What, After All, Is Apollos? and What Is Paul? Only Servants, Through Whom You Came to Believe—As the Lord Has Assigned to Each His Task

5 What, after all, is Apollos? And what is Paul? Only servants, through whom you came to believe—as the Lord has assigned to each his task. 6 I planted the seed, Apollos watered it, but God has been making it grow. 7 So neither the one who plants nor the one who waters is anything, but only God, who makes things grow. 8 The one who plants and the one who waters have one purpose, and they will each be rewarded according to their own labour. 9 For we are co-workers in God’s service; you are God’s field, God’s building.

10 By the grace God has given me, I laid a foundation as a wise builder, and someone else is building on it. But each one should build with care. 11 For no one can lay any foundation other than the one already laid, which is Jesus Christ. 12 If anyone builds on this foundation using gold, silver, costly stones, wood, hay or straw, 13 their work will be shown for what it is, because the Day will bring it to light. It will be revealed with fire, and the fire will test the quality of each person’s work. 14 If what has been built survives, the builder will receive a reward. 15 If it is burned up, the builder will suffer loss but yet will be saved—even though only as one escaping through the flames.

1 Corinthians 3:5-15, New International Version (NIV) Bible

DEDICATION

This Thesis is dedicated to my wife Dinknesh and children

DECLARATION BY CANDIDATE

I hereby declare that the thesis submitted for the degree, Doctor Technologiae; Civil Engineering, at Tshwane University of Technology is my own original work and has not previously been submitted to any other institution of higher education. I further declare that all sources cited or quoted are indicated and acknowledged by means of a comprehensive list of references.

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ACKNOWLEDGEMENTS I thank Professor G.M. Ochieng for his decision to supervise my thesis. He risked himself to rescue me when I was in a bad situation. I am indebted to Professor G.M. Ochieng and Professor J. Snyman for organizing fund to settle all my debts in 2015 academic year and carefully commenting on the thesis report. I am grateful to M. Makaleng for his outstanding assistance towards completion of this thesis report. This report could not have been accomplished without the support and cooperation of him. R. J. van Vuuren contributed outstanding advice whenever I experienced problems. Professor B. van Wyk and Professor J.L. Munda played a great role towards the completion of this thesis report hence, I appreciate their remarkable decision.

I thank iThemba Labs of National Research Fund (NRF) and Science Faculty Labs of Tshwane University of Technology for analyzing all the samples. I also acknowledge Institute of Agricultural Research, Department of Water Affairs and Department of Environmental Affairs for providing data to complete this thesis project. I also would like to thank members of community forum of Mafefe wetland and farmers who allowed us to install all hydrometric equipments and monitor during the last seven years.

APPROVED BY STUDY PANNEL:

PROFESSOR G.M. OCHIENG: SUPERVISOR

______

PROFESSOR J. SNYMAN: CO-SUPERVISOR

______

ABSTRACT This study presents the findings of long-term monitoring of groundwater (GW) table levels, surface water (SW), environmental isotopes and water quality in the Mohlapitsi/Mafefe wetland and highlights the applicability of monitoring data to water resources issues. The specific objectives were to analyze and quantify the dynamics of water generation and retention within the wetland, trace flow dynamics using environmental isotopes and water chemistry as well as develop a workable water balance of the study site.

Piezometers were installed along seven transects namely T1, T2, T3, T4, T5, T6 and T7. Long-term groundwater levels (GWL) were monitored in order to understand water table fluctuations. Water samples were collected from 2007 to 2013 for tritium, deuterium, oxygen-18 and water quality analyses, and analyzed in iThemba laboratory, Johannesburg. Water balance of the Middle Mohlapitsi Wetland was conducted and estimated using data from South African Weather Service (SAWS) and Department of Water Affairs (DWA) for the period 2006- 2012.

Most of the piezometers closest to the river channel showed the lowest variations. For example, piezometer MRB101 (next to river channel) showed 1.42 m variation, while MRB102 (110 m from the channel) showed 3.21 m variation. In addition, MLB702 (102 m from the channel) in T7 showed least variation, which is 0.55 m, while MLB703 (154 m from the channel) showed 0.79 m variation. Hydraulic gradient is mainly towards the river, indicating GW moves from the wetland to the river. The relationships between rainfall, groundwater, and surface water showed that stream flow did not respond quickly to precipitation as

expected. Statistical analysis showed that there is a significant moderate positive correlation (p = 0.0041) between rainfall and streamflow.

The average Oxygen-18 composition between winter and summer seasons was significantly different (p = 0.0026), indicating winter season had higher O-18 values than summer (average 31.27 vs 20.43). The highest tritium value for tritium (3.2 TU) was measured during May 2008; indicating new rainfall water entered the spring storage and mixed with old water. The lowest tritium value measured for Valis bore hole was 0.3 TU, indicating this water is the oldest.

Electrical conductivity (EC), alkalinity (Alk) and major ion analysis proved low mineralization CaMa-HCO3 type of water for samples from 2007 to 2010, while

Na-HCO3 type water was analyzed for samples from 2011 to 2014. In both cases ion samples clustered together in the cation triangle, indicating the same origin of water. There was no significant difference (p = 0.4196) between average EC between summer and winter season.

Water-budget equation was calculated for evapotranspiration (ET), the value of which was affected by errors of missing data, overestimated/underestimated quantities, and poor measurements. No water was imported to the study area, and no groundwater (GW) was exported to the surrounding catchments.

In conclusion the results obtained in this thesis can be used as a tool in semi-arid wetlands conservation and management practices. This can be achieved by means of long-term monitoring research of wetland hydrological processes. It is recommended that in order to optimally manage a groundwater resource that is being utilised, it is highly important to update water balance calculations.

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Table of Contents

Acknowledgements iv

Abstract vi CHAPTER 1: BACKGROUND 1

1.0 Introduction 1

1.1 Wetlands definitions, identifications, loss and threats 6

1.1.1 Wetland definition 6 1.1.2 Wetland identifications 7

1.1.3 Global wetlands loss and their threats 8

1.2 South African wetlands 13

1.2.1 Issues in wetlands 13 1.3 Key questions 15

1.4 Background to the study 16

1.5 Problem statement 17

1.6 Aims and objectives of the study 17 1.7 Contribution of this thesis report 18

1.8 Structure of the thesis 22

CHAPTER 2: LITERATURE REVIEW 24

2.1 Introduction 24 2.2 Structure of the literature review 25

2.3 Wetland and ecological indicators 26

Acknowledgements2.3.1 Wetland vegetation ...... ? 27 Abstract2.3.2 Hydric …………………………………………………………………….. soils ... i 27 CHAPTER2.3.3 Wetland 1:BACKGROUND hydrology ...... Error! Bookmark not defined. 29 2.4 Wetland processes 31

2.5 Ecological importance of wetlands 33 2.6 Values of wetlands viii 35

2.5 Ecological importance of wetlands 38

2.6 Values of wetlands 40

2.7 Threats to wetlands 41

2.7.1 Introduction 41

2.7.2 Wetland degradation due to agriculture 42

2.7.3 Impacts of irrigated agriculture on wetland ecosystem 46

2.7.4 Wetland degradation due to hydropower development 50

2.7.5 Natural impacts on wetlands 52

2.8 Groundwater and surface water interactions 53

2.8.1 Introduction 53

2.8.2 Interaction of groundwater and streams 55

2.8.3 GW-SW interactions in a catchment 61

2.8.4 GW-SW interactions in a wetland environment 67

2.8.5 GW-SW interactions in Karst terrain 83

2.8.6 GW-SW interactions in glacial and dune terrain 84

2.8.7 GW-SW interactions in coastal terrain 85

2.8.8 GW-SW interactions in River valley terrain 86

2.8.9 GW-SW interactions in mountainous terrain 87

2.9 Methods of investigation of GW-SW interactions 89

2.9.1 Wetlands water budget 89

2.9.2 Piezometers and wells 91

2.9.3 Seepage meters 92 2.9.4 Temperature 93

2.9.5 Hydrogeophysics 93

2.9.6 Hydrological models 94

ix Figures Figure 1.1 South African Wetlands………………………………………... ..10 Figure 1.2 South African Ramsar Sites…………………………………….. ..12

2.9.7 Isotopes and hydrochemistry 96

2.9.7.1 Stable isotopes 97

2.9.7.2 Radioactive isotopes 101 2.9.7.3 Hydrochemistry 104

2.10 Wetland management 105

2.11 Summary and conclusions 109

CHAPTER 3: STUDY CATCHMENT 120 3.1 Site descriptions 120

3.2 Climate of the study area 125

3.3 Population and unemployment 127

3.4 Geology 127 3.5 Soils 130

3.6 Hydrology of the wetland area 131

3.7 Sources of water feeding the wetland 135

3.8 Engineering structures 137 CHAPTER 4: METHODOLOGY 140

4.1 Instrumentation 140

4.2 Weather data 140

4.3 Piezometer installation and groundwater monitoring 143 4.3.1 Conceptual Modeling for flow generation within each Transect 148

4.4 Streamflow measurements 148

4.5 Water sampling for environmental isotopes, hydrochemistry and field

parameters analysis 149 4.5.1 Water sampling for stable isotopes 149

4.5.2 Water sampling for tritium analysis 150

x Figures Figure 1.1 South African Wetlands………………………………………... ..10

4.5.3 Hydrochemistry 152

4.5.3.1 Alkalinity, electrical conductivity and major ions 152

4.6 Application of Darcy’s Law to understand groundwater 156 4.6.1 Wetland soil permeability 156

4.6.2 Other groundwater hydraulics components 157

4.7 Water budget 158

4.7.1 Data collection 158 4.7.2 Study basin water budget calculations 159

4.8 Statistical analyses 164

CHAPTER 5: RESULTS AND DISCUSSIONS 166

5.1 Rainfall and streamflow 166 5.2 Piezometers response 167

5.2.1 Piezometers in T1 167

5.2.2 Piezometers in T2 174

5.2.3 Piezometers in T3 178 5.2.4 Piezometers in T4 183

5.2.5 Piezometers in T5 187

5.2.6 Piezometers in T6 192

5.2.7 Piezometers in T7 197 5.3 Hydraulic characteristics of groundwater in the wetland environment 205

5.4 Discussions 208

5.5 Environmental Isotopes 213

5. 5.1 Stable isotopes 213 5. 5.2 Tritium 221

5. 6 Water quality 227

5.6.1 Electrical Conductivity (EC) and Total Alkalinity (Talka 227

5.6.1.1 Analysis of variance (ANOVA) 231 5.6.2 Major ion chemistry 233

5.6.3 Pollution by water 242

5.6.3.1 Causes of water pollution 244

5.6.3.2 Measures to prevent water pollution in the catchment 251 5.6.4 Cation-Anion Balance Analyses 255

5.7 Study wetland water balance 256

5.7.1 Wetland water balance conceptual model 256

5.7.2 Analysis of water balance of the study site 261 CHAPTER 6: CONCLUSIONS, RECOMMENDATIONS AND SUGGESTIONS

FOR FURTHER STUDIES 267

6.1 Conclusions 267

6.2 Recommendations 272 6.3 Suggestions for future study 274

REFERENCES 279

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Figures

Figure 1.1 South African Wetlands 14

Figure 1.2 South African Ramsar Sites 15 Figure 2.1 Gaining streams receive water from the groundwater system 56

Figure 2.2 Losing streams lose water to the groundwater system 57

Figure 2.3 Disconnected streams 58

Figure 2.4 Bank storage 59 Figure 2.5 Glacial and dune terrain 85

Figure 2.6 Coastal terrain 86

Figure 2.7 Surface water exchange with groundwater 87

Figure 2.8 Mountainous terrain 88 Figure 2.9 Processes that could alter the water’s signature as a result of differences

in the degree to which the various isotopes participate in chemical and

physical processes 99 18 2 Figure 2.10 The meteoric relationship for O and H in precipitation 101 Figure 3.1 Map showing the location of the study area in B71C Quaternary

Catchment within the Oliphants Catchment 120

Figure 3.2 Valley bottom wetland surrounded by mountains in east and west

directions 121 Figure 3.3 Locations of transects, water resources and sampling points in the study

wetland during 2007 through 2013 Wetland and ecological indicators

122

Figure 3.4 Longitudinal conceptualization of the Mohlapitsi River flow 123 Figure 3.5 Sediments at T1 environment transported by the river 124

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Figure 3.6 Laminar River Flow in T3 environment 125 Figure 3.7 Seasonal distribution of rainfall, stream flow and potential evaporation for the period 1920 to 1990 126 Figure 3.8 Geological Map of the study site 129 Figure 3.9 Dolomite rock at the study area roadside 130 Figure 3.10 Time series of observed stream flow for gauge B7H013 for the period 1970 to 2008 132 Figure 3.11 Animals grazing at T1 134 Figure 3.12 Artificial drainage ditch at the study wetland 134 Figure 3.13 The river water assumed to be infiltrating and moving horizontally to wetland environment 136 Figure 3.14 Gabion dam structure at the head of the valley 138 Figure 3.15 Asbestos pipe installed at right bank of T4 environment 139 Figure 4.1 Location of rain gauges 141 Figure 4.2 Cross-section of a PVC piezometer 146 Figure 4.3 Dutch Auger with extension 147 Figure 4.4 Water Level Indicator 147 Figure 4.5 DWA weir site 149 Figure 4.6 Piper Diagram 154 Figure 4.7 Classification diagram for anion and cation facies in the form of major- ion percentages 155 Figure 4.8 Schoeller’s Diagram 156 Figure 4.9 Soil hydraulic permeability using Falling head method 157 Figure 4.10 Thiessen Polygons of the piezometers 162 Figure 5.1 Rainfall over the wetland and daily streamflow observations at B7H013 167

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Figure 5.2 Groundwater table fluctuations November 2006 to December 2014 for T1 169

Figure 5.3 Lithological sections of piezometers at T1 171

Figure 5.4 Conceptual model of flow generation in T1 173

Figure 5.5 Groundwater table fluctuations November 2004 to December 2014 for T2 174

Figure 5.6 Lithological sections of piezometers at T2 175

Figure 5.7 Conceptual model of flow generation in T2 177

Figure 5.8 Groundwater table fluctuations November 2006 to December 2014 for T3

178 Figure 5.9 Conceptual model of flow generation in T3 180

Figure 5.10 Lithological sections of piezometers at T3 182

Figure 5.11 Groundwater table fluctuations November 2005 to December 2014 for

T4 184 Figure 5.12 Conceptual model of flow generation in T4 185

Figure 5.13 Lithological sections of piezometers at T4 186

Figure 5.14 Groundwater table fluctuations November 2005 to December 2014 for

T5 188 Figure 5.15 Conceptual model flow generation in T5 190

Figure 5.16 Lithological sections of piezometers at T5 191

Figure 5.17 Groundwater table fluctuations November 2006 to December 2014 for

T6 192 Figure 5.18 Conceptual model flow generation in T6 194

Figure 5.19 Lithological sections of piezometers at T6 196

Figure 5.20 Groundwater table fluctuations November 2005 to December 2012 for

T7 198

Figure 5.21 Conceptual model of flow generation in T7 204

Figure 5.22 Mean GW flow patterns in 2013 210

Figure 5.23 Deuterium and Oxygen-18 plot for water samples during, June 2010,

November 2011, July 2012, December 2012 and November 2013 217

Figure 5.24 Deuterium and Oxygen-18 plot for water samples based on water

source 220

Figure 5.25 Plot showing δD 0/ SMOW versus source of water 220 00 Figure 5.26 Tritium Values during May 2010, December 2011, April 2012 and

October 2013 224

Figure 5.27 Total alkalinity against electrical conductivity during May 2007-

November 2013 228

Figure 5.28 Electrical conductivity against sampling sites during May 2007-

November 2013 230

Figure 5.29 Mean Schoeller diagram from 2007 to 2008 234

Figure 5.30 Mean Piper diagram from 2007 to 2010 for selected 6 water samples

235

Figure 5.31 Mean chloride concentration versus δ18O plot for May 2007, December

2008, April 2009 and November 2010 236

Figure 5.32 Mean sulphate concentration versus calcium plot for May 2007,

December 2008, April 2009 and November 2010 237

Figure 5.33 Mean chlorides concentration versus sodium plot for May 2007,

December 2008, April 2009 and November 2010 237

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Figure 5.34 Mean Schoeller diagram for 16 different water resources samples from

2011, 2012, 2013 and 2014 239

Figure 5.35 Mean Piper diagram from 2011to 2014 for 16 selected water samples ...

240

Figure 5.36 Mean chloride concentration versus δ18O plot for 2011, 2012, 2013

and 2014 240

Figure 5.37 Mean sulphate concentration versus calcium plot from 2007 to 2010

241

Figure 5.38 Mean chloride concentration versus sodium plot from 2011 to 2014

241

Figure 5.39 Cation-anion balance table from 2007 to 2010 255

Figure 5.40 Cation-anion balance from 2011 to 2014 256

Figure 5.41 Water losses at Mashushu earth canal 257

Figure 5.42 Conceptual model of the study site water balance 259

Figure 5.43 Rainfall vs Evapotranspiration plot 265

Figure 5.44 Median monthly rainfalls and mean monthly potential

evapotranspiration for the whole of the Oliphants catchment 266

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Tables

Table 4.1 Mean rainfall obtained from manual rain gauges from January 2006 to

December 2014 142

Table 4.2 Long term water level data from observation well at study area 163

Table 5.1 Summary of water level variations in the study area during November

2005 to December 2014 212

Table 5.2 δD and δ18O isotopic concentrations from 2007 to 2009 at the Middle

Mohlapitsi Wetland 213

Table 5.3 δD and δ18O isotopic concentrations from 2011 to 2013 at the Middle

Mohlapitsi Wetland 215

Table 5.4 Details of δD and 18O during May 2007 through November 2013 217

Table 5.5 Tritium values during May 2010, December 2011, April 2012 and October

2013 220

Table 5.6 Mean values of anion and cation analysis from November 2007 to

November 2010 at the middle Mohlapitsi Wetland 232

Table 5.7 Mean values of anion and cation analysis from 2011 to 2014 at the middle

Mohlapitsi Wetland 234

Table 5.8 South African Bureau of Standards specification for domestic water 238

Table 5.9 Sodium composition in different sampling times in the study site 242

Table 5.10 Sodium percent water class 254

Table 5.11 Study basin water budget for the Middle Mohlapitsi Wetland Catchment

254

Table 5.12 Water budget for the Middle Mohlapitsi Wetland Catchment 264

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CHAPTER 1: BACKGROUND

1.0 Introduction

Wetlands are productive ecosystems and important components of many river basins world-wide (Jogo and Hassan, 2010). Wetlands are areas where water is the primary factor controlling the environment and they occur where the water table is at or near the surface of the land, or where the land is waterlogged (Mitsch & Gosselink, 1993). Wetland ecosystems cover approximately six to nine per cent of the Earth’s land surface and contain approximately 35 per cent of global terrestrial carbon. Wetlands are mainly found in low-energy environments with shallow depths and low slopes, where water normally flows with a slow velocity (Orme 1990). These are important for trapping nutrients and sediments. One of the important attributes of wetlands is the condition of oxygen shortage in wetland soils (Moustafa and Hamrick, 2002).

