot of controversy among the citizens (especially the communities around Lake Bosomtwi) is the collection and management of the gate proceeds from the tourists. While tourists and operators of tourist‟s facilities complain of multiple charges, residents in the other communities apart from Abono complain of not knowing what the proceeds are used for. Stakeholder consultations as well as forums should be held and revenues accruing from tourism should be declared and its usage also deliberated upon.

Finally, the study demonstrated that tourism in the study areas (especially Wli Waterfalls) is still at its early stage of development. As a result issues on sustainability are not given much attention. This is likely to lead to the problem of exceeding carrying capacity in

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terms of the number of tourists that visit the study areas or the development of tourism facilities such as hotels. There is therefore the need to try and prevent this by developing other tourist attractions found in the surrounding areas of the attractions. Attractions such as the Fetish Groove (Abrodwum stone) at Abrodwum; the Holy Rock of Atafrani; the

Abrewa River and nthe bird‟s ests at Hantaase, all in the Lake Bosomtwi basin should be developed. In the basin of Wli Waterfalls, attractions like the Tafi Atome Monkey

Sanctuary and Cultural Village; Tafi Abuife Kente Weaving Village, Akpafu Todzi Iron

Artifacts Village; Mountain Afadjato at Liate Wote; the Tsatsadu Falls and the Catholic

Convert of Spiritual Silence known as Foya De Charite all at Alavanyo Abehenease should be developed to reduce the pressure on Wli waterfalls.

6.7.2 Recommendations for Further Studies First, as the number of tourists visiting the study areas increases, so will the number of tourist‟s facilities. This is likely to affect other elements of the bio-physical environment such as soils and air. Further studies should therefore include other elements such as soils and air in the bio-physical environment.

Second, results from the economic impacts were based on assumptions (perceived). It has been established that perceptions are sometimes affected by other factors apart from the real facts on the ground. Studies should be conducted to establish the relationships between the perceptions of residents and realities on the ground at the study areas.

Third, the study took place in the immediate communities surrounding the tourist‟s attractions. Distance however is known to affect the perceived impacts of tourism on destination areas. The Distance Decay Model should therefore be used to assess the impacts of tourism on the communities further away from the attractions.

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Finally as the industry grows with increased tourist and the economic status of the residents changes, aspirations and needs of these residents in the host communities will also change and with it their perception and attitudes towards the industry. As a result, studies of environmental, economic as well as socio-cultural effects of tourism on the two communities should be a continuous process. This will help the monitoring and detection of any changes in the inspirations and attitudes of the local residents so as to allow the introduction of preventive measures to reduce or prevent an avoidable antagonism from the residents towards the tourist.

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Appendix I

UNIVERSITY OF GHANA ENVIRONMENTAL SCIENCE PROGRAMME (ESP) PhD. IN ENVIRONMENTAL SCIENCE

RESEARCH TOPIC AN ASSESSMENT OF ENVIRONMENTAL AND ECONOMIC EFFECTS OF TOURISM IN COMMUNITIES AROUND WLI WATERFALLS AND THE LAKE BOSOMTWI IN GHANA

QUESTIONNAIRE RESIDENTS

RESPONDENTS’ ASSURANCE

Please be assured that this exercise is purely academic and any information solicited is intended solely for the purpose of data analysis and will be kept absolutely confidential. All your responses will be held in strict confidence; findings will be presented in aggregates, and no statements used in the report will be attributed directly to you.

Date: Locality: Serial No:

BIO-DATA

Age: 20- 30- 40- 50- 60- 70+ Sex: F M Educational Level: Others (specify)…………………………………………………………………………………………… … Occupation: (Specify)…………………… Marital Status:

Religion: (Specify)………………………. Number of Children if any: 1- 4- 7- 10 and

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A. ENVIRONMENTAL IMPACTS A1. How long have you lived here? [ ]

A2. What do you think are the critical environmental issues in your community? ……………………………………………………………………………………………… ……………………………………………………………………………………………… ……………………………………………………………………………………………… A3. Are the causes of these environmental problems related to tourism activities in any way?

A4. What in your opinion can be done to solve these problems?

……………………………………………………………………………………………………… ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

A5. What type of vegetation (ecosystem) is found in this area?......

A6. Has it always been so?

A7. If there has been a change, describe it ……………………………………………………… ……………………………………………………………………………………………………… ……………………………………………………………………………………………………..

A8. If no, i

The following questions are related to environmental impacts of tourism development measured on a scale from 1 to 5. Please read each item carefully and circle the appropriate number that indicates how much you agree or disagree with each statement SCALE: 1 = Strongly Disagree; 2 = Disagree; 3 = Moderate; 4 = Agree; 5 = Strongly Agree

STATEMENT (ENVIRONMENTAL) SD D M A SA A9. Construction of hotels and other tourist facilities has led to a 1 2 3 4 5 deterioration in the natural environment in this community

A10. Tourism development has resulted in an increase in problems such 1 2 3 4 5 as congestion and noise in this community

A11.Patronage of water bodies by tourist has led to an increase water 1 2 3 4 5 pollution in this community

A12. Increase in foodstuff to feed the tourist has resulted in the clearing 1 2 3 4 5 of more vegetative lands 1 2 3 4 5 A13. Vandalism in this community increased because of tourism development in the tourism industry has led to clean environment 1 2 3 4 5 A14. Sanitation and road facilities are kept at high standard due to the development of tourism

A15. Development in tourism in this community has provided an 1 2 3 4 5 incentive for the restoration of historic buildings and other environmental resources in this community

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B. ECONOMIC IMPACTS

B1. Has the development of tourism brought any economic benefit to you within last three

If yes, how?…………………………………………………………………………………. ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

If no, during which period (months) are the benefits at its peak come?…………………... ………………………………………………………………………………………………………

B3. Have you ever worked in the tourism sector in your community within the last three months?

If no, why the change……………………………………………………………………….... ………………………………………………………………………………………………………

B5. Any member of your family employed in tourism industry within the last three months?

If yes, how many? …………………………………………………………………………….

B6. If Any member of your family employed in tourism industry, has it always been so?

