MORPHOLOGICAL AND SOCIO-ECONOMIC EFFECTS OF SAND
MINING ON RIVER TYAA IN KITUI COUNTY, KENYA
MUIRURI PHILIP GATHOGO
C50/CE/26072/2014
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE
REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF
ARTS IN GEOGRAPHY (GEOMORPHOLOGY) IN THE SCHOOL OF
HUMANITIES AND SOCIAL SCIENCES OF KENYATTA UNIVERSITY.
OCTOBER, 2020
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DECLARATION This Thesis is my original work and has not been presented for a degree award in any other University, or for any other award.
Signature ______Date__22/09/2020______
Muiruri Philip Gathogo
Reg. No: C50/CE/26072/2014
We confirm that the work reported in this thesis was carried out by the candidate under our supervision.
Signature
Date___22/09/2020______
Professor Joy Obando
Associate Professor
Department of Geography
Kenyatta University
Signature Date___22/09/2020______
Dr. Ishmail O. Mahiri
Lecturer
Department of Geography
Kenyatta University
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DEDICATION To all who value and fight for environmental management, planning andconservation for a better world to all organisms.
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ACKNOWLEGMENTS I’m delighted to thank many people who made this work possible. First, I thank the almighty God for giving me favour and strength to carry out this study successfully and for a purpose. Secondly, I express my sincere gratitude to my able supervisors, Prof. Joy Obando and Dr. Ishmail Mahiri for their unreserved guidance and mentorship throughout this journey. Their sagacious advise, constructive criticism, patience, encouragement and being available has helped me greatly while undertaking this study. May God bless them bountifully.
My sincere gratitude also goes to my family, principally to my mother Margaret Wairimu Muiruri and the late dad Mzee John Muiruri. Your great effort and sacrifice in bringing me up in an upright manner and in a conducive family environment are whole heartedly appreciated. Your candid advice that hard work pays and that no task is insurmountable have been my inspiration in this journey and have remained true as clearly reflected in the accomplishment of this study. To my siblings; Joseph Maina and Elizabeth Muthoni, your constant encouragement and jamboree of my little achievements is highly appreciated.
It’s my pleasure too to register appreciation to my friends and peers who supported me in one way or another in this journey. In particular, I wish to greatly thank Meshack Owira Amimo for generously tutoring me various statistical techniques in various software’s. I am also highly indebted to the members of the Kenyatta University Geography Department Cartographic Unit namely Belta Makato and Isaiah Ebole for their apt help in developing maps used in this study.
Lastly, I wish to thank the Mwingi Sand Mining Cooperative fraternity for providing me with the data that I really needed to accomplish this study. In the same vein, I appreciate all the anonymous respondents who took part in providing information reported in this work.
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LIST OF ABBREVIATIONS AND ACRONYMS AME: Average marginal effects
ANOVA: Analysis of Variance
EA: Environmental Audit
EIA: Environmental impact assessment
GPS: Geographical positioning system
GIS: Geographical information system.
MSMCS: Mwingi Sand Mining Cooperative Society
NEMA: National Environment Management Authority
NHIF: National Health Insurance Fund.
R: Free open-source statistical software.
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OPERATIONAL DEFINITION OF TERMS: Extent of sand mining- Is the temporal, spatial and magnitude of sand mining in
River Tyaa.
High level of sand mining- refers to sand extraction which exceeds the natural
replacement rates and which results to environmental degradation.
Low level of sand mining- refers to sand extraction which is below the natural
replacement rates.
Morphological factors- Are the measurable aspects characterizing a natural
landform on the surface of the earth such as slope angles, width, depth,
vegetation cover and weathering status.
River Morphology- Is the physical form or shape of the river channel in terms of
width, depth and slope angles.
Sand- Is the loosely bound, fine and naturally occurring granular materials found on
and along the river bed; also known as quartz oxide or quartzite.
Sand mining- Is the removal of sand from its natural configuration in the river
channel in a non-regulated way.
Sand harvesting- Is the removal of sand from its natural configuration in a regulated
way.
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Socio-economic effects- Is both positive and negative outcomes that sand mining
activity has brought in the locality on social and economic dimensions. Such
may include prostitution, school dropout rate, social conflicts, improved living
standards as well as infrastructural development.
Stable river Channel-Refers to a state of balance in a river channel whereby the rate
of sand removal matches the rate of sand replenishment.
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TABLE OF CONTENTS DECLARATION…...... ii
DEDICATION……...... iii
ACKNOWLEGMENTS ...... iv
LIST OF ABBREVIATIONS AND ACRONYMS ...... v
OPERATIONAL DEFINITION OF TERMS: ...... vi
TABLE OF CONTENTS ...... viii
LIST OF TABLES… ...... xii
LIST OF FIGURES...... xiii
LIST OF PLATES… ...... xiv
ABSTRACT………...... xv
CHAPTER ONE: INTRODUCTION ...... 1
1.1 Background of the Study ...... 1
1.2 Statement of the Problem ...... 4
1.3 Objectives of the Study ...... 5
1.3.1 Main Objective ...... 5
1.3.2 Specific Objectives ...... 5
1.4 Study Hypotheses ...... 6
1.5 Justification and Significance of the Study ...... 6
1.6 Scope and Limitations of the Study ...... 7
CHAPTER TWO:LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK…… ...... 8
2.1 Introduction ...... 8
2.2 Extent of Sand Mining ...... 8
2.3 Factors Influencing Sand Abundance in River Channels ...... 11
2.4 Effect of Sand Mining on the River Morphology ...... 13
2.5 Socio-economic Effects of Sand Mining ...... 17
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2.6 Conceptual Framework ...... 21
CHAPTER THREE: METHODOLOGY ...... 23
3.1 Research Design ...... 23
3.2 Study Area ...... 23
3.2.1 Climate and Vegetation ...... 24
3.2.2 Geology and Drainage ...... 25
3.2.3 Socio-economic Activities ...... 26
3.4 Sampling Techniques ...... 27
3.4.1 Sampling of River Sites ...... 27
3.4.2 Sampling of the Study Population ...... 31
3.5 Research Instruments ...... 32
3.6 Pilot Study ...... 32
3.7 Data Collection ...... 32
3.8 Data Analysis and Presentation ...... 34
3.8.1 Binary Logistic Regression ...... 35
3.8.2 Multiple Logistic Regression ...... 36
CHAPTER FOUR: RESULTS AND DISCUSSIONS……………...……………39
4.1 Introduction ...... 39
4.2 Demographics ...... 39
4.2.1 Age of the Respondents ...... 39
4.2.2 Gender of the Respondents ...... 40
4.2.3 The Duration of Stay in the Study Area ...... 42
4.2.4 Education Level of the Respondents ...... 43
4.2.5 Current Occupation of the Respondents ...... 44
4.3 Background Information of Sand Mining in the Study Area ...... 45
4.3.1 Involvement Level of Members of the Local Area in Sand Mining ...... 46
4.3.2 Duration of Sand Mining ...... 47
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4.3.3 Licensing of Sand Miners and Land Ownership ...... 48
4.3.4 Leasing Criteria and the Sand Mining Agreement ...... 48
4.3.5 Destination of the Sand Mined ...... 49
4.4 The Extent of Sand Mining in river Tyaa ...... 49
4.4.1 Temporal Extent of Sand Mining in River Tyaa ...... 49
4.4.2 Spatial Extent of Sand Mining in River Tyaa ...... 50
4.4.3 Quantity of Sand Mined In River Tyaa Annually ...... 51
4.4.3.1 Hypothesis Test ...... 52
4.5 Morphological Factors Influencing Abundance of Sand in River Tyaa ...... 53
4.5.1 Effect of River Bank Position on Sand Abundance ...... 55
4.5.2 Role of Slope Angles on Sand Abundance ...... 55
4.5.3 River Channel Depth and Sand Abundance ...... 56
4.6 Effects of sand Mining on the Morphology of the River Channel ...... 57
4.6.1 Sand Mining and the River Channel Width ...... 58
4.6.2 Contribution of Sand Mining to the River Channel Depth ...... 59
4.6.3 Effect of Sand Mining on River Channel Slope Angle ...... 61
4.7 Socio-economic effects of sand mining in river Tyaa ...... 63
4.7.1 Social Effects of Sand Mining ...... 63
4.7.1.1 Sand Mining and Community Conflicts ...... 63
4.7.1.2 Effects of Sand Mining on Schooling ...... 64
4.7.1.3 Sand Mining and the Stability of the Family Unit ...... 65
4.7.1.4 Effect of Sand Mining on Prostitution ...... 66
4.7.1.5 Association of Sand Mining with Drug Abuse ...... 66
4.7.1.6 Sand Mining and Security in the Study Area ...... 67
4.7.2 The Economic Significance of Sand Mining ...... 68
4.7.2.1 Effects of Sand Mining on Livelihoods ...... 68
4.7.2.2. Contribution of Sand Mining to Developments ...... 69
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4.7.2.3. Influence of Sand Mining on Health ...... 70
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSION, AND RECOMMENDATIONS ...... 71
5.1 Introduction ...... 71
5.2 Summary of Findings ...... 71
5.3 Conclusion ...... 72
5.4 Recommendations ...... 73
5.5 Area for Further Study ...... 74
REFERENCES……...... 75
APPENDICES……...... 85
Appendix 1: Questionnaire for Sand Miners, Land Owners and Households…...….85 Appendix 2: Rules of Logic Applied in Data Collection on Some Physical Variables as inspired by a study on ecological informatics by Ekström (2018)……………….94
Appendix 3: Data attachments…………………………..…………………………..98
Appendix 4: Research Permits……………………………………..………………104
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LIST OF TABLES Table 2. 1: Summary of Key Literature Reviewed ...... 20
Table 3. 1: Summary of the Sample Size ...... 32
Table 3. 2: Summary of the Methodology ...... 38
Table 4. 1: Age of the respondents ...... 40
Table 4. 2: Chi-Square Test on Quantity of Sand Mining in River Tyaa for 2008-2012 and 2013-2017 ...... 53
Table 4. 3: The Binary Logistic Regression Model Output ...... 54
Table 4. 4: Logistic Regression Model Output Effect of Sand Mining on River
Channel Depth ...... 58
Table 4. 5: Logistic Regression Output on Influence of Sand Mining on the River
Channel Depth ...... 60
Table 4. 6: Logistic Regression Model Output of Sand Mining on the River Channel
Slope Angles ...... 61
Table 4. 7: Chi-Square test results on social effects of sand mining ...... 63
Table 4. 8: Social effects of sand mining ...... 64
Table 4. 9: Economic effects of sand mining ...... 68
Table 4. 10: Results for the economic effects of sand mining ...... 69
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LIST OF FIGURES Figure 2. 1: Relationship between Sand Mining, Dynamics of River Channel and
Socio-economic Variables...... 22
Figure 3. 1: Study Area Showing River Tyaa in Kitui County, Kenya ...... 24
Figure 3. 2: A Section of River Tyaa Showing the Active Sand Mining Sites ...... 28
Figure 3. 3: Active Sand Mining Site and the Control Sites ...... 29
Figure 3. 4: Summary of The River Sampling Techniques ...... 30
Figure 4. 1: Gender of the respondents...... 41
Figure 4. 2: Duration of stay of respondents in the study area ...... 42
Figure 4. 3: Level of education of the respondents ...... 44
Figure 4. 4: Current occupation of the respondents ...... 45
Figure 4. 5: Level of involvement of members of the local area of study ...... 46
Figure 4. 6: Sand mining duration in river Tyaa ...... 47
Figure 4. 7: The distribution of sand mines along river Tyaa ...... 51
Figure 4. 8: Sand mining trend from year 2008 up to 2017 ...... 52
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LIST OF PLATES Plate 4. 1: Effect of sand mining on the river bank stability and the riparian vegetation...... 59
Plate 4. 2: Effect of sand mining to the river channel depth and bank slope agle ...... 61
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ABSTRACT Current global rate of sand mining in river channels is unsustainable, and in Kenya the activity going on unregulated. This study established the morphological and socio-economic effects of sand mining in river Tyaa by addressing the following objectives: To determine the: extent of sand mining; morphological factors influencing abundance of sand; effects of sand mining on the morphology of River Tyaa and Socio-Economic effects of sand mining in river Tyaa. Random sampling technique came up with an active sand mining site. Systematic sampling was used on this section to select the areas to collect data. Stratified sampling was used to select respondents using the records from M.S.M.C.S. This sample size comprised of 100 households, 50 sand miners and 5 land owners. Data on channel depth, width, vegetation cover, erosion status, sand volume status, channel slope angles, and bank position were obtained through physical measurements in the field while data on sand quantity mined per year for a decade was obtained from secondary sources. Structured questionnaires were used to obtain socio-economic data. ArcMap GIS was used to map the spatial extent of sand mining along river Tyaa. Descriptive statistics was used to analyse the quantitative data and the results presented in graphs and percentages. The binary logistic regression analysis was employed to show factors influencing abundance of sand in river Tyaa’s channel. The multiple logistic regression analysis was used to examine the effect of sand mining to the river Tyaa channel morphology. Finally, chi-square test was used to test the hypotheses. Chi-Square test indicated that there were significant sand mining activities in river Tyaa (Df = 1, χ2= 9, P=0.003). The study established that river channel width (P=6.47e-05), depth (P=7.00e-07), slope angles (P=3.36e-06) and bank position (P=2.2e-16) were significant in influencing sand abundance in the river channel as indicated by the respective marginal effects and p-values. Additionally, sand mining had modified the river channel morphology through causing increase in depth (P=7.19e-02), width (P=9.95e-03) and slope angles (P=9.37e-03) at the active mining sites, compared with the control sites as shown by the respective p-values. Finally, sand mining had caused positive economic effects (Df = 3, χ2= 201.65, P=0.000) such as reduced school drop- out rates, infrastructural developments, enhanced livelihoods as well as affordability of medication. On the other hand, sand mining got associated with destruction of the riparian vegetation, lowering of water table in the sand reserves, prostitution, community conflicts and drug and substance abuse (Df = 3, χ2= 42.33, P =0.000). The study concluded that sand mining had over stretched on temporal, spatial and quantity basis; that sand abundance in a river channel is a factor of channel width, depth slope angles and the type of the bank. Further, the study concluded that sand mining had caused increased river channel depth, width and slope angle and that sand mining had caused significant Socio-Economic effects. The study recommended reduction in quantities of sand mined from river Tyaa through curbing illegal mining and closure of some mines; siting of mines on convex banks by regulatory authorities such as NEMA; Regular EIA as well as EA was recommended as a way of monitoring the activity. Lastly, the study recommended placement of an elaborate revenue collection system from sand mining industry by the county government to help give back to the community, and increasing involvement of the local area members in the sand mining industry to help resolve resultant conflicts.