Wetlands are formed as a result of geologic forces such as rivers, tectonics uplift, dissolution in carbonate rock, and erosion (Kadlec et al., 1988). Rivers form flood plains that provide a landscape position that enhances wetland development. Tectonic uplift and subsidence create depressional features that are favourable to wetland formation. Wilson et al. (1995) stated that carbonate aquifers dissolve over time, leaving behind depressions where wetlands can form. In addition, accelerated soil erosion transports sediment out of natural channels, leading to down-cutting and deepening of channels. This leads to a lowering of riparian water tables and the reduction of overland flows, both of which alter wetland saturation (McCuen, 1998; Todd, 2008). Damian et al. (2014) stated that globally accelerated soil erosion is a serious issue, and it is difficult to assess its economic and

environmental impacts accurately because of its extent, magnitude, rate, and complex processes associated with it. Many human-interventions, such as mining, construction, and agricultural activities, disturb land surfaces, resulting in accelerated erosion.

Stuurman et al. (1999) demonstrated that wetlands in a natural setting are constantly being formed and lost—depending on the balance of forces. Thus, wetland hydrology changes over time. Reducing the volume of storage within a wetland decreases the residence time, and can also reduce the depth and hydropattern by removing storage volume within the deep-water areas that would normally remain wet under drought conditions (Carter, 1996).

Sediments that fill wetlands, as well as accelerated processes such as upstream development and direct alteration of the wetland, all cause changes that affect wetland hydrologic behavior. Hydrologic alteration upstream of the wetland affects wetland evolution (Hey and Nancy, 1999).

As wetlands are centres of high productivity in the landscape, they have a high capacity to sequester and store carbon (Ferreti et al., 2005; Fiona et al., 2010). Wetlands are now recognized as important features in the landscape that provide beneficial services for people and for ecosystem. Wetlands provide services such as crop production, grazing, timber production, flood risk, nitrogen capture, flow regulation, and water quality (Mitch and Gosselink, 1993). They can improve water quality by trapping and removing sediments and nutrients. These beneficial services, considered valuable to societies worldwide, are the result of unique natural characteristics of wetlands (Adekola, 2007; Troy et al., 2007).

Wetland plants capture carbon dioxide (CO2) through photosynthesis. The overall chemical reaction involved in photosynthesis is 6CO2 + 6H2O (+ light energy) →

C6H12O6 + 6O2. Photosynthesis takes place primarily in plant leaves, and the presence of much vegetation means a large amount of carbon is captured in the wetland (Kevin, 2009). Additionally, wetland soils are largely anaerobic so carbon that entered into the soils decomposes very slowly and can persist for hundreds or even thousands of years (Soil Survey Staff, 1999).

Bullock &Acreman (2003) demonstrated that wetlands are crucial for pollution control, nutrient recycling, soil formation, ground water recharge, climate regulation, and erosion control. In addition, they provide other services that support peoples’ livelihoods such as domestic water supply, fishing and reed (Phragmites mauritanus) harvesting for roof construction (Kotze, 2005).

Wetlands have played a great role in the growth of human civilisations and cultural development. For example, major pre-historic civilisations, including those on the Nile, Euphrates and Tigris, have emerged and developed due to the presence of wetlands (Finlayson & van der Valk, 1995). Wetlands function like sponges of landscapes, store water and slowly release it. This process slows the water’s momentum and erosive potential, reduces flood heights, and allows for ground water recharge, which contributes base flow to surface water systems during dry periods (Finlayson & D’Cruz, 2005).

Wetlands play important roles in helping to maintain streamflow and groundwater supplies by holding water that otherwise would run off the land surface (Tooth & McCarthy, 2007). Wetlands slowly release stored water to streams and to underlying groundwater systems.

Even though Africa is best known for its savannahs and hot deserts, only a surface area of 345,000 km2 is covered by wetlands (Melton et al., 2013). These ecosystems range from Senegal River and Inner Niger Deltas in the West, to the Sudd Floodplains and the Ethiopian Wetlands in the East. Furthermore, important wetlands include Zaire Basin Swamps, Okavango Inland Delta, Kafue Flats, African Great Lakes and extensive Malagarasi-Moyovosi Wetlands in Tanzania (Finlayson & van der Valk, 1991). Wetland characteristics will also vary with altitude, with highland wetlands, such as those found in the Ethiopian and Kenyan mountain systems, complementing lowland types found in the semi-desert (Lehner & Döll, 2004).

Inland wetlands are hydrologically complex as they are influenced by processes within them as well as those in the surrounding catchments. In these wetlands their boundaries are not well defined (McCartney et al., 2005). It is apparent that the hydrological processes within them are quite complex (Mekiso et al., 2014).

Groundwater table level monitoring in a wetland catchment is an essential element for water resources management decisions. Monitoring provides important data that can serve as input into the appropriate decision process (Combalicer et al., 2008). Combalicer et al. (2008) demonstrated that monitoring of groundwater will enable water resources managers, policy makers and engineers to: i) Track changes in groundwater (GW) levels to understand the long-term sustainability of an aquifer, ii) Identify and obtain GW contamination information and better understand water quality problems impacting on public and ecosystem health, and address the problem,

iii) Assess the effects of climate change on GW table levels to issue timely warnings, iv) Understand potential changes in flow due to GW withdrawal, and v) Assist especially wetland managers and agricultural extension workers in monitoring artificial drainage ditches in the wetland.

McGuire & McDonnell (2010) noted that declines in water levels due to human intervention have occurred in critical aquifer systems, including the High Plains of the United States, the Murray-Darling Basin of Southeastern Australia (Commonwealth Scientific and Industrial Research Organisation, 2008), and the Wailapally area of India (Reddy et al., 2009). Overuse of groundwater resources is a growing problem throughout the world, yet the underlying mechanisms of groundwater supply over many areas, such as release of water from storage and recharge through deep unsaturated zones, have only recently been investigated (Konikow and Kendy, 2005; Scanlon et al., 2006; Stonestrom et al., 2007; Konikow and Neuzil, 2007).

In Africa, the exact role of wetland and sustainable use of wetlands is poorly understood. People want to know definitions, functions, values and objectives of sustainable use and management of wetland resources (Millennium Ecosystem Assessment, 2005). To arrive at such goal, continuous research and education are extremely important.

1.1 Wetland definition, identifications, loss and threats

1.1.1 Wetland definitions

Davis (1994) stated that the most widely accepted definition by Ramsar Convention on Wetlands Bureau manual (1997) as “areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres”. However, this definition is modified by South African National Wetland Classification System (NWCS) (FCG, 2009) and defined as ‘an area of marsh, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salty, including areas of marine water, the depth of which at low tide does not exceed ten metres’. Ramsar Convention included marine water to a depth of six metres, while the definition used by the NWCS extends to a depth of ten metres at low tide (Lombard et al. 2005). This report uses Ramsar Convention on Wetlands Bureau manual (1997) and NWCS definitions identifications by FCG (2009).

Given the diversity of wetland environments, many classification schemes have been proposed and utilised over the years. Cowardin et al. (1979) suggested a hierarchy that consists of wetland systems, subsystems, and classes. The aim of this doctoral thesis report is on the quantification of hydrological processes in a wetland environment. Water is the first requirement for wetlands to exist. It is hydrology that controls the formation, persistence, size, and function of wetlands (Balla, 1994; Barbier, 1993; Mitsch and Gosselink, 1993). In addition, geology and topography contribute to distribution and differences in wetland type, vegetative

composition, and soil type (Carter, 1996; Brinson, 1993). Wetlands are present in climates and landscapes that cause ground water to discharge to land surface or that prevent rapid drainage of water from the land surface (Riddell, 2011).

1.1.2 Wetland identification

A wetland can be identified by three basic factors: soil, vegetation, and hydrology. A wetland is described as an area where water is the dominant factor, which determines the nature of soil development and the types of plant and animal communities living in the soil and on its surface (FCG, 2009; Dahl, 2005). A wetland is an area that is periodically or permanently saturated or covered by surface water or groundwater, which displays hydric soils. Hydric soils are unique soils associated with extended saturation, and support hydrophytic (water-loving) vegetation (Schot, 1999).

Wetlands fall between two extremes with respect to where and how they get their water. Wetlands may receive water supply from precipitation and groundwater by means of baseflow. A wetland that receives its water from precipitation is called a vernal pool (Mitsch and Gosselink, 2000). These pools dry up when there is drought. Other wetlands may receive most of their water from groundwater discharge (Barraque et al., 2008). A wetland that receives its water from groundwater discharge is called a fen. Fens usually occur in low areas, for example at the base of hillsides or in land-surface depressions or valley bottoms. Riverine or riparian wetlands exist along stream channels (Riddell et al., 2012; Riddell et al., 2010). Wetland at the left bank of the middle Mohlapitsi River is good example of fen.

1.1.3 Global wetlands loss and their threats

Wetland loss is the gradual reduction of wetland area, due to the conversion of wetland to non-wetland habitats, as a result of anthropogenic activities (Kingsford, 1997). Conference of the parties (2015) and Costa et al. (1996) clearly showed that the loss and degradation of wetlands reduces their ability to provide goods and services to humankind and to support biodiversity, and are therefore associated with economic costs.

Wetlands have been degraded in ways that are not direct physical destruction (Conway & Dixon, 2000; Barbier, 1993). Major causes of wetland loss and degradation due to anthropogenic actions are drainage, dredging and stream channelization, deposition of fill materials, diking and damming, tilling for crop production, mining activities, construction of infrastructure, runoff, changing nutrient levels, releasing toxic chemicals and pollutants, grazing by domestic animals and introducing non-native species (Grundling et al., 2013). Other wetland destructions are caused by natural threats and global climate changes such as erosion, subsidence, sea level rise, droughts, increased air temperature; shifts in precipitation; increased frequency of storms, floods and increased atmospheric carbon dioxide concentration (Turner & Townley, 2006). These impacts could affect species composition and wetland functions. Unfortunately, calculating the magnitude of the wetland degradation is difficult, although their reduction is clearly observed.

Although Africa still has a significant number of pristine wetlands left when compared to Europe or parts of North America, many wetland areas are still experiencing pressures (Dahl & Steadman, 2013). Current major threats are

drainage for agriculture and settlement, excessive exploitation by local populations and improperly planned development activities (Turner & Townley, 2006; Carter, 1996; Chilton et al, 1995). For example, in Lake George, Uganda, threats to the wetland come from pollution from copper and cobalt mines and uncontrolled charcoal burning, which deplete tree resources (Grundling et al., 2013). In the ephemeral wetlands of central north Namibia, the major threat is rapid population growth that puts increasing pressure on the wetland resources (Kolberg, 2002).

As populations in Africa are expected to grow (McCartney et al., 2011) into the future, pressures on wetlands are likely to increase. According to the Ramsar Bureau, the future of African wetlands lies in a stronger political will to protect them, based on sound wetland policies and encouragement for community participation in their management (Chilton et al., 1995).

Furthermore, there are two major reasons for continuous destruction of wetlands in Africa. The first one is the public nature of many wetlands products and services (Grundling et al., 2013). Often, much of the land and water of wetlands do not have property rights, which means it is not clear who actually owns the wetlands and their products. The second reason for wetland loss is associated with policy intervention failures due to a lack of consistency among government policies in different areas, including environment, nature protection and physical planning. Such failures arise due to insufficient understanding of the functions and values of wetlands and thus the consequences when wetlands are lost (Brooks et al., 2004).

Due to the reasons mentioned above, wetland areas are gradually reducing and habitats are disappearing (Hollis, 1993; Dini and Goodman, 1998).The major limitations to sustainable wetland management by decision makers and wetland

users in Africa has been insufficient understanding of the values and functions of wetlands and the consequences of alternative management and policy regimes on wetland functioning, ecosystem services and human well-being (Cowan, 1995). Understanding the hydrology of a wetland is important to decisions involving its future and to evaluating trade-offs involved in protection, development, and mitigation.

Addressing the questions of wetland protection, development and mitigation need an understanding of why wetlands occur in a particular place (Wood, 2000c). Compensatory mitigation of wetlands destroyed during residential and industrial development has spawned the most widespread and sophisticated ecosystem service markets in the United States (ELI, 2007; Madsen et al., 2010). During this process, developers were asked to minimize or avoid wetland loss in the United States (EPA, 2010), while compensating for unavoidable impacts are inevitable (Ruhl et al., 2005). ‘Compensation’ in this case often means restoring alternate ecosystems damage to one resource is ‘traded’ for restoration, or sometimes the creation, of another (NRC, 2001). These wetland and stream trades now form aquatic ecosystem markets throughout the United States, leading to nearly $3 billion in wetland and stream restoration annually (ELI, 2007; Madsen et al., 2010).

Understanding the effects of aquatic ecological restoration on community real estate value could have substantial implications for local efforts to protect natural resources, increase tax bases, and develop well-designed urban growth policies. The middle Mohlapitsi Wetland was facing agricultural and road construction development pressure and experiencing unwanted wetland loss. In order to protect the existing wetland area in the Capricorn District, a partnership with federal, local

governments, non-governmental organizations (NGO) was not developed to carry out an advanced wetland identification study. This study is needed in order to provide basic information to the wide audience and enable water resources managers to carry out an inventory of wetland resources in Limpopo province. This will assist in defining wetland that provides the following functions; habitat quality, stormwater storage, and water quality mitigation (Nikhil & Todd, 2013; Woodward & Wui, 2001). One of the major watershed functions wetlands provide is maintenance of water quality in surface waters and groundwater by means of contaminant removal. Wetlands are natural filters that can remove, retain, or transform a variety of pollutants. Through biogeochemical processes, wetlands intercept surface runoff and remove or sediment, nutrients, pesticides, metals and other contaminants, and reduce suspended sediment transport (Mitsch and Gosselink, 1993).

The data from the study provides upfront information on the location of wetlands designated for protection which allows more predictability in the wetland permitting and management process (Strand, 2010; Mitsch and Gosselink, 1993). The study is used at the federal level as an advisory document during federal wetland permit reviews, at the local level to inform local land use decisions, identify potential mitigation/restoration sites, and identify potential sites for acquisition (Nikhil & Todd, 2013).

The wise use and sustainability conception in the study watershed is not practised (Dixon & Wood, 2001). For example, the farmers who use the wetland and the municipality who constructs roads in the wetland are contributing to the wetland degradation. They do not show responsibility. In addition, the departments who are responsible for agricultural land and water do not show interest to share their

responsibilities by means of training the communities to use resources and prepare for future generations. Furthermore, there is no significant governmental body and NGO’s that provide adequate water and land resources plan in the future for both people and the environment. The current approach to using water resources is not sustainable in the wetland. There is very little involvement of wetland scientists in discussions and implementation of studies and research in the wetland in order to gain better understanding of its potentials and limitations. Many management strategies that have been proposed in South Africa are untried in the study area. There has never been a comprehensive scientific, managerial experience that understood management options for minimising wetland degradation.

In order to properly protect water and related land resources, we need to understand what is going on with the middle Mohlapitsi Wetland’s surface and subsurface water. An important tool that helps us assesse and evaluate how best to protect the study site water quantity and quality is a water budget. Water budget information can be used to evaluate the occurrence and movement of water through the natural environment (Fomchenko, 1998).

Water budgets are important tools for characterizing the behavior of wetland systems. A water budget is used to account for the inputs and outputs to the wetland (Riddell et al, 2012). Balancing the inputs are the possible outputs, including evaporation, transpiration, ground water recharge, and surface water outflows (Black, 1996). Water levels rise over time when hydrologic inputs exceed outputs, and fall when outputs exceed inputs. The first types of water sources and sinks in the wetlands include atmospheric inputs and outputs, such as rainfall, evaporation, and transpiration. The second type of water exchange includes groundwater inflows and outflows. Another exchange mechanism results from

interaction with surface water, including overland flow, as well as from rivers and streams (Cowardin et al., 1979).

It is important to note that the utilization of water budgets information goes beyond how much water is available. Furthermore, it helps to understanding of the flow dynamics. These flow dynamics include the origin and movement of groundwater and surface water and the interaction between the two systems. This overall interdependent understanding is necessary for sound water management (Daniels et al., 2000).

1.2 South African wetlands

1.2.1 Issues in Wetlands

Wetlands are distributed unevenly throughout South Africa because of differences in geology, climate, and source of water. South African inland wetlands cover approximately 20% of the landscape (Masiyandima et al., 2004; Cowan, 1995; Taylor et al., 1995). Figure 1.1 depicts wetland distribution, while in Figure 1.2 shows Ramsar recognised sites (World-Wildlife Fund, 2007). As with wetlands worldwide, South African ones have been subject to pressure, as a result of natural events, such as a major flood during 2000, but mainly as a result of agricultural and urban development during the last decades (McCartney et al., 2011).

Figure 1.1 South African Wetlands shown in blue (modified from World Wildlife Fund, 2007)

Figure 1.2 South African Ramsar Sites shown in green (modified from World Wildlife Fund, 2007)

1.3 Key questions

The brief introduction of wetland provided above raises several key questions that need to be answered before effective management plans can be designed and implemented. The key questions are:  What is the hydrological function of the wetland in the Mohlapitsi River catchment?  Is the wetland a regulator of water which sustains the low flows, or is the wetland a net consumer of water?  Is the wetland becoming wetter or drier?

1.4 Background to the study

To ensure sustainable exploitation of the wetland there is need to quantify the inflows and outflows, while taking into account the temporal and spatial variability of the input parameters as well as uncertainty due to inadequate data measurement.

A number of research studies have been carried out in the study area through the International Water Management Institute (IWMI) during the last decade (Troy et al., 2007). These studies were based on environmental science, water management for food production, sociology and socio-economics. Three hydrological studies were recorded at the right bank of the wetland. The first one was MSc thesis on environmental engineering (Sarron, 2005). The thesis was based on the hypothesis that wetlands can be managed in a sustainable manner, achieving a balance between protection and agricultural production, thereby ensuring optimal use of wetlands. The McCartney et al. (2005) and McCartney (2006) reports focused on the hydrology of the Mohlapitsi River catchment.

However, none of the above studies was based on laboratory analyses. Rather, they concentrated on field measurement and questionnaires. There have been no surface water and groundwater generation processes, which are of key importance for understanding the dynamics of the water in the wetland and the conditions of its sustainability documented. This study was aimed at contributing to bridging this knowledge gap.

The groundwater table analysis was, in itself, unlikely to answer the research questions hence, the environmental isotope tracers and hydrochemical analyses were used to assist in understanding the water flow paths in the wetland.

1.5 Problem statement

Due to a lack of scientific investigation and inconsistent mapping, an exact estimate of the total extent of wetlands and their use in South Africa is still in question. Poor understanding of the values and uses of wetlands accelerate their loss. Understanding the dynamics of the wetland and its sustainability require the knowledge of Surface water – Groundwater (SW-GW) interaction processes, which are pre-requisites for sustainable exploitation of the wetland. Overexploitation of water and land resources due to human activities is threatening the sustainability of the Mohlapitsi/Mafefe Wetland. A combination of agricultural and urban activities as well as the diversion of river for irrigation purposes have affected the functioning of the wetland and are the major causes of its degradation. Uncontrolled subsistence cultivation, artificial drainage by farmers and grazing practices are further exacerbating its degradation. Increased use of fertilizers and pesticides are affecting the aquatic environment such as fish and reptiles.

Furthermore, lack of quantification and development of an advanced scientific understanding of wetland hydrological processes, tracing dynamics of water generation by means of environmental isotopes and water chemistry, artificial drainage by famers as well as wetland water budget deteriorated wetland hydrological and ecological functions.