If no, why the change……………………………………………...... ……………………………………………………………………………………………………

B7. Any member of your family engaged in other tourism related economic activity within the last three months? If yes, how many? ………………………………………………………………………….

B8. Have you ever been involved in the making of any tourism – related policy for your community?

B9. Do you or any member of your family use the tourist facility for any other economic activity apart from tourism? If yes, list them……………………………………………………………………………… ……………………………………………………………………………………………………

B10. What are the major types of diseases prevalent in the community? ………………………………………………………………………….. B11. Do you think the diseases prevalent in this community are related to the pollution of water bodies by tourist?

B12. Apart from tourism, what other jobs are the community members engaged in? ………………………………………………………………………………… ………………………………………………………………………………… B13. Has farming activities been affected in any way by tourism? If yes, how? ……………………………………………………………………….

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The following questions are related to economic impacts of tourism development measured on a scale from 1 to 5. Please read each item carefully and circle the appropriate number that indicates how much you agree or disagree with each statement SCALE: 1 = Strongly Disagree; 2 = Disagree; 3 = Moderate; 4 = Agree; 5 = Strongly Agree

STATEMENT (ECONOMIC) SD D M A SA B14. Tourism has led to the creation of more jobs in this 1 2 3 4 5 community B15. Tourism has attracted more investments to this community 1 2 3 4 5

B16.Tourism has led to an increase in spending in this community 1 2 3 4 5

B17. Tourism has led to a considerable increase in standard of 1 2 3 4 5 living in this community

B18. Tourism has led to an increase in the prices of goods and 1 2 3 4 5 services in our community

B19. Tourism has led to a growth in local businesses and 1 2 3 4 5 productions in this community

B20. Tourism revenues are more important to the community than 1 2 3 4 5 revenues from other sectors of the economy.

B21. High spending by tourist is negatively affecting ways of life 1 2 3 4 5 in this community

C. Level of Participation

C1. Any form of interaction between the locals and tourist. If yes, describe the interaction……………………………………………………………… ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

C2. Have you ever taken part in the activities that tourist do take when they come?

C3. Do the activities of the tourist affect the community in any way? If yes, describe it……………………………………………………………………………. ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

C4. Does the community like anything about the tourist visit? If yes, describe them…………………………………...... ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

C5. Would you like the tourist to come all year round?

C6. If no, which periods do you want them to come?...... Please explain the reasons for the above answer ......

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………………………………………………………………………………………………………

C7. If yes, explain……………………………………………………………………………… ……………………………………………………………………………………………………… ………………………………………………………………………………………………………

C8. How would you evaluate the level of tourism development in your community?

C9. Do you think tourism activities in your community should be encouraged? Please explain the reasons for the above answer......

C10. Are satisfied with the above Why......

C11. What role would you like tourism to play in your community?…….………………………. ………………………………………………………………………………………………………. ……………………………………………………………………………………………………….

The following questions are related to the perception of residents on the tourism development measured on a scale from 1 to 5. Please read each item carefully and circle the appropriate number that indicates how much you agree or disagree with each statement SCALE: 1 = Strongly Disagree; 2 = Disagree; 3 = Moderate; 4 = Agree; 5 = Strongly Agree

STATEMENT LEVEL OF PARTICIPATION SD D M A SA C12 I am invited to attend forums on tourism management always 1 2 3 4 5

C13. I attend forums on tourism management whenever I am 1 2 3 4 5 invited

C14. I know how much this community generates from tourism as 1 2 3 4 5 gate proceeds

C15. I know what the gate proceeds from tourism are used for 1 2 3 4 5

C16. I take part in management decisions on the tourism facility 1 2 3 4 5

C17. The TMC seeks my opinions on issues concerning the 1 2 3 4 5 management of tourism in this community

C18. Our representatives on the TMC reports back to us on 1 2 3 4 5 deliberations on TMC meetings

C19. The TMC renders accounts on their stewardship to us 1 2 3 4 5 regularly

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Appendix 2a-b: Monthly Mean Rainfall for Kumasi and Hohoe (a) Rainfall/mm Jan Feb Mar April May June July Aug Sept Oct Nov Dec 2008 111 98 113 67 187 145 67 65 216 158 33 4 2009 0 16 56 311 164 176 193 118 535 154 52 20 2010 0 54 97 132 240 287 131 193 171 75 18 55 2011 0 131 111 140 165 377 274 18 99 139 45 33 2012 15 53 53 77 109 226 83 113 166 178 81 38

(b) Rainfall/mm Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 19 34 137 58 214 114 79 340 204 181 31 16 2009 0 34 25 90 160 158 239 142 319 171 54 3 2010 0 51 53 256 236 99 307 243 105 134 0 22 2011 0 60 52 113 123 201 208 237 164 221 60 18 2012 4 36 162 94 162 115 99 137 97 168 30 0

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Appendix 3a-b: Monthly Min. and Max. Temperature for Kumasi and Hohoe (a) Minimum Temperature/°C Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 22.6 23.1 22.5 23.4 22.7 22.5 21.8 21.3 21.1 21.5 21.8 20.7 2009 19.9 22.5 22.6 21.7 22.2 22.6 22.1 22.0 22.1 21.9 22.2 22.0 2010 19.2 21.7 22.6 22.9 22.8 22.5 22.3 22.0 22.3 22.0 23.4 23.0 2011 21.8 23.2 23.2 23.0 22.9 22.1 21.5 21.9 22.1 22.1 22.2 23.1 2012 22.9 23.4 23.3 23.4 23.3 22.3 21.7 22.1 22.1 22.5 22.8 23.2

Maximum Temperature/°C Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 32.1 32.6 32.5 33.3 31.5 31.0 29.5 29.0 29.8 31.4 32.6 32.9 2009 33.8 34.5 35.0 32.7 32.1 30.7 29.4 28.7 29.7 31.1 31.8 32.3 2010 33.2 35.1 34.2 32.6 32.4 30.6 29.3 29.0 29.8 31.9 32.8 32.5 2011 33.4 33.6 33.4 32.6 32.2 30.8 29.1 28.0 29.5 30.9 32.0 32.7 2012 33.6 35.2 34.3 33.8 32.4 30.9 29.6 29.4 30.1 31.7 32.1 32.5