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CHAPTER ONE: INTRODUCTION 1.1 Background of the Study
Sand mining is a phenomenon that is evident in many places across the world, mainly associated with the construction industry (Rinaldi et al., 2005). The construction industry prefers sand from the river channels, floodplain and shores of the lake and oceans, simply because it is clean and its grains are angular, a factor that enhances the strength of the concrete (Kondolf, 1997). Sand from the desert terrain is least preferred because its grains are rounded and for that reason does not bind well with cement (Lu et al., 2007). According to Peduzzi (2014), between 47 and 59 billion tonnes of solid materials are mined globally in a year at the current period. Of this, sand accounts for the largest share ranging between 68 and 85%.
This value was arrived at by looking into the cement production across the world, and subsequently computing the quantities of sand recommended for a given amount of cement in the certified ratio in which they are mixed to make concrete.
Studies worldwide have documented the economic significance of sand mining, and their findings tend to corroborate that it is a highly viable economic activity (Bruce,
2015; Rajesh & Anushiya, 2013). However, in most parts of the world, it is being carried out in an unregulated manner, thus causing it to yield adverse environmental impacts. Research by Peduzzi (2014) shows that the current levels of sand exploitation globally are not sustainable. As a result, this activity should be regulated through the appropriate mechanisms so as to achieve sustainable development. The level of sand consumption is directly proportional to the rate of economic growth as well as the economic status of a country. This is clearly depicted by the facts on sand mining that places the United States of America,
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Australia, Austria, South Africa and Kenya respectively as the leading nations in sand mining (Wambua, 2015). In addition, a country like Dubai which is economically fair, depleted its marine sand reserves during the construction of the beautiful island of Palm Jumeirah between year 2001 and 2006. Today, it is importing sand for its local consumption from Austria (Bruce, 2015). Sand mining has been reported widely across the world. For instance in China, sand mining has been reported along many rivers such as river Pearl and its tributaries, whereby channel incision have ensued as a result of unregulated sand mining (Lu et al.,
2007). In Europe, Rinaldi et al., (2005) conducted a study on five rivers in Poland and Italy and found out that the activity was being carried out unregulated, and had resulted in some adverse environmental impacts such as river channel incision, banks instability as well as the river bed armouring.
In South Africa, sand mining is said to be taking place uncontrolled, a factor that has resulted in environmental degradation especially in the river beds as well as on the riparian zones (Mkando 2004). A similar case has been reported in South Africa by
Amponsah-Dacosta & Mathada (2017) on river Nzhelele in Limpopo province. In
Nigeria, Nabegu (2014) reported that unregulated sand mining had caused modification of the river channel morphology at the active sites of mining, an effect which is negative. Sand mining was also reported to cause lowering of the water table in the sand aquifers along river Kano in Nigeria (Nabegu, 2013). Despite many negative effects resulting from sand mining, the activity has been credited on some economic grounds. For instance, Atejioye & Odeyemi (2018) and Madyise (2013) established that sand mining had empowered the sand miners economically in
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Nigerian and Botswana respectively. In Ghana, Salifu (2016) established that sand mining had enabled people to acquire assets from the proceeds of sand mining.
In Kenya, sand mining is taking place near areas that the rapidly urbanising such as
Thika, Nairobi, Machakos, among others due to the rapidly rising demand for housing as well as the upgrading of the roads and other infrastructures (Mwaura,
2013). As such, sand mining had been reported in different parts of the country. For instance, Nguru (2007) reported that sand mining was going on unregulated in
Magarini division, a factor that had degraded the environment leading to loss of biodiversity as well as eroding the culture of the predominant inhabitants of the area.
Elsewhere in Kerio valley, Meli et al., (2017) reported that sand mining is an activity that has empowered people economically by enabling them initiate other forms of livelihoods such as goat rearing, fruit farming and Cereal crop farming such as millet and sorghum.
In Kitui County, sand mining is taking place in order to meet the high demand by the construction industry in the nearby urbanizing centres such as Thika, Nairobi,
Mwingi, Kiambu and Kajiado; with a lot of sand being exploited due to ease of accessibility (Mwaura, 2013). Kitui County has got several ephemeral streams namely Thunguthu and Tyaa in the Mwingi sub-County on one hand, and rivers
Tiva and Mwitasyano in the Yatta sub-County of Kitui. Others are Nzeeu, Kalundu,
Thavu and Kiindu seasonal flows, among others from which sand mining is taking place (Van Loon & Droogers, 2006). Most of these rivers lie in the Ukambani region covering areas such as Machakos and Kitui. Research undertaken by Muiruri
& Amimo (2017) in Kitui confirms that sand mining is taking place unregulated, a factor that had caused negative environmental effect such as lowering of the water
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table in sand aquifer as well as modification of the river channel morphology. The study further established that the activity had caused social conflicts, findings which agreed with those of Wambua (2015) and Mutisya (2006). Additionally, the three aforementioned studies have also acknowledged the positive role of sand mining in the local economies through job creation which has empowered people financially.
The present study undertook to establish the morphological and socio-economic effects of sand mining in river Tyaa in Kitui County.
1.2 Statement of the Problem
A significant number of studies have shown that unregulated sand mining within river channels have greatly accelerated natural geomorphic processes resulting in negative consequences such as modification of channel morphology, lowering of ground water table, streambank instability, flood flow increase and several other biological impacts (Kondolf, 1997; Nabegu, 2013; Rinaldi et al., 2005). Sand mining from river channels in Kitui has risen to a level that is raising concern
(Mwaura, 2014; Muiruri & Amimo, 2017). This has resulted from high population growth coupled with a rapid urbanisation rate (Republic of Kenya, 2014), a factor which has raised demand for the grade sand for construction of houses as well as other infrastructures in the country. In this case, Nairobi, Thika, Mwingi and Kitui towns derive their sand for construction from the ephemeral streams in the Kitui
County, thus exacerbating the rate of sand mining. At the moment, sand mining in these river beds is uncontrolled (Mwaura, 2013), basically due to lack of informing principles and guiding policies to this activity. As noted by Kondolf (1997) and
Nabegu (2013), such high rates of uncontrolled sand mining lead to degradation of the river environment, mainly the river channel morphology and the riparian
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vegetation zones. Additionally, the activity as practiced in Kitui has resulted into social conflicts due to lack of proper guiding regulatory framework on the exploitation and sharing of the proceeds from the sand mining industry (Muthomi et al., 2015). Going by that, this study found need to examine the phenomena in order to understand its effects on the river channel morphology and on socio-economic effects to help devise suitable mechanisms and strategies of promoting sustainable sand mining activity. Despite presence of some studies on sand mining in Kitui
County, presence of regional differences in lithology, drainage among other sub- catchment characteristics justifies need for a localized study as urged by Nabegu
(2014) to reliably inform the state, extent and effects of sand mining in river
Tyaa.This study focused on river Tyaa which is located in Kitui County, Kenya and from which sand mining has been taking place unregulated due to its ease of accessibility.
1.3 Objectives of the Study
1.3.1 Main Objective
The main objective of this study was to establish the morphological and socio- economic effects of sand mining on River Tyaa.
1.3.2 Specific Objectives
In order to achieve the main objective, the study addressed the following specific objectives:
(i) To determine the extent of sand mining along the river Tyaa channel.
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(ii) To establish the morphological factors influencing abundance of sand in the
River Tyaa channel.
(iii) To examine the effects of sand mining on the morphology of River Tyaa.
(iv) To establish the socio-economic effects of sand mining.
1.4 Study Hypotheses
The study addressed the following hypotheses:
Ho1.There is no significant sand mining taking place in the river Tyaa
channel.
Ho2. There are no significant morphological factors influencing sand
abundance in the river Tyaa channel.
Ho3. There are no significant effects of sand mining on the morphology of
river Tyaa.
Ho4. There are no significant social effects resulting from sand mining in river
Tyaa.
Ho5. There are no significant economic effects resulting from sand mining in
river Tyaa.
1.5 Justification and Significance of the Study
Due to the rapidly growing building and construction industry both in Kitui County and beyond, need for grade sand from the ephemeral rivers in the study area is on the rise. This has led to a considerably high rate of sand mining on the river beds, which is the storage form of the water available for the people in the study area
(Muiruri & Amimo, 2017). In Kenya, Sand mining is being carried out in a highly unregulated and uncontrolled manner, which is alarming. Such high rates of sand mining that may exceed the natural replacement rates leading to the occurrence of
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environmental problems to the river environment. River Tyaa was selected for the study owing to the unregulated state of sand mining that is taking place as reported by Wambua (2015) and Muiruri & Amimo (2017). In addition, the activity has brought about crises whereby conflicts between the sand miners and the community members have resulted in deaths (Gitonga, (2017). Following that, this study found a dire need to examine the activity in order to help develop intervention measures to salvage the environment from human destruction as well as offer practical solution to social conflicts emerging from exploitation of sand resource. The knowledge obtained from this study has built on the existing technical literature and may also be used to inform sand mining policy making process by the relevant authorities such as NEMA.
1.6 Scope and Limitations of the Study
This study was undertaken on river Tyaa which is in Kitui County. Through purposive sampling, a stretch of the river extending up to a length of 35 km was considered from which a site measuring 1.5 km was sampled for the study. This comprised an active site of mining, and two portions that are not affected to the up and downstream reaches of the active sand mining site which acted as control sites.
The study considered a population from the whole sub-catchment in areas where sand miming was taking place. The major limitation of this study was the hostility from sand miners on the site during the data collection process due to their perception that the study was out to disable their activity. Towards this, the local area chief was engaged, in order to introduce the researcher to the sand miners, state the intentions of the study as well as its legality since a permit had been obtained to allow data collection. In addition, the village elders in the study area accompanied the researcher throughout the data collection process for security purposes.
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CHAPTER TWO: LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK 2.1 Introduction
Sand mining from rivers is an activity that has taken place for centuries across the world. However, demand for sand has risen significantly owing to the increase in demand from the construction industry aimed at meeting the housing needs for the increasing population across the world as well as the vast infrastructural developments that are being actualized (Peduzzi, 2014). The activity has been associated with adverse environmental effects in areas where it has been carried out unregulated thus raising need to undertake a study at the local setting to help enhance understanding of the activity. This chapter discusses the key literature pertaining to sand mining activity in line with the topic of study and the study objectives. The areas discussed include the spatial extent of sand mining, factors influencing abundance of sand along the river channel, effects of river sand mining on the river channel morphology and the socio-economic effects of sand mining.
Finally, this chapter also discusses the conceptual framework which is drawn from the geomorphic concept of positive and negative feedback mechanisms of the river channel development.
2.2 Extent of Sand Mining
The ever growing building and construction industry have prompted continued sand mining over the years with sand mining being carried out along the river channels, on the floodplains, and on the shores of the lakes and oceans (Orr & Krumenacher,
2015). According to Kondolf (1997), sand from such sites is usually clean, and its grains are angular, a factor that enhances the strength of the concrete. On the other hand, sand from the desert terrain is less preferred for construction purposes because
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its grains are rounded and smooth (Lu et al, 2007). Over the years, America had been the leading continent in terms of sand mining, with multiple cases of sand mining reported along the rivers and by the shores of the ocean (Peduzzi, 2014).
According to Schloesser et al., (2008) who carried out a research on river sand mining in U.S.A., the activity was going on unregulated, leading to some environmental challenges. In view of their study which agrees with that of Kondolf
(1997), the understanding of the geomorphic processes would help provide an insight into the effects of sand mining on the river systems.
On the other hand, Asia is the leading continent in sand mining today as depicted by its high volume of cement production and consumption which is rated at 58% of the cement produced in the world (Peduzzi, 2014). In a global based study, Peduzzi
(2014) pointed out that sand mining is taking place in an unsustainable way. The study estimated that about 40 billion tonnes of sand are mined each year which happens to be twice the estimated total amount of sediments carried by rivers of the world in a year. Going by that, it is evident that sand mining is a global issue which should be closely examined to protect the natural sand reserves from depletion as well as the environment from degradation.
In Africa, sand mining has been reported from different places such as on the shores of the lakes and oceans and mainly from the river channels (Mensah, 1997;
Madyise, 2013). For instance, in Nigeria, sand mining has been reported in the river channels, an activity that has been discredited on the grounds that it is taking place unregulated thus breeding adverse environmental effects (Nabegu 2014; Ako et al.,
2014; Atejioye & Odeyemi, 2018). Similar findings have been arrived at in South
Africa by Kori & Mthanda (2012) in a study on effect of river sand mining. As
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established by Chevallier (2014) sand mining is an activity that is directly proportional to the economic level of development of a country. Following that, countries such as South Africa, Egypt, Nigeria and Kenya which are economically fair have been ranked as the leading sand consumers in Africa (Wambua, 2015).
Additionally, the trend of sand mining has been noted to increase gradually over the years, with the highest rates being witnessed at present time (Kori & Mathada,
2012). This has resulted from the rapid rate of urbanization that is taking place across the continent as well as across the world, a factor that has raised demand for the construction sand.
In Kenya, sand mining has been taking place for a long period of time with the frequency and intensity of the activity gradually rising up to the present time
(Gitonga, 2017). In line with that, Kimenyi et al., (2015) established that the high annual economic growth ranging between 4.37% and 5.6% has sparked fast growth of the construction industry thus raising demand for construction sand. According to
Mwaura (2013), sand mining is highly undertaken in river channels near the rapidly urbanizing centres such as Nairobi, Thika among other towns. Following that, sand mining has been reported in rivers, along the shores of Lake Victoria as a well as on the shores of Indian Ocean near the rapidly growing urban areas, (Mutisya, 2006;
Nguru, 2007; Muendo, 2015; Gitonga, 2017). From the findings aforestated above, it is clear that sand mining in Kenyan rivers is taking place unregulated thus resulting into negative environmental effects.
In some parts of Kitui county studies by Muiruri & Amimo (2017); Wambua (2015) and Mutisya (2006) have established that sand mining is taking place uncontrolled
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from the ephemeral streams in Kitui County. This implies that large quantities of sand is leaving the river channels, a factor that has raised a lot of concern from inhabitants of the respective areas affected. Sand mining in Kitui is taking place from different rivers such as Kivou, Tyaa, Thwake, and Kasieku among others as established by Wambua (2015) and Muendo (2015). Despite presence of some studies on sand mining in some parts of Kitui county, there is still limited understanding of the state of the activity due to presence of local variations in sub- catchment characteristics and human activities. In efforts to shed more light on that and help in policy formulation regarding sand mining, this study undertook to establish the spatial, temporal and quantity extents of sand mining from river Tyaa.