1.6 Aims and objectives of the study

The aim of this study was to quantify and develop an advanced understanding of hydrological processes and dynamics of wetland. The specific objectives of this research were to:

 analyze the processes and dynamics of water generation and retention within the wetland using conceptual model,  use environmental tracers and water chemistry to trace water flow dynamics in the study catchment, and  use relevant equation in order to develop site-specific and workable water balance for the research site

The main outputs from the study are expected to be an improved physical, environmental and chemical hydrological database for the Mohlapitsi/ Mafefe Wetland. An updated conceptual model of the water dynamics of the wetland and guidelines for future sustainable management of natural resources of the wetland are important outputs from this study.

1.7 Contribution of this study

Wetland ecosystems have been destroyed due to lack of knowledge about them, especially wetlands’ definition, functions and values worldwide. For example, a member of US senate gave an order to farmers to drain them, because wetlands were lands that were worthless (Dahl, 1990). The effects of wetland loss, has been poorly understood and wetland research was immature. When scientific research exposed values of wetlands, US congress passed laws to restore and create artificial wetlands (Mitsch and Gosselink, 1993). Hence creating new wetland technology has spread all over America and Europe.

Another important aspect of wetlands in Africa is that the public and even wetland researchers do not clearly understand how wetlands receive water. Understanding groundwater-surface interactions in the wetland environment is crucial for sustainable use and management of these important landscapes. For example,

many authors stated that the study wetland is fed by the Mohlapitsi River. They even made a conceptual model, which showed that the wetland is sustained because of the river’s lateral flow. As it is shown in the result section in this study, the wetland is about 2.5 metres higher than the river. There is no way that the wetland receives water from the river. This obviously sends wrong message to water resources managers.

In addition to supporting the well-being of the ecosystem, wetlands in Africa and elsewhere have been means for food security. It is imperative that the net gain to society and sustainability and importance of wetlands be clearly enumerated. A well informed and cautious approach to assigning uses to wetlands for integrated planning in the watershed areas is needed. This may be achieved through involvement of wetland conservation experts in strengthening integrated research in wetlands to gain better understanding of their potentials and limitations.

Apparently Africa has been lacking basic research techniques that can easily assess the functions occurring within the wetlands, hydrological processes and their role in supporting human livelihood and ecosystem. Wetland scientists are becoming aware that the many uncertainties make it practically impossible to provide definitive guidelines for successful wetland research, assessment and design.

Continuous and advanced research in wetland hydrological processes enables governments to develop and implement educational strategies, targeted both at formal school/university systems and at the non-formal education of youth and adults in order to promote conservation education and public awareness. Moreover, research supports appropriate training programs stressing the responsibility of development agencies toward wetlands.

Continuous data collection for academic and integrated wetland research to prepare teaching materials in order to save and manage existing ones needs emphasis. The research findings will be used to train stakeholders, extension agents, universities, responsible government officials and the public at large. In other words, general public awareness to wetlands will be achieved by means of long-term monitoring research of wetland hydrological processes.

Moreover, this study demonstrates the importance, functions, threats, current status, conservation and management of wetlands. Furthermore, this study quantifies the importance of long-term monitoring of GW table levels in the wetland environment and highlights the applicability of monitoring data to water resources issues (Lombard et al., 2005; Burt et al., 2002).

The following publications were published as contributions of this study: 1. F.A. Mekiso, J.M. Ndambuki, D.A. Hughes. 2013. Hydrological processes in the middle Mohlapitsi Catchment/ Wetland, Capricorn district of Limpopo Province, South Africa. International Journal of Development and Sustainability Online ISSN: 2168-8662 – www.isdsnet.com/ijds Volume 2 Number 2 (2013): Pages 1263-1279 ISDS Article ID: IJDS13041708 2. F.A. Mekiso, J.M. Ndambuki.2013. Deuterium (2H) and Oxygen-18 (18O) Isotopes as Tracers of Water Flow Dynamics in Limpopo Province of South Africa. 21st Canadian Hydrotechnical Conference 3. F.A. Mekiso. 2013. Hydrological processes in the Middle Mohlapitsi Catchment/Wetland, Capricorn District of Limpopo Province, South Africa. Test and Measure 2013 Conference, Misty Hills Conference Hotel, Mulders Drift, Tuesday 8th October 2013

4. F.A. Mekiso, G.M.Ochieng & J. Snyman. 2014. Long-Term Wetland Hydrological Monitoring in the Mohlapitsi Catchment, South Africa. International Journal of Civil and Environmental Engineering, ISSN:170- 8285,Vo.36,Issue.2 5. F.A. Mekiso, G.M. Ochieng & J. Snyman. 2014. Isotope Hydrology in the Middle Mohlapitsi Catchment, South Africa. International Journal of Engineering Research and Development e-ISSN: 2278-067X, p-ISSN: 2278- 800X, www.ijerd.com Volume 11, Issue 01 (January 2015), PP.01-07 6. F.A. Mekiso, G.M. Ochieng & J. Snyman. 2014. Physical Hydrology of the Middle Mohlapitsi Wetland, Capricorn District, South Africa. GLOBAL Journal of Engineering Science and Researches 7. F.A. Mekiso, G.M. Ochieng.2014. Stable Water Isotopes as Tracers at the Middle Mohlapitsi Catchment/ Wetland, South Africa. International Journal of Engineering and Technology (IJET) 8. F.A.Mekiso, G.M.Ochieng, J Snyman, 2015. Recent findings in Tritium Isotopes in Small Catchment: A Case of the Middle Mohlapitsi Wetland, South Africa” to be published on “International Journal of Civil Engineering, Serial Publications The following publications were submitted as contributions of this study (waiting for publications): 1. Mekiso, F.A. & Ochieng, G.M. 2015. Tritium (3H) as a hydrologic tracer: A case study in the middle Mohlapitsi catchment/wetland, Limpopo Province, South Africa, Journal for new generation sciences, Central University of Technology, Free State, South Africa

2. Mekiso, F.A., Ochieng, G.M. and Snyman, J. 2015. Water budget analysis for the middle Mohlapitsi Wetland in the Oliphants River Basin, Limpopo Province, South Africa. International Journal of Environmental Engineering, Inderscience Publishers, UK (in press)

3. Mekiso, F.A., Ochieng, G.M. and Snyman, J. 2015. Electrical conductivity, alkalinity and major ion analysis of water samples to investigate water quality of the middle Mohlapitsi Wetland, South Africa. International Journal of Environmental Engineering, Inderscience Publishers, UK

1.8 Structure of the thesis

This thesis is divided into six chapters. Chapter 1 has provided background to the study in terms of the current situation of worldwide and South African wetlands, especially the threats they face and how they are classified, and describes the issues, aims and objectives, contributions, key questions and expected outputs of the project. A literature review that is focused on previous work related to understanding wetland hydrological processes and the contributions that this understanding can make to their sustainable management is presented in Chapter 2. Descriptions of the physical setting and human modifications affecting the Mohlapitsi/Mafefe Wetland is provided in Chapter 3, together with information about the topography, climate, geology, soils and vegetation as well as a discussion of the relationship of the wetland to the Mohlapitsi River and the available information on springs and drains.

Chapter 4 presents the research methods that have been applied and the resources used to achieve the objectives of the project. It includes information about the

hydrometric data available from other sources as well as the instrumentation and sampling sites that were established as part of this study (including stream flow and rainfall gauges, groundwater monitoring piezometers, springs, drains and boreholes). Chapter 5 presents the interpretation of the available data, the results of the data analyses and discusses the limitations of both the data and the results. In addition, Chapter 5 presents the development of the conceptual model of the wetland hydrology, water balance and a diagram that summarizes the paths of river water through the wetland environment. Chapter 6 presents a discussion of the implications of the project results for future sustainable management of the wetland, conclusions of the project and makes some recommendations for future research work or management actions.

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction

Although wetlands are important components of ecosystems, they have been considered an irritating area and a source of disease associated with their role as breeding grounds for mosquitoes and other disease causing organisms, or has been used as dumping grounds for human waste products (Dahl, 1990; Brinson, 1993). Moreover, loss of wetlands has been practised due to increased agricultural, commercial and residential development, road construction, resource extraction, impoundments, and waste disposal practices in many parts of the world. Those wetlands that remain are badly degraded (Mitsch and Gosselink, 1993). The severity of the problem in southern California (United States) was shown by Sutula and Stein (2003), where about 75% of 53 000 acres of wetlands were destroyed between 1700 and 1870. Mekiso et al. (2013) demonstrated that literature on wetlands has focussed on developing systematic approaches to wetland study and on prioritizing the wise use of these ecosystems.

Converting natural wetlands for agricultural production during the last 20th century was considered to be one of the main wetland management measures (Dixon & Wood, 2002 & 2003; Holland et al., 1995). To achieve such measures, managers used artificial drainage systems as an important tool, because any change in the wetland environment was accepted (McCartney &Acreman, 2009; McCartney & Van Koppen, 2004; Kusler, 2003). The functions and values of these important ecosystems were not understood by indigenous people, academicians, or by natural resources managers (Hollis, 1993). Kusler (2003) proposed that once

wetland values are understood and recognized, wetland hydrology and water quality can be improved.

Bullock & Acreman (2003) concluded that there is no single wetland assessment method that best meets the needs of all situations in all geographic areas. According to McCartney et al. (2004), classifying, quantifying, evaluating, measuring their functions and even establishing wetland boundaries are not easy tasks, since wetlands are highly dynamic ecosystems. The existing knowledge was conducted to obtain an understanding of the hydrological functions of wetlands, specifically the water dynamics and groundwater-surface water interactions. The review also focuses on the methods that have been used to study the hydrological functioning of wetlands.

2.2 Structure of the literature review

The principal objective of this literature review is to illustrate the scientific understanding of wetland processes, the ecology of wetlands and their management. It deals with surface water-groundwater interactions in the wetland environments as well as the catchment. A secondary objective is to focus on wetland identification and investigation, the latter emphasizing the use of environmental isotopes, hydrochemistry and ecological indicators. The review starts with a brief summary of the general concepts relating to wetlands and provides explanations of key terminologies relating to wetlands such wetland hydrology, functions, and degradation in the United States (Sutula and Stein, 2003). While there is not much information available that is directly relevant to the wetland under study, there is extensive literature from South Africa that can contribute to understanding the dynamics of the Middle Mohlapitsi wetland. While

there are a substantial number of wetlands being degraded in South Africa (Grundling, 1999), the existing knowledge does not include descriptions of the measures taken by relevant management agencies to protect the wetlands. There is abundant information available about the use of environmental isotope and hydrochemistry (geochemistry) methods in South Africa and other parts of the world. However, there are no reports of the use of these approaches in the Mohlapitsi River basin.

2.3 Wetland and ecological indicators

USACE (1987) stated that one of the wetland indicators must be fulfilled in order to identify a land as a wetland. Mapaure and McCartney (2001) concluded that the most common ecological indicators are aquatic plants, phreatophytes and hyporheic biota. According to these authors, specific vegetation communities or biota can indicate groundwater discharge to surface water features. Changes in the composition and accumulated biomass of submerged aquatic plants can relate to groundwater seepage. Kotze (2005) also indicated that the near-stream presence of phreatophytic plants, which are deep-rooted and that access groundwater, can indicate a shallow water table. The extent and composition of biota that habitat the hyphoreic zone, can also describe the processes of near-stream groundwater and surface water mixing. The accepted wetland indicators by authors such as Cowardin et al. (1979) and USACE (1987) in the field are vegetation, hydric soil and hydrology. The following sub-sections will briefly explain these ecological indicators.

2.3.1 Wetland vegetation

Wetland vegetation can be described as plants that exhibit adaptations to allow, under normal conditions, germination or propagation and to allow growth with at least their root systems in water or saturated soil (Richard et al, 2006). Powell (1990) agreed that wetland vegetation is the plant life that occurs in areas where the frequency and duration of inundation or saturation exerts a controlling influence on the plant species. The area should have plant communities that require standing water for part of the growing season. Balla (1994) noted that complex dynamic wetland surface water groundwater interactions with climate, soil type, and position in the landscape could determine the composition of the plant community.

An indicator of aquatic life can either be visual observation of physical features associated with aquatic life or visual observation of aquatic life. Mapaure and McCartney (2001) stated that each wetland community has a variety of plants which provide shelter and food for animals living there. Hydrophytic plants have adapted to survive in wetlands despite the stress of an anaerobic and flooded environment. Unlike common land plants that are able to get oxygen directly into their roots, the hydrophytes have internal oxygen-transporting tubes, the ability to float on shallow water to take oxygen down to the roots of the plants. These plants are often the first and most important indicators of a wetland (Semeniuk & Semeniuk, 1995).

2.3.2 Hydric soils

An important characteristic of a wetland is its soil that helps to determine the type of wetland and what plants and animals can survive in it. Among the physical

characteristics of wetland soils, the resistance to soil erosion hazards is very important, mainly in the tropical countries (Soil Conservation Service, 1994). Field indicators are usually designed to identify soils which meet the hydric soil definition without further data collection. NRCS (1994) indicated that field indicators are soil characteristics, which are documented to be strictly associated only with hydric soils, and are an efficient on-site means to confirm the presence of wetland soils (Soil Survey Staff, 1999). The concept of hydric soils includes soils developed under sufficiently waterlogged conditions to support the growth and regeneration of hydrophytic vegetation (Tiner, 1999). The plants that live in wetlands are only those that can adapt to these wet soils. Also, soils that are sufficiently wet because of artificial measures, or soils in which the hydrology has been artificially modified, are hydric (Soil Survey Staff, 1999). The nutrients in the soil often depend upon the water supply. However, if the water source is primarily rain, the wetland soils do not receive as many minerals as those fed by groundwater. Hence, soil in floodplains is very rich and full of nutrients, including potassium, magnesium, calcium, and phosphorus (Environmental Laboratory, 1987).

The presence of hydric soil is one of the three important wetland identifying characteristics such as hydrophytic vegetation, hydric soils, and wetland hydrology (Cowardin et al., 1979; Tiner, 1999; USACE, 1987; National Research Council, 1995). Organic matter content, permeability, texture, drainage and colour are important soil properties that play a key role in the development and identification of wetland soils (Soil Survey Staff, 1999) and these properties, and associated morphological characteristics, are unique to each soil type and can be described when examining a soil profile for a particular soil type. Hydric soils can be either

organic (peat or muck) or mineral soils (USACE, 1987; National Research Council, 1995). In some bogs (a wetland type that accumulates acidic peat), a deposit of dead plant material is developed to form muck. This type of soil is dark and glue-like. To classify as muck, a soil must contain not less than 20 percent organic (derived from living organisms) matter.

Organic soils formed in waterlogged situations (wetlands), where decomposition is inhibited and plant debris slowly accumulates, are called Histosols (National Research Council, 2001 & 2000). Organic soil material includes muck, mucky peat, and peat (NRC, 2001). All histosols are hydric soils, which are freely drained (Folists) occurring on dry slopes where excess litter accumulates over bedrock. Mineral hydric soils are those soils periodically saturated for a sufficient duration to produce chemical and physical soil properties associated with a reducing or anaerobic environment (USEPA, 1994; Soil Survey Staff, 1999).

Furthermore, hydric soil indicators for non-sandy soils are Gleyed soils (gray colours), soils with bright mottles with low matrix chroma. On the other hand, hydric soil indicators for sandy soils are high in organic matter in the surface horizon, streaking of subsurface horizons by organic matter, and organic pans (SSSA, 1975).

2.3.3 Wetland hydrology

The hydrology of a wetland is mainly responsible for the vegetation of the wetland, which affects the value of the wetland to animals and people (Acreman et al., 2007). The duration and seasonality of flooding and soil saturation, ground-water level, soil type, and drainage characteristics exert a strong influence on the plant density, type, and distribution of plants and plant communities in wetlands. Black

(1996) and Golet and Lowry (1987) showed that surface flooding and duration of saturation within the root zone, while not the only factors influencing plant growth, account for as much as 50 percent of the variation in growth of some plants. Plant distribution is also closely related to wetland water chemistry; the water may be fresh or saline, acidic or basic, depending on the sources (Richardson, 1995).

Todd (1980) stated that hydrology of wetlands includes the inflow and outflow of water through a wetland and its interaction with other site factors such as land use and land cover. It is the hydrological processes that control the formation, persistence, size, and functions of wetlands (Carter, 1996; Glenn et al., 1999). Dahl (1990) and Tiner (1999) stated that wetland degradation has a negative impact on the global hydrological cycle.

Dugan (1992) and Mitsch and Gosselink (1993) demonstrated that the major governing force that controls the functioning of a wetland is hydrology, while De Groot et al. (2006) confirmed that changes in hydrology directly or indirectly affect the shape, size and structure of a wetland. USACE (1987) and Price and Maloney (1994) stated that land is identified as experiencing wetland hydrology when the surface of the top soil is waterlogged for several months or throughout the year in order to create anaerobic conditions. There is a number of wetland hydrology indicators, among which are standing or flowing water observed in the area during the growing season, soil water logging during the growing season, and the presence of water marks and debris on trees and other objects (Sutula and Stein, 2003).

McCartney et al. (2005) characterized a wetland by its water table being at or near the land surface for part of the year, by soil conditions that differ from adjacent

uplands, and by vegetation adapted to wet conditions. Parsons (2004) and Finlayson & Van der Valk (1995) classified wetlands of South Africa as marine, estuarine, lacustrine, riverine, palustrine and endorheic wetlands. Parsons (2004) further showed that one or more indicators of wetland vegetation, hydric soil and wetland hydrology must be present for an area to be considered as a wetland.

2.4 Wetland processes

Precipitation, surface-water flow, groundwater flow, and evapotranspiration (ET) are the major components that make up the wetland processes and the hydrological cycle (Brown et al., 1998; Allen et al., 2005; Walton et al., 1994; Roulet, 1990; Freeze and Cherry, 1979). Although the relative importance of each component in maintaining a wetland varies both spatially and temporally, all these hydrological components interact to create the hydrology of a wetland (Carter, 1996). The water balance of a wetland can therefore be affected by one or more of the following hydrological processes:

 Direct precipitation on the wetland.  Evapotranspiration losses from the wetland vegetation and surface water.  Surface, or near-surface (saturated soil water flow or spring flow), runoff from the adjacent hillsides.  Exchanges with the underlying groundwater body.  Surface flooding from an adjacent river or lake.  Surface drainage from the wetland to a river or lake.  Sub-surface water exchanges with a river or lake through the wetland soils or sediments at the channel or lake margins (i.e. river banks).  Tidal influences in coastal wetlands (Harvey and Odum, 1990).

De Groot et al. (2006) found that wetland conditions occur when topographic and hydrogeologic conditions are favourable and a sufficient, long-term, source of water exists. Ellery et al. (2005) and De Groot et al. (2006) agreed that the occurrence of wetland in land-surface depressions in drainage basins is governed by favourable topographic conditions. Ellery et al. (2005) added that these depressions may be found in upland areas, along hillsides where there may be a change in slope or geology, in floodplains of streams or rivers.

National Research Council (1995) and Bullock & Acreman (2003) argued that the development of wetland hydrology could be affected by the presence of impermeable bedrock near the land surface. Glenn et al. (1999 and 2006) stated that a persistent, long-term source of water is a prerequisite to the development and existence of wetlands. Moreover, Glenn et al. (1999) and Galatowitsch & Van der Valk (1994) explained that the development of wetland conditions depends on a long-term balance between wetland inflow and outflow.