(b) Minimum Temperature /°C Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 22.6 23.8 23.7 24.2 22.8 22.5 22.5 21.9 22.0 22.5 21.8 21.4 2009 21.6 23.7 24.4 24.2 23.6 22.8 22.5 22.1 22.2 22.2 22.6 21.5 2010 20.3 23.6 23.9 23.1 22.7 22.5 22.1 22.0 22.5 22.6 22.8 22.2 2011 22.4 23.6 23.6 23.3 23.2 22.7 22.2 22.4 22.4 22.1 21.6 23.0 2012 23.1 24.6 24.6 24.4 24.2 23.3 22.3 22.7 22.4 23.1 22.9 22.3

Maximum Temperature /°C Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 33.6 35.2 33.9 34.6 32.2 31.4 30.6 29.5 30.0 31.6 32.5 32.9 2009 33.2 35.0 35.2 34.0 33.1 31.3 30.1 29.2 30.3 31.4 32.2 32.8 2010 32.6 35.0 34.5 33.3 32.1 30.6 29.9 29.4 30.3 31.6 32.9 33.2 2011 33.3 35.1 34.4 32.7 32.5 31.9 29.6 29.2 30.4 31.5 32.3 33.5 2012 34.1 36.1 34.6 34.6 33.6 31.7 30.8 30.5 30.6 34.1 32.7 33.7

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Appendix4a - b: Monthly Min. and Max. Relative Humidity for Kumasi and Hohoe (a) RH0600% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 91 93 93 93 95 94 94 93 96 95 94 93 2009 65 92 91 94 94 94 95 95 97 96 95 93 2010 59 90 91 94 96 95 95 95 95 95 94 93 2011 76 92 93 95 94 98 97 97 97 98 98 97 2012 96 93 94 94 96 98 97 97 98 98 98 97

RH1500% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 53 55 56 58 63 64 69 68 69 64 51 44 2009 29 45 45 61 63 66 71 71 73 65 65 50 2010 24 38 52 59 62 67 71 69 70 63 55 53 2011 36 54 57 61 61 67 74 76 71 67 60 56 2012 50 47 54 58 63 68 69 70 69 65 62 53

(b) RH0600% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 92 93 94 94 96 96 95 94 97 96 95 94 2009 66 93 92 95 95 95 96 96 98 97 96 94 2010 61 92 93 95 97 96 96 96 96 96 95 94 2011 78 94 95 96 95 98 98 98 98 99 98 97 2012 97 95 96 96 97 98 98 98 99 98 98 99

RH1500% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2008 55 57 58 60 65 66 71 70 71 66 53 46 2009 31 47 47 63 65 68 73 73 75 66 66 52 2010 28 41 55 61 64 69 73 71 72 65 57 55 2011 38 56 59 63 63 69 76 78 73 69 62 58 2012 52 49 56 60 65 70 71 72 71 67 64 55

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Appendix 5: Values, Periodic and Sites Means for Physical Parameters WUF WLF WPS WBR WDR 23.8 26.6 24.9 25.7 24.9 25.4 25.1 25.5 24.4 25.4 24.8 25.6 25.8 25.8 25.9 26.1 25.4 25.6 26.1 25.8 24.1 27.9 23.7 25.2 24.7 25.8 24.9 25.4 26.1 25.4 23.6 25.2 24.9 25.6 25.4 25.6 24.9 26.2 25.1 25.4 25.1 25.5 26.1 26.9 26.2 26.3 24.7 25.9 25.9 24.8 TEMP 25.6 26.1 26.4 26.1 26.2 26.4 26.4 25.6 26.1 25.2 24.50 26.15 25.30 25.88 25.55 25.93 25.23 25.70 25.62 25.33 25.33 25.59 25.74 25.47 25.48 B BAB BOB BNK BAM NY 31.8 30.4 31.9 29.6 28.9 29.2 28.4 28.3 30.7 29.2 30.6 28.5 30.2 29.5 29.6 30.2 28.4 29.2 29.6 30.2 31.2 28.5 30.2 28.4 29.6 29.7 28.8 28.9 29.6 29.7 28.2 30.9 31.4 30.9 30.7 30.9 28.3 29.6 28.2 31.1 30.4 29.8 29.6 29.2 31.1 29.8 29.4 28.7 31.1 29.8 31.2 29.9 30.5 28.1 30.8 28.2 28.9 28.2 30.9 28.9 30.57 29.67 30.63 29.28 30.12 29.67 28.70 28.82 30.02 29.82 30.20 29.97 29.89 28.76 29.90

WUF WLF WPS WBR WDR 7.2 6.9 7.2 6.7 6.9 6.6 7.1 7.4 7.2 6.6 7.2 7.1 7.2 6.7 7.1 6.4 6.9 6.6 7.8 8.7 7.2 6.7 6.7 6.5 6.6 6.3 6.7 6.1 7.7 6.5 7.4 7.3 6.9 6.6 7.5 6.5 6.2 6.3 6.7 6.7 7.6 7.4 7.1 7.3 7.1 7.3 7.2 7.1 7.8 7.1 pH 7.5 6.8 8.1 6.9 7.2 6.8 6.9 6.8 7.5 6.7 7.35 7.03 7.20 6.78 7.07 6.65 6.83 6.72 7.45 7.05 7.19 6.99 6.86 6.78 7.25 B BAB BOB BNK BAM NY 9.5 9.5 9.5 9.5 9.5 9.4 9.5 9.5 9.5 9.4 9.5 8.8 9.6 8.7 9.5 8.6 9.6 8.6 9.5 8.6 8.8 8.9 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.9 9.2 8.8 9.1 8.9 9.2 8.7 9.1 8.9 9.4 8.9 9.2 8.9 9.3 8.9 9.2 8.9 9.2 8.9 9.4 9.2 8.8 9.2 8.7 9.2 8.7 8.9 7.4 9.2 8.7 9.13 9.01 9.13 9.02 9.13 8.98 9.07 8.77 9.13 9.05 9.07 9.08 9.06 8.92 9.09