2.3 Factors Influencing Sand Abundance in River Channels
The presence of sand in a river channel is a function of several natural watershed factors such as erosion status, slope angles, vegetation cover density, and the climate of the area (Osterkamp et al. 1994; Raj & Azeez, 2012). Additionally, the channel width, depth and meanders also influences the amounts of sand deposited in a river channel, as stated by Charlton (2008) who also remarked that the stream velocity is higher at the constricted portions of the channel, a factor which promotes hydraulic erosion as opposed to the wider and shallower sections of the river where the deposition processes take place due to reduced velocity of the stream current.
According to Davis (1899), the stage of the river significantly influence the abundance of sand in the river channel whereby increasing amount of sand is noted from the youthful to the old stage where the main activity is deposition. From the findings by Davis (1899), there is little sand deposits at the youthful stage of the river because the rivers main activity is erosion coupled with a steep channel
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gradient which promotes removal of the eroded materials. The middle stage of the river is marked by a near equilibrium state between the inflow of water and sediments, a factor that causes a constant river bed elevation, thus moderate amounts of sand. The old stage of the river is characterized by aggradation of the river channel due to deposition that takes place, primarily promoted by the gentle slope gradient thus causing abundance of the sand.
On a study on the perennial river channel evolution, Duvall et al., (2004) established that changes along the river channel such as local uplift, change in resistance of the rocks over which the stream flows as well as discharge variation may influence abundance of sand on a river channel. This is because such factors promotes river rejuvenation, a factor that acts against deposition of materials on a river channel. A study on ephemeral rivers in Spain by Sandercock & Hooke (2011) focused on the significance of vegetation on a river system. The study established that presence of riverine vegetation along the river banks helped reduce the bank erosion hence protecting the sand reserves deposited on the shifting banks of the rivers. The roots of such vegetation bound the sand materials thus making them firm and resistant to quick removal by the river current. The present study assessed how factors such as geology/erosion status, slope angles, width, depth, vegetation cover density, and river bank position influence the sand abundance in the seasonal Tyaa
River. This aimed at presenting appropriate data that would help in proper siting of the sand mines along the river channel, a type of information that remains scarce in studies carried out in Kenya dryland areas.
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2.4 Effect of Sand Mining on the River Morphology
Lu et al., (2007) studied sand mining in river Pearl which is the second largest river in China in terms of river discharge, mainly focusing on how the activity affected the river morphology. The findings indicated that sand mining had led to river channel incision, an outcome which closely agrees with that of Nabegu (2014);
Rinaldi et al. (2005) and Kondolf (1997). This study established the morphological effects of sand mining on river Tyaa in Kenya, basically informed by the fact that the results obtained elsewhere lack application in another area due to the variation in multiple local and regional factors, as espoused by Nabegu (2014).
Elsewhere in India, a study aimed at establishing the environmental effects of sand mining was carried out in Chalakudy, Periyar and Muvattupuzha rivers by Sreebha
& Padmalal (2011). From the findings, sand mining was taking place uncontrolled due to lack of a proper informing policy, a factor that had led to modification of the river channel morphology. To address this, the study recommended that scientific assessments be carried out in rivers suffering from the same to help in formulating suitable river management strategies. Since this situation is evident in Kenyan rivers today, this study conducted an assessment in river Tyaa in a bid to help come up with suitable strategies to carry out sand mining without causing negative environmental effects.
In Europe, Rinaldi et al. (2005) carried out a study on some five rivers
(Tagliamento, the Brenta, the Arno, the Ropa and Wisloka), basically looking at the effect of sand mining to the channel morphology. The study compared aerial photographs for four past decades and their findings ascertained that sand mining was positively contributing to the adjustment of the river channel. Preciso et al.
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(2012) also carried out a study on the impacts of land use change and sand mining to the change in river Reno channel morphology in Italy. The study employed aerial vertical photographs to compare the longitudinal river profiles for the past three decades. Their findings agreed with those of Rinaldi et al. (2005) which found out that high levels of sand mining had led to modification of the river channel. The present study employed the Logistic Regression analysis to establish the effects of sand mining on river Tyaa channel morphology, an aspect that is paramount for developing sustainable sand harvesting strategies. This study has given a new dimension of assessing environmental soundness of river sand mining in Kenya, which enriches the existing technical literature in this field.
Studies have been carried out in Africa regarding the effect of sand mining to the river morphology. For instance, Ta et al. (2014) studied the effects of sand mining to the soils and land in southern Nigeria using field observations and laboratory tests.
The study established that rampant sand mining had led to collapsing of the river banks thus affecting the river geometry negatively. In Botswana, a study on the environmental effects of sand mining by Madyise (2013) established that sand mining had led to an increase in river channel depth and width. Further, it also pointed out that this activity had led to the degradation of the river water quality emanating from the oil spills of the loading tracks. The study by Madyise employed a purely descriptive approach while this study used both qualitative and quantitative approaches. Elsewhere in Nigeria, Nabegu (2014) carried out a study on the morphological impacts of sand mining on river Kano. The study employed the
Analysis of Variance (ANOVA) to compare the variation in the channel morphological aspects at the active site of mining and the control sites. The study
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established that sand mining had contributed to alterations in the river channel morphology. In addition to that, the study also pointed out that this alteration had led to other environmental effects to the river system such as river incision and destruction of the riparian vegetation.
According to Nabegu (2014), the ephemeral streams have been remotely studied across the world, thus raising a need to undertake studies on them in a bid to enhance understanding of their dynamics. In addition to this, the study pointed out that river channels are quite dynamic and the extrapolation results of a study in one area lack application credibility in another. Going by these, there was imminent need to carry out a study at the local area in context of this study in order to secure the site-specific dynamics of the ephemeral river Tyaa channel especially in light of sand mining. This study employed multiple logistic regression analysis to examine the effect of sand mining on river morphology thus enriching the technical literature in this domain both quantitatively and qualitatively to help in policy making on river sand mining in Kitui County
Hemalatha et al. (2005) carried out a study on sand mining in Uttara Pinakini River in India, and the study findings confirmed that sand mining contributed to depletion of the sand reserves along the river. Elsewhere in Europe, Salit and Ioana-Toroimac
(2013) undertook a study in Siret and Buzau Rivers and found out that sand mining had caused sediment deficit in the rivers leading to channel incision up and downstream of the mining areas. The study used aerial photos of the last three decades and closely assessed the morphological impact of the sand mining in the stretch of the river visa-a-vis the increasing extraction of sand due to increasing
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demand. Similar results were obtained by Nabegu (2013) in Nigeria on a study conducted in Wudil river channel.
In their research, Mmom and Chukwu-Okeah (2012) found out that sand mining in the new Calabar river in Nigeria had resulted in significant down-cutting of the riverbed. In addition, it had caused an increase in channel slope angles which led to significant increase in stream velocity. This, in turn, increased the sediment transport capacity which accelerated channel incision causing some significant changes in channel morphology. However, the study did not inform on the best sand mining practices to be adopted. The findings of that study agreed with those of Lu et al.,
(2007); Nabegu (2013); and Rinaldi et al. (2005) who also found out that sand mining had resulted into negative environmental effects such as alteration of the river channel morphology. However, a common factor is that all these studies were undertaken in perennial rivers in Europe, Nigeria and China, while the present study was carried out in an ephemeral stream in Kitui County, Kenya.
In Kenya, few studies have focused on the effects of sand mining on the river morphology. For instance, a study by Muiruri & Amimo (2017) established that indiscriminate sand mining activities in a river channel had caused increase in river channels width, depth and slope angles. The findings of that study agreed with those of Mutisya (2006) and Nguru (2007) who established that river sand mining had caused river bank instability leading to collapsing. On the other hand, a study by
Wambua (2015) on effects of sand mining in river Kivou showed that high rates of sand mining had caused widening of the river channel at the mining sites. Unlike these studies, this study focused on sand mining on river Tyaa aiming at
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quantitatively informing on the effects of sand mining on the river channel morphology.
2.5 Socio-economic Effects of Sand Mining
According to Rajesh and Anushiya (2013) in a study in Kathmandu River in Nepal, sand mining has got economic and social benefits as well as environmental challenges. Environmental problems occur when the rate of extraction of sand, gravel and other materials exceeds the rate at which natural processes generate these materials (Kondolf, 1997). A study by Carrere (2004) in Uruguay established that sand mining had helped to raise the living standards of the people involved in the industry through income generation. However, the study pointed out need for practicing sand mining using prudent methods to help avoid environmental degradation. In India, sand mining has been reported to be a bright economic activity in Bangladesh (Khan & Sugie, 2015). The activity has employed thousands of people both in the mines and in the transportation sector thus checking unemployment rates. However, the study established that some people had privatized pubic land to enable them benefit from sand mining, a factor that generated conflicts. In Austria, sand mining in rivers has been reported to be taking place and generating significant amount of income to the country once exported
(USGS, 2014).
In Africa, sand mining has been reported widely. For instance, in Botswana a study by Madyise (2013) has established that sand mining is a viable economic activity since it has empowered people with capital to undertake other projects. In South
Africa, Mkando (2004) found out that sand mining industry had created many employment opportunities for the young population, a factor that made the industry
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to be regarded economically viable. This agrees with findings of Salifu (2016) in
Ghana where sand mining has enabled young people to acquire assets and establish other small scale businesses. In Nigeria, sand mining has been reported in many rivers, and a study by Rinaldi et al., (2005) cites sand mining as an economic activity that has facilitated developments in the rural areas.
In Kenya, a study by Mwaura (2013) assessed the economic impacts of sand mining in Machakos, and found out that sand mining is impacting significantly the economic status of the inhabitants. However, the study cautioned that the social impacts of the activity should be reviewed in light of the adverse environmental consequences of sand mining. On the other hand, Nguru (2007) in a study in
Mjanaheri area of Magarini Division established that sand mining had led to erosion of some of the cultural practices of the inhabitants as sand mining activities were to a great extent involving people from outside Magarini division. Elsewhere in Kerio valley, a study by Meli et al., (2017) on impacts of sand harvesting on the livelihoods along Kerio River established that sand mining activity had helped people to earn income that had enabled them to obtain assets such as goats and sheep which are a key source of income in Kerio river sub-catchment.
In Kitui County, Wambua (2015) undertook a study on the socio-economic effects of sand mining and established that the activity had positively impacted on people through earning them substantial amount of income. However, the study established that sand mining had caused some negative social effects such as increased insecurity and conflicts. In Machakos, a study by Nthambi and Orodho (2015) found out that sand mining had contributed to high rates of school dropout. Another study
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by Muiruri and Amimo (2017) on socio-environmental effects of sand mining in
Kitui established that sand mining had caused both economic and social effects. For instance, the study established that sand mining had enabled people involved in the activity to earn appreciable income compared to the ones not involved in the activity. Additionally, the study established that sand mining had brought about some negative social effects such as insecurity, prostitution, conflicts, and drug abuse. Regional differences inherent between this study and the aforestated studies present need to conduct a study in river Tyaa sub-catchment to inform on the socio- economic effects of sand mining. Table 2.1 shows a summary of the key literature reviewed in this study.
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Table 2. 1: Summary of Key Literature Reviewed
AUTHOR FOCUS OF THE STUDY GAP FOCUS OF THIS STUDY AND STUDY YEAR Nabegu, Change of river The study was carried Focused on sand mining on an 2013 morphology in out on a perennial ephemeral river in a bid to inform relation to the sand river, thus creating the on the effect of sand mining to mining. need to seek an the river morphology. understanding of the same phenomenon on The study used logistic regression the ephemeral streams. analysis. The study used ANOVA. Mmom and Effect of sand mining The study was carried To study an ephemeral stream in Chukwu- on the morphology out on a perennial river Kitui county, Kenya. Okeah of New-Calabar using hydrographical (2012) River, Nigeria. data. Pointed out need It has recommended suitable to control sand mining measure to control high rates of to avoid adverse sand mining in River Tyaa. environmental impacts.
Rinaldi et Effects of sand The rivers in this study The study employed logistic al, 2005. mining on the river were all perennial, and regression analysis to examine the morphology of five used vertical aerial effects of sand mining to the river rivers in Europe. photographs of morphology. different historical periods. Mwaura, Economic impacts of Only considered the The study factored both the social 2013. sand mining in economic impacts. and economic effects. Machakos, Kenya The study was carried Was carried out in Kitui County. out in Machakos County.
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2.6 Conceptual Framework
The study adopted a conceptual framework of morphological feedback responses in a natural system. This conceptual framework posits that a river channel is always in a dynamic state of change and this change is influenced by the factor that has triggered it, thus it can either be positive or negative feedback response (Huggett,
2007). A negative feedback is a situation whereby the effects introduced into a system progressively diminish and finally the system gets back to its normal state.
On the other hand, positive feedback refers to a situation whereby the change introduced into a system gets amplified progressively, eventually causing the system to be very much unstable. In this case, various elements of the river channel system are observed to interact, with the dependent and independent variable being sand mining.
The river channel stability is influenced by the independent variable; sand mining, which is basically the main agent of change introduced into river Tyaa channel system. High rate of sand mining from river Tyaa channels influence other independent variables that lead to an increase in channel width, depth and slope angles, which in turn lead to high speed of channel flow when it rains, eventually leading to high soil erosion. The gross effect of this is a degraded channel which has little sand deposits and minimal capacity to store water in the sand reserves. In a nutshell, high rates of sand mining in the river channel lead to a positive feedback, which in turn lead to adverse effects on the environment such as increased slope angles, width and depth. Conversely, if safe levels of sand mining are observed, negative feedback results, thus leading to a sustainable sand harvesting activity. As illustrated in figure 2.1, realisation of sustainable sand mining may be aided by
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formulation and enforcement of suitable policies. Such polices will help deal with both adverse environmental and socio-economic effects associated with high levels of sand mining.
Figure 2. 1: Relationship between Sand Mining, Dynamics of River Channel and Socio-economic Variables.
Source: Modified from Hugget (2007)
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CHAPTER THREE: METHODOLOGY
3.1 Research Design
This study used both quantitative and descriptive research designs. According to
Cooper et al., (2013) descriptive research design is concerned with finding out the what, where and how of a phenomenon. On the other hand, quantitative research design involves the numerical presentation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect
(Sukamolson, 2010). This research design enabled the researcher to obtain physical measurements on the current status of sand mining in river Tyaa with respect to the existing conditions. Additionally, it enabled the researcher to obtain and hence describe the socio-economic effects resulting from sand mining in the river Tyaa locality.