Watson and Burnett (1995) showed that the amount of water lost through evapotranspiration may exceed the rate of all water inflow to a wetland. Evapotranspiration varies regionally and seasonally; during a drought it varies according to weather and wind conditions (Dasgupta et al., 1998). During a drought, the significance of evapotranspiration is magnified, because evapotranspiration continues to deplete the limited remaining water supplies in lakes and streams and the soil (Allen et al., 1998). Forested wetlands may have greater evapotranspiration rates, due to higher leaf areas. Allen et al. (2005) demonstrated that evapotranspiration is the largest component of the hydrologic cycle, 60 percent of annual precipitation falling over the land surface is consumed

by ET (Hart, 1997). Quantification of ET is used for many purposes, including crop production, water resources management, and environmental assessment. In agriculture, accurate quantification of ET is important for effective and efficient irrigation management. When evaporative demand exceeds precipitation, plant growth and quality may be adversely affected by soil water deficit (Brown, 2014).

Brown and Stark (1989) and Ridell et al. (2008) confirmed that extreme declines in the water table could result from water loss through evapotranspiration. Neglect of interaction of groundwater and surface water in the water resources management leads to disastrous consequences (Wang et al., 2007). For example, when the rate of withdrawals by pumping from an aquifer exceeds the rate of recharge, the resulting water table decline leads to the gradual decreasing of spring and stream flow, drying of wetlands, decrease in river flow, and losses of vegetation. Diminishing the flow of a river, the construction of dams and reservoirs, decreasing frequency of flood events, and pumping groundwater along its course, will lead to water table declines for hundreds of kilometres downstream with impact on the ecology of riparian zones (Sophocleous, 2010).

Kusler (1987) demonstrated that precipitation and surface runoff from the surrounding catchments are the main sources of water for a wetland that is formed in the valley. Precipitation that falls on the continents either runs over the surface of the Earth into streams, lakes, and wetlands, or soaks into the ground. Water that remains on the Earth's surface, such as streams, lakes, and wetlands, is called surface water (Nikhil & Todd, 2013).

To develop a clear understanding of the dominant wetland processes for a specific site, it is important to be able to quantify the various processes referred to above.

Given that they are expected to be variable over time, this is never a simple task, particularly for short-term studies that do not have the luxury of extended data collection periods.

ET losses from wetlands vary with plant species, plant population, and plant status

(Schilling, 2009). Seasonal changes in ET also relate to the water-table position. For instance, more water evaporates from the soil or is transpired by plants when the water table is closer to the surface.

Establishing the dynamics of water exchanges between the wetland soils and underlying groundwater can be achieved using shallow piezometers and deeper boreholes. However, while these may indicate differences in water levels and hydraulic heads between the wetland soils and the regional groundwater body (Siegel, 1983), it will be always more difficult to quantify likely flow rates. Vertical drainage (or recharge) rates in wetlands can be much slower than those in adjacent uplands as the upland soils will be generally more permeable than the clays or peat that usually underlay wetlands (Johnston et al., 1990). It was long assumed that the discharge of groundwater through thick layers of well- decomposed peat was negligible because of its low permeability, but recent studies have shown that these layers can transmit ground water more rapidly than previously thought (Siegel, 1983).

Contributions from flooding of an adjacent river channel can be obtained from time series of either river discharge (preferable measured upstream of the wetland) coupled with a stage-discharge relationship for representative channel cross- sections, or through direct measurements of river water levels. These type of observations may indicate that flooding occurs and the relative degree of severity,

but not provide accurate measurements of flooding volumes or the extent to which the floodwaters remain on the wetland or drain back to the river downstream (Finlayson, 2012). To achieve the latter would require more detailed topographic surveys of the channel and wetland coupled with a two-or three-dimensional hydraulic model (Nolan et al., 1987). This would be beyond the resources of most small scale studies. The patterns of flow or surface storage across wetlands during flooding events can be very complex and affected by the topography and vegetation of the wetland surface (McCarthy, 2005).

Wetlands that retain flood waters may act as a temporary store, keeping water during periods of increased runoff, or following inundation from a river or lake, and allowing water to return to the water body relatively slowly. This may modify the river flood pulse, reducing its amplitude while extending its duration. Floodwater may be discharged over a longer time period or removed completely through evapotranspiration and percolation to groundwater. All such circumstances can reduce considerably the damage caused by floodwaters (Richard et al., 2006).

Exchanges of water between the bed and banks of a river and an adjacent wetland will always be very difficult to monitor, because of the degree of variability in their systems. In other wetlands the exchanges may be reversed depending on the level of flow in the river and the level of saturated storage in the wetland sediments and soils. However, these exchanges (together with the degree of over-bank flooding during high flows) are very important with respect to understanding the impact of wetlands on downstream river flow regimes (Johnston et al., 1990).

Contributions to stream flow from wetlands dominated by groundwater inputs tend to be more evenly distributed in time, because natural groundwater levels vary

slowly over time (Harvey and Odum, 1990). Wetlands dominated by groundwater contribute flow to streams throughout the year by means of baseflow. Water after moving vertically upwards and laterally into a wetland from an underlying aquifer is released slowly to the river system (Acreman & Miller, with no date). Alteration of the catchment hydrology, including abstraction from surface and groundwater, impoundment or diversion of rivers or land use change can have a significant impact on wetlands and the functions they perform. To maintain the goods and services provided by wetlands, there is a need to assess and where necessary control these impacts (Parsons, 2014; Bullock & Acreman, 2003).

Storage (and any outflows to river channels) in wetlands fed mainly by surface hydrological processes (for example, hillslope runoff or direct precipitation) will tend to be more variable, particularly in strongly seasonal climates (Gosselink and Turner, 1978; Finlayson, 2012). Storage will also be strongly affected by the seasonality of the evapotranspiration regime determined through seasonal climate fluctuations and water demands of the wetland plants.

The occurrence of wetlands in different geologic and physiographic settings helps to group or classify them in such a way as to identify similarities in hydrology. For example, Novitzki (1979 & 1982) developed a hydrologic classification for Wisconsin (USA) wetlands based on topographic position and surface water- ground water interaction. Gosselink and Turner (1978) grouped freshwater wetlands according to hydrodynamic energy gradients and Brinson (1993) developed a hydrogeomorphic classification for use in evaluating wetland function.

Peatland type (fen or bog) and plant communities are affected by the chemistry of water in the surface layers of the wetland and the source of water (precipitation,

surface water, or groundwater) will largely control the water chemistry and determine the nutrients that are available for plant growth (Siegel, 1983; Siegel and Glase, 1987). Water moving into wetlands has chemical and physical characteristics that reflect its source. For example, older ground water generally contains chemicals associated with the rocks through which it has moved; younger ground water has fewer minerals because it has had less time in contact with the rocks. Which processes can and will occur within the wetland are governed by the characteristics of the water entering and the characteristics of the wetland itself; its size, shape, soils, plants, and position in the basin (Roulet, 1990).

Groundwater recharge is an important socio-economic benefit derived from wetlands. Water moves via the wetland to underground aquifers that hold 97% of the world’s potable water (Bouwer & Maddock, 1978). During the process of infiltration, water undergoes various physical and chemical processes, which ameliorate the potable quality, resulting in a reduced treatment cost if ultimately used for human consumption.

There are many biogeochemical processes that wetlands perform, which result in significant benefit to humans as well as supporting overall ecological quality. These include the immobilization and transformation of excess nutrients, heavy metals and other toxicants in forms that are tightly bound to sediments or soil particles. Eutrophication, which may threaten potable water supplies as well as impairing ecological quality, can be reduced or prevented by wetland processes. Phosphorus can be inactivated by chemical bonding to inorganic ions or through storage in plant biomass. Nitrate can also influence eutrophication (Price et al., 2003) though is of particular interest due to its additional toxicity to human as well as aquatic life (James et al., 2005).

2.5 Ecological importance of wetlands

Wetlands are found throughout African, Asian, Australian, American and European continents, and play a significant role in the livelihoods of mainly rural communities in Southern Africa (Acreman, 2012; Turpie et al., 1999). The ability of wetlands to store water during the wet season and release it during the dry season provides farmers living in semi-arid areas opportunities to grow crops all- year round, thereby improving their food security and incomes (Acreman & Miller, no date). Besides crop production, wetlands provide other services that support human welfare such as livestock grazing and watering, water supply, fishing and natural products (Finlayson, 2012).

The largest wetlands include the Okavango Delta, the Sudd in the Upper Nile, the wetlands of Lake Victoria and Lake Chad and the floodplains and deltas of the Congo, Niger and Zambezi rivers (Alexander & McInnes, 2012; Glen et al., 1999). All these wetlands are able to store flood waters and slowly release the stored water, thereby reducing the amount of flood damage caused downstream. For example, surface water - groundwater interactions in the Okavango Delta of Botswana plays a major role in restricting the formation of salt pans and the general functioning of the wetland ecosystem (McCarthy, 2005). When the seasonal flood advances, the water table in the Okavango Wetland is raised by the infiltrated groundwater.

Dahl and Johnson (1991) showed that wetlands act like sponges, slowing the flow of surface water and reducing the impact of flooding. Wetlands also prevent soil erosion and buffer water bodies from potentially damaging land use activities such as agriculture (Millennium Ecosystem Assessment, 2005). Wetlands can remove

and store greenhouse gases from the Earth’s atmosphere, slowing the onset of global warming (Council on Environmental Quality, 2008; Kusler, 1999; International Institute for Sustainable Development, 1999). Furthermore, Kusler (1999) noted that they serve as breeding grounds for migrating birds and resident amphibians, permanent homes for fish species, social interaction amongst mammals who congregate there for water, and an escape from the heat of the sun for countless reptiles, amphibians and mammals.

Wetlands are seen as the cornerstone of wildlife populations (Craft, 2001; Costa et al., 1996). Wetlands are able to filter out sediment, nutrients and toxic chemicals before they reach the water table (Glenn et al., 1999). Cowardin et al. (1979) and Denny (1993) agreed that development around wetlands is a major threat to how they function and their survival in general must be preserved. Sutula and Stein (2003) argued that even though a number of studies regarding the ecological importance of wetlands have been conducted, understanding their functions and values need more investigation.

Hailu (1998), Hailu and Abbot (1999) and Wood (2000b &c) indicated that wetlands are very valuable areas for rural communities in the highlands of western Ethiopia. They directly contribute to food security through the production of green and mature maize and vegetables (Wood, 2000a). In addition, they are a source of drinking water (from wetland edge springs) and traditional medicines for many of the rural people (Hailu and Abbot, 1999). The functioning of these sources of relatively safe water is dependent on the water table level which is maintained by the wetland (Brown et al., 1998).

2.6 Values of wetlands

Estimating the value of an individual wetland is not a simple task, as they differ widely and perform different functions. For example, the value of wetlands along the Charles River in USA is estimated as $17 million per annum, which includes contributions to the mitigation of flood damage (Costanza et al., 2008; Ramsar Convention Bureau, 1997).

Other studies have attempted to quantify the economic value of wetland systems in Southern Africa (for example, FCG, 2009; Adekola, 2007; Turpie et al., 1999; Davies & Claridge, 1993). However, these studies were conducted at the local level due to limited data on the actual extent of wetlands at national and regional levels. In addition, the valuation of the studies focused on quantifying a few key services as some wetland services are difficult to quantify given the available data and resource limitations. For example, DWA (2010) used a simple approach that takes into account the common problem of data limitations and estimated that the use value of the Zambezi basin wetlands was US$123 million per year, which was equivalent to 4% of Zambia’s GDP in 1990. Adekola (2007) estimated that the direct use value of the main provisioning of the Ga-Mampa Wetland in Limpopo Province of South Africa is US$ 90 000 per year.

Wetlands provide essential ecosystem functions and services, including regulation of water quality, sustainable control and mitigation of flooding, greenhouse gas reduction, essential habitats for plants and animals, and cultural and recreational facilities (Barbier, 1997 & 2011).

2.7 Threats to wetlands

2.7.1 Introduction

In spite of their considerable value, 50% of wetlands in South Africa have already been destroyed due to unsustainable development (Bunting et al., 1998; Paersell and Mulamoottil, 1994; McCartney, 2006; Melton et al., 2013). Sarron (2005) pointed out that mechanisms leading to their destruction include draining for crops or housing developments; pollution; building dams; existing and additional obstructions which interfere with natural estuarine and coastal lake dynamics, the clearing of natural vegetation for the extension of agriculture, overgrazing increases in domestic livestock, particularly goats, increased extraction of underground water for irrigation and vegetation, burning and planting of water- thirsty alien trees too close to their edges (Grundling, 1999; McCartney, 2006). Dixon (2003 & 2001) demonstrated that mosquito control is one reason that wetlands have historically been drained and it remains a cause of wetland loss today.

Wetland losses were due primarily to agricultural conversion, but the ultimate responsible factor is urbanization that consumes agricultural areas (Azous & Richard, 2001). Agriculture is then pushed onto wetlands in order to maintain its surface area. Weak policy, lack of or poor law enforcement, inappropriate governance and limited knowledge of wetland functions and values in national and local land-use planning and development programmes have been the main drivers of wetland degradation (Mediterranean Wetlands Observatory, 2012).

2.7.2 Wetland degradation due to agriculture

Globally, wetland areas are continually decreasing due to drainage, cultivation and urbanization, and it is therefore necessary to protect and sustainably utilize the remaining wetland areas (Masiyandima et al., 2004; Dahl, 2005 &2006; McCartney et al., 2011; Dahl & Steadman, 2013). Wetlands have been drained and converted to farmland, filled for housing developments and industrial facilities and used as waste dumping areas (Ramsar Wetlands Convention, 1971). Liang & Ding (2004) confirmed that human activities continue to adversely affect wetland ecosystems. Furthermore, Williams (1995) demonstrated that since the 1600s, more than half of the original wetlands in the 48 United States have been destroyed due to mostly human interventions.

By 1970, 60% of the valuable waterfowl habitat on the coastal lowland of New South Wales and the Swan Coastal Plain of Western Australia had been destroyed. Land in Australia is extensively farmed. These lands require the application of phosphate as well as zinc, copper, cobalt and molybdenum minerals (Conservation International, www.biodiversityhotspots.org/xp/hotspots/australia/Pages/conser).

The wheat belt zone is the most highly cleared area in Western Australia due to past human activity. Local government areas in the west have less than 5% of original native vegetation remaining (State of the Environment Report, 2007). Large scale mining for bauxite is increasingly a threat to South West Australia’s ecosystems, including waterfowls. The region is one of the largest producers of alumina in the world. Open-pit mining destroys habitats and pollutes water ways (State of the Environment Report, 2007).

In Tasmania, the button grass mires have suffered the majority of human impacts on wetlands, adversely affected by grazing and burning over many years. In New Zealand it is estimated that about 90% of the original wetland area has been lost (Moser et al., 1996), with wetlands now covering only 2% (5 323 km2) of the country’s total land area (266 171 km2) (Dugan, 1993). Loss has been due to drainage, gold mining, flood control, land clearance, agricultural development, kauri-gum digging and flax milling. The wetlands of Papua New Guinea are poorly known (Gopal et al., 1982) and Moser et al. (1996) reports that little published quantitative information is available for wetland loss in the South Pacific island nations (New Caledonia, Fiji, Western Samoa, American Samoa, Guam, Northern Mariana Islands, et cetera).

Rates of wetland loss are less well documented in Europe (Dugan, 1993) than in the United States, but the conversion of natural ecosystems such as wetlands is believed to be greater due to Europe’s high population density and longer history of economic development. The considerable wetland losses in Europe are demonstrated by the example of Finland, which originally had 10.4 million ha of mires (30% of its land area), but has lost 5.5 million ha, due to forest drainage. Loss rates for peat lands in excess of 50% have been reported (Oxtobee & Novakowski, 2002) for 11 European countries. In western and central Europe, the majority of the wetlands were destroyed for the sake of extensive industrialization and agriculture. In Eastern Europe, political changes contributed losses in wetland (Immirzi & Maltby, 1992). For example, in Poland 95% of the original mire area of 1.5 million ha has been exploited. In general, European wetlands have been lost mainly due to drainage and conversion to agriculture and grazing land, and urban and industrial development.

Estimates by (Bullock & Acreman, 2003) suggest that the area occupied by wetlands in the UK has declined by 90% since Roman times. This decline has accelerated substantially in the last few centuries – with the introduction of intensive agriculture, the degradation of floodplains, the draining of the fens, the mining of lowland bogs for peat, the erosion of coastal wetlands and salt marsh, and climate change (Richardson & Vepraskas, 2001).

According to the report made by Dahl and Johnson (1991), there were approximately 90.2 million ha of wetlands in the contiguous 48 states of the USA prior to European settlement. At least half that area has disappeared (USEPA, 1994 & 2001), due to wetland drainage for crop production. Frayer et al. (1983) estimated that millions of hectares of drained wetlands are now poor-quality agricultural land in the eastern United States. Frayer et al. (1983) and USEPA (2001) also concluded that agricultural and forest lands are being converted to commercial and residential development, because of drainage (Jones, 1993a & 1993b). Wetland and aquatic wildlife species have declined in this area although wetlands and riparian areas support a higher diversity and abundance of wildlife species than other farmland habitats (Mitsch and Gosselink. 2000).

Sixty percent of the original wetlands in the lower Atlantic Flyway still exist (Brown and Stark, 1989). The remaining wetlands are declining in quality due to nutrient loading, altered hydrology and urban encroachment (Dahl, 1990). Moreover, wetland wildlife species have experienced long-term declines and loss and degradation of the south aquatic system and loss of much of the native fauna contribute to the decline of global biotic diversity (Holland et al., 1995).

Dahl (1990) stated that the loss and decreased quality of existing wetlands have resulted in declining wildlife populations. Significant loss and degradation of estuaries in the Gulf Coast have occurred because of saltwater intrusion from canal construction and development and other developmental pressures along the coastal regions (Watson & Burnet, 1995).

Gulf estuaries are characterised by a high degree of variance in nutrient dynamics. River dominated estuaries of the northern Gulf such as Mobile Bay display strong seasonal cycles in nutrient concentration. However, dissolved inorganic nitrogen

(DIN) and phosphate (PO4) concentrations are 5-10-fold lower than in similar systems along the U.S. east coast and in Western Europe, where significant point- source inputs are found (Gulf Coast Ecosystem Restoration Task Force, 2011).

Smith & Townley (2002) also demonstrated that drainage for crop production has severely reduced wetland area and most of the wetland acreage that remains is either forested or degraded. According to Shaw and Fredine (1956), nearly 60 percent of the rural land in this region is cropland and pasture. Erickson (1979) found that declines in wetlands in the United States are mainly caused by wetland drainage and other alterations of associated uplands. In addition, population levels of certain species of waterfowl and other migratory birds are declining and the recreational and economic impacts of wetland loss are a major concern (Dahl and Johnson, 1991). Wooten and Jones (1955) stated that this area, although one of the most altered ecosystems in the USA is still one of the most ecologically rich regions in the world. Of nearly half of the original wetlands remaining were cropped when the weather permits. Frayer et al. (1983) confirmed that agricultural practices often result in sedimentation and addition of pesticides and fertilizers, resulting in degraded wetland vegetation, water quality, and wetland habitats.

Furthermore, Frayer et al. (1983) suggested that losses of wetlands in arid areas are particularly detrimental to wildlife and Dahl (1990) noted that wetlands in California's Central Valley have been reduced from more than 1 640 000 hectares to about 123 000 hectares.

Wood (2000a); Dixon (2001) and Dixon & Convey, (2000) demonstrated that wetlands in Ethiopia are at a critical point in their history, due to a new government policy that attempts to address the increasing food security problems. Wood (2000b) stated that the wetland policy has instructed Ethiopian farmers to intensify wetland agriculture and to start cultivating plots that are currently left to restore naturally. Wood (2000c) and Hailu et al. (2000) agreed that farmers’ indigenous hydrological management knowledge can be sustainable, while the government ultimately possesses the power to change the way that wetlands are managed.