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WUF WLF WPS WBR WDR 7.29 14.86 5.81 7.81 8.92 24.25 7.13 12.84 5.24 16.22 9.81 15.48 6.28 5.52 5.12 16.14 10.21 14.23 11.92 7.62 17.32 17.12 13.31 18.31 29.48 26.45 15.62 16.82 15.21 17.91 13.21 17.48 13.21 17.62 6.18 59.15 14.15 17.85 15.12 18.42 15.12 11.19 10.21 24.21 12.61 15.64 15.22 17.21 24.22 18.62 TURB 9.22 16.12 15.32 39.21 14.65 28.21 12.44 14.81 5.71 18.22 11.99 15.38 10.69 18.78 12.83 28.31 12.46 15.63 12.09 16.19 13.69 14.74 20.57 14.05 14.54 B BAB BOB BNK BAM NY 5.72 18.08 4.12 8.64 3.71 8.22 4.63 8.51 3.71 8.21 3.32 6.44 3.94 9.22 3.27 7.45 2.91 4.03 3.27 7.45 6.94 4.92 4.12 5.92 3.04 5.54 4.21 5.62 3.01 5.54 8.72 7.42 4.42 7.24 4.82 7.14 8.32 7.12 4.83 7.11 4.74 5.74 9.12 5.32 12.02 7.52 9.01 5.61 12.01 7.52 4.82 10.22 4.92 8.41 5.42 8.21 4.22 8.38 5.42 8.21 5.71 8.80 5.11 7.46 5.38 7.35 5.55 6.55 5.38 7.34 7.26 6.29 6.38 6.05 6.36

WUF WLF WPS WBR WDR 25.6 29.8 26.2 32.1 47.5 78.6 16.5 26.6 26.2 38.6 25.7 23.2 26.4 23.1 75.4 96.4 22.4 28.2 26.3 12.9 21.3 18.8 22.2 20.3 56.4 98.7 22.8 22.1 23.2 21.9 19.5 39.4 19.5 38.6 54.7 101.1 20.1 30.8 20.2 39.6 2.2 24.6 23.6 26.3 42.6 58.9 24.3 28.4 26.1 27.4 COND 35.3 28.8 23.9 26.6 60.5 74.2 19.8 25.4 26.2 27.9 21.6 27.43 21.6 27.43 56.18 84.65 20.98 26.92 24.7 28.05 24.52 24.52 70.42 23.95 26.38 B BAB BOB BNK BAM NY 1290 1381 1286 1252 1287 1252 1291 1132 1287 1252 1377 1284 1352 1289 1371 1306 1376 1317 1371 1306 1276 1282 1048 1279 1058 1279 1280 1270 1058 1279 1280 1348 1180 1248 1160 1228 1150 1128 1160 1228 1233 1345 1243 1338 1233 1337 1038 1341 1233 1337 1148 1371 1374 1291 1376 1287 1061 1235 1375 1287 1267.33 1335.17 1247.17 1282.83 1247.50 1281.50 1199.33 1237.17 1247.33 1281.50 1301.25 1264.99 1264.50 1281.50 1264.42

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WUF WLF WPS WBR WDR

1 2 2 3 2 3 1 2 2 4

1 2 2 2 3 3 3 3 3 2 1 2 1 1 2 3 1 2 1 3

1 3 1 1 1 3 1 2 2 2

1 1 1 5 4 4 3 4 4 6 TSS 2 2 1 2 1 2 1 2 2 2 1.17 2.00 1.33 2.33 2.17 3.00 1.67 2.50 2.33 3.17 1.59 1.83 2.59 2.09 2.75 B BAB BOB BNK BAM NY 2 2 1 1 1 2 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 3 1 3 4 3 3 1 2 3 3 1 3 1 1 1 1 2 1 1 1 2 1 2 1.67 1.83 1.33 1.83 1.17 1.17 1.33 1.50 1.50 1.50 1.75 1.58 1.17 1.42 1.50

WUF WLF WPS WBR WDR 14.6 18.2 15.8 18.4 8.6 12.3 14.2 17.6 15.3 19.2 14.5 12.7 14.1 12.7 10.8 12.7 13.5 12.2 14.4 17.9 12.1 11.2 11.7 10.3 10.8 9.4 12.4 12.8 12.8 12.1 10.6 18.2 10.4 17.8 20.7 32.6 10.2 17.6 10.8 18.6 12.9 14.5 14.1 13.5 13.8 19.4 11.7 13.5 14.4 15.1 TDS 13.9 18.4 14.4 14.6 12.9 16.4 12.8 16.4 14.4 18.4 13.10 15.53 13.42 14.55 12.93 17.13 12.47 15.02 13.68 16.88 15.03 13.96 15.03 13.75 15.28 B BAB BOB BNK BAM NY 708 765 707 685 708 765 650 689 709 735 758 718 760 709 758 718 575 724 757 766 708 703 710 703 708 703 704 700 702 704 693 790 690 788 692 690 699 698 692 718 678 735 684 736 678 735 679 736 678 740 668 756 658 756 668 756 499 710 688 754 702.17 744.5 701.5 729.5 702 727.83 634.33 709.5 704.33 736.17 723.25 715.50 714.92 671.92 721.92