3.2 Study Area
This study was conducted in Kitui County in the Eastern Region of Kenya which covers an area of 30,437 km2 (Republic of Kenya, 2018). The County has an altitude ranging from 400 m to 1800 m above sea level. It is bordered by Machakos and
Makueni Counties to the west, Tana River County to the East, Taita Taveta to the
South and Embu and Tharaka Nithi counties to the North. It is located between longitudes 370 00’ E and 380 30’ E, and latitudes 000 50’S and 010 00’ S (National
Atlas of Kenya, 2003). River Tyaa on which this study focused lies between longitude 370 55’ E and 380 05’E and latitude 10 05’ S and 00 45’ S (Figure 3.1).
River Tyaa was selected because sand mining was reported to take place unregulated thus causing negative environmental effects on the river and social conflicts between
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the sand miners and the locals on economic and environmental grounds (Wambua,
2015).
Figure 3. 1: Study Area Showing River Tyaa in Kitui County, Kenya
Source: Extracted From National Atlas of Kenya (2003)
3.2.1 Climate and Vegetation
Kitui County is a semi-arid area which falls within the Tana Catchment drainage basin (Republic of Kenya, 2014), with an annual rainfall and temperatures ranging
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from 400 mm to 800 mm, and 240 to 260 C, respectively. The area has a bimodal rainfall pattern, with the long rains spanning from March to May and the short rains from November to December (Nissen, 1982). In this regard, the seasonal rivers in this area experience flows during the said months and in extension for a time period not exceeding a week after the rains. On the other hand, the evaporation rates of this area range from 1800 mm to 2000 mm per annum (Munyao et al., 2004). This implies that the total annual evaporation rates exceed the total annual rainfall. As a result, the area suffers shortage of surface water, with the locals left dependent on water embedded in sand aquifers where it is protected from evaporation on the dry river channels (Munyao et al., 2004). Due to its hot and dry climate, the area is characterized by thorny drought resistant vegetation such as Acacia, which is scantly distributed. Additionally, the area develops tall grasses during the rainy season which fades out shortly after the rains.
3.2.2 Geology and Drainage
The dominant rocks in this area are metamorphic rocks namely biotite gneisses, leucocratic gneisses and granulite’s, all of which are of sedimentary origin (Pulfrey,
1954). These rocks have over time undergone intensive chemical and physical weathering, leading to formation of a thin crust of weathered regolith. The soil covering the area is basically red-brown sandy type, but of low fertility index due to scarcity of moisture (Mburu, 2013). This supports the growth of thorny bushes and scanty grass, a factor that makes the area to experience severe soil erosion especially when it rains.
From its general topography, the area slopes from west to East, with most rivers traversing the area owing their origin in the higher grounds in the west. Remarkably,
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most rivers traversing the area are ephemeral flows and join river Tana downstream.
Further, owing to the sandy nature of the soils covering the landscape, the area is characterised by high rate of infiltration in events of light rains, and profound amount of surface flows during high rainfal events due to presence of scanty vegetation cover (Muthomi et al., 2015)
3.2.3 Socio-economic Activities
Being a marginal area, the possibilities of man utilizing the environment for crop farming is limited. However, the dominant economic activity in this area happens to be rain-fed agriculture in its broad coverage. According to GOK (2010), the dominant economic activity in Kitui and more particularly in Mwingi is livestock farming, whereby drought resistant species of beef cattle and goats are reared. In addition, cereal crop growing such as sorghum and millet is also carried out, though on small scale basis owing to the low crop production potential of the area due to low and unreliable rainfall received in the area. Fruit farming such as orange farming is also practiced by most farmers. As depicted by the areas high poverty index (61.56%) compared to the national poverty index (45.2%), rain-fed agriculture is not a well rewarding enterprise in Kitui (GOK, 2010). Other than rain-fed agriculture which has been depicted to earn the residents a mean amount of income, sand mining from the seasonal river beds happen to be a popular undertaking.
According to Republic of Kenya (2013), sand mining fetches appreciable income to those involved in it. However, the study remarks that it is associated with local conflicts between the sand miners and the members of the community as it interferes with their sources of water which is impounded on the sand reserves and which they largely depend on during the dry season.
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3.3 Target Population A sampling frame for the target population was obtained from Mwingi sand mining
Co-Operative Society at Mwingi Town and comprised 1550 stakeholders in the sand mining industry. The target population comprised three strata namely the sand miners, the households and the land owners. On the other hand the study targeted all the five sand mining sites along river Tyaa namely Kyome, Tumila, Kilisasi,
Kanginga and Kiomo.
3.4 Sampling Techniques
Sampling for this study was done at two levels namely the river channel and the target population. Sampling at the two levels was necessary since this study involved examining both the physical aspects of the river as well as the socio- economic effects of sand mining to the inhabitants of river Tyaa sub-catchment.
3.4.1 Sampling of River Sites
This study employed purposive sampling technique to select river Tyaa. This was informed by the existing literature and the researcher’s expert knowledge based on the fact that unregulated sand mining activities were taking place there and thus would provide a good representative information on sand mining. Five sand mining sites along river Tyaa were identified. Random sampling was done on the five sites thus arriving at one site namely Kanginga which acted as a representative site.
Figure 3.2 shows a section of river Tyaa and the sand mining sites.
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Figure 3. 2: A Section of River Tyaa Showing the Active Sand Mining Sites
Source: Author (2018).
The selected site (Kanginga) measured 500 m and additional 500 m was also selected up and downstream of the active site to act as control sites (Figure 3.3). The adjacency of the sites made it possible to obtain data on parameters with similar characteristics thus enabling comparison between the active and control sites, a concept that was used by Brown et al. (1998) to determine the morphometric response of the river channel to sand mining.
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Figure 3. 3: Active Sand Mining Site and the Control Sites
Source: Author (2018)
After identifying the site, systematic sampling technique was applied to collect data on variables of interest as stated in table 3.2, at intervals of 10 meters over a stretch of 1500 m along the river channel thus enabling adequate coverage and detailed study of the river channel as illustrated on Figure 3.3. River Tyaa is at the middle stage as suggested by the numerous numbers of tributaries and therefore a width of
50 metres to either side of the channel was considered since sand mining activities extended up to that extent. Figure 3.4 shows a summary of the river sampling techniques employed in this study.
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Figure 3. 4: Summary of The River Sampling Techniques
Source: Author (2018)
On the other hand, sampling was done on the study population in order to come up with a suitable sample size that is all representative.
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3.4.2 Sampling of the Study Population
The study population was convened from river Tyaa sub-catchment at large. A sampling frame comprising 1550 members involved in sand miing activities was obtained From Mwingi Sand Mining Cooperative. Stratified sampling technique was employed to select a sample size from the target population. The use of stratified sampling technique was neccesary because the target population comprised a number of heterogenous sub-populations, whereby the elements within each strata were relatively homogenous compared to the population as a whole. In this regard, the target population comprised three stratas namely sand miners, land owners and the households whose members undertake sand mining upto a distance not exceeding five kilometres in the affeced areas.
To be consindered as a sand miner, one had to be the head of the family and engaging in sand mining activity. The consideration made for stratification as a household was that one engaging in sand mining had to be a memebr of the family but not a household head. Further, the study characterized the land owners as the members of the community whose land boarders river Tyaa. These people claimed ownership of the the sand resource on such reaches of the river despite such being a public property, and thus were consindered imporant for this study. From that criteria, the study got 500 and miners, 50 land owners and 1000 households. This was consindered as an adequate representative sample size since it comrised of atleast 10% of the target population as reccommended by Mugenda and Mugenda
(2003) (see table 3.1).
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Table 3. 1: Summary of the Sample Size
Sub-Population Target Population Sample Size Households 1000 100 Sand Miners 500 50 Land Owners 50 5 Total 1550 155 Source: Author, 2018. 3.5 Research Instruments
Being a mixed methods research, the study used different types of data collection tools. These included the use of questionnaires to get data on socio-economic effects of sand mining in the study area (Appendix 1). On the other hand, the study used a hand held GPS, Abney level and a tape measure on the river section selected in order to obtain data on some physical variables.
3.6 Pilot Study
In order to evaluate the functionality and suitability of the questionnaires considered for this study, a pilot study was conducted. A team of two trained research assistants was used to help in the process of data collection from respondents using questionnaires. The piloting exercise helped to readjust the questionnaires to enhance their effectiveness and ease of use in the field for the actual data collection exercise. For purposes of avoiding repetitive administering of questionnaires, the respondents considered in the pilot study were exempted in the actual data collection.
3.7 Data Collection
Data collection was done using both quantitative and qualitative methods. These included physical measurements, administering questionnaires to the selected respondents and desktop survey. For objective one which was to establish the
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extent of sand mining in river Tyaa, data on the spatial extent of sand mining was collected using a GPS to give the actual geographic references for locations or sites with active sand mining activities along the river channel. Data on temporal extent of sand mining was obtained from the respondents using a structured questionnaire and also from records at Mwingi Sand Mining Cooperative. Further, the quantity of sand mined from the respective sites for the number of years the activity had been documented was obtained from secondary sources at the Mwingi Sand Mining
Cooperative Society.
In objective 2 for establishing the morphological factors influencing sand abundance in river Tyaa, data on the independent variables influencing sand abundance as stated in table 3.2 was obtained through measuring and application of set rules of logic (Appendix 2, i-v). This was undertaken fortnightly at intervals of
10 metres over the 1.5 km river stretch unaffected by sand mining in the whole stretch of the selected site for a duration of two months (See Figure 3.3). This generated a dataset with 100 entries. According to Starkweather and Moske (2011), this is a dataset with adequate entries as needed when using the logistic regression analysis in order to enhance accuracy while determining the categorical placements of the entries.
Data on bank position of the sites along the river channel was obtained through observation while that on the slope angles of the river channel were obtained through physical measurements by use of an Abney Level. Data on vegetation cover, weathering status/geology and erosion status was acquired through use of observation and application of the set rules of logic (Appendix 2,i-v). For the river
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channels width and depth aspects, physical measurements using a tape measure were conducted.
For objective three which is examining the effects of sand mining on the morphology of river Tyaa, data on the variables such as river channels depth and width was obtained through physical measurements by use of a tape measure while the channel slope angles was obtained through measuring by use of an Abney Level.
Measurements were undertaken fortnightly just after the rains for a duration of two months. This enabled measurements to be taken when sand reserves have been replenished by the seasonal stream flow, and later monitor the alterations inflicted by mining at the said time intervals for the whole period of time.
Finally on objective four, data on socio-economic effects of sand mining was obtained from field survey using structured questionnaires administered to the sand miners, land owners and the house heads for the selected households (Appendix 1).
Variables such as Community conflicts, School drop-out rates, Prostitution, Drug and substance abuse, Insecurity, Family unit breakdown and Sand mining economic significance on households were considered in the questionnaire.
3.8 Data Analysis and Presentation
Both quantitative and qualitative methods were used in data analysis, presentation, and interpretation of the results. The latter was used to make inferences into the relationships existing between the dependent and independent variables in this study. In determining the extent of sand mining along river Tyaa, the GPS generated data was downloaded into ArcMap GIS environment for further processing and mapping to provide spatial and/ or location-based information for characteristics of sand mining sites. Data on temporal and quantity extents of sand mined in river
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Tyaa was analysed using percentages and presented using line graphs. A chi-square test was conducted on data on quantity of sand mining to help point out whether significant sand mining was taking place. The inferences made from these insights were useful tools in recommending the necessary measures to address issues regarding the extent of sand mining along river Tyaa.
In establishing the morphological factors influencing sand abundance along river
Tyaa (dependent variable), data on variables namely the bank position, slope angles of the channel, vegetation cover, weathering status/geology, erosion status and the river channels width and depth were imported into R-statistical software environment and the binary logistic regression analysis was carried out. The marginal effects and p-values generated helped to point out the significant morphological variables influencing abundance of sand in the river channel.
3.8.1 Binary Logistic Regression
To establish the morphological factors influencing abundance of sand along river
Tyaa, a binary logistic regression analysis was applied. This predicts the presence or absence of a characteristic or outcome based on values of a set of predictor variables. This procedure is similar to linear regression but is suited to models in which the dependent variable is dichotomous (Tranmer & Elliot, 2008). In this study, sand abundance status is dichotomous in that a point along the river may be having either high (1) or low (0) sand abundance status as predicted by the independent variables stated above. Equation 3.1 shows a binary logistic regression model.
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……………………… ………….….……Equation 3.1
Whereby “e” is the exponential function and the “ß0 + ß 1X1” is the familiar equation for the regression line.
3.8.2 Multiple Logistic Regression
In examining the effect of sand mining on the morphology of river Tyaa, multiple logistic regression analysis was carried out using R- statistical software. This classified subjects based on values of a set of predictor variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories (Starkweather & Moske,
2011). See Equation 3.2 showing the multinomial logistic model.
…………….…….….……Equation 3.2
Whereby, Y is the river morphology, e is the exponential value, is the intercept value in the normal linear regression model, ß1 is the gradient for an independent variable X1 while ßnxn represents the gradient values multiplied by the respective independent variables considered in this case, up to the last value.
A data set with dependent variable namely the river morphology and the independent variables namely the altitudes, sand volume leaving the site fortnightly for two months duration, the river channels depth and width, and channel slope angles was used. All these were imported into R-statistical software environment and multiple logistic regression analysis employed. The results from the analysis clustered the effects of the independent variables to the river morphology into three
37
categories. These included highly modified, moderately modified and normal, denoted as 1, 2 and 3 respectively. The multiple logistic regression provided information on whether there was a change in river channel morphology and also showed the magnitude of this change. This ability was important as it provided information which was used in devising a mechanism to recommend on safe sand mining practices.
In establishing the socio-economic effects of sand mining (objective four), descriptive statistics was used to analyse the data to produce percentages of the respective variables of interest. These were further interpreted to express the socio- economic effects of sand mining to the community living along river Tyaa. The null hypothesis on socio-economic data was tested using Chi-Square test. The nature of the data prompted use of Chi-Square test which is inferential statistics because it provided a relationship between two variables. It was preferred because it enabled easy comparison of the observed and the expected frequencies in order to show their discrepancies. Table 3.2 gives a summary of the methodology.