2.7.3 Impacts of irrigated agriculture on wetland ecosystem

Irrigation schemes or water diversions for irrigation have undoubtedly caused adverse effects to wetland ecosystems (Galbraith et al., 2005). At their most severe, these effects have included the submersion of wetlands, or their replacement by upland vegetation communities, with consequent effects on the biota that depend on these wetlands. Documented examples of these extreme cases include the Aral Sea literature by Kotlyakov (1991); Micklin (1988); and Precoda (1991). Similar problems were documented by Scholte et al. (2000); Tchamba et al. (1995); Drijver and Marchand (1985); Wesseling and Drijver, (1993) on impacts of dam construction on the floodplain of the Longone and Benue Rivers in Cameroon. Drijver and Marchand (1985) and Vinke (1996) documented similar

problems in the Senegal delta. In addition, Lemly et al. (2000) demonstrated the impacts of dam construction on the Hadejia-Nguru wetland complex, in Nigeria and the Nanni Swamp in Surinam.

Also, the size of the marine harvest of prawns off the coast of Mozambique is positively correlated with the flow entering the sea from the Zambezi River (Gammelsrod 1996). According to Galbriath et al. (2005), recent declines in marine prawn populations and impacts to the commercial prawn fishery have been ascribed to reduced flows from the Zambezi River due to dams in Mozambique (Collier et al., 1996; DWAF, 2008 a & b). The damming of the Indus in Pakistan, like the Nile example, has also reduced sediment transport with subsequent die-off of mangrove forest communities in the downstream delta (Meynell and Qureshi 1995).

The ecological impacts caused by schemes such as the Aral Sea diversions, the Indus River dam, or the Kano River Irrigation Project are expected and are largely a function of the scale of water diversion (Galbraith, 2005). Although no quantitative relationships have been established, and the resilience of any particular wetland ecosystem will vary depending on other anthropogenic and natural stresses, it may be likely that relatively small percentage diversions may be ecologically sustainable in some wetlands, whereas larger diversions as have occurred in many schemes, are more likely than not to be unsustainable. Also, it is at least possible that the relationship between the scale of the withdrawal or diversion and the ecological impact may not be linear. Furthermore, the ability of a wetland to withstand a level of diversion may be partly a function of the intrinsic variability of the wetland itself (Richardson, 1995). Wetlands that go through marked natural cycles of water inflow may be more resilient than more stable

wetlands. However, given that so little quantitative information concerning ecological impacts has been generated by past irrigation projects, the above considerations are largely speculative.

Unfortunately, too few rigorous studies have been performed to determine the levels of withdrawals that may be adequately protective of the environment; and this is the crucial question determining the likelihood of coexistence of ecological resources and irrigated agriculture (Thibault and Zipperer, 1994). Resilience will be a function of a number of important site-specific factors, including the type of wetland and its intrinsic robustness, and the existing level of stress (natural and anthropogenic). By failing to monitor the ecological consequences of the implementation of irrigation projects, we have lost an important opportunity to understand the relationships between levels of stress (for example, water withdrawals) and ecosystem resilience and impacts (Spaling, 1995). Apart from failing to realize the ecological consequences of the scale of diversions, the other main problem that has contributed to impacts is a failure to plan at the level of the watershed scale.

The literature reviewed concerned situations in which upstream withdrawals had affected downstream wetlands. However, extractions may take place in the wetland itself, to irrigate either surrounding upland areas or other parts of the same wetland (for example, the situation may pertain in many Southern African dambos). If the water being extracted from the wetland is for irrigation of adjacent uplands, but return flows are large, the impacts may be less severe. And if the water is being shunted around different parts of the wetland, the consequences may also be less severe. In these situations, a number of important site-specific considerations arise:

loss to evaporation of the return flow and functionality of different parts of the same wetland ecosystem (Fujioka and Lane, 1997).

Water withdrawals for irrigation exacerbated the effects of other stressors on the wetland ecosystems, resulting in effects that exceed those that would be expected from dewatering, alone. For example, Lake Kus in western Turkey is under stress from a growing use of the lake by the local human population. One of these stresses is the increasing pollution of the lake by organic materials. This, in conjunction with dewatering for irrigation, has resulted in the increasing eutrophication of the lake and changes in the aquatic biota toward an assemblage more characteristic of nutrient rich systems (Altinsacli and Griffiths 2001). Wildlife responses to the implementation of irrigation schemes can, in turn, result in stress to wetlands. In and around the Waza National Park in Cameroon, dewatering of the Logone River has resulted in the loss of prime grazing habitat for wildlife. Elephants have responded differently: they have been displaced from their traditional areas, resulting in damage to wetland (Tchamba et al., 1995).

Moreover, Water diversion schemes from the Indus River are among the largest diversions in the world and total irrigated area covers 12 million hectares. Of total annual inflow of 180 billion m3, 129 billion is diverted for agriculture; while during dry years virtually no water reaches the delta. During normal flow time, the delta supported highly important ecological resources including 260000 ha of mangrove forests. However, due to dewatering and sediment trapping, the diversions upstream have been experiencing erosion of the delta and loss of the mangroves, forest fragmentation, and replacement of mangroves by salt-tolerant species and reduction in area of mangroves from 260000 to 160000 ha (Meynell and Qureshi, 1995).

2.7.4 Wetland degradation due to hydropower development

Hydropower developments in the wetland catchment affect the hydrology and the hydrologic connectivity of the watershed, with cascading impacts on aquatic biota. Ahearn et al. (2005); Bunn & Arthington, (2002); Collier et al. (1996) demonstrated that alteration of natural flow regimes by construction of dams affects the magnitude and timing of river flows and disrupts natural connections between upstream and downstream reaches, between channel and floodplain, and between channel and groundwater. Maintenance of forested areas after dam construction is also a primary management concern for other stakeholders in the catchment, especially municipal water users and those involved with the region’s tourism industry (Kingsford, 2000). Hence, major conservation concerns in the watershed are that hydropower developments may threaten the survival of native aquatic biota and isolate headwater streams (Dyson et al., 2003; Griebler & Avramov, 2015; Korbel & Hose, 2015).

Another important management objective of municipal water users, the tourism industry, and local residents of river basin is maintaining adequate river flows for human uses and for fish habitat (Anderson & Woosely, 2005). Municipal water users express concern that operation of existing and proposed hydropower projects will negatively affect downstream ecosystem (Rosenberg et al., 2000).

Hydropower often requires the use of dams, which can greatly affect the flow of rivers, altering ecosystems and affecting the wildlife and people who depend on those waters (Richter et al., 2006). Often, water at the bottom of the lake created by a dam is inhospitable to fish because it is much colder and oxygen-poor compared with water at the top (Ahearn et al., 2005). When this colder, oxygen-poor water is

released into the river, it can kill fish living downstream that are accustomed to warmer, oxygen-rich water. In addition, some dams withhold water and then release it all at once, causing the river downstream to suddenly flood. This action can disrupt plant and wildlife habitats and affect drinking water supplies.

Furthermore, local residents and the tourism industry worry that the increasing hydropower development will detract from the scenic beauty of the river/wetland, by replacing natural wonders like canyons and waterfalls with concrete impoundments and pipelines (Richter & Thomas, 2007).

These hydropower projects function as water diversion dams, thus their operation results in the ‘de-watering’ of the reach of river between the diversion site and the water return site (Wondzell, 2015). For example, at Sarapiqui catchment in Costa Rica, this ‘de-watered’ reach carries 5-10% of average annual discharge. Discharge reductions in the de-watered reach have been shown to affect the quantity and quality of habitat for aquatic biota and affect the temperature regime of a river (Galbraith et al. (2005); Willis & Griggs (2003).

The ecology of river reaches downstream from the turbines and water release is also altered by hydropower project operations. For instance water releases during peak periods of electricity generation can be linked to abrupt changes in discharge and water temperature. These unnatural fluctuations affect the stability of aquatic habitat for several kilometres downstream and may alter the composition of biotic assemblages in these reaches by favouring species better adapted to highly dynamic environments (Olivas, 2004).

2.7.5 Natural impacts on wetlands

Wetlands have been lost over time as a result of natural processes and new ones created. Examples of a number of natural disturbances which may potentially influence wetlands include floods, cyclones, landslides, temperature extremes and drought (Kevin, 2009; Federal lnteragency Stream Restoration Working Group, 1999). While such disturbances may alter the structure and functioning of wetland systems, wetlands generally appear to be better able to accommodate natural disturbances than anthropogenic disturbances (BredenKamp & Vogel, 2007). The Federal lnteragency Stream Restoration Working Group (1999) argues that natural disturbances are frequently agents for regeneration and restoration. Species of riparian plants, have adapted their life cycles to include the occurrence of destructive high-energy disturbances, such as alternating floods and drought. Wetlands may evolve into dryland as a result of lowered water tables, sedimentation and plant succession, or alternatively be submerged by rising water- tables associated with relative sea level rise or climatic change (Caldwell et al., 2015).

The permanence of wetland impacts may vary from transient or temporary to irreversible (Finlayson & D’Cruz, 2005). If the disturbance is severe enough, it can alter the structure and function of a wetland to a point where the dynamic equilibrium is disrupted. Generally, impacts that change wetland substrate or hydrology are more permanent than those that influence biota (Finlayson and Moser, 1991).

2.8 Groundwater and surface water interactions

2.8.1 Introduction

The interaction between groundwater and surface water are characterised by a high degree of variability and is difficult to quantify. The variability is a result of climate which defines the hydrological input to groundwater and surface water and the hydrogeological variability within the media, where the interaction takes place (Gemitzi and Stefanopoulos, 2011; Hatch et al., 2006). The hydrological inputs and outputs, such as precipitation, evaporation or infiltration are labour-intensive to measure, however, this can usually be quantified with an acceptable uncertainty (Klove et al., 2011a). The uncertainty in quantifying the exchange of water and solutes between surface water and groundwater can be much greater due to our limited knowledge of the geological information. For example, at a riparian wetland, the groundwater can either be directed through the wetland sediments and discharge directly into the stream, or seep to the surface at the boundary between aquifer and wetland and discharge to the stream as overland flow (Rosenberry and LaBaugh, 2008). The determining factors in this case would be the contrast in hydraulic properties of the aquifer and the wetland together with the geometry of the system.

The potential vulnerability of groundwater-dominated lakes, wetlands and streams has to be further investigated in order to manage and understand mainly the exchange of water. From a practical viewpoint this ideally involves a few basic aspects:

 Solute concentrations (for example, nutrients or pesticides) at the interface of the surface water body;

 The spatial and sometimes the temporal distribution of the groundwater discharge to the surface water have to be understood and quantified.  To meet these requirements; the use of hydrogeophysical and environmental tracer techniques can be quite promising for mapping the conditions for seepage on the scale of the lake itself. Groundwater and surface water are often interconnected, should be regarded as a single resource and involve many physical, chemical, and biological processes that take place in a variety of physiographic and climatic settings (Nyquist et al., 2008). Groundwater contributes to rivers in physiographic and climatic settings, even, at times, in situations where streams are primarily losing water to groundwater. Rivers may receive groundwater inflow during some seasons. The quantity of stream flow that is derived from ground-water inflow varies according to physiographic and climatic conditions (Freyer et al., 2006).

GW-SW interaction studies all over the world are well documented. For example, USGS (2003), Harvey et al. (2000) and Brodie et al. (2005), Hornberger et al. (1998) did extensive research, although interactions between surface water and groundwater are complex and unique to a specific location. The interactions of wetlands, headwater streams and lakes against GW have attracted worldwide researchers (Harvey and Bencala, 1993; Gardner, 1999). Even though studies of the interaction of groundwater and surface water concentrated primarily on the interaction of groundwater with streams in alluvial systems, no analytical solutions have been developed (Kalbus et al., 2006). Due to uncertainties, GW-SW interactions need continual improvement (Harvey & Wagner, 2000; Seward & Baron, 2001).

2.8.2 Interaction of groundwater and streams

Groundwater and surface water interact in a variety of physiographic and climatic landscapes (Doell et al., 2012). Hence, development or contamination of one commonly affects the other and therefore, an understanding of the basic principles of interactions between groundwater and surface water (GW-SW) is needed for effective protection and management of water resources.

Streams interact with ground water in all types of landscapes and the interaction takes place in three basic ways:

 Streams gain water from inflow of groundwater through the streambed (gaining stream) (Figure 2.1). Another name for gaining streams is effluent streams. Effluent streams are common in temperate to tropical climates.  They lose water to ground water by outflow through the streambed (losing stream) (Figure 2.2). Losing streams are called influent streams, and are found only in arid climate.  They do both, gaining in some reaches and losing in other reaches (Figure 2.3).

For ground water to discharge into a stream channel, the altitude of the water table in the vicinity of the stream must be higher than the altitude of the stream-water surface. Conversely, for surface water to seep to ground water, the altitude of the water table in the vicinity of the stream must be lower than the altitude of the stream-water surface (Brooks et al., 2004). Contours of water-table elevation indicate gaining streams by pointing in an upstream direction (Figure 2.1B), and they indicate losing streams by pointing in a downstream direction (Figure 2.2D) in the immediate vicinity of the stream.

Figure 2.1 Gaining streams receive water from the groundwater system (A). This can be determined from water table contour maps because the contour lines point in the upstream direction where they cross the stream (B) (USGS, 2013)

Figure 2.2 Losing streams lose water to the groundwater system (C). This can be determined from water table contour maps because the contour lines point in the downstream direction where they cross the stream (D) (USGS, 2013).

Losing streams can be connected to the ground-water system by a continuous saturated zone (Figure 2.2) or can be disconnected from the ground-water system by an unsaturated zone. Where the stream is disconnected from the ground-water system by an unsaturated zone, the water table may have a discernible mound below the stream (Figure 2.3) if the rate of recharge through the streambed and unsaturated zone is greater than the rate of lateral ground-water flow away from the water-table mound. An important feature of streams that are disconnected from ground water is that pumping of shallow ground water near the stream does not affect the flow of the stream near the pumped wells (Taniguchi & Fukuo, 1993).

Figure 2.3 Disconnected streams are separated from the groundwater system by an unsaturated zone (USGS, 2013)

A type of interaction between ground water and streams that takes place in nearly all streams at one time or another is a rapid rise in stream stage that causes water to move from the stream into the stream banks (Mekiso et al., 2015). This process, termed bank storage (Figure 2.4), usually is caused by storm precipitation, rapid snowmelt, or release of water from a reservoir upstream. As long as the rise in stage does not overtop the stream banks, most of the volume of stream water that

enters the stream banks returns to the stream within a few days or weeks (Caldwell et al., 2015). The loss of stream water to bank storage and return of this water to the stream in a period of days or weeks tends to reduce flood peaks and later supplement stream flows. If the rise in stream stage is sufficient to overtop the banks and flood large areas of the land surface, widespread recharge to the water table can take place throughout the flooded area (Wan Jaafar et al., 2011). In this case, the time it takes for the recharged floodwater to return to the stream by ground-water flow may be weeks, months, or years because the lengths of the ground-water flow paths are much longer than those resulting from local bank storage. Depending on the frequency, magnitude, and intensity of storms and on the related magnitude of increases in stream stage, some streams and adjacent shallow aquifers may be in a continuous readjustment from interactions related to bank storage and overbank flooding.

Figure 2.4 If stream levels rise higher than adjacent ground-water levels, stream water moves into the stream banks as bank storage (USGS, 2013). 59

Brunke and Gonser (1997) comprehensively summarize the interactions between rivers and subsurface water, and base flow in many streams constitutes the discharge for most of the year under conditions of low precipitation. On the contrary, under conditions of high precipitation, surface runoff and interflow gradually increase, leading to higher hydraulic pressures in the lower stream reaches, which cause the river to change from effluent to influent condition, infiltrating its banks and recharging the aquifer (Harvey et al., 2002). During flooding, the river contributes flow to bank infiltration, which decreases the flood level and recharges the aquifer. This bank storage volume depends on flood duration, height, and shape of the flood hydrograph, as well as on the transmissivity and storage capacity of the aquifer. During a dry season, however, the release of stored water compensates for a decrease in stream discharge. In some river reaches, the water released to the river from bank storage originating from flood runoff exceeds groundwater discharge under base flow conditions, which creates a buffering effect on the runoff regimes of rivers (Brunke and Gonser 1997).

It is the regularity of base flow conditions that govern perennial, intermittent, or ephemeral stream-discharge conditions in streams. In perennial streams, base flow is more-or-less continuous, whereby these streams are primarily effluent and flow continuously throughout the year (Harvey et al., 2006). Intermittent streams receive water only at certain times of the year and are either influent (losing) or effluent (gaining), depending on the season. In ephemeral streams the groundwater level is always below the channel, so they are exclusively influent when they are flowing (Harvey et al., 2006).

Either gaining, or losing stream channels are most likely to occur when the stream channel is oriented parallel to the alluvial plain. Parallel-flow channels occur when the channel stage and groundwater head are equal (Woessner, 2000). Flow-through river reaches, which occur where the channel stage is less than the groundwater head on one bank and is greater than the groundwater head at the opposite bank, most often exist where a channel cuts perpendicular to the fluvial-plain groundwater flow field (Hoehn, 1998; Huggenberger et al. 1998; Wroblicky et al. 1998).

2.8.3 GW-SW interactions in a catchment

Doell et al. (2012) strongly argue that to understand GW–SW interactions, it is extremely necessary to understand the effects of topography, geology, and climate. In addition to topographic and geologic effects, groundwater flow is affected by climate Sophocleous (2000). Based on their relative position in space, Doell et al. (2012) recognise three distinct types of flow systems-local, intermediate, and regional -which could be superimposed on one another within a groundwater basin. Water, in a local flow system, flows to a nearby discharge area, such as a pond or stream (Boulton et al., 1998). Water, in a regional flow system, travels a greater distance than the local flow system, and often discharges to major rivers, large lakes, or to oceans. On the other hand, an intermediate flow system according to Boulton (1993) is characterized by one or more topographic highs and flows located between its recharge and discharge areas, but, unlike the regional flow system, it does not occupy both the major topographic high and the bottom of the basin.

Tóth (1999) states that flow systems depend on both the hydrogeologic characteristics of the soil-rock material and landscape position. Areas of pronounced topographic relief tend to have dominant local flow systems, and areas of nearly flat relief tend to have dominant intermediate and regional flow systems.

Furthermore, Tóth (1999) demonstrates that in topography-controlled flow regimes, groundwater moves in systems of predictable patterns, and various identifiable natural phenomena are regularly associated with different segments of the flow systems. The interactions of streams, lakes, and wetlands with groundwater are governed by the positions of the water bodies with respect to groundwater flow systems, geologic characteristics of their beds, and their climatic settings (Winter, 1999). Therefore, for a thorough understanding of the hydrology of surface-water bodies, all three factors should be taken into account. As Tóth (1999) points out, such recognition was not appreciated until the 1960s (Tóth, 1963), when the systems-nature of groundwater flow became understood. This recognition of the systems-nature of subsurface water flow has provided a unifying theoretical background for the study and understanding of a wide range of natural processes and phenomena and has thus shown flowing groundwater to be a general geologic agent.

The spatial distributions of flow systems also influence the intensity of natural groundwater discharge. The main stream of a basin receive groundwater from the area immediately within the nearest topographic high and from far areas. Base flow conditions cannot be used as indicators of average recharge, because base flow would represent only a relatively small part of the total discharge occurring down gradient (Ebersole et al., 2015; Hughes & Kapangaziwiri, 2010).