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Appendix 6: Values, Periodic and Sites Means for Nutrients Parameters WUF WLF WPS WBR WDR 0.31 0.43 0.31 0.35 0.21 0.35 0.29 0.33 0.14 0.37 0.14 0.39 0.15 0.41 0.34 0.15 0.33 0.14 0.48 0.23 0.31 0.41 0.31 0.21 0.15 0.03 0.24 0.24 0.47 0.43 0.25 0.41 0.25 0.21 0.24 0.09 0.22 0.29 0.26 0.29 0.33 0.88 0.38 0.21 0.24 0.86 0.22 0.35 0.35 0.49 PO4 0.31 0.35 0.32 0.45 0.36 0.65 0.33 0.63 0.36 0.46 0.28 0.48 0.29 0.31 0.26 0.36 0.27 0.33 0.34 0.38 0.38 0.30 0.31 0.3 0.36 B BAB BOB BNK BAM NY 0.85 0.65 0.64 0.61 0.26 0.41 0.31 0.71 0.35 0.41 0.32 0.26 0.23 0.23 0.26 0.28 0.68 0.11 0.26 0.24 0.46 0.31 0.46 0.24 0.35 0.25 0.47 0.47 0.38 0.38 0.31 0.42 0.31 0.41 0.31 0.41 0.31 0.41 0.31 0.41 0.52 0.35 0.59 0.42 0.82 0.45 0.37 0.47 0.82 0.45 0.42 0.31 0.36 0.35 0.41 0.18 0.35 0.16 0.41 0.16 0.48 0.38 0.43 0.38 0.41 0.33 1.42 0.39 0.42 0.34 0.43 0.41 0.37 0.91 0.38

WUF WLF WPS WBR WDR 0.015 0.014 0.017 0.028 0.018 0.026 0.026 0.022 0.025 0.046 0.001 0.024 0.001 0.024 0.011 0.011 0.011 0.018 0.022 0.025 0.021 0.027 0.024 0.027 0.011 0.013 0.021 0.019 0.025 0.028 0.016 0.019 0.012 0.039 0.011 0.039 0.011 0.019 0.032 0.029 0.012 0.024 0.029 0.029 0.028 0.037 0.018 0.051 0.048 0.061 NO2 0.018 0.021 0.021 0.038 0.012 0.054 0.012 0.081 0.038 0.056 0.02 0.02 0.02 0.03 0.02 0.03 0.02 0.04 0.03 0.04 0.02 0.03 0.03 0.03 0.04 B BAB BOB BNK BAM NY 0.041 0.014 0.028 0.024 0.032 0.012 0.011 0.015 0.021 0.012 0.038 0.031 0.031 0.029 0.021 0.019 0.012 0.014 0.041 0.024 0.031 0.068 0.039 0.021 0.029 0.026 0.014 0.027 0.024 0.025 0.042 0.019 0.021 0.029 0.022 0.019 0.025 0.019 0.024 0.022 0.032 0.064 0.032 0.016 0.072 0.051 0.035 0.011 0.042 0.055 0.049 0.013 0.022 0.027 0.022 0.021 0.031 0.021 0.037 0.011 0.04 0.03 0.03 0.02 0.03 0.02 0.02 0.02 0.03 0.02 0.04 0.03 0.03 0.02 0.03

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WUF WLF WPS WBR WDR 0.12 0.28 0.14 0.38 0.12 0.43 0.01 0.02 0.15 0.52 0.28 0.24 0.31 0.28 0.21 0.12 0.01 0.02 0.34 0.51 0.21 0.24 0.18 0.35 0.12 0.12 0.01 0.02 0.11 0.15 0.18 0.25 0.16 0.36 0.23 0.34 0.01 0.02 0.33 0.32

0.32 0.36 0.34 0.27 0.14 0.51 0.01 0.05 0.22 0.44

NO3 0.28 0.28 0.53 0.48 0.82 0.41 0.08 0.02 0.42 0.52 0.23 0.28 0.28 0.36 0.27 0.32 0.02 0.03 0.26 0.41 0.26 0.32 0.30 0.03 0.34 B BAB BOB BNK BAM NY 0.12 0.14 0.12 0.15 0.16 0.11 0.29 0.01 0.11 0.13 0.25 0.16 0.31 0.13 0.21 0.15 0.11 0.04 0.21 0.08 0.13 0.13 0.15 0.14 0.14 0.13 0.14 0.12 0.08 0.09 0.32 0.32 0.25 0.22 0.33 0.24 0.25 0.41 0.25 0.31 0.24 0.21 0.12 0.23 0.12 0.22 0.14 0.22 0.12 0.19 0.21 0.12 0.23 0.15 0.25 0.16 0.18 0.05 0.21 0.09 0.21 0.18 0.19 0.17 0.21 0.17 0.19 0.14 0.16 0.15 0.20 0.18 0.19 0.17 0.16

WUF WLF WPS WBR WDR 0.7 0.6 1.4 0.7 1.1 0.9 0.9 0.8 1.2 1.1 0.7 0.6 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 1.1 0.4 0.7 0.4 0.8 0.9 0.7 0.8 0.9 0.9 0.5 0.3 0.5 1.7 1.4 1.1 0.6 1.1 0.9 1.2 0.8 0.9 1.3 0.8 0.8 1.2 0.8 1.1 1.6 1.1 K 1.1 1.3 1.5 0.8 1.3 0.7 1.2 1.3 1.1 0.9 0.82 0.68 1.02 0.85 1.03 0.93 0.82 0.93 1.10 1.02 0.75 0.94 0.98 0.88 1.06 B BAB BOB BNK BAM NY 22.7 20.6 22.5 24.4 12.2 19.6 20.1 20.2 12.3 19.6 21.5 26.2 22.5 10.1 19.7 6.3 19.5 6.2 19.7 4.3 24.5 22.1 24.5 24.2 19.7 19.9 19.9 20.1 19.7 19.9 22.1 22.6 21.1 24.6 20.2 20.6 20.1 20.6 20.1 20.6 23.7 22.8 24.7 25.3 19.9 25.4 21.1 24.8 19.9 22.8 24.1 22.2 25.5 20.4 22.8 19.4 15.5 19.4 25.4 19.4 23.10 22.75 23.47 21.50 19.10 18.53 19.34 18.55 19.52 17.77 22.93 22.49 18.82 18.95 18.65

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Appendix 7: Values, Periodic and Sites Means for Chemical Parameters WUF WLF WPS WBR WDR 1.4 1.8 1.6 2.2 1.6 2.2 1.4 2.1 1.6 2.4 1.6 2.4 2.4 2.4 3.2 1.6 2.8 1.8 2.2 2.6 1.9 1.8 0.8 1.6 2.4 3.2 2.1 3.4 3.2 2.4 1.4 1.6 1.8 2.6 1.6 2.4 1.6 2.2 1.8 2.6