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Table 3. 2: Summary of the Methodology
Objectives Variables Data Collection Data Analysis To determine Coordinates of sand mining sites - GPS mapping - Used GIS the extent of along river Tyaa. techniques - Administering sand mining The number of years sand mining questionnaires. - Use of along the river has taken place. percentages and Tyaa channel -Secondary data line-graphs. Total sand quantity of sand mined from Mwingi per year for 10 years. sand mining - Chi-square test cooperative. used to test hypotheses. To establish the Dependent variable: -Field - Binary Logistic Sand abundance status. observation and regression Morphological use of logic. analysis. factors Independent Variables: Bank influencing sand position, slope angles of the Physical abundance in channel, vegetation cover, measurements River Tyaa weathering status/geology, using: channel. erosion status, and river channels -Tape measure. width and depth. -Abney level. To examine the Dependent Variable: -Physical Used Multiple effect of sand River morphology (channels measurement logistic regression mining to the depth, width and slope angles) using Tape analysis. morphology of measure and Independent variables: -Description and river Tyaa. Abney level. interpretation. Sand volume leaving the site per -Taking day for a two months duration. photographs To establish the Community conflicts Administering Use of socio-economic structured percentages. School drop-out rates effects of sand questionnaires. Chi-square test mining in river Prostitution used to test Tyaa. Drug and substance abuse hypotheses. Insecurity Family unit breakdown Water resource availability. Sand mining economic significance on households. Source: Author, 2020
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Table 3. 2: Summary of the Methodology CHAPTER FOUR: RESULTS AND DISCUSSIONS
4.1 Introduction
This chapter presents results of the study according to the data collected from the
field and analyzed using various methods. The results are presented starting with the
background information of the respondents and sand mining activity in the study
area. The results are also presented and discussed as per the study objectives in order
to draw the study conclusions.
4.2 Demographics
This section provides results on the general characteristics of the respondents. These
include aspects such as age, gender, length of stay in the study area, educational
level and occupation.
4.2.1 Age of the Respondents
Respondents aged 18 years and above were considered for this study. This was
arrived at because such people are adults and are well informed about sand mining
activities, thus ensuring the reliability of the information that they provide.
However, the questionnaire was structured in such a way that it was able to capture
respondents below age of 18 years, primarily to establish whether sand mining had
involved children who otherwise ought to be in school. Further, the questionnaire
categorized the respondents into three main classes which include young adults (19-
35 years), middle aged (36-59 years) and the aged (60 years and above).
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Table 4. 1: Age of the respondents
Age in Years Frequency (n=155) Percentage (%) 18 and Below 0 0 19-35 99 64 36-59 56 36 Above 60 0 0 Total 155 100 Source: Author, 2018
In table 4.1, most of the respondents were between ages 19-35 (64%). This implies that majority of the sand miners in the study area are youths. These finding agrees with Ilke et al., (2012) that people’s age has a significant influence on their job selection. The youths and the middle aged expressed different interests in the sand mining activity. For instance, most of the youths expressed satisfaction from the sand mining occupation they pursued contrary to the middle aged respondents, most of whom expressed dissatisfaction and lack of better alternative jobs to engage in for an income. A higher percentage of youth involvement in sand mining can be attributed to the rising levels of unemployment in the country currently standing at
40%. Additionally, it may also be attributed to its high economic advantage over other economic activities in the area such as farming. This may help check possibility of increase in crime rate in the study area since the unemployed youths are able to generate some income hence being self-reliant.
4.2.2 Gender of the Respondents
The number of male respondents (82%) was noted to be more than that of female respondents (18%) (Figure 4.1).
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Figure 4. 1: Gender of the respondents.
Source: Field data, 2018
The results in figure 4.1 showed that sand mining is a male dominated activity. This could be attributed to the strenuous nature of the work involved which is more suited to masculine gender. This was also coupled with the cultural perceptions of the respondents that attributed sand mining activity to the male gender. It was noted that females featuring in this activity were involved in peripheral roles such as supplying food and water to the sand miners and loaders. Despite their low involvement, females in the study area were highly affected by sand mining activities since it made them walk for longer distances (8km) in search of water and wood fuel hence wasting a lot of time which they ought to engage in other income generating activities as was established by this study. This was because the river beds where sand mining is carried out stored no water due to depletion of the sand reserves which act as aquifers for water during the dry season, and that most of the riparian vegetation had been destroyed.
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4.2.3 The Duration of Stay in the Study Area
From the responses obtained from the questionnaires, 69% of the respondents have stayed in the study area for over 20 years, 10% for over 15 years, 12% for over 10 years, 6% for 5 years and 3% for a period less than five years (Figure 4.2)
Figure 4. 2: Duration of stay of respondents in the study area
Source: Field Data, 2018
The respondents’ duration of stay in the study area had influenced the respondents their level of participation in sand mining activities. As shown in Figure 4.2, participation of the respondents in sand mining activity was seen to be higher for the members who had stayed for a long duration in the study area (69%). The high involvement of the respondents who had stayed in the study area for a long duration may be attributed to economic viability of sand mining (58%) compared to other forms of livelihoods such as agriculture that are practiced in the area. The limited participation of respondents who have stayed in the study area for a short duration may be due to low relocation rate of people from other places into the study area due
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to limited economic options in the area (9%). Lastly, ease of accessibility and affordability of education in Kenya today may have contributed in lowering the number of young people (who have spent short durations in the study area) engaging in the sand mining activity since they are able to secure jobs in other sectors
(Gitonga, 2017).
4.2.4 Education Level of the Respondents
It was noted from the study that there were no degree and diploma holders who were involved in sand mining activities. However, 21% of the respondents were identified as O-level holders, 48% were primary school certificate holders while 31% were people who dropped out of the primary school at different levels before sitting for the Kenya National Certificate of Primary Education (KCPE) (Figure 4.3). As deduced from the results, sand mining had attracted people with low or no academic qualifications. This may be attributed to the fact that sand mining does not require any specialized skills, a factor that has attracted many people with low or no education qualifications. Actually, the only requirements for one to become a sand miner in the study area was a legal age of above 18 years and physical strength to dig and load sand on the trucks. Further, high levels of unemployment in the formal sectors characterizing the respondents with low or no academic qualifications may also be attributed to high involvement of respondents with low academic levels in sand mining activities as the only other viable economic activity in the study area.
This is because employment in the formal sectors demand higher levels of education and specialized skills.
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Figure 4. 3: Level of education of the respondents
Source: Field Data, 2018
4.2.5 Current Occupation of the Respondents
The study showed that sand mining in the study area has attracted three main categories of people, namely farmers (35%), people in business (16%) and another group that wholly depend on sand mining (49%) for income (Figure 4.4).
Professionals were noted not to engage in sand mining activity. This may be attributed to their high employability in other sectors since they possess specialized skills which are valuable in the formal jobs. On the other hand, respondents engaged in business and farming perceived sand mining as an additional source of income, particularly farmers who associated farming to low income which is not sufficient to cater for their families. Additionally, some farmers (46%) and business people
(57%) claimed that they could not cope with the hard nature of the work involved in sand mining activities hence their low levels of participation. On the other hand,
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lack of required skills for formal employment and sufficient capital to venture into business made many respondents (49%), to opt for sand mining as their main source of income.
Figure 4. 4: Current occupation of the respondents
Source: Field Data, 2018 4.3 Background Information of Sand Mining in the Study Area
This section provides insights on the background status of the sand mining activities in the study area. Regarding this, the level of involvement of the local area members, duration over which sand mining has taken place, licensing of sand miners and land ownership, leasing criteria and sand mining agreement as well as the destination of the sand mined were considered. This information is key to this study as it enhances better understanding of sand mining activities in the study area thus making it easier to relate some of the challenges facing the activity in the process of seeking workable solutions.
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4.3.1 Involvement Level of Members of the Local Area in Sand Mining
The respondents were highly divided on the extent of involvement of the local area members in sand mining activities. For instance, 24% of the respondents felt that members of the local area were least involved in the activity, 56% felt that they were fairly involved, 15% felt that they were moderately involved while 5% felt that members of the local area were highly involved in sand mining activities (Figure
4.5). Men were mainly involved in brokering, selling and loading sand in trucks while women were involved in peripheral roles such as hawking snacks and water.
Figure 4. 5: Level of involvement of members of the local area of study
Source: Field Data, 2018
From the results in figure 4.5, it is clear that sand mining had to a great extent involved the members of the local area. This could be attributed to their close proximity to the river, a factor that makes them to operate comfortably while commuting from their homes. Additionally, most people from the local area of this study may have opted to engage in sand mining due to its economic viability
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compared to other economic activities practiced in the area such as farming whose returns are remarkably low. However, 24% of the respondents held a contrary opinion. This implied that a significant number of workers in the sand mining activity from other regions pose some stiff competition over job opportunities to the members of the local area, a factor that may partly help explain a probable cause of some sand mining related conflicts in the study area.
4.3.2 Duration of Sand Mining
The study established that sand mining was taking place in river Tyaa, with 94% of the respondents acknowledging existence of the activity. However, 10% of the respondents said that sand mining had taken place for 10 years, 25% said it had taken place for 20 years while 65% said a duration of over 30 years (Figure 4.6).
Figure 4. 6: Sand mining duration in river Tyaa
Source: Field Data, 2018
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It was also noted that sand mining had increased both in magnitude and frequency over time, with the highest levels of exploitation witnessed at present time (Table
4.2). As noted by Mwaura (2013), this trend is shaped up by the economic development of the country, a factor that is reflected by tremendous growth in the building and construction industry both at the locality and at the nearby towns such as Mwingi, Thika and Nairobi. Uncontrolled exploitation of sand from the river channel for a prolonged duration as reported in figure 4.6 may serve to explain some of the adverse environmental effects facing river Tyaa channel such as depletion of the sands, loss of water impounded in the sand reserves as well as bank instability.
4.3.3 Licensing of Sand Miners and Land Ownership
The study established that 96% of the respondents were not aware of any licensing body and that they were not licensed to carry out sand mining. The study further revealed that a majority of the riverine land in the study area was owned by individuals (94%). However, granting of permission for sand mining was determined by local authorities (Chiefs and Mwingi Sand Mining Cooperative society) in collaboration with the land owners. The leasing was termed as a temporary non-formal agreement between the said authorities and the different independent sand miners, basically based on agreed time durations. From these findings, it is clear that sand mining was taking place illegally.
4.3.4 Leasing Criteria and the Sand Mining Agreement
The study findings showed that 87% of the respondents were not aware of any criteria for qualifying one to obtain leasehold of the land for sand mining, while
13% were not sure of existence of such a criteria while 35% of the respondents acknowledged presence of sand mining agreement detailing how the activity is
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undertaken, 24% did not know, while 41% were not sure. The conditions set in the agreement were limited only to the time duration over which mining by the independent sand miner would take. These findings confirm that sand mining was largely taking place unregulated, a factor that may lead to environmental degradation as well as social conflicts among the people as they grab the natural resource for their own benefit.
4.3.5 Destination of the Sand Mined
From the questionnaire administered to the sand miners, the study established that the sand mined in river Tyaa was destined for Nairobi (52%), Thika (42%) and
Mwingi (6%) towns. The high percentage of sand destined outside Kitui county shows that there is rapid urbanization in Nairobi and Thika compared to Mwingi, a factor which has execrated sand mining activities in river Tyaa. These findings agree with those of Mwaura (2013) and Wambua (2015) who established that most of the sand mined in Ukambani area was destined for Nairobi and Thika towns respectively.
4.4 The Extent of Sand Mining in river Tyaa
The study sought to establish the extent of sand mining in river Tyaa by assessing the temporal, spatial, and quantity aspects of sand mining in the river.
4.4.1 Temporal Extent of Sand Mining in River Tyaa
Data obtained from Mwingi Sand Mining Cooperative Society shows that commercial sand mining in river Tyaa started way back in 1990. This was prompted by growth of Mwingi town which served as an administrative center as well as development of public facilities such as schools and hospitals in the area. However,
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data obtained from questionnaires indicated that sand mining in river Tyaa started earlier than the year 1990, with 10% citing that it started before 30 years ago, 25% citing over 20 years ago and 65% citing that sand mining activities have been ongoing over the last 10 years. Respondents further expressed that sand mining before the year 1995 was taking place in small non-commercial and undocumented basis for local consumption in brick making for house building. From the results presented, prolonged duration (30 years) of sand mining has been noted. In light of that, it is logical to infer that cumulatively, significant amount of sand have left the river Tyaa’s channel over time, a factor that may have contributed to the negative effects facing the channel such collapsing of the banks, depletion of sand reserves and loss of riparian vegetation.
4.4.2 Spatial Extent of Sand Mining in River Tyaa
Five sites where active sand mining was taking place were identified along river
Tyaa. Locational data was plotted using ArcMap GIS to show the spatial distribution of the sites namely Kyome, Tumila, Kilisasi, Kanginga, and Kiomo sites (Figure
4.7). The siting of the identified sand mining sites was influenced by the ease of accessibility as well as abundance of sand reserves along the river for mining. Ease of accesibility promotes exploitation since it eases the transportation process while sand abundance enhances large scale exploitation which in turn attracts more income. Presence of many sand mining sites along river Tyaa is an indicator that a lot of sand leaves the channel per year. The effects of that are evident in the river channel which include instability of the banks, loss of riparian vegetation as well as widening of the river channel.
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Figure 4. 7: The distribution of sand mines along river Tyaa
Source: Extracted From National Atlas of Kenya (2003) and Field Data, 2018.
4.4.3 Quantity of Sand Mined In River Tyaa Annually
Annual data obtained from Mwingi Sand Mining Society on sand quantity mined from river Tyaa was available in the records of dating back to year 2000. However, this study focused on data dating from year 2008 to 2017 as presented in Figure 4.8 since it was found to be consistent. The data presented in figure 4.8 shows that the
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quantity of sand mined has been rising over the years at an annual average increment rate of 15%. Actually, the trend line indicates that this quantity is highly likely to increase in future (Figure 4.8). This may be attributed to various reasons such as high demand for houses due to rapid population growth, urbanization and increased infrastructural developments such as roads, all of which require sand in the construction process. These findings agree with those of Mwaura (2013) that sand mining had been on the rise and exacerbated by the continued rising demand for sand in the construction industry, with the highest rates witnessed presently. The rising quantity of sand mined from river Tyaa implies that the river channel is no longer stable, and as a result the channel is prone to degradation.
Figure 4. 8: Sand mining trend from year 2008 up to 2017
(The continuous line shows the actual plot of the sand mined while the dotted line depicts the general trend of the sand mined over the years.)
Source: Mwingi sand mining cooperative society, 2018
4.4.3.1 Hypothesis Test
Upon analyzing the difference in sand quantity mined between year 2008-2012 and that of year 2013-2017, the Chi-square test results (Df = 1, χ2 = 9.00, P =0.003)
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indicate presence of significant amount of sand mining in river Tyaa (Table 4.2). As a result, the study hypothesis that there is no significant sand mining taking place in river Tyaa channel was rejected.