In characterizing larger-scale GW–SW interactions and in estimating the extent and location of such interfaces a geomorphologic perspective is also helpful. For example, Larkin and Sharp (1992) classify stream–aquifer systems (based on the predominant regional groundwater flow component) as

 underflow-component dominated (the groundwater flux moves parallel to the river and in the same direction as the stream flow);  base flow-component dominated (the groundwater flux moves perpendicular to or from the river depending on whether the river is effluent or influent, respectively;); or  mixed.

Larkin and Sharp (1992) conclude that the dominant groundwater flow component, base flow or underflow, can be inferred from geomorphologic data, such as channel slope, river sinuosity, degree of river incision through its alluvium, the width-to-depth ratio of the bank full river channel, and the character of the fluvial depositional system.

Kurtz et al. (2012); Saenger et al. (2005); Storey et al. (2003) demonstrated that the main uncertain factors for predicting river-aquifer water exchange fluxes are riverbed and aquifer properties. A better characterisation of riverbed structures representing more realistic properties may lead to an improved estimation of river- aquifer exchange fluxes (Kurtz et al., 2012).

In another study, Brunke and Gonser (1997) state that hydrologic interactions between surface and ground water occur by subsurface lateral flow through the unsaturated soil and by infiltration into or exfiltration from the saturated zones. In the case of karst or fractured terrain, interactions occur through flow in fracture/

solution channels. Fetter (2001) defined water that enters a SW body immediately, in response to such individual water input events as rain or snowmelt as event flow, direct flow, storm flow, or quick flow, which is distinguished from base flow or water that enters a stream from persistent, slowly varying sources and maintains stream flow between water-input events. Although base flow is derived from drainage of lakes or wetlands, or even from the slow drainage of relatively thin soils on upland hill slopes, base flow is contributed from groundwater flow (Sophocleous, 1998).

As Dunne and Black (1970) and Beven (1983) indicated, if the water table and capillary fringe are close to the soil surface, then not all applied water is necessary to saturate the soil profile thoroughly. This saturation could lead to the discharge of subsurface water onto the surface as return flow. The contributing area of return flow could expand rapidly in an area where the capillary fringe is close to the surface and would be expected to serve as an area of saturation-excess surface- runoff production, so that discharge into the stream would be expected to be a mixture of both event and pre-event water.

The response of any particular catchment could be dominated by a combination of mechanisms, depending on the magnitude of the rainfall event, the antecedent soil- moisture conditions of the catchment, and the heterogeneity in soil hydraulic properties (Sklash, 1990; Woessner, 2000). Thus, during any particular storm event, different mechanisms generate runoff from different parts of a catchment. Surface runoff from these contributing areas is generated either

 by the infiltration excess mechanism, where the rainfall rate exceeds the infiltration capacity of the soil; or

 from rainfall in areas of soil saturated by a rising water table, even in high- permeability soils.

The hydrologic exchange of groundwater and surface water in a landscape is controlled by

 the distribution and magnitude of hydraulic conductivities, both within the channel and the associated alluvial-plain sediments;  stream stage relation to the adjacent groundwater level; and  the geometry and position of the stream channel within the alluvial plain (Woessner, 2000).

The direction of the exchange processes varies with hydraulic head, whereas flow depends on sediment hydraulic conductivity. Storm events and seasonal patterns alter the hydraulic head and thereby induce changes in flow direction. Brunke and Gonser (1997) have distinguished two directions of water flow:

 the influent condition, where surface water contributes to groundwater flow; and  the effluent condition, where groundwater drains into the stream.

On the other hand, variable flow regimes could alter the hydraulic conductivity of the sediment via erosion and deposition processes and thus affect the intensity of the GW–SW interactions.

There are common concepts that apply to all kinds of fluid flow in porous media. The first and most important one is Darcy's Law, which states that the fluid flows through a permeable medium in response to a hydraulic potential field. It simply shows that specific discharge equals the product of the hydraulic potential

difference, i.e. the hydraulic head, the hydraulic conductivity of the medium and the area over which the discharge occurs (Fetter, 1994). Furthermore, the amount of fluid flowing through a rock depends on its ability to conduct fluids, which is a rock property, and the pore-water pressure difference between the two ends of this flow. Darcy's Law describes the fluid flow systems of continental margins except for situations in which the underlying assumption of flow through a bulk medium with a given hydraulic conductivity is not valid. Such situations, for instance include flow through fractured rocks if the fractures are big compared with the area of interest (Zhang, 2015). Due to the fact that Darcy's Law depends on the presence of hydraulic heads, it is necessary to understand what gives rise to these pressure differences.

Mekiso et al. (2014); Woessner (2000) and Stephens (1996) illustrate in areas of low precipitation, the water table is usually well below the base of the channel; as a result, channel seepage is often the largest source of recharge. The magnitude of the infiltration depends upon a variety of factors, such as vadose-zone hydraulic properties, available storage volume in the vadose zone, channel geometry, wetted perimeter, flow duration and depth, antecedent soil moisture, and clogging layers on the channel bottom. If the value of the depth of the water table underneath the stream stage is greater than twice the stream width, the seepage begins to rapidly approach the maximum seepage for an infinitely deep water table (Bouwer and Maddock, 1978).

Despite its general abundance, water does not always occur in the place, at the time, or in the form desired. People struggle to grow crops and other water- consuming products in semiarid regions, and they attempt to use water simultaneously as a pure source. Consequently, society faces increasingly serious

water management problems (National Research Council, 2000; Sophocleous, 1997, 1998, 2000). The decline of groundwater levels around pumping wells near a SW body creates gradients that capture some of the ambient groundwater flow that would have, without pumping, discharged as base flow to the surface water. At sufficiently large pumping rates, these declines induce flow out of the body of surface water into the aquifer, a process known as induced infiltration, or induced recharge. The sum of these two effects leads to stream flow depletion. Quantifying the amount of induced infiltration, which is a function of many factors, is an important consideration in conjunctive water use as water demand increases and the reliability of surface supplies is threatened by stream flow depletion (Sophocleous, 2000).

The ecological integrity of groundwater and fluvial systems is often threatened by human activities, which can reduce connectivity, disturb exchange processes, and lead to toxic or organic contamination. Brunke and Gonser (1997) reviewed human impacts on alluvial hydro systems. Scanlon et al., 2006 summarised human- induced disruptions of hydrologic-exchange processes and their ecological consequences.

2.8.4 Groundwater-surface water interactions in a wetland environment

Wetlands typically occur in areas where groundwater discharges to the land surface or in areas where ground conditions impede the drainage of water (Scoones, 1991a). For situations where impeded drainage occurs, stream depletion effects are unlikely to be significant because the layer of impeded drainage is also likely to inhibit the upward transmission of any pumping effects.

The need for information on wetland and GW-SW interactions has been emphasised by water resources and wetland managers throughout the world. For example, Winter et al. (1998) and Fetter (1994) carried out extensive studies in UK and recommended wetland management based on their studies. The different conclusions reached by various authors about both the functioning and the management of wetlands indicate that there is still more to know about wetlands (McCartney et al., 2005). According to Cowardin et al. (1979) and Mitsch and Gosselink (1993), there seem to be general agreement that for an area to be defined as a natural wetland three main components must be included:

 Wetlands must have water present throughout the year or part of the year, either at the surface or within the plant root zone.  Wetlands must have unique soil conditions that differ from the adjacent upland.  Wetlands must support water tolerant plants (hydrophytes).

Furthermore, Cowardin et al. (1979) demonstrated that each wetland’s hydrology, soil, and plants vary from season to season and from year to year due to alterations by chemical and mechanical processes that include weathering and erosion. With all the above conclusions, defining wetland is not easy, because each wetland has its own unique hydrology, soil and plants according to its location (Jolly et al., 2002). In addition, defining a wetland is subject to individual or professional interpretations. Thus a geologist, hydrologist, biologist or ecologist can each define a wetland according to their professional experience and understanding (National Research Council, 1995).

Since people have gained a better understanding of wetlands and how they benefit the environment, today’s view is quite different and wetland rehabilitation has

taken place in many countries namely Africa, Europe, North America, South America, Asia and Australia. Lack of natural wetlands and recognition of the beneficial role that they can play have led to the construction of man-made wetlands, particularly in urban environments (Dixon, 2003). As with the definition of a wetland, managing both natural and constructed wetlands is not a simple task. There is no uniformly applicable approach that can apply to all wetlands, because they are all different and located in different ecological, hydrological and climatological zones (Cowardin et al., 1979). Even though wetlands are hard to define because of the variations in hydrology, hydric soil, and hydrophytic plants, most people have recognised that wetland protection and management is important (USACE, 1987).

Given the importance of GW-SW interactions within wetland systems it has been considered important to include more detail on this aspect of wetland hydrology in the literature review. Winter et al.(1998) and Fetter (1994) pointed out that one of the important aspects of the hydrology of wetlands is their interaction with groundwater. Such interactions play an important role in determining the water balance of a wetland. Winter et al. (1998) further indicated that SW dominated wetlands typically have both inflow and outflow streams. Seepage wetlands, on the other hand, are groundwater dominated (Britton & Crivelli, 1993). Bloom (1998) indicated that there are wetlands that recharge, where excess surface water recharges the water table. However, Bloom (1998) added that other wetlands are maintained by groundwater discharges. For instance, fens are supported by groundwater discharge, whereas bogs could be groundwater recharge areas (Ellery et al., 2005).

Wetlands are linked through the hydrological system to both upstream and downstream areas. In other words, what happens upstream will affect a wetland, while what happens in a wetland will affect the ecosystem and people living downstream. Wetlands may be influenced by broad environmental changes, such as deforestation and climate change driven by socio-economic factors, including national economic policies and local market conditions (Abbot & Hailu, 2001). Worldwide it has become evident that most aquatic ecosystems have changed as a result of modification of the flow regime caused by river regulation (Poff et al., 1997; McCully, 2001; Bunn & Arthington, 2002; Tharme, 2003; Postel & Richter, 2003; and Brown & King, 2003). The modification of the hydrologic regime can indirectly alter the composition, structure, or function of aquatic, riparian and wetland ecosystems through their effects on physical habitat characteristics, including temperature, oxygen content, water chemistry and substrate particle sizes (Dynesius and Nilsson, 1994; Richer et al., 1996).

Wetlands have gained great attention, since they control surface water flow and downstream water quality (Richardson, 1995; Mitsch & Gosselink, 2000). Due to their ability to decrease the surface runoff peaks and improve the surface runoff and water quality, wetlands are considered as a best management practice method (Larned et al., 2015; Borin et al., 2001; Moore et al., 2002). A number of researchers have been challenged when developing sophisticated wetland models in order to be able to adequately model the wetland dynamics and nutrient transport in wetland environments. Moreover, GW-SW interactions play an important role in wetlands. These hydrological processes affect the dynamics of wetland hydrology and solute transport significantly. Hence, incorporating the effect of GW-SW interactions into wetland models and understanding its

consequences for wetland sites with different characteristics are highly emphasised.

Studies to understand the interaction mechanisms between wetland and ground water have been well documented. Among many, the interactions between ground water and streams, lakes and wetlands are discussed by Winter et al. (1998) in detail. In addition, Wood (2000b) discussed the role of topography, geologic framework, water table level and climate on ground water interaction with streams, lakes and wetlands. In another study, Price and Wadington (2000) indicated the importance of GW-SW interactions in wetlands on wetland functions. Harvey et al. (2006) tried to quantify recharge and discharge in the Water Conservation area in the Central Everglades, United States of America by using the inflow and storage model (OTIS). Furthermore, Restrepo et al. (1998) developed a computer package for MODFLOW to simulate the interaction of wetlands with aquifers.

The hydrology of a created riparian wetland system and observation of water seepage from the wetland into a subsurface environment which has local ground water flow system characteristics was investigated by Koreny et al. (1999). Crowe & Ptacek (2004) developed a numerical model to simulate the ground water– wetland interactions and contaminant transport. These researchers also applied their model to a wetland site at Point Pelee, Ontario, Canada. McHale et al. (2000) investigated stream–wetland interactions by measuring nitrogen in stream and ground water at a riparian wetland site located in the Archer Creek watershed in the Adirondack Mountains of New York State.

The importance of hydrology in the functioning or maintenance of wetlands is widely recognised. However, knowledge of the interlinkages between upstream

land use and water diversions and the resulting impacts on wetland hydrology and spatial dynamics as well as the implications for downstream flows is still limited. Hayashi and Rosenberry (2001) showed the need for understanding the linkages between adjacent uplands and wetlands because of their importance in maintaining the hydrological and ecological integrity of wetlands. Also, Bedford (1999) and Hill (2000) both emphasized the need for a catchment/landscape approach to understand upland-wetland linkages and the potential impact of individual and entire catchment disturbance on the receiving wetland. Therefore, an integrated understanding of both upstream and downstream of the wetland is required.

The available studies in arid and semi-arid zones suggest that GW-SW interactions in wetlands are highly dynamic (Dahm, 1998), are both temporally and spatially complex, and often extend beyond the surface water boundaries of the wetland. As Cant et al. (2003) showed, in zones where groundwater is low in salinity, it has beneficial impacts on wetland ecology which can disappear in dry seasons when groundwater level inflows to wetlands are reduced or even cease. On the contrary, if groundwater is saline, and inflows increase due to raised groundwater levels caused by factors such as land use change and river flow regime, then this may have negative impacts on the ecology of the wetland and its environment (Halse et al., 2003).

Harvey et al. (2006) state the salinity in wetlands of arid and semi-arid environments will vary naturally due to high evaporative conditions, sporadic rainfall, groundwater inflows, et cetera. However, wetlands are often at a particular risk of secondary salinity because their generally low position in the landscape exposes them to increased saline groundwater inflows caused by rising water tables. Terminal wetlands are potentially at higher risk than flow through systems

as there is no salt removal mechanism. As Price et al. (2005) noted there has been almost no modeling of groundwater/surface water interactions in arid/semiarid wetlands with respect to water fluxes, let alone salinity or ecology. Hansen & Gorbach (1997) argued that there is a clear need to develop modeling capabilities for the movement of salt to, from and within wetlands so as to provide temporal predictions of wetland salinity which can be used to assess ecosystem outcomes.

Although there has been a coordinated effort in Australia to collect and collate data on the salinity tolerance and sensitivity of freshwater aquatic biota and riparian vegetation, there are many shortcomings and knowledge gaps in these data, a fact recognised by authors of this work (Borisko et al., 2007). In light of these and other shortcomings identified, Jolly et al. (2002) argue that the data is a useful guide but must be utilised with some caution.

Other authors like James et al. (2005) explored that secondary salinity can impact on wetland biota through changes in both salinity and water regime which result from the hydrological changes associated with secondary salinity. On the other hand, there have been some detailed studies of these interactions for some Australian riparian tree species, though the combined effects on aquatic biodiversity have not yet been fully elucidated, and therefore future research need is highly emphasised (Herczeg et al., 2001).

Rainfall-flow pulses in arid and semi-arid areas have an important indirect role through their impacts on wetland salinity (Reynolds et al., 2004). Schwinning & Sala (2004) indicated that freshwater pulses can be the primary means by which salt stored in both the water column and in the underlying sediments are flushed from wetlands. On the contrary, increased runoff is a commonly observed

consequence of secondary salinity and so wetlands can experience increased surface water inflows which are often higher in salinity than under natural conditions. Moreover, changes in rainfall-flow pulse regimes can have pronounced impacts on wetland GW-SW interactions. According to Schwinning and Sala (2004) and Skinner et al. (2001), it is possible in some situations that the groundwater inflow to a wetland may become so large that it could become a major component of the water balance and hence mask the role of natural pulsing regimes.

Finlayson and D'Cruz (2005) stated that estimates of the extent of wetlands ecosystems worldwide are uncertain, due to misunderstanding over what constitutes a wetland and the difficulties of delineating and mapping habitats with variable boundaries. This is particularly pertinent in arid and semiarid areas where the majority of wetlands are temporary, such as dambos in Zimbabwe (McCartney, 2006). What is certain though is that a large percentage of wetlands have been lost in the last century and that ongoing degradation and loss is occurring worldwide (Williams, 1999). Whilst there are many causes, including drainage and land clearance, they are all related to agricultural, urban and industrial development associated with human population pressure (Finlayson and D'Cruz, 2005).

Subsequently, a number of research activities have been conducted and results are reported on international scientific journals on the function and value of wetlands. The role of wetlands in the hydrological cycle, for flood mitigation, biogeochemical functions, as nutrient and pollution filters for water quality improvement, and maintenance of food webs as habitats for a diverse range of biota has been well documented (Bullock and Acreman, 2003; Land Use and Wetland/Habitat Working Group, 2001). During the past 15-20 years there has also

been interest in the economic value of wetlands for the provision of these services along with fisheries production and wetland ecology, and its value for tourism (Richard, 2007). At the same time there are increasing needs being made on water supplies, and concerns over climate change and the expected increase in extent and distribution of arid and semi-arid areas.

As highlighted by Sophocleous (2002) there has been increasing attention given to the interactions between groundwater and surface water (GW-SW). Similarly, the review of Danielopol et al. (2003) highlights the linkages between groundwater and ecosystems and the ever-increasing human-induced pressures on groundwater systems that have flow on ecological impacts. As far as GW-SW interactions in wetlands are concerned, emphasis has been given to temperate and tropical environments. Wetlands in arid/semi-arid areas have all the problems of temperate and tropical areas, i.e. pollution, drainage, eutrophication and changes to hydrological regime, including surface water impoundment and diversion and groundwater extraction (Cant et al., 2003). But they are also prone to salinization due to human induced changes to the hydrological cycle. Surface water volume is declining and the over-pumping of groundwater beyond natural recharge rates is occurring, lowering the water table and thereby causing an increase in groundwater salinity and ecological degradation (Danielopol et al., 2003).

The role of wetlands in the hydrology of arid and semi-arid environments is still poorly understood, particularly GW-SW interaction. In arid and semi-arid areas, where rainfall is variable, wetland ecosystems provide vital habitat for unique biota in an otherwise dry environment. Due to the temporary nature of many wetlands, and the resultant variability of physico-chemical factors, the biota have evolved unique features and life cycle adaptations that enable them to persist over dry

intervals. Arid/semi-arid wetlands show faunal diversity as high as or greater than in temperate and tropical wetlands (Williams, 1998a; 1998b).

Fortunately, the arid and semi-arid areas contain some of the world’s largest river systems (for example, the Colorado, Nile, and Murray-Darling River systems) as the source of the rivers are from wetter areas (Williams, 1998a). Also, some of the most important wetlands of the world are in the arid/semi-arid zone including the Okavango Delta (Botswana), the Kafue Flats (Zambia), the Hadejia-Jamaare (Nigeria) and the Prairie Potholes (North America) (Kingsford, 1997). Advances in hydrological research have seen surface water and groundwater increasingly being treated as part of the same system (Winter et al., 1999; Winter, 1999; Winter, 2001; Hayashi and Rosenberry, 2002; Sophocleous, 2002) and it is increasingly recognised that sustainable management of wetlands systems requires a multidisciplinary approach which includes both GW-SW hydrology and ecology (ecohydrology or hydroecology). Ecologists have not looked at groundwater issues, and hydrology has often been studied in isolation from ecology (Lamontagne et al., 2005).

This part of literature review brings together the state of knowledge of hydrological processes worldwide, especially GW-SW interaction, and the role of groundwater in wetlands of arid/semi-arid areas. The literature on the ecological impacts of salinity is from Australia where research in this area is more advanced due to the extent of salinisation in that country. However, it is expected that many of the concepts developed from the Australian experience will apply to arid/semi- arid wetlands in other areas of the world that are influenced by groundwater (Herczeg et al., 2001).