1.4 2.4 2.4 2.4 1.8 3.2 2.1 3.2 3.2 3.2

Ca 2.4 2.2 0.8 2.2 3.2 2.4 2.8 2.4 3.2 2.4 1.68 2.03 1.63 2.23 2.30 2.50 2.13 2.52 2.53 2.60 1.86 1.93 2.40 2.33 2.57 B BAB BOB BNK BAM NY 6.4 6.8 6.2 6.7 6.4 6.2 8.1 6.6 6.3 6.4 7.2 12.2 7.3 12.6 8.1 9.6 8.1 18.1 8.2 9.4 18.8 28.1 18.5 25.1 20.1 24.1 17.6 28.1 20.1 24.3 26.4 42.4 25.4 40.4 25.1 40.4 25.1 40.4 25.2 40.4 44.1 28.1 43.1 27.1 16.1 20.1 28.1 32.1 16.3 20.2 8.1 20.1 9.1 21.1 13.6 16.8 2.8 24.1 13.6 16.8 18.50 22.95 18.27 22.17 14.90 19.53 14.97 24.90 14.95 19.58 20.73 20.22 17.23 19.94 17.27

WUF WLF WPS WBR WDR 1.5 1.4 1.5 1.5 3.1 3.2 1.4 1.2 1.9 1.9 1.5 1.1 1.5 1.2 3.1 2.8 1.4 1.4 1.9 1.5 1.8 0.5 1.5 0.5 2.8 2.2 1.1 0.8 1.5 1.2 1.2 0.6 1.5 1.5 2.6 2.1 0.8 1.4 1.4 1.5 1.5 1.6 0.5 1.5 4.8 2.6 1.8 0.6 1.5 1.5 Mg 1.5 0.9 1.5 1.2 3.8 2.1 1.2 0.9 1.6 1.2 1.50 1.02 1.33 1.23 3.37 2.50 1.28 1.05 1.63 1.47 1.26 1.28 2.94 1.17 1.55 B BAB BOB BNK BAM NY 17.2 14.2 15.5 14.4 14.6 14.2 14.6 13.4 14.6 14.1 14.6 14.6 13.1 14.6 13.6 12.6 14.6 15.1 14.1 15.1 29.1 31.6 17.8 17.1 12.6 14.5 21.6 26.7 24.3 26.7 14.1 12.4 14.4 12.6 14.8 13.6 14.2 12.2 13.8 12.2 13.1 14.6 21.2 24.3 20.6 18.6 11.2 10.1 10.7 24.3 38.9 14.6 24.3 15.6 16.6 12.1 41.3 15.2 43.7 14.2 21.17 17 17.72 16.43 15.47 14.27 19.53 15.45 20.21 17.77 19.09 17.08 14.87 17.49 18.99

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WUF WLF WPS WBR WDR 12.6 9.6 12.2 11.6 12.2 11.4 12.2 11.3 12.2 10.4 10.4 9.8 12.2 11.2 12.2 10.2 12.1 11.2 12.2 11.6 11.4 7.8 9.8 4.9 13.6 9.8 12.6 10.8 14.6 9.8 12.8 8.2 6.4 10.2 6.2 10.4 9.2 10.6 7.2 10.6 10.4 9.4 12.8 9.8 12.2 10.4 12.2 11.8 12.2 11.4

HCO 11.6 10.3 12.2 7.3 12.6 9.8 11.6 10.8 12.2 9.8 3 11.53 9.18 10.93 9.17 11.50 10.33 11.65 11.08 11.77 10.60 10.36 10.05 10.92 11.37 11.19 B BAB BOB BNK BAM NY 290 298 300 280 240 320 222 272 298 265 296 334 268 305 270 303 285 207 275 300 300 318 290 261 220 175 249 298 293 271 320 300 300 300 290 290 308 310 280 285 376 304 347 307 356 229 309 337 332 295 386 302 312 282 306 272 398 282 314 262 238.00 303.33 302.83 289.17 280.33 264.83 295.17 284.33 298.67 279.67 270.67 296.00 272.28 289.75 289.17

WUF WLF WPS WBR WDR 9.2 11.1 10.1 10.2 10.2 8.4 9.4 8.6 10.2 8.3 12.1 11.1 10.2 10.1 10.1 10.2 9.1 9.1 10.4 9.6 9.2 8.4 8.1 6.2 8.4 8.3 8.3 8.2 10.2 8.2 14.4 10.3 8.3 8.2 7.2 8.4 8.2 9.1 8.6 10.1 9.6 10.4 9.1 8.2 10.3 9.1 9.2 9.2 9.4 8.4 ALKA. 14.5 10.2 10.2 10.2 10.4 9.2 9.4 8.3 10.1 9.2 11.50 10.25 9.33 8.85 9.43 8.93 8.93 8.75 9.82 8.97 10.88 9.09 9.18 8.84 9.40 B BAB BOB BNK BAM NY 450 424 440 398 446 358 448 390 446 350 448 368 450 364 450 362 444 366 448 368 360 346 360 360 362 348 354 346 354 348 380 400 350 420 345 410 340 410 355 400 394 426 390 319 370 406 422 322 370 378 426 372 438 332 410 322 532 384 418 312 409.67 389.33 404.67 365.50 397.17 367.67 423.33 369.67 398.50 359.33

399.50 385.06 382.42 396.50 378.92

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WUF WLF WPS WBR WDR 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001

NH 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 3 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 B BAB BOB BNK BAM NY 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