Table 4. 2: Chi-Square Test on Quantity of Sand Mining in River Tyaa for
2008-2012 and 2013-2017
SN. Years Quantity Percentage Rate of % Df Chi- P- (tons) increase Mean Sq Value (%) 1 2008 720000 5 10 2 2009 790000 6 33 3 2010 1050000 7 1 35 4 2011 1065000 7 34
5 2012 1430000 10 6 6 2013 1520000 11 6 1 9.00 0.003
7 2014 1610000 11 12 8 2018 1800000 13 15 65 9 2016 2070000 15 21 10 2017 2500000 15 --- 11 Total 14215000 100 Annual 1,421,500 15 average
Source: Mwingi Sand Mining Cooperative Society, 2018
4.5 Morphological Factors Influencing Abundance of Sand in River Tyaa
The study sought to establish the morphological factors influencing abundance of sand in river Tyaa’s channel, by examining data on variables such as the river bank position, channel width, depth, slope angles, vegetation cover status, weathering status and erosion status from Kangiga site which served as a representative site. A
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binary logistic regression model was employed to determine the influence of the afore-stated variables to sand abundance in the river channel. Data was imported into R-Statistical software’s environment whereby it was divided into model training data (70%) and model testing data (30%) (Kim et al., 2018). Training data was used to develop a Binary Logistic Regression model as well as optimizing its accuracy, while the testing data was used to test the accuracy of the model.
The model testing results arrived at indicated that the model was able to predict the placements of the data with an accuracy of 85%. In addition, the model gave out marginal effects and P-values which showed the level of significance of each variable in influencing abundance of sand in river Tyaa’s channel. The results pointed out that the river bank position, channel width, depth and slope angles were the significant variables influencing sand abundance in the river channel. Table 4.3 shows the logistic regression outputs for individual variables as predicted by the model.
Table 4. 3: The Binary Logistic Regression Model Output
Variables Marginal Effects Std. Err. Z P>|z| Bank position -0.749897 0.065864 -11.386 2.2e-16 *** Slope Angles -0.234497 0.050459 -4.6473 3.363e-06 *** Width 0.146518 3.9948 0.036677 6.474e-05 *** Depth -1.44542 0.29134 -4.9613 7.001e-07 *** Vegetation Status -0.021309 0.112042 -0.1902 0.8492 Erosion Status -0.083333 0.099355 -0.8387 0.4016 Weathering Status 0.076923 0.099510 0.773 0.4395 Significance Codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Source: Field Data, 2018.
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4.5.1 Effect of River Bank Position on Sand Abundance
The results showed that river bank position had actively contributed to abundance of sand in a river channel as seen from the marginal effects and p-values of river bank position in table 4.3 respectively. This implies that sand quantity increased by 74.9% as one moved from concave to convex bank, which is significant as indicated by the respective p-value 2.2e-16. As a result, the convex banks have more sand compared to the concave banks. The finding of this study agrees with those of Hugget (2007) who established that the convex banks were characterized by deposition while the concave banks were characterized by active erosion. In the same vein, the findings agree with those of Cameron & Baucher (2014) who expressed that the concave banks experience greater hydraulic impact of the river water current, a factor that weakens the river bank thus promoting removal of materials unlike in the convex banks.
4.5.2 Role of Slope Angles on Sand Abundance
The results indicated that slope angles were active contributors of sand abundance on the river channel as seen from the marginal effects and p-values in table 4.3 respectively. This means that a unit reduction in slope angle led to 23.44% increase abundance of sand, which is significant as indicated by the respective p-value
3.363e-06. The convex banks were established to have lower slope angles and high sand abundance compared to the concave banks. According to Cameron & Baucher
(2014), low river channel angles characterizing the convex banks encourage deposition of sand since it facilitates slow movement of water. On the other hand,
Varouchakis et al., (2016) pointed out that concave banks are characterized by
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active erosion, a factor that discourages deposition and accumulation of sand since the slope angles on such banks are high.
4.5.3 River Channel Width and Sand Abundance
The results indicated that slope angles were active contributors of sand abundance on the river channel as seen from the marginal effects and p-values in table 4.3 respectively. As deduced from marginal effects and p-values in table 4.3, a unit increase in river channel width led to 14.65% increase in sand abundance, which is significant as pointed out by the respective p-values 6.474e-05. This implies that sand abundance increases with increase in width of a river channel. The study established that an increase in channel width causes spreading out of the river water thus compromising its speed hence the load carrying ability. Reduced speed of the river water leads to deposition at wider sections of the river channel as opposed to the narrow sections of the channel which are often characterized by high speed of water flow which in turn promotes erosion as opposed to deposition. Elliott (2006) arrived at similar results in a study on sand mining in a perennial river.
4.5.4 River Channel Depth and Sand Abundance
The channel depth was established to influence sand abundance along the river channel. Regarding this, the marginal effects and p-values in table 4.3 indicate that a unit decrease in the river channel depth leads to 144.54% increase in sand abundance, which is significant as indicated by the respective p-value 7.001e-07.
Going by this, it is evident that shallower sections of the river channel are characterized by high sand deposition and accumulation. This agrees with findings by Varouchakis et al, (2016) that narrow and deep sections of the river channel are
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characterized by high speed of the river current since they act as constrictions, a factor that promotes erosion processes as opposed to deposition. Increase in depth of a river channel is usually coupled with increasing slope angle, a factor that discourages deposition. Additionally, sections of the river channel characterized by great depths experience more erosion since they are characterized by softer rocks, and this discourages sand deposition process in such sections. On the other hand, active deposition of sands on a river channel leads to reduced depth and slope angles, an aspect that promotes presence of high sand abundance.
The marginal effects (ME) and p-values obtained for some variables such as the river channel width (ME=0.146518, P= 6.474e-05), depth (ME=-1.44542, P=7.001e-
07), slope angle (ME=-0.234497, P=3.363e-06), and bank position (ME= -0.749897,
P=2.2e-16) indicate that there were some variables that significantly influenced sand abundance in the river Tyaa channel. This informed the rejection of the null hypothesis and adoption of the alternative hypothesis.
4.6 Effects of sand Mining on the Morphology of the River Channel
The study sought to establish the effect of sand mining to the river morphology.
Data on variables such as the sand mined, river channel width, depth and slope angles from the control and active sites was imported into R environment whereby multiple logistic regression technique was applied to analyze it. The data was divided into model training (70%) and testing portions (30%), whereby the training data was used to develop the model as well as optimizing its accuracy. The model was able to compare data from the control and active sites while taking low as the reference category. This enabled the model to generate an output indicating whether
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sand mining activity had either caused modification of the channel morphology or not. The test results using the testing data showed that the model was able to predict the categorical placements of the data variables with an accuracy of 87%.
4.6.1 Sand Mining and the River Channel Width
Sand mining was established to significantly contribute to the increase in the river channel width, as seen from the marginal effects and p-value in table 4.4.
Table 4. 4: Logistic Regression Model Output Effect of Sand Mining on River
Channel Depth
Factor AME SE |Z| |P| Sand mined on Width 0.1192 1.516870 -1.7850840 9.959148e-03***
Significance Codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: Field Data, 2018
As deduced from the marginal effects, a unit increase in sand mined led to 11.92% increase in the river channel width as compared to the control sites, an increase which is significant as indicated by the p-value (9.959148e-03). The study finding agrees with those of Muiruri & Amimo (2017) who established that uncontrolled sand mining leads to increased width of the river channel especially if carried out at higher levels than the natural replenishment. In this case, sand replenishment rates are low since the river channel only gets water during the rainy season. According to results in this study, sand mining has also caused steepening and collapsing of the channel banks in the active mining sites. This has in turn caused loss of some riparian vegetation along such banks, a factor that affects the environment adversely as shown in plate 4.1. This agrees with a study by Nguru (2007) which established that high rates of sand mining had led to loss of riparian vegetation as one of the
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negative environmental effects. Therefore, it is logical to infer that sand mining rates in river Tyaa could be taking place at a higher rate than the natural replenishment rates since positive geomorphic feedback response of the channel is evident.
26.02.2018
Plate 4. 1: Effect of sand mining on the river bank stability and the riparian vegetation.
Source: Field Data (Author)
4.6.2 Contribution of Sand Mining to the River Channel Depth
The results indicated that sand mining had a significant influence on the river channel depth.
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Table 4. 5: Logistic Regression Output on Influence of Sand Mining on the
River Channel Depth
Factor AME SE |Z| |P|
Sand mined on Depth 0.3088 1.998685 -2.82307997 7.193669e-02***
Significance Codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Source: Field Data, 2018.
The marginal effects in table 4.5 shows that a unit increase in sand mined led to
30.88% increase in in channel’s depth compared to the control sites. This increase was significant as suggested by the p-values (7.193669e-02). Other studies on sand mining by Kondolf (1997) and Amponsah-Dacosta & Mathada (2017) also indicate that uncontrolled sand mining results in increased depth of the channel, a factor that comes about due to depletion of sand reserves. Those studies agree with this study, which established that sand mining had caused increased depth of the river channel
(Plate 4.2). According to Nabegu (2014), change in river channel morphology comes about in cases where sand mining rates exceed the replenishment rate through natural means. Following that, it is logical to infer that sand mining in river Tyaa is being undertaken at high rates which are not sustainable as confirmed by the positive geomorphic feedback response of the river channel.
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26.02.2018
Plate 4. 2: Effect of sand mining to the river channel depth and bank slope agle
Source: Field Data (Author)
4.6.3 Effect of Sand Mining on River Channel Slope Angle
As deduced from the marginal effects of sand mined on channel slope angle in table
4.6, sand mining had caused a significant increase in channel slope angle.
Table 4. 6: Logistic Regression Model Output of Sand Mining on the River
Channel Slope Angles
Factor AME SE |Z| |P| Sand mined on Slope Angle 0.2894 1.789966 -0.2283078 9.378761e-03*** Significance Codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Source: Field Data, 2018.
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A unit increase in sand mined led to 28.94 % increase in the river channel slope angles compared to slope angles of the control sections, which is significant as pointed by the p-value (9.378761e-03). This implies that sand mining has contributed to increased channel slope angle, a factor that is associated with adverse environmental effect such as accelerated stream flow resulting to channel erosion.
That agrees with Kondolf (1997) who established that high rates of sand mining had led to increased slope angle of the channel, a factor that promotes increased instability of the channel. The study indicated that sand mining zones were characterized by unstable banks, with some collapsing thus leading to loss of riparian vegetation (Plate 4.1). High channel slope angle led to accelerated erosion, a factor that promoted positive feedback process of the river system.
The test results have indicated that sand mining have significantly influenced the channel morphology through causing increased channel width (AME=0.1192, P =
9.959148e-03), depth (AME=0.3088, P=7.193669e-02) and slope angle (AME=
0.2894, P=9.378761e-03) as informed by respective marginal effects and p-values.
Following that, the study rejected the null hypothesis thus adopting the alternative hypothesis. The fact that the said morphological parameters have been modified at the active mining sites by sand mining in river Tyaa implies that sand mining is taking place at high rates which are unsustainable. This agrees with findings by
Ashraf et al., (2010) who established that high rates of sand mining brings about negative effects to the river channel such as modified river morphology.
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4.7 Socio-economic effects of sand mining in river Tyaa
This section have presented and discussed the social and economic effects of sand mining respectively to the respondents and community living in the study area.
4.7.1 Social Effects of Sand Mining
The study established that sand mining had caused both positive and negative social implications. For instance, 76% of the respondents associated sand mining with negative effects while 24% associated it with positive social effects. A hypothesis test for objective four showed that sand mining had caused significant negative social effects in the area (Df = 3, χ2 = 27.04, P =0.000), thus the rejection of the null hypothesis (Table 4.7).
Table 4. 7: Chi-Square test results on social effects of sand mining
Frequency Percentage Df Chi-Sq P-Value Positive 37 24
Negative 118 76 Total 155 100 1 42.33 0.000
Source: Field Data, 2018
4.7.1.1 Sand Mining and Community Conflicts
When the respondents were asked about the effects of sand mining on community conflicts, 49% said they strongly agreed that sand mining spurred conflicts, 42% agreed while 9% were not sure (Table 4.7). The respondents further said that the conflicts were between the sand miners and the local community. Some of the underlying issues highlighted were destruction of riparian vegetation (83%) and drying up of water holes sunk on the dry river beds experiencing sand mining (65%) thus forcing the locals to travel for long distances in search of water. Secondly, 48%
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of locals felt that only a small percentage of their people benefited from the activity due to the continued influx of the non-locals in the sand mining activity, who ended up taking their jobs. Further, unequal sharing of the proceeds from sand mining activities was also highlighted as a cause of sand-mining related conflicts (52%), whereby some people earned more than others from undertaking the same tasks.
Table 4. 8: Social effects of sand mining
(SA- Strongly Agree, A-Agree, NS- Not sure, D- Disagree, SD- Strongly Disagree) S SA % A % NS % D % SD % N 1 Community 76 49 65 42 14 9 0 0 0 0 Conflicts 2 School Drop Out 0 0 19 12 26 17 75 48 42 27 3 Family Break-Ups 0 0 12 8 65 42 52 34 25 16 4 Prostitution 16 10 70 45 21 14 25 15 23 16 5 Drug Abuse 28 18 71 46 25 16 19 12 12 8 6 Insecurity 0 0 19 12 25 16 71 46 40 26
Source: Field Data, 2018
4.7.1.2 Effects of Sand Mining on Schooling
The study showed that sand mining had affected schooling in the area, with 12% of the respondents attributing it to school drop-out rates, 17% were not sure, 48% disagreed while 27% strongly disagreed (Table 4.8). These findings differs with those of Nthambi & Orodho (2015) who established that sand mining activities in
Machakos County had caused high school dropout rates. The reduced school drop- out rates may be attributed to the strict regulations by the stakeholders in the sand mining activities, whereby school-going students are discouraged from engaging in the activity. Further, people involved in sand mining are able to support educational
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demands of their children either from direct income or proceeds of investments made from income obtained from sand mining. Additionally, there is increased value attachment by parents to education of their children, and thus they have become more assertive, not forgetting their appreciation to the free primary and day secondary education which has relieved them of the burden of extra educational expenses. Increased presence of various NGO such as Trocaire and World Vision who have funded projects aimed at improving livelihoods for the people living in the area has also enlightened the community on how to practice profitable agriculture in the prevailing semi-arid conditions. Such knowledge have enabled people to realize improved income from their farms thus equiping them with a relativeley reliable economic option. Presence of such income was estabished to be a factor contributing positively to low rates of school drop-out cases. This factor has discouraged school going children to engage in sand mining since parents are abe to meet their basic requirements unlike the case in earlier years as reported by Nthambi & Orodho
(2015).