Groundwater systems are dynamic three-dimensional flow fields where movement of groundwater is driven by potential gradients (usually described by hydraulic heads) from areas where water is added to the aquifer (recharge) to areas where it is lost from the aquifer (discharge). The flow fields can be comprised of different sizes and depths and can overlie one another. Local flow systems are the most dynamic and the shallowest and therefore have the greatest interaction with surface water bodies (Filippini et al., 2015).

Because the shape of the water table often mimics the shape of the land surface topography, it is generally shallow beneath the riparian zone and deeper below the upland areas (Danielopol et al., 2003). However, because groundwater flow directions are governed by the slope of the water table, and given the elevation of the water table under the upland area is higher than that beneath the riparian zone then groundwater flows into the riparian zone. Conversely, Danielopol et al., (2003) pointed out that if the elevation of the water table beneath the riparian zone is higher than that below the upland area the groundwater will flow from the riparian zone into the upland area.

As Hayashi and Rosenberry (2002) showed it is the relative water table elevation that governs the flow of groundwater between the riparian zone and the wetland. Amoros & Bornette (2002) pointed out at GW-SW interactions can be very dynamic in the short-term as a result of varying river and wetland water levels. In the long-term groundwater exchange directly affects the ecology of surface water by sustaining stream base flow and moderating water level fluctuations of groundwater fed water bodies such as lakes and wetlands (Hayashi and Rosenberry, 2002). This is particularly the case in arid/semi-arid environments, where surface water regimes are vulnerable to rainfall variability and/or river

regulation and abstraction activities, and so the persistence of wetlands can be dependent either completely or partially on contributions from groundwater.

Groundwater and surface water heads govern GW-SW interactions of wetlands which can vary significantly over the short-term. A good example of this is the study of Rosenberry and Winter (1997) which showed that evapotranspiration in an upland area separating two prairie-pothole wetlands in North Dakota (USA), combined with highly variable rainfall, led to the formation of a water table trough between the wetlands in dry seasons and a water table mound in wet seasons, and such dynamic groundwater behaviour affected water levels in the wetlands.

Changes in GW-SW interactions over the long-term could exist when there are changes in the heads driven by factors such as climate change, modifications to the management of the uplands-hillslope (i.e. land use change such as clearing of native vegetation for dryland agriculture, irrigation, forestry, urban development) and the riparian zone (urbanization, agricultural development), and/or changes in the flow regimes of the river due to regulation, channelization, upstream water abstractions, et cetera. For example, Wurster et al. (2003) describe an interesting historical case study where over a 100 groundwater-fed wetlands in Colorado (USA) had disappeared between 1937 and 1995 due to changes in the climate of the region.

Conversely, some land use and river management changes can lead to rises in water tables which result in continual movement of groundwater into ephemeral wetlands. The life cycles of species in arid and semi-arid wetlands require periods of drying which are lost if there is continual movement of groundwater into a wetland. The lower Murray River in south-eastern Australia (Walker, 1992;

Walker and Thoms, 1993; Jolly, 1996) is a good example where changes in upland use and river management contributed to rises in riparian zone groundwater levels.

Local geomorphology strongly governs the exchange of groundwater in wetlands and most wetlands occur at low points in the terrain where heavy textured soils are commonplace due to alluvial depositional processes (Stewart & Thomas, 2008). If the hydraulic conductivity of these clays and silts are lower than that of the underlying aquifer then they can impede groundwater movement between the aquifer and the wetland. The study conducted by Lamontagne et al. (2005) is concerned with a river, and is a good example of the role that heavy textured banks and beds can play in controlling GW-SW interactions in semi-arid floodplains. If the soils are very high in sodium (i.e. as a result of natural or human-induced salinisation processes) then the impedance can be further exacerbated because these soils can disperse and swell when wetted with low salinity surface water, leading to significant reductions in hydraulic conductivity (Jolly et al., 1994).

As demonstrated by a series of theoretical and field studies by Townley and Davidson (1988), Townley and Trefry (2000), Smith and Townley (2002) and Turner and Townley (2006), flow geometry of wetland and groundwater are important controls on the exchange of groundwater at the wetland scale. These studies have highlighted that GW-SW interactions in wetlands can be broadly classified into three flow regime types:

 recharge - wetland loses surface water to the underlying aquifer;  discharge - wetland gains water from the underlying aquifer; or  flow through - wetland gains and losses from GW.

It is important to note that individual wetlands may temporally change from one type to another depending on how the surface water levels in the wetland and the underlying groundwater levels change over time in response to climate, and catchment and river management.

As Roberts et al. (2000) investigated, wetlands have historically been described by their surface water regime, which is characterised by water depth through time and relates to the duration of inundation, seasonality, rate of rise, frequency, interflood level and variability. Their contribution from groundwater is progressively being included into the characterisation of the water regime of wetlands. For example Roberts et al. (2000) use a water balance approach to describe the water regime of wetlands by including surface water, groundwater, atmospheric water, and the storage volume. Hayashi and Rosenberry (2002) refer to the hydroperiod of ephemeral wetlands as determined by climatic factors (precipitation and evaporation), amount of surface runoff and input from groundwater exchange.

The most difficult components of the wetland water balance are groundwater inputs and outputs since they are very small compared to surface water inputs and rainfall. (Hunt et al. (1996) and Hunt et al. (1998)) provide good summaries of methods for measuring groundwater exchange with wetlands. This difficulty in quantifying groundwater inputs and outputs is further complicated by the possible variations in the surface water connection between wetlands and surface water bodies. The majority of literature on groundwater components of wetland water balances concerns studies in temperate areas (e.g. Gilvear et al., 1993; Rosenberry & Winter, 1997, Hunt et al., 1999; Raisin et al., 1999) and they generally do not consider wetland salt balances.

In another study of the transfer of water and chloride between a wetland and its adjacent uplands in a semi-arid area of Saskatchewan, Canada, Hayashi et al. (1998a), (1998b) showed that while there was large infiltration of water under the wetland, less than 0.5% of it recharged the underlying aquifer, the rest moved horizontally in the groundwater to the adjacent upland areas where it was transpired by trees and crops.

As a result, chloride was found to move from the adjacent upland areas to the wetland by mixing with snowmelt runoff, then infiltrate under the wetland and move laterally back up to the uplands with the shallow horizontal groundwater flow. Under the upland, the chloride moves upward in the vadose zone with soil water, and accumulates near the ground surface as the water is lost by evapotranspiration.

Marimuthu et al. (2005) used geochemical and stable isotope data to supplement hydraulic data in order to explain the complex GW-SW interaction processes for a series of coastal dune wetlands in a semi-arid area near Esperance, Western Australia. Water quality (particularly salinity) in the wetland system was being affected by land use changes in the surrounding catchment due to volumetric increases in the influx of surface waters and solutes. However, McCarthy (2005) showed that it was unclear how and why this was affecting the groundwater inputs to the wetlands from regional aquifers, and whether the effects were occurring uniformly over all the wetlands that comprised the system. While a comprehensive water and salt balance was not completed, the study is an interesting one because it illustrates the value in supplementing hydraulic methods with hydrochemistry when investigating complex wetlands systems and their interactions with groundwater (Marimuthu et al., 2005).

Although Wurster et al. (2003) did not assess salt balances; they demonstrated that the water balance of groundwater-fed wetlands can be dramatically disturbed by changes in the groundwater conditions in the surrounding areas. Their example was the disappearance of wetlands in the arid Great Sand Dunes National Monument in Colorado, USA. Using a range of hydrological, hydrogeological, hydrochemical, and ecological techniques they concluded that these wetlands were in fact ephemeral features that disappeared for several years during dry periods in which regional water table levels drop.

These studies mentioned in the literature review are examples of the efforts toward a better understanding of wetland dynamics by incorporating GW-SW interactions into wetland models. This study contributes to these research efforts by investigating the effect of GW-SW interactions on wetland hydrology for different wetland characteristics.

In arid/semi-arid areas the interactions between wetlands and GW are highly dynamic, are both temporally and spatially complex, and often extend beyond the surface water boundaries of the wetland (Johns et al., 2015). In areas where groundwater is low in salinity, it has beneficial impacts on wetland ecology which can be diminished in dry times when groundwater levels and hence inflows to wetlands are reduced or even cease. Conversely, if groundwater is saline, and inflows increase due to raised groundwater levels caused by factors such as land use change and river regulation, then this may have detrimental impacts on the ecology of a wetland and its surrounding areas.

2.8.5 GW-SW interactions in Karst terrain

Karst may be broadly defined as all landforms that are produced primarily by the dissolution of rocks, mainly limestone and dolomite (Csaky, 2003). Karst terrains are characterised by:

 closed surface depressions of various sizes and shapes known as sinkholes;  an underground drainage network that consists of solution openings that range in size from enlarged cracks in the rock to large caves; and  highly disrupted surface drainage systems, which relate directly to the unique character of the underground drainage system (Devilbiss,1995).

Groundwater recharge is very efficient in karst terrain because precipitation readily infiltrates through the rock openings that intersect the land surface. Water can move at faster rates through karst aquifers and moves slowly through fine fractures and pores and rapidly through solution-enlarged fractures and conduits (Gillieson and Spate, 2003). As a result, the water discharging from many springs in karst terrain may be a combination of relatively slow moving water draining from pores and rapidly moving storm-derived water.

Water movement in karst terrain is difficult to predict because of the many paths groundwater takes through the network of fractures and solution openings in the rock. Because of the large size of interconnected openings in well-developed karst systems, karst terrain can have true underground streams (White, 1988). These underground streams can have high rates of flow, in some places as great as rates of flow in surface streams. Furthermore, it is practical for medium-sized streams to disappear into the rock openings, thereby completely disrupting the surface

drainage system, and to reappear at the surface at another place, which might even be in a different surface water catchment (Williams, 1993).

2.8.6 GW-SW interactions in glacial and dune terrain

Glacial and dune terrain is characterised by landscape of hills and depressions. Lakes and wetlands in glacial and dune terrain can have inflow from groundwater, outflow to groundwater, or both. The interaction between lakes and wetlands and groundwater is determined to a large extent by their position with respect to local and regional groundwater flow systems. A common conception is that lakes and wetlands that are present in topographically high areas recharge groundwater, and that lakes and wetlands that are present in low areas receive discharge from groundwater (Marti, 2011). However, lakes and wetlands underlain by deposits having low permeability can receive discharge from local groundwater flows system even if they are located in a regional groundwater recharge area. Conversely, they can lose water to local groundwater flow systems even if they are located in a regional groundwater discharge area (Figure 2.5).

Figure 2.5 In glacial and dune terrain, local, intermediate, and regional groundwater flow systems interact with lakes and wetlands. (USGS, 2013).

2.8.7 GW-SW interactions in coastal terrain

Coastal terrain extends from inland scarps and terraces to the ocean (Figure 2.6); which is characterised by (1) low scarps and terraces that were formed when the ocean was higher than at present; (2) streams, estuaries, and lagoons that are affected by tides; (3) ponds that are commonly associated with coastal sand dunes; and (4) barrier beaches and bars. Wetlands cover extensive areas in some coastal terrains (Cook, 2012 & Coggin, 2008)

The interaction of groundwater and surface water in coastal terrain is affected by discharge of groundwater from regional flow systems and from local flow systems associated with scarps and terraces. The local flow systems associated with scarps and terraces are caused by the configuration of the water table near these features. Where the water table has a downward break in slope near the top of scarps and terraces, downward components of groundwater flow are present; where the water table has an upward break in slope near the base of these features, upward components of groundwater flow are present.

Figure 2.6 In coastal terrain, small local groundwater flow cells associated with terraces overlie more regional groundwater flow systems (USGS, 2013)

2.8.8 GW-SW interactions in River valley terrain

The interaction of groundwater and surface water in river valleys is affected by the interchange of local and regional groundwater flow systems with the rivers and by flooding and evapotranspiration. Small streams receive groundwater flow primarily from local flow systems, which usually have limited extent and are highly variable seasonally. Therefore, it is usual for small streams to have gaining or losing reaches that change seasonally. River valley alluvial deposits range in size from clay to boulders, but in many alluvial valleys, sand and gravel are the predominant deposits (Figure 2.7).

Figure 2.7 Surface water exchange with groundwater is associated with abrupt changes in streambed slope (A) and streambed meanders (B) (USGS, 2013).

2.8.9 GW-SW interactions in mountainous terrain

The hydrology of mountainous terrain is characterized by highly variable precipitation and water movement over and through steep land slopes (Figure 2.8). On mountain slopes, macropores created by burrowing organisms and by decay of plant roots have the capacity to transmit subsurface flow downslope quickly (USGS, 1988). In addition, some rock types underlying soils may be highly weathered or fractured and may transmit significant additional amounts of flow through the subsurface. In some settings this rapid flow of water results in hillside springs (USGS, 1985).

A general concept of water flow in mountainous terrain includes several pathways by which precipitation moves through the hillside to a stream. Between storm and snowmelt periods, stream flow is sustained by discharge from the groundwater system. During intense storms, most water reaches streams very rapidly by partially saturating and flowing through the highly conductive soils. On the lower parts of hill slopes, the water table sometimes rises to the land surface during

storms, resulting in overland flow. When this occurs, precipitation on the saturated area adds to the quantity of overland flow (McGuire & McDonnell, 2010; USGS, 1988).

Near the base of mountainsides, the water table intersects the steep valley wall some distance up from the base of the slope (Figure2.8) that results in perennial discharge of groundwater and, in many cases, the presence of wetlands (Harvey et al., 2004). A more common hydrologic process that results in the presence of wetlands in some mountain valleys is the upward discharge of groundwater caused by the change in slope of the water table from being steep on the valley side to being relatively flat in the alluvial valley (Figure 2.8).

Figure 2.8 In mountainous terrain, groundwater can discharge at the base of steep sloped (left side of valley) at the edges of flood plains (right side of valley), and to the stream (USGS, 2013)

Another dynamic aspect of the interaction of groundwater and surface water in mountain settings by Wilson & Guan (2004) is caused by the marked longitudinal component of flow in mountain valleys. The high gradient of mountain streams, coupled with the coarse texture of streambed sediments, results in a strong down- valley component of flow accompanied by frequent exchange of stream water with groundwater. Streams flowing from mountainous terrain commonly flow across alluvial fans at the edges of the valleys. Streams in this type of setting lose water to groundwater as they traverse the highly permeable alluvial fans seepage of water from the stream can be the principal source of aquifer recharge.

2.9 Methods of investigation of GW-SW interactions 2.9.1 Wetland water budget

Water budgets provide scientific information for evaluating availability and sustainability of a water supply (Healy et al., 2007). A water budget shows the rate of change in water stored in an area (watershed) and is balanced by the rate at which water flows into and out of the area (Changnon, 1993). It is a water management tool that helps to understand hydrologic processes and provides a foundation for effective water-resource and environmental planning and management (Lerner et al., 1990). McCartney et al. (2005) suggested the main components of the natural water balance of a wetland are given below and quantifying the importance of each component helps to understand the dynamics and functioning of individual wetlands:

 Inflows from river channels originating from the upstream catchment area.  Inflows from adjacent hillsides, springs and tributaries flowing into the wetland.  Inflows from groundwater lying below the wetland.

 Inputs from rain falling directly on the wetland.  Outflows to downstream river channels.  Drainage to groundwater (recharge from the wetland area).  Evapotranspiration losses from the wetland area.  Changes in storage (surface pools, soil moisture and groundwater below the wetland).

In the GaMampa Valley (Limpopo Province of South Africa), Masiyandima et al. (2006) reported that runoff from the local catchment and groundwater components of the water balance were effectively nil. Masiyandima et al. (2006) argued that the peat soils in the valley suggest that there is no direct runoff to the river, although it is possible that some runoff may occur when the soil is saturated. It is therefore not easy to develop a fixed water budget that can be applicable in a watershed (McCartney, 2006). Unmetered extraction, evaporation, ungauged tributary flows, overbank flooding losses, flood return flows, human activities, errors in instruments and weather variability are some of the uncertainties associated with water budgets. Winter (1981) stated that errors in measurement of individual rainstorms due to gauge placement and spacing can be up to 75 percent. It is therefore clear that while water budget methods can be extremely useful for developing an understanding of the dynamics of wetlands, they are not simple to quantify and errors made in quantifying one of the components can lead to false conclusions about the hydrological functioning of wetlands.

In the protection and management of lakes, wetlands and rivers, water budgets are always central because they indicate the starting framework on ecology, the use of the water body for water supply or industry, or recreational use. For example, the residence time of water in a lake can be calculated based on the estimated fluxes in

or out of a lake. But the interaction between groundwater and surface water is not only important in terms of water budgets, but also because chemical solutes can be transported by groundwater to surface water bodies.

2.9.2 Piezometers and wells

Installation of piezometers and wells are probably the most commonly used tools to interpret the exchange of flow of water between surface waters and connecting aquifers (Lee, 1985; Kishel and Gerla, 2002; Simpkins, 2006). In catchments, wells are mostly used to establish the overall flow direction in the aquifer. With continuous monitoring, transient effects in lake stage, groundwater table or piezometric head is observed and used to understand either the short term or long term temporal changes of GW-wetland and lake interaction. Measurements of piezometric head will often constitute the basic observation/data for calibration of a catchment groundwater flow model (Kurtz et al., 2014; Shaw et al., 1990; Hunt et al., 2006). Closer to the GW-lake and wetland interface, installation of piezometer- transects are often used in order to characterise small-scale heterogeneity and its effect on groundwater-surface water exchange (Kishel and Gerla, 2002).

Small-scale heterogeneity can also be characterised by the use of hydraulic equipment such as potentiomanometer as described by Winter et al. (1998). This device measures the hydraulic gradient between the lake/wetland and aquifer. Besides measurement of piezometric heads or lake-groundwater hydraulic gradients, piezometer and wells are used for taking water samples, conducting hydraulic test of aquifer properties (Simpkins, 2006). Hydraulic conductivity and surface water-aquifer gradients can be used for a simple flow net analysis or

segmented lakeshore water budget calculations applying Darcy’s law (Rosenberry and LaBaugh, 2008).

2.9.3 Seepage meters

Seepage meters have been used extensively to quantify the exchange of water through the lake and wetland beds (Lee, 1985; Cherkauer & Nader, 1989; Belanger and Kirkner, 1994; Rosenberry et al. 2000; Kishel and Gerla, 2002; Schneider et al., 2005). Measurements from seepage meters generally need no post-processing although most users multiply the measured flux with a correction factor (Rosenberry and Manheer, 2006).

The use of seepage meters is labour intensive if the goal is to obtain a spatially- distributed estimate of the flux; provided measurements are carried out at many locations. Technical advances has somewhat solved this problem by replacing the sampling with an automated flow meter. Automated seepage meters have been applied and tested with the electromagnetic and heat pulse methods as the most popular (Taniguchi and Fukuo, 1993; Rosenberry & Winter, 1997; Taniguchi et al., 2008). Rosenberry & Manheer (2006) found that some of the spatial heterogeneity of groundwater discharge through surface water beds can be handled by gauging seepage meters.

Other chemical compounds such as sodium, magnesium, chloride, dissolved organic carbon, strontium isotopes, rare earth elements, and sulphur hexafluoride, have been applied to quantify groundwater exchange with lakes (Labaugh et al., 1997; Ojiambo et al., 2003; Wollschläger et al., 2007). In some cases the geo- biochemical processes occurring at the interface between lakes and groundwater

result in differences of electrical conductivity to detect zones of groundwater discharge (Lee, 1985).