WUF WLF WPS WBR WDR 2.8 2.1 2.7 0.8 2.9 0.8 2.7 0.8 3.1 1.1 2.2 1.7 2.4 3.8 1.4 3.4 1.2 3.2 2.5 3.3 1.6 1.4 2.4 0.9 1.4 1.1 1.2 1.1 1.1 1.7 2.1 1.2 2.4 2.2 2.2 1.8 2.1 1.7 2.2 1.8 2.2 2.1 3.7 2.2 3.7 3.5 3.2 3.5 3.2 2.3 Na 2.8 1.8 3.5 1.8 1.4 3.2 2.4 1.8 1.9 1.9 2.28 1.72 2.85 1.95 2.17 2.30 2.13 2.02 2.33 2.02 2.00 2.40 2.24 2.08 2.18 B BAB BOB BNK BAM NY 128 120 117 122 115 110 121 122 112 118 210 171 110 173 106 168 140 155 105 162 200 192 188 193 170 165 168 165 162 159 190 204 200 214 180 200 180 198 185 190 292 288 263 210 271 163 267 210 272 165 196 196 220 164 194 158 192 165 184 146 202.67 195.17 183.00 179.33 172.67 160.67 178.00 169.17 170.00 156.67

198.92 181.17 166.67 173.59 163.34

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WUF WLF WPS WBR WDR 3 2 3 3 3 2 3 2 3 3 3 3 3 2 2 3 2 3 3 2 2 2 3 2 3 3 3 3 3 2 4 3 2 3 2 2 2 2 2 2 3 4 3 4 5 3 5 3 5 3 Cl 3 2 4 3 2 2 2 2 2 2 3.00 2.67 3.00 2.83 3.33 3.33 2.83 2.50 3.00 2.33 2.84 2.92 3.30 2.67 2.67 B BAB BOB BNK BAM NY 109 101 112 114 116 144 114 105 119 116 107 102 126 108 125 101 104 100 102 123 128 103 113 111 131 106 114 119 129 128 110 142 152 115 142 102 118 120 119 121 110 119 124 122 115 116 103 118 138 119 164 104 108 108 121 112 149 104 154 114 121.33 111.83 122.50 113.00 125.00 113.50 117.00 111.00 126.83 120.17 116.58 117.75 119.34 114.00 123.50

WUF WLF WPS WBR WDR 0.585 0.455 0.471 0.344 0.514 0.304 0.404 0.314 0.411 0.314 0.725 0.567 0.822 0.622 0.793 0.672 0.783 0.682 0.596 0.411 0.486 0.002 0.512 0.005 0.005 0.005 0.322 0.348 0.005 0.005 0.396 0.003 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.003 0.003 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 F- 0.003 0.003 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.37 0.17 0.31 0.16 0.22 0.17 0.25 0.23 0.17 0.13 0.27 0.24 0.20 0.24 0.15 B BAB BOB BNK BAM NY 0.309 0.376 0.501 0.802 0.401 0.202 0.364 0.364 0.597 0.324 0.422 0.506 0.202 0.101 0.302 0.601 0.392 0.222 0.311 0.611 0.409 0.574 0.201 0.111 0.101 0.101 0.418 0.424 0.437 0.255 0.672 0.105 0.211 0.422 0.111 0.402 0.642 0.412 0.632 0.402 0.072 0.179 0.421 0.202 0.603 0.104 0.045 0.067 0.094 0.068 0.393 0.424 0.102 0.801 0.404 0.801 0.071 0.342 0.287 0.371 0.38 0.36 0.27 0.41 0.32 0.37 0.32 0.31 0.39 0.34 0.37 0.34 0.35 0.32 0.37 WUF WLF WPS WBR WDR 9.1 11.2 10.2 10.1 10.1 10.2 9.1 9.4 12.4 10.1 12.2 16.1 12.1 10.1 14.2 10.1 13.2 15.1 14.2 12.3 6.1 8.2 8.2 6.2 10.1 10.4 9.1 9.2 10.1 10.2 14.4 20.3 12.1 8.1 12.2 18.1 11.3 8.2 14.3 14.4 9.6 16.4 4.2 12.2 13.2 10.2 14.1 19.1 10.5 14.1 T. HARD 10.2 14.5 12.1 14.6 10.1 15.5 9.2 14.1 12.5 18.5 10.27 14.45 9.82 10.22 11.65 12.42 11.00 12.52 12.33 13.27 12.36 10.02 12.04 11.76 12.8 B BAB BOB BNK BAM NY 76.8 78.5 82.2 72.4 86.2 70.4 80.3 70.2 80.2 72.5 74.6 80.4 72.1 80.2 80.5 84.3 80.2 82.1 76.4 82.2 120.2 130.1 150.2 160.3 170.1 190.1 190.1 180.3 170.3 170.2 145.1 150.2 135.3 140.1 130.4 136.2 130.2 136.3 132.1 134.1 146.4 270.1 101.4 140.2 88.2 110.2 78.2 220.2 101.1 160.3 160.2 186.3 140.1 166.3 150.1 176.1 140.1 160.1 160.2 170.4 120.55 149.27 113.55 126.58 117.58 127.88 116.52 141.53 120.05 131.62 134.91 120.06 122.73 129.03 125.84

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Appendix 8: Values, Periodic and Sites Means for Trace Metals Parameters WUF WLF WPS WBR WDR 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 Pb 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 B BAB BOB BNK BAM NY 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005

0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005

0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

WUF WLF WPS WBR WDR 0.8 4.2 0.9 5.2 6.2 5.8 1.1 4.8 5.2 3.1 1.1 0.8 0.9 0.9 1.1 1.1 1.2 1.9 2.1 2.9 0.9 1.7 1.1 1.8 0.9 2.5 2.4 4.8 1.6 1.8 3.1 2.3 3.2 2.3 3.4 2.2 1.1 2.1 2.2 3.9 2.1 0.1 0.4 0.1 0.1 3.8 0.7 1.1 3.4 3.4

Fe 0.8 2.7 0.1 2.8 0.1 2.2 0.3 0.9 2.8 3.2

1.47 1.97 1.10 2.18 1.97 2.93 1.13 2.60 2.88 3.05 1.72 1.64 2.57 1.87 2.97 B BAB BOB BNK BAM NY 0.3 0.3 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.3 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.1 0.2 0.1 0.1 0.2 0.2 0.1 0.3 0.1 0.1 0.1 0.3 0.1 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.3 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.17 0.25 0.10 0.13 0.12 0.13 0.10 0.13 0.13 0.17 0.21 0.12 0.13 0.12 0.15