4.7.1.3 Sand Mining and the Stability of the Family Unit
The study established that sand mining had affected family unit negatively as reported by 8% of the respondents. However, 42% of the respondents were not sure,
34% disagreed while 16% strongly disagreed (Table 4.8). Following that, the study did not establish a direct association between sand mining and family unit breakdown, since most respondents (55%) agreed that disfunctional family units were due to multiple causes, which essentially affect both the ones involved in sand mining as well as those not involved in the activity. However, 8% of the respondents acknowledged that drug and substance abuse as well as prostitution (12%) that
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characterize some sections of the sand miners has posed a great challenge to the family unit and a proven cause of family break-ups. Despite that, the study noted that sand mining had contributed to strengthening of family unit as reported by 28% of the respondents through enabling provision of basic necessities by the sand miners.
4.7.1.4 Effect of Sand Mining on Prostitution
On prostitution, 10% of the respondents strongly agreed that sand mining has significantly contributed to acts of prostitution in the area, while 45% agreed and
14% were not sure. On the other hand, 15% disagreed, while 16% of the respondents strongly disagreed (Table 4.8). The study established that people who are engaged in sand mining earn a higher net income compared to the non-sand mining population.
The presence of such an improved economic status against a high poverty index averaging 61% in the area GOK (2010), were identified as the key drivers of the increased prostitution in the area. The vice was mostly reported to take place in bars and in lodgings in Mwingi town. This study finding agree with those of Mburu
(2013), in a study conducted in Yatta sub-catchment in Kitui County, Kenya.
4.7.1.5 Association of Sand Mining with Drug Abuse
The study established a high level of assocation between sand mining and drug abuse. As depicted in Table 4.8, 18% of the respondents strongly agreed that sand mining had significantly contributed to drug abuse by sand miners, 18% agreed while 16% were not sure. The study further revealed that 12% of the respondents disagreed that sand mining had significantly contributed to drug abuse, while 8% strongly disagreed. Some of the drugs that were prominently mentioned in equal measure include Miraa, alcohol and bhang. The high attribution of sand mining to
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drug abuse may be explained variously. For instance, the improved income resulting from sand mining had enabled most sand miners to afford drugs and sustain the habit. Additionlly, sand mining activity was established to be a high energy demanding job, and some of the respondents urgued that Miraa and Bhangi helped them to keep alert and energetic especially during working hours. The study findings are similar with other studies on sand mining, such as that of Muiruri & Amimo
(2017) who conducted a study in Kivou sub-catchment in Mwingi area, and
Nthambi & Orodho (2015).
4.7.1.6 Sand Mining and Security in the Study Area
The study established that sand mining had not contributed much to insecurity in the study area, with only 12% of the respondents agreeing that sand mining had contribted to increased insecurity in the area, 16% said they were not sure, 46% of the respondents disagreed with the statement while 26% of the respondents strongly disagreed with the statement (Table 4.8). The insecurity associated with sand mining may be as a result of increased drug abuse in the area, esspecially the high bhang consumption which make people violent and irrational. Further, it may be attributed to the increasing poverty levels by some of the sand miners who are hooked into drug abuse during times when sand mining jobs are not available, or when their physical strength has been depleted due to usage of some drugs such as alcohol, yet they need to sustain the behaviour. Due to the increased acts of promiscuity that the study has established in the sand mining activities, some of the families have been affected by domestic violence which is a form of insecurity to the affected, and in some instances leading to divorve.
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4.7.2 The Economic Significance of Sand Mining
The economic effects of sand mining considered matters of livelihoods, developments, jobs, and health. Overall, 87% of the respondents attributed sand mining to positive economic effects, 6% stated that it had no impact while 7% were not sure (Table 4.8). Chi-square test results on hypothesis five indicated that sand mining had caused significant positive economic effects (Df = 3, χ2 = 129.62, P =
0.000) (Table 4.9). As a result, this led to rejection of the null hypotheses and adoption of the alternative hypotheses. This implies that sand mining had caused more advantages to majority of the respondents thus empowering them economically.
Table 4. 9: Economic effects of sand mining
Number Percentage Df Chi-SQ P-Value Positive 135 87
No Effect 9 6 Not sure 11 7 2 201.65 0.000 Total 155 100
Source: Field Data, 2018
4.7.2.1 Effects of Sand Mining on Livelihoods
The study established that sand mining had caused improved livelihoods income, as reported by 46% who strongly agreed to the statement, 27% who agreed and 13% who were not sure. Conversely, 8% of the respondents disagreed while 6% strongly disagreed (Table 4.10). Asked how sand mining has improved incomes, the respondents said that the activity provided job opportunities to many people (75%), a factor that has improved their income thus raising their living standards. From the
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proceeds of sand mining activity, many people (65%) were able to afford three meals per day, establish other forms of livelihoods such as livestock keeping (71%), crop farming (85%), and small scale retail shops (6%) in the area. As acknowledged by 67% of the respondents, closure of sand mines would make many jobless thus making them to resort to alternative livelihoods such as farming which they associated with marginal income. Therefore, the net effect of sand mining was increased income for people engaging in sand mining activities, findings which agree with those of Wambua (2015) on a study on sand mining in river Kivou in
Mwingi, Kitui County.
Table 4. 10: Results for the economic effects of sand mining
(SA- Strongly Agree, A-Agree, NS- Not sure, D- Disagree, SD- Strongly Disagree) SN SA % A % NS % D % SD % 1 Livelihoods 71 46 42 27 20 13 13 8 9 6 2 Developments 67 43 50 32 17 11 15 10 6 4 4 Medication 63 41 37 24 19 12 22 14 14 9
Source: Field Data, 2018
4.7.2.2. Contribution of Sand Mining to Developments
The study established that sand mining had caused personal and general developments in the area as shown in Table 4.10 whereby 43% of the respondents strongly agreed that sand mining had caused various personal and general developments, 32% agreed and 11% were not sure. On the other hand, 10% disagreed while 4% strongly disagreed. Similar results were obtained by Muendo
(2015) who found out that sand mining was had positively influenced development of roads. The respondents indicated that sand mining was seen to positively impact
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on the development by ensuring better maintenance of some of their roads (39%), and that income generated from the activity had enabled them to install electricity in their homes (54%) and buy water tanks (34%).
4.7.2.3. Influence of Sand Mining on Health
The study established that sand mining had significantly influenced access to good medication that has ultimately improved their health, with 41% of the respondents strongly agreeing, 24% agreed while 12% were not sure. Further, 14% disagreed while 9% strongly disagreed (Table 4.10). The extra income that sand miners earn from sand mining activities compared to the general population in the area had enabled them to secure NHIF health insurance for their families, a factor that ensured they access good and reliable health care. Following that, 78% of the sand miners linked sand mining activities to their improved health status, a factor that they valued much since it enhanced their productivity.
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CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSION, AND RECOMMENDATIONS 5.1 Introduction
This chapter presents the summary of findings, conclusion and recommendations based on the objectives of this study. The chapter also outlines the area for further research proposed in this study.
5.2 Summary of Findings
The objectives of this study were to determine the extent of sand mining along the river Tyaa channel; to establish the morphological factors influencing the abundance of sand in river Tyaa channel; to examine the effect of sand mining on the morphology of river Tyaa; and to establish the socio-economic effects of sand mining in river Tyaa.
Firstly, the study established that sand mining had taken place in river Tyaa for over three decades (65%), 25% citing over 20 years ago while 10% said the activity had been ongoing for the past 10 years. Five sites were identified as active sand mining areas where the activity had been taking place along the river Tyaa. The study also established that the rate of sand mining in terms of quantity has gradually increased over time, reaching a peak at the present time. A chi-square test indicated that significant sand mining is taking place in river Tyaa (P = 0.003)
Secondly, the study established that there were four significant morphological variables that were responsible for sand abundance in the river channel namely the river channel width (P= 6.474e-05) depth (P= 7.001e-07), slope angle (P= 3.363e-
06), and bank position (P= 2.2e-16) as shown by their respective p-values (Table
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4.3). This plays a significant role in informing suitable siting of sand mines on a river channel so as to minimize environmental damages.
Thirdly, the study established that sand mining had modified the river channel morphology through causing increase in depth by (P=7.193669e-02), width (P =
9.959148e-03) and slope angles (P=9.378761e-03) at the active mining sites compared to the control sites as shown by their respective Marginal effects and P- values (Table 4.4, 4.5 and 4.6). This has resulted in adverse environmental effects such as river bank instability, loss of riparian vegetation and lowering of water table impounded in sand aquifers.
Finally, sand mining was seen to cause both positive (24%) and negative (76%) socio-economic effects. This is because sand mining was associated with reduced school drop-out rates (75%), developments (75%), improved livelihoods (73%) as well as medication affordability (65%) as positive effects. On the other hand sand mining got associated with adverse effects such as prostitution (55%), community conflicts (91%) and drug and substance abuse (64%). The Chi-Square test of the hypotheses showed that sand mining had caused significant social effects (Df = 3, χ2
= 42.33, P =0.000) and economic effects (Df = 3, χ2 = 201.65, P = 0.000).
5.3 Conclusion
Based on the findings of this study, the following conclusions were arrived at:
Firstly, the extent of sand mining in river Tyaa has over stretched in terms of temporal, spatial and quantity with mining having taken place over 30 years. Five sites were identified along the river where active sand mining was taking place, a factor that contributed to more sand leaving the river channel. Secondly, the abundance of sand along the river Tyaa channel was influenced by the river width,
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depth, slope angle and the position of the river bank. Therefore, there is need to observe these factors while siting sand mining sites so as to minimize adverse environmental effects to the river environment.
Thirdly, sand mining is causing negative effects to the river system such as alteration of channel morphology and loss of riparian vegetation, a factor that shows that sand mining rate in river Tyaa is unsustainable since the channel is undergoing positive geomorphic feedback.
Finally, sand mining is a mixed-blessing in the area of study since it is characterized by negative social effects such as conflicts, prostitution, and drug and substance abuse and positive economic effects such as improved livelihoods, developments and enhanced medication affordability. The Socio-Economic effects. Better strategies may help practice sustainable sand mining with minimal adverse social effects.
5.4 Recommendations
In a bid to ensure environmental sustainability and continued socio-economic benefits of sand mining to the community and the society at large, this study gave the following recommendations:
(i) NEMA as well as other legal authorities should undertake to regulate quantities
of sand mined from river Tyaa through curbing illegal mining and through
closure of some mines in order to reduce the spatial extent of sand mining.
These shall occasion reduced unit quantities of sand leaving river Tyaa per
year thus promoting sustainable sand mining.
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(ii) Siting of Sand Mines should be done appropriately by regulatory authorities like
NEMA by ensuring that sand mines are sited at the shallow convex banks
with low slope angles and at the wide sections of the river channel to ensure
minimal adverse environmental effects. There should also be strict
enforcement of sand mining guidelines on riparian belts and other relevant
regulatory requirements.
(iii) There is need to carry out regular Environmental Impact Assessment (EIA) and
Environmental Audit (EA) by the regulatory authorities like NEMA to help
monitor the environmental effects resulting from sand mining. This will help
detect early signs of high rates of sand mining such as increased slope
angles, width and depth of the river channel and the bank instability in order
to continuously inform on the best ways of sand mining.
(iv) There is need to put in place a suitable revenue collection system by the county
government in conjunction with NEMA in order to realize continued
economic benefits from sand mining by the stakeholders including the local
communities. Strategies to increase participation of the local area members
in the sand mining activities should be considered and adopted. This will
reduce or eliminate sand mining conflicts and other social vices arising from
unfair sharing of the proceeds from activity.
5.5 Area for Further Study
This study proposes a study on an analysis of sand influx and efflux rates on the ephemeral river channels. Such a study would be instrumental in computations of the actual volumes of sand that can be mined from such river channels without causing adverse environmental effects to the river system as reported in this study.
75
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APPENDICES Appendix 1: Questionnaire for Sand Miners, Land Owners and Households
Introduction
I am a student at Kenyatta University undertaking a Master’s degree in Geography
(Geomorphology) in the Department of Geography, School of Humanities and
Social Sciences. I am conducting a survey on the socio-economic impacts of sand mining in areas along river Tyaa in Kitui County. I kindly request that you assist me in filling in this questionnaire. Your sincere and honest answers to the questionnaire will be highly appreciated. The information you provide shall be treated with utmost confidentiality and will purely be used for the purposes of this study.
Thank you for your time and cooperation.
Part I: Background Data of the Respondents
Tick the option applicable for each of the questions listed below.
1. Sex: Male [ ] Female [ ]
2. What is your age range in years?
18 and Below [ ] Between 19-35 [ ] 36-59 [ ] 60 and Above [ ] 3. How long have you lived in Mwingi area?
Below 5 years [ ] 5-9 years [ ] 10-14 years [ ] 15-19 years [ ] Above 20 years [ ]
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4. For how many years have you been involved in sand harvesting activities in river Tyaa whether directly or indirectly? Below 5 years [ ] 5-9 years [ ] 10-14 years [ ] 15-19 years [ ] 20 years and above [ ] 5. What is your highest level of academic qualification?
A degree [ ] A diploma [ ] A-Leve/ O-Level [ ] Primary Level [ ] Any other, please specify:~………………………………………………………… 6. What is your current occupation? Farmer [ ] Professional [ ] Business [ ] Any other, please specify: ~
……………………………………………………………
7. Are you a local member in Mwingi area or a non-local?
Local [ ] Immigrant [ ]
Part 2: Questionnaire for Households to Household Heads
1. In your opinion, what effect does sand mining have to the people of Mwingi area?
Positive [ ] Negative [ ] Don’t know [ ]
Explain:~………………………………………………………………………………
…………………………………………………………………………………………
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2. To give the true picture of the social impacts of sand mining, please show your preference by ticking appropriately in the columns below.
(1. Strongly agree. 2. Agree 3. Not sure 4. Disagree 5. Strongly disagree.)
S/NO: STATEMENT (Has sand mining led to: ..) 1 2 3 4 5 a. Community conflicts? b. School drop-outs? c. Family break ups? d. Prostitution? e. Drug and substance abuse? f. Cases of insecurity? g. Negative effects on the family unit? h. Any other. Please specify ………………………………………………..……... ………………………………………………………. ……………………………………………………….
3. Is the sand mining activity participatory? Are all the community members fully involved in sand harvesting? (Tick the applicable answer)
i. Least involved [ ]
ii. Fairly involved [ ]
iii. Moderately involved [ ]
iv. Most involved [ ]
4. What do you think is the solution to all the above negative social impacts mentioned?
…………………………..…………..…………………………..…………..…………
5. Suggest ways and means of enhancing the positive social effects of sand mining.
…………………………..…………..…………………………..…………..…………
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6. In your own opinion, do you think Sand harvesting has improved you economically?