2.9.4 Temperature

Stonestrom & Constanz (2007) pointed out that temperature plays a key role in the health of a stream’s aquatic life, both in the water column and in the benthic habitat of streambed sediments. Furthermore, Constanz et al. (2014) confirmed that stream temperatures are influenced by exchanges between streams and nearby ground water; protecting stream habitat and water supplies thus requires an adequate understanding of ground-water movement near streams. Similarly, Rau et al. (2010) stated that heat provides a natural tracer of ground-water movement that is readily tracked by measuring temperature. Alley et al. (2002) agrees that water that moves between a stream and adjacent sediments carries with it measureable amounts of heat. Therefore, solar-driven temperature fluctuations at the land surface provide signals for tracing exchanges between surface water and ground water.

During the last decade, the use of temperature in surface water beds to directly estimate groundwater discharge rates has become more widespread (Jensen and Engesgaard, 2010, Hatch et al., 2006; Anderson & Woessner, 1992; Lee, 1985; Silliman and Booth, 1993; Rosenberry et al., 2000).

2.9.5 Hydrogeophysics

Hydrogeophysical methods have been used to distinguish groundwater-surface water interactions such as resistivity profiling if the electrical properties of the two water bodies are different. This is observed at the interface between groundwater

and marine environments (Taniguchi et al., 2008; Andersen et al., 2007). However, such difference is not observed between inland lakes and groundwater. Pollution of either lake or groundwater with solutes changes the resistivity, which can be used to identify recharge of lake water through a receiving aquifer or discharge pathways of groundwater to lake systems. Geophysical methods can also be used to investigate the geological framework or geometry of an aquifer (Corriels and Dahlin, 2008) or in-lake sedimentation (Buynevich and Fitzgerald, 2003).

2.9.6 Hydrological models

Models are needed in order to understand why a flow system is behaving in a particular observed manner and to predict how a flow system will behave in the future. Furthermore, models can be used to analyse hypothetical flow situations in order to gain generic understanding of that type of flow system (Anderson and Woessner, 1992).

The term model refers to any representation of a real system. A conceptual model is a good tool to understand a groundwater flow system. Conceptual models are static and describe the current condition of a system. In order to make predictions of future behaviour, it is necessary to have some sort of dynamic model that is capable of manipulation. There are many types of dynamic models of groundwater flow, namely, physical scales models, analog models, and mathematical models (Wondzell et al., 2009 & Witte et al., 1992).

Mathematical models rely upon the solution of the basic equations of groundwater flow, heat flow, and mass transport. The simple mathematical model of groundwater flow is Darcy’s law and to apply it one needs to have a conceptual model of the aquifer and to develop data on the physical properties of the aquifer

system, the potential field, and the fluid properties. Darcy’s law is an example of an analytical model and to solve such problems one needs to know the initial and boundary conditions of the flow problem (Fetter, 1994).

Numerical models are used when there are complex boundary conditions or where the value of parameters varies within the model area (Hamid, 2012). Numerical solutions to the flow, heat, and mass transport equations require that they be recast in an algebraic form. These recast equations are numerical approximations and the solutions obtained are also approximations. The equations are shown most commonly in matrix form; and are solved on a digital computer and are one of the important developments in hydrogeological investigations during the last 30 years (Fetter, 1994).

Stochastic models of groundwater flow are based on statistical theories and have been applied for determination of head and velocity fields as well as solute transport problems (Dagan, 1986; Gelhar, 1986; Rubin and Dagan, 1992a). Since the early 1980s a large number of scientific papers have been published, in which many different types of stochastic models of groundwater flow have been described. However, these manuscripts are difficult for people not trained in the specific mathematics utilised to read and understand.

Groundwater models have been applied to four general types of problems, namely, groundwater flow, solute transport, heat flow, and aquifer deformation (Mercer and Faust, 1981). In addition, two broad classes of models have appeared: those that deal with flow through porous media and those that deal with flow through fractured media. A sand and gravel or sandstone aquifer is an example of an aquifer best described by use of porous-media model; whereas a fractured

crystalline rock with widely spaced fractures would be an example of an aquifer best described by use of a fractured-rock model (McDonald and Harbaugh, 1988).

Groundwater flow models have been applied to the study of regional steady-state flow in aquifer systems; regional changes in hydraulic head caused by changes in discharge or recharge; changes in head near a well field, dewatering well system, injection well, or infiltration basin; and surface water-groundwater interactions (Pinder and Gray, 1977; Fetter, 1994).

As the computational power has increased the models have evolved from vertical 2D simulations of aquifer-lake sections (Winter 2000) to 3D models simulating flow regime and controls on the lake-groundwater interaction (Cheng and Anderson, 1993; Townley and Trefry, 2000; Genereux and Bandopadhyay, 2001; Turner and Townley, 2006). Besides the exchange of water, models have been used to simulate exchange of natural tracers (Krabbenhoft et al., 1990; Wollschläger et al., 2007) and groundwater discharge of nutrients (Shaw et al., 1990; Taniguchi & Wakawa, 2001; Kang et al., 2006; Nakayama and Watanabe, 2008).

2.9.7 Isotopes and hydrochemistry

Reference has already been made to the use of isotope and geochemical tracers for understanding GW-SW interactions. This section of the literature review summarises the approaches to using isotopes and hydrochemistry in understanding wetland processes in more detail. Gibson et al. (2005); Coplen et al. (2000), Clark & Fritz (1997) and McDonnell & Kendal (1992) defined isotopes as forms of a given chemical element that have different atomic masses. For a particular element, Clark and Fritz (1997) and Coplen & Kendall (2000) indicated that the

isotopes have the same numbers of protons, and therefore the same atomic number, while each isotope has a different number of neutrons and therefore a different atomic mass.

2.9.7.1 Stable Isotopes

Stable isotopes are those isotopes that do not undergo radioactive decay, so their nuclei are stable and the masses remain the same (Dansgaard, 1964; Gat, 1996; Williams, 1997 & Coplen, 1994). The common stable isotopes extensively used in hydrological studies are H, C, N, O, S, B, and Li (Hooper & Shoemaker, 1986; Yurtsever & Gat, 1981). For example, oxygen has three stable isotopes, 16O, 17O, and 18O and hydrogen has two stable isotopes, 1H (protium) and 2H (deuterium) and one radioactive isotope-3H (tritium) (Mekiso, 2013, Schulte et al., 2011; Gat & Kemndal, 1994; Clark & Fritz, 1997). The stable isotopes of 18O (oxygen-18) and 2H (deuterium) are frequently used to provide information on hydrological processes, including groundwater-surface water interactions (Winter, 1999; Sophocleous, 2002; Harvey, 2005).

Stable isotopes have been applied to surface water and subsurface water research for decades. Dincer (1968) and Dingman (2002) proposed that oxygen (18O) and deuterium (2H) could be used to estimate water balances. Similarly, decades later Taylor (1993) and Kraemer & Genereux (1998) showed that the ratio between 16O and 18O isotopes can be used to estimate groundwater inflow and outflow with a mass balance approach. Krabbenhoft et al. (1990) further showed that oxygen isotopes generally can be used as a tracer between groundwater and surface water interactions. The general principle of these studies rest on the fractionation between 16O and 18O when water evaporates. Water molecules containing the

lighter 16O evaporate more than that of water containing the heavier 18O. Therefore, surface water exposed to evaporation will become relatively enriched by the 18O isotope compared to average precipitation or groundwater (Appelo and Postma, 2005).

Studies by Reddy et al. (2009) have shown that characterization of seasonal variation of δ18O in groundwater and surface water can be used to determine mean lake residence time. Stets et al. (2010) showed by using a time series model, that even at lakes with residence times lower than 0.5 year, the groundwater-lake exchange can be determined if enough seasonal δ18O-data are obtained.

The isotope fractionations that accompany evaporation from the ocean and other surface water bodies and the reverse process of rain formation account for the most notable changes (Gat, 1996). One naturally occurring example of kinetic fractionation is the evaporation of seawater to form clouds (Gat and Gonfiantini, 1981). The water molecules in the ocean contain an O16 atom, in which a very small proportion of those molecules contain an O18 atom. When seawater evaporates, it forms water vapour and, the water molecules consisting of O18 tend to stay in the ocean instead of evaporating into the atmosphere because they are slightly heavier. So the proportion of O16 in water vapour is higher than seawater. Over time, ocean water gets slightly enriched in the isotope O18. The warmer the ocean water is, the stronger this difference becomes (Coplen et al., 2000; Rozanski et al., 2001).

The average relationship between hydrogen and oxygen isotope ratios in natural terrestrial waters, expressed as a worldwide average can be calculated by applying the Global Meteoric Water Line (GMWL) equation : D = 8 18O+10 (Craig,

1961b). Craig (1961b) also demonstrated that a meteoric water line can also be calculated for a given area, and used as a baseline within that area (Figure 2.9). Kinetic fractionation will cause the isotope ratios to vary between localities within that area.

Figure 2.9 Processes that could alter the water’s signature as a result of differences in the degree to which the various isotopes participate in chemical and physical processes (Evaporation

from open surface, H2S exchange, hydration of silicates, CO2 exchange, high/low temperature exchange with rock minerals), or due to the rates of interaction (source: Harvey, 2005).

Gat et al. (2003) found that comparison of the stable isotope data for surface water and groundwater samples relative to the global or local meteoric water lines can provide information on processes. For example, isotopically light water molecules

evaporate more efficiently than isotopically heavy water molecules (Rozanski et al., 2001; Gat and Gonfiantini, 1981). Due to this variability, Rozanski et al., (1993) indicated that in isotopic vapour pressures, evaporation produces residual water enriched in the heavier isotopes relative to the initial isotopic composition. Therefore water that has undergone evaporation lies to the right of the local meteoric water line due to this enrichment (Coplen, 1993). The trend line for evaporation from surface water tends to have a slope between 4 and 6 (Figure 2.10), with a slope less than 4 indicating evapotranspiration of soil water in the unsaturated zone (Allison, 1988; Harvey, 2005).

According to Butler (1998), water samples collected for isotopic analysis should be stored in bottles with tight closures, such as caps with conical plastic inserts. Neal et al. (1990) collected water samples in 1000 ml polyethylene (HDPE) narrow- mouth round bottles for both isotopic and chemical analyses. Prior to sampling, brand new HDPE bottles were rinsed with stream water at least three times, were filled (with no air gaps above the liquid) to minimise post-sampling alteration in water isotopic composition and were stored immediately in a paper box (Rozanski et al., 1993).

Coplen (1993) and Cook and Herczeg (2000) reported that oxygen and hydrogen stable isotopic ratios are measured by isotope mass spectrometry. Hydrogen analysis is done on hydrogen gas obtained through high-temperature reduction of water on metal (Kendall and Coplen, 1985). Oxygen analyses are done on carbon dioxide that has equilibrated with water at a constant temperature (Epstein and Mayeda, 1953). Oxygen and hydrogen isotope compositions are commonly reported relative to an agreed sample of ocean water, referred to as the Standard Mean Ocean Water (SMOW), representing the largest and most homogenous

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(salty) water body. Stable isotope ratios of deuterium/hydrogen (2H/1H) and 18O/16O of water are conventionally expressed as units of parts per thousand (per mil, ‰) deviation from SMOW (Gat et al., 2003).

Figure 2.10 The meteoric relationship for 18O and 2H in precipitation (Source: Mekiso, 2011; Craig, 1961b)

2.9.7.2 Radioactive isotopes

Gat (1996) defined radioactive isotopes as nuclides that have unstable nuclei that decay, emitting alpha, beta, and sometimes gamma rays. Such isotopes eventually reach stability in the form of non-radioactive isotopes of other chemical elements, termed radiogenic daughters. Decay of a radionuclide to a stable radiogenic daughter is a function of time measured in units of half-lives (Coplen & Kemndal, 2000). According to Gibson et al. (2005), radioactive isotopes are useful indicators

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of the time that water has spent in the groundwater system. For example, tritium (3H) is a well-known radioactive isotope of hydrogen that had peak concentrations in precipitation in the mid-1960s as a result of nuclear testing conducted at that time (Clark and Fritz, 1997).

Tritium as a form of hydrogen is found naturally in both air and water. Tritium is most useful for distinguishing between pre-bomb and post-bomb recharge. Tritium is a naturally occurring radionuclide as well as one that is artificially produced. It has one proton and two neutrons and emits low-energy beta particle (Craig, 1961a; Rozanski et al., 2001). Tritium is naturally produced in the atmosphere by cosmogenic processes and interacts with atmospheric nitrogen and oxygen. Atmospheric tritium is formed when cosmic rays bombard nitrogen to yield 3H; and this occurs according to the following reaction: 14N + n 12C + 3H (2.1) where n is a neutron from cosmic radiation. Tritium atoms then combine with oxygen, forming water that subsequently falls as precipitation. Small amounts of natural tritium are also produced by alpha decay of lithium-7 in the earth (Schlosser et al., 1988).

Tritium decays to 3He by beta particle emission, and knowing this decay rate allows for a more accurate shallow groundwater recharge age. 3H/3He ratios are useful for groundwater ages ranging from several months to less than 50 years (Schlosser et al., 1988). Natural concentration of tritium in precipitation is between 4 and 20 TU, in the northern hemisphere is between 10 and 20 TU and less than 10 TU in the inter-tropical belt and the southern hemisphere. Tritium was produced in all types of atmospheric nuclear tests between 1952 and 1963 (Solomon et al., 1992). Tritium as a part of water takes place in the water cycle and the possibility

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of measuring the low level of its radioactivity gives a chance to use tritium as a natural tracer in the water systems. It is especially useful for tracing groundwater movement in young hydrologic systems and for determining the relatives ages of groundwater because it has a short half-life of 12.4 years (Villa & Manjón, 2004). The concentration of naturally-produced tritium in precipitation prior to 1954 was estimated to be 5 to 24 tritium units (TU). However, tritium was produced in large amounts during atmospheric nuclear tests conducted during 1950s and 1960s (Fontes & Edmunds, 1989). For example, the progress in nuclear testing increased tritium in Arizona precipitation to levels as great as 4,400 TU (GNIP, 2005). The average tritium concentration in Arizona precipitation for the period 1962-1965 was 1140 TU (Rozanski et al., 2001). After the Nuclear Test-ban Treaty in 1963, this level decreased steadily to present levels of about 8–10 TU. On the other hand, it is estimated that in 1987 all 417 nuclear power stations in 26 countries released approximately 680,000 Curies of tritium into the environment (Fontes &Edmunds 1989).

Nowadays, the levels of tritium in the atmosphere are those of natural origin before the nuclear tests. Furthermore, nuclear power plants (NPP), for both civilian and military uses of nuclear energy, have become a significant source of tritium in today’s environment (Rozanski et al., 2001). These facilities release tritium mostly into the close surface waters and therefore the global distribution of tritium is not uniform. Thus, a local radioactive impact can be observed in the vicinity of Nuclear Power Plants, where the tritium activity concentration in waters might be over the natural levels (Coplen, 1993).

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2.9.7.3 Hydrochemistry

Hydrochemistry plays a key role in the biological, chemical and physical processes in small catchment water movement (Jeffries et al., 1988). It is associated with terrestrial processes, including plant decomposition, soil cation exchange, chemical weathering, biological uptake and mineralisation. In hilly areas of the Karoo,

Adams et al. (2001) determined that Ca (HCO3)2 type waters are prevalent, while the dominating water types in topographical flat areas are NaCl. Saline soils are formed in areas where water is close to or at the surface and salts are leached to the subsurface during significant recharge periods. Neal et al. (1990) confirmed that these important findings are good tools for identifying suitable locations of future groundwater developments. Sprinkle (1989); Gat (1996); Katz et al. (1997) and Kumaresan (2006) demonstrated that major ions data may be presented in graphical format, of which the most useful plots are the trilinear diagram that show the total major anion or cation composition on separate or combination (Piper) diagrams (Figure 4. 6 in methodology chapter).

Gonfiantini (1986); Coplen et al. (1991) and Mazor (1997) indicated that major anions (chloride, bromide and sulphate) can be determined by ion chromatography and major cations (calcium, magnesium, sodium and potassium) by atomic absorption spectrophotometry (AAS) or by inductively coupled plasma - atomic emission spectrometry (ICP-AES). These are routinely undertaken in most analytical laboratories and the accuracy must be demonstrated both by the use of appropriate standards and also by use of the ionic balance to check electrical neutrality (Coplen et al., 2000).

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2.10 Wetland management

Wetland management strategies are developed at watershed or landscape scales, yet specific guidance about how to relate such strategies back to the site scale, where management decisions are ultimately implemented, tends to be limited (EPA, 1992; DWAF, 2005). Barbier (2011) proposed that wetland management generally involves activities that can be conducted within, and around wetlands, both natural and man-made, to protect, restore, manipulate, or provide for their functions and values. Barbier (1997) added that the management goal for natural wetlands is generally constrained by regulatory and other government programme requirements to the protection of existing functions or restoration of degraded functions. Hook (1988) confirmed that the management goal for undisturbed natural wetlands is typically to keep-up existing functions. Kusler (2003) and Baskaran et al. (2004) found that the two major aspects of managing wetlands for protection include stopping human misuse of wetlands and maintaining natural processes in surrounding lands.

Payne (1994) demonstrated that the wetland type and landscape position, surrounding land uses, vegetation quality, presence or absence of rare or endangered species, surface water quality (Hughes and Munster, 2010), wildlife habitat, and cultural values are the major issues to account for when establishing a management strategy for a wetland. The goal of protecting a wetland's existing functions can be incredibly complex in the modern landscape, since it involves minimizing the human-induced changes affecting the natural forces that shape and sustain a wetland, such as hydrology, climate, biogeochemical fluxes, fire, and species movement (Wenzel, 1992).

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The stability of wetlands has been undermined by development initiatives that ignore indigenous knowledge in wetland hydrology (Dixon, 2001; Hailu et al. ,2000) reported that local or indigenous knowledge develops over time from experience and a detailed understanding of local environmental conditions, and could be modified in response to changing conditions. Furthermore, Dixon (2001) explained that farmers’ indigenous knowledge must be recognized and must not be ignored for the sustainability of these important eco-systems. However, there are also some areas where knowledge from scientific monitoring is greater than local knowledge. Both indigenous and scientific knowledge are important tools that can help in wetland management (Dixon, 2001 and Ellery et al., 2005).

Wood (2000a) demonstrated that unpredictable climatic conditions and government policy have been impacting wetland management in African continent. Farmers argue that external influences on their management practices have been very small and management techniques, such as drainage design, have been adapted by their communities through generations (Hailu, 1998). While no wetland farmers are experimenting greatly with new management techniques introduced by wetland scientists, there were many examples of small-scale modifications to existing management practices and tools. Wetland management programmes can only be achieved if the necessary funding is available and where community participation is included (Hailu and Abbot 1999).

Road construction has contributed to habitat change and disturbance and has impacted on wetland habitat populations in the world (Hink and Ohmart, 1984). The quantity and quality of wetland habitats can significantly be diminished in addition to a reduction in wetland area. For unavoidable road alignments through wetlands, it is, however, possible to reduce the negative impacts during

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construction (Dixon and Convey, 2000). In addition, efforts should be made during construction to minimize loss of habitats by making use of existing roads for all transportation. Rheinhardt et al. (1997) demonstrated that all topsoil removed for construction should be stockpiled and used as surface fill during