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WUF WLF WPS WBR WDR 0.062 0.028 0.068 0.054 0.028 0.052 0.022 0.038 0.011 0.032 0.035 0.022 0.023 0.018 0.033 0.026 0.036 0.032 0.027 0.021 0.042 0.022 0.054 0.061 0.057 0.055 0.032 0.028 0.012 0.042 0.042 0.028 0.042 0.022 0.042 0.022 0.029 0.032 0.042 0.022 0.048 0.058 0.005 0.011 0.017 0.008 0.042 0.039 0.064 0.005 Mn 0.052 0.062 0.035 0.061 0.005 0.006 0.018 0.008 0.005 0.005 0.05 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.02 0.05 0.04 0.03 0.03 0.03 B BAB BOB BNK BAM NY 0.006 0.005 0.014 0.015 0.011 0.012 0.011 0.016 0.012 0.012

0.006 0.005 0.013 0.017 0.011 0.013 0.017 0.013 0.013 0.011

0.015 0.005 0.005 0.009 0.005 0.005 0.009 0.014 0.005 0.007 0.011 0.008 0.009 0.007 0.008 0.007 0.009 0.011 0.006 0.006 0.008 0.008 0.021 0.009 0.011 0.012 0.027 0.015 0.024 0.012 0.001 0.006 0.013 0.005 0.015 0.014 0.028 0.015 0.016 0.012 0.01 0.01 0.02 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.02 0.01 0.02 0.01

WUF WLF WPS WBR WDR 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

Cu 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 B BAB BOB BNK BAM NY 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

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WUF WLF WPS WBR WDR 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 Cd 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

BAB BOB BNK BAM BNY 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

WUF WLF WPS WBR WDR 0.008 0.007 0.009 0.009 0.016 0.008 0.011 0.009 0.009 0.008 0.009 0.007 0.009 0.008 0.017 0.012 0.018 0.014 0.011 0.011 0.011 0.006 0.005 0.005 0.005 0.005 0.005 0.009 0.005 0.005 0.009 0.006 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.152 0.014 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 Zn 0.012 0.012 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.04 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.03 0.01 0.01 0.01 0.01 B BAB BOB BNK BAM NY 0.011 0.011 0.021 0.012 0.039 0.021 0.038 0.011 0.033 0.021 0.019 0.018 0.021 0.017 0.029 0.011 0.027 0.006 0.012 0.011 0.024 0.019 0.021 0.019 0.017 0.014 0.028 0.022 0.023 0.019 0.018 0.032 0.018 0.031 0.015 0.031 0.038 0.031 0.026 0.032 0.029 0.026 0.035 0.029 0.029 0.031 0.005 0.022 0.027 0.019 0.029 0.024 0.031 0.022 0.027 0.022 0.019 0.021 0.025 0.021 0.02 0.02 0.03 0.02 0.03 0.02 0.03 0.02 0.02 0.02 0.02 0.03 0.03 0.03 0.02

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Appendix 9: Values, Periodic and Site Means for Bacteriological Parameters

WUF WLF WPS WBR WDR 556 605 651 786 930 1786 942 1234 465 1886 505 651 651 837 840 1860 1076 1876 930 1209 1250 1345 1395 1488 1953 1674 1628 2096 1488 1488 1100 1250 642 1476 742 1476 898 2208 792 1876 785 845 930 651 2418 744 1524 1963 1302 858 T. COL 815 995 1102 1555 1580 1870 1642 2142 1402 1008 835.17 948.50 895.17 1132.17 1410.50 1568.33 1285.00 1919.83 1063.17 1387.50 891.84 1013.67 1489.42 1602.42 1225.34 BOSOM BOSOM BOSOM - BOSOM BOSOM - AB - OB - NK AM - NY 1024 1248 744 1048 554 1068 930 1028 558 1068 1488 1488 1674 2603 1023 1581 588 1048 1023 1581 1123 1837 576 559 656 850 1209 1651 656 650 1876 2046 1676 1976 1676 1926 1576 1876 1676 2594 1946 1684 1116 668 1594 679 1674 958 1926 1279 1112 998 1674 874 660 1128 1209 1234 656 1242 1428.17 1550.17 1243.33 1288.00 1027.17 1205.33 1197.67 1299.17 1082.5 1402.33 1489.19 1265.67 1116.25 1248.42 1242.42

WUF WLF WPS WBR WDR 125 194 127 432 117 832 220 432 190 742 185 208 292 340 651 465 396 562 364 372 360 425 468 1209 609 744 456 610 646 666 295 360 322 654 352 654 208 986 362 524 225 310 252 108 1488 670 666 708 465 360 F. COLI 228 325 637 725 324 520 892 942 570 482 236.33 303.67 349.67 578.00 590.17 647.50 473.00 706.67 432.83 524.33 270.00 463.84 618.84 589.84 478.58 BOSOM BOSOM BOSOM - BOSOM BOSOM - AB - OB - NK AM - NY 476 646 376 456 168 656 113 636 112 656 744 848 444 648 126 322 126 452 113 611 551 604 651 746 492 225 372 111 492 225 602 704 672 744 470 704 432 684 470 704 544 604 744 547 324 262 112 168 324 110 494 556 444 396 147 386 744 468 147 478 568.50 660.33 555.17 589.50 287.83 425.83 316.50 419.83 276.33 464.00 614.42 572.34 356.83 368.17 370.17

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Plate 3: Researcher Fetching Water in Lake Bosomtwi for Analysis in the Laboratory

Plate 4: Researcher Taking in–situ Measurement of Some Parameters at Wli Waterfalls

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Plate 5: Tourists Swimming in Lake Bosomtwi

Plate 6: Traders Selling Their Wares on a Festive Occasion at the Shores of Lake Bosomtwi

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Plate 7: Tourists Swimming in the Wli Waterfalls

Plate 8: Tourists Waiting to Cruise on the Lake Bosomtwi

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Plates 9: Wli Waterfalls Cascading Down the Mountain at the Lower Falls

Plates 10: The Pool at Wli Waterfalls where Tourists Swim

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