Yes [ ] No [ ]
7. To indicate a specific area of economic empowerment, please tick appropriately in the columns below.
(1. Strongly agree 2. Agree 3. Not sure 4. Disagree 5. Strongly disagree).
SN STATEMENT 1 2 3 4 5
1 Life is economically better now with sand harvesting than it was before. 2 Local livelihoods are positively affected by sand mining.
3 Sand mining has led to the general development in the area in terms of infrastructure such as, electricity, healthcare and transport. 4 The economic changes that may occur or have occurred as result of the sand mining such as economic returns to local settlements through royalties and mine taxes, and mine development initiatives are satisfactory? 5 Some of the economic implications of closure of mines may include: e.g. loss of jobs and change in lifestyles both of which are significant economic aspects. 6 Has the living standards of the people in river Tyaa catchment improved in the following ways? a). People are able to take three meals a day? b).The local households are able to take their sick to the hospital and afford drugs? c). The number of school dropouts due to lack of school fees has decreased.
8. In your opinion, what do you think is the best strategy in realizing sustainable sand harvesting in order to enhance economic benefits?
......
......
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Part 3: Questionnaire for Sand Miners
1. In your knowledge, does sand mining take place in this locality?
Yes [ ] No [ ] I don’t know [ ]
2. For how many years has sand mining taken place in River Tyaa?
Less than 5 [ ]
5 years [ ]
10 years [ ]
15 years [ ]
Over 20 years [ ]
3. Do sand miners in river Tyaa obtain license? Yes [ ] No [ ] I don’t know [ ] 4. If yes, do you have it?
Yes [ ] No [ ]
5. From whom do the sand miners in River Tyaa secure permission/ licence?
Chiefs [ ]
Land owners [ ]
The local authority [ ]
Individual land owners [ ]
I don’t know [ ]
Others: specify~…………………………………………………………………..
6. Do you think there is an agreement detailing how sand mining should be carried out in river Tyaa?
Yes [ ] No [ ] I don’t know [ ]
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7. Do you think there is a set criteria for one to qualify for permission to carry out sand mining?
Yes [ ] No [ ] I don’t know [ ]
8. If yes, what is the criteria and between which parties is an agreement to that effect made?…………………...... 9. Do most sand miners do what the agreement states? Yes [ ] No [ ] I don’t know [ ] 10. What it the destination of the sand you mine?
Local [ ] Outside the county [ ] I don’t know [ ]
11. Is sand mining a beneficial economic activity? Yes [ ] No [ ] 12. If yes, please rank the following benefits:
Income to county government […]
Income to land owners […]
Income to sand miners/ employment […]
Local construction materials […]
Construction of good roads […]
Construction of social amenities […]
13. Do you think sand mining is a problem for the communities living along River Tyaa? Yes [ ] No [ ] I don’t know [ ] 14. If yes, which are the key challenges arising from sand mining in this area? (Rank them) Availability of water […] Destruction of vegetation […]
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Community conflicts […]
School drop-out rates […]
Prostitution […]
Drug and substance abuse […]
Insecurity […]
Family unit breakdown […]
Other: specify~ ………………………………………………………………………………………… ………………………………………………………………………………………...
15. What measures do the County Government take to curb these negative effects?
………………………………………………………………………………… …………………………………………………………………………………
16. Are the measures successful? [Yes] [No] 17. If No, Why are those measures unsuccessful?
…………………………………………………………………………………
18. How should the problem regarding sand mining be dealt with? …………………………………………………………………………………
Part 4: Questionnaire for Land Owners
1. What is the name of the community in Tyaa locality? …………………………………………………………………………… ……… 2. What are the predominant economic activities of this community?
Agriculture [ ]
Pastoralism [ ]
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Others: Specify.……………………………………………………………………
3. Who owns land in this community?
Individuals [ ]
Clan [ ]
Chiefs [ ]
Family [ ]
4. Who rightfully leases land for sand mining?
Individual owner [ ]
Clan heads [ ]
Chiefs [ ]
Family heads [ ]
5. To whom is the land for sand mining leased?
Local government [ ]
Independent sand miners/ contractors [ ]
6. For how many years has sand mining taken place here?
Less than 5 [ ]
5 years [ ]
10 years [ ]
15 years [ ]
Over 20 years [ ]
7. Which authorities are involved in leasing land for sand mining?
NEMA [ ]
Mwingi Sand Mining Cooperative [ ]
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County government [ ]
8. What is the destination of the sand mined in River Tyaa? Local [ ] Outside the county [ ] I don’t know [ ] 9. Are there conditions placed on leasing land for sand mining? Explain. …………………………………………………………………………… …………………………………………………………………………… 10. Are those conditions observed by sand miners? Yes [ ] No [ ] 11. If No, why not? …………………………………………………………………………… …………………………………………………………………………… 12. On average, about how many Lorries of sand get loaded per day? 13. Is sand mining associated with benefits? If yes, please rank the following benefits. Income to county government […] Income to land owners […] Income to sand miners/employment. […] Local construction materials […] Construction of good roads […] Construction of social amenities […]
Others: specify~ ………………………………………………………………………………………… …………………………………………………………………………………………
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Appendix 2: Rules of Logic Applied in Data Collection on Some Physical
Variables as inspired by a study on ecological informatics by Ekström (2018)
(i) Data on Sand Abundance Status:
Longitude Latitude Sand Abundance Status
High (1) Moderate (2) Low (0)
Whereby:
Sand occupying the river bed at levels above 1.5 metres from the top of the
river bank was termed as high while that occupying the river bed at levels
below 1.5 metres from the top of the river bank was considered low.
(ii) Data on Vegetation Cover:
Longitude Latitude Vegetation Cover status High (1) Low (0)
Whereby:
A slope with less than 30% vegetation cover were deemed to have low vegetation, those with above 30% vegetation cover were termed high.
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(iii) Data on Erosion Status:
Longitude Latitude Erosion status High (1) Low (0)
Whereby:
Slopes characterized by both rills and gullies and are scantly vegetated were
considered highly eroded, while those characterized by simple rills but
without gulley’s and were vegetated termed as lowly eroded.
(iv). Data on Weathering Status/Geology
Longitude Latitude Weathering Status High (1) Low (2)
Whereby:
An area where the bedrock is wholly covered by the detritus derived from its
degradation was termed as highly weathered and where the bedrock was
partly covered and wholly visible due to the absence of surficial detritus was
termed as lowly weathered.
(v) Data on slope angles Longitude Latitude River channel slope angles in degrees
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(vi) River channel width
Longitude Latitude River channel width in meters
(v) River channel depth
Longitude Latitude River channel depth in meters
(vi) River Bank position
Longitude Latitude River Bank position Concave (0) Convex (1)
(vii) Data on Channel Width and Depth and slope angles
L L Width Depth Slope Angles Amount of o a Sand n t Mined
High (3) Moderate Low high Moderate( low high moderate( low Quantity (tons) (2) (1) (3) 2) (1) (3) 2) (1)
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In this, the amount of sand mined per day from the secondary sources at the Mwingi
Sand Mining Cooperative Society was obtained. The slope angles above 300 were considered high, those between 15-290 considered moderate and those below 150 be considered low. Channel width less than 20 meters was considered low, that above
20 meters and below 25 meters was considered moderate and that above 25 meters high. Channel depth above 2.5 meters was considered low, between 2.6 and 3.5 meters moderate and below 3.6 meters high.
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Appendix 3: Data attachments
(i) Data on Morphological Factors Influencing Sand Abundance in River Tyaa
ID Depth Width Slope Bank Vegetation Weathering Erosion Sand (meters) (meters) Angle Status Status Status Abunda- (Degrees) Position nce 1. 2.6 28 14 0 1 1 1 1 2. 2.7 28 12 0 1 0 1 1 3. 3 27 13 0 0 0 0 1 4. 2.8 27 15 0 0 0 1 1 5. 2.5 25 15 1 1 0 1 0 6. 3.2 24 17 1 0 1 1 0 7. 3.6 24 17 1 1 1 1 0 8. 3.4 23 16 1 1 0 1 0 9. 3.1 23 15 1 0 1 0 0 10. 3.1 24 14 0 1 0 1 1 11. 2.9 26 17 0 1 1 0 1 12. 2.7 26 16 0 1 0 0 1 13. 2.6 25 16 0 0 0 0 1 14. 2.9 26 15 0 0 1 1 1 15. 3 25 21 1 1 0 0 0 16. 3.1 24 21 1 1 1 0 0 17. 3.5 24 20 1 0 1 1 0 18. 3.4 26 25 1 1 1 1 0 19. 2.5 26 24 1 1 1 0 1 20. 2.6 27 18 0 0 1 0 1 21. 2.5 27 16 0 1 1 0 1 22. 2.1 27 16 0 1 0 1 1 23. 2.3 26 17 0 1 1 1 1 24. 2.6 26 17 0 0 0 1 1 25. 2.8 25 17 0 1 1 1 1 26. 3.1 25 18 1 1 1 0 0
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27. 3.1 24 19 1 0 0 1 0 28. 3.4 24 19 1 1 1 0 0 29. 3.3 24 18 1 1 0 1 0 30. 3.2 23 18 1 1 1 1 0 31. 3.1 23 18 0 0 0 1 0 32. 2.8 23 17 0 0 1 0 0 33. 2.5 24 16 0 0 1 0 1 34. 2.3 26 16 0 1 0 0 1 35. 2.4 28 15 0 1 0 0 1 36. 2.3 28 16 0 1 1 1 1 37. 2.4 27 15 0 0 1 1 1 38. 2.5 28 15 0 0 0 0 1 39. 2.8 26 16 1 1 0 1 1 40. 2.9 24 16 1 1 0 0 0 41. 3.3 24 17 1 0 0 0 0 42. 3.2 22 18 1 0 0 1 0 43. 3.1 22 17 1 1 1 0 0 44. 2.9 23 16 0 0 0 0 1 45. 2.7 23 15 0 1 1 1 1 46. 2.4 24 15 0 0 0 0 1 47. 2.6 25 15 0 0 1 0 1 48. 2.8 26 16 0 1 1 1 1 49. 2.6 26 16 0 1 1 0 1 50. 2.8 5 17 0 0 1 1 1 51. 2.9 24 17 0 0 0 1 0 52. 3.9 24 17 1 1 0 0 0 53. 3.8 23 18 1 1 1 1 0 54. 3.5 24 18 1 1 0 1 0 55. 3.7 23 17 1 0 0 1 0 56. 3.3 23 19 1 0 0 1 0
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57. 3.1 25 18 1 0 0 0 0 58. 3.1 24 17 1 0 1 1 1 59. 2.9 25 17 0 1 1 1 1 60. 2.8 28 16 0 1 0 1 1 61. 2.9 29 15 0 1 1 0 1 62. 2.9 28 15 0 0 0 1 1 63. 2.5 27 14 0 1 1 0 1 64. 2.6 27 14 0 1 1 0 1 65. 2.3 27 14 0 1 1 1 1 66. 2.3 26 14 0 1 1 1 1 67. 2.5 25 15 0 1 1 0 1 68. 2.6 25 15 0 1 1 0 0 69. 3.1 24 16 1 1 1 1 0 70. 3.2 23 16 1 1 0 1 0 71. 3.5 22 17 1 1 1 0 0 72. 3.4 23 18 1 1 1 0 0 73. 3.5 23 18 1 1 1 1 0 74. 3.6 23 18 1 1 0 0 0 75. 3.1 24 18 0 1 1 1 0 76. 2.9 25 16 0 1 1 0 1 77. 2.7 26 16 0 1 0 0 1 78. 2.6 26 15 0 1 0 0 1 79. 2.8 27 15 0 1 0 0 1 80. 1.9 26 14 0 1 1 1 1 81. 1.7 25 14 0 1 1 0 1 82. 2.1 25 16 1 1 0 0 1 83. 2.2 24 16 1 1 0 1 0 84. 3.2 23 18 1 1 1 0 0 85. 4.1 22 17 1 1 0 1 0 86. 4.1 22 18 1 1 0 1 0
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87. 3.9 19 18 1 1 1 1 0 88. 3.6 20 17 1 1 0 1 0 89. 3.6 20 19 1 1 1 1 0 90. 3.9 21 15 0 1 0 0 0 91. 3.5 22 15 0 1 1 0 1 92. 3.2 23 14 0 1 0 1 1 93. 2.9 24 14 0 1 1 1 1 94. 2.8 24 13 0 1 0 0 1 95. 2.4 25 13 0 1 0 1 1 96. 2.9 26 14 0 1 1 0 1 97. 2.8 24 14 0 1 0 1 1 98. 3 24 16 0 1 1 0 0 99. 3.1 24 16 0 1 0 0 0 100. 3.2 24 17 0 1 0 0 0
Source: Author’s Field Data.
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(ii) Data on Effect of Sand Mining to River Channels Depth, Width and Slope Angles I.D Sand mined Depth Width Slope Angle 1. 12000 2 2 1 2. 9000 2 2 1 3. 10000 2 2 2 4. 10000 3 2 2 5. 5000 3 1 2 6. 0 3 2 2 7. 12000 2 2 1 8. 16000 2 2 1 9. 10000 2 2 2 10. 10000 2 2 2 11. 10000 2 2 2 12. 10000 2 2 2 13. 0 2 3 2 14. 5000 3 3 3 15. 5000 3 2 3 16. 0 3 3 3 17. 0 3 2 3 18. 5000 2 2 2 19. 5000 2 2 2 20. 12000 1 2 2 21. 10000 1 1 2 22. 10000 2 1 2 23. 10000 2 1 2 24. 10000 2 1 2 25. 10000 2 2 1 26. 10000 2 2 1 27. 0 3 2 1 28. 10000 2 1 1 29. 10000 2 1 1
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30. 10000 2 2 1 31. 10000 2 2 1 32. 10000 2 2 1 33. 10000 1 2 2 34. 10000 1 1 2 35. 10000 2 2 2 36. 10000 2 3 2 37. 10000 2 3 2 38. 10000 2 3 2 39. 2000 3 3 3 40. 2000 3 2 3 41. 5000 3 2 3 42. 8000 2 2 2 43. 10000 2 2 2 44. 10000 2 2 2 45. 10000 2 2 2 46. 10000 1 2 2 47. 10000 2 2 1 48. 10000 2 1 1 49. 10000 2 1 2 50. 10000 2 1 2 Source: Author’s Field Data.
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Appendix 4: Research Permits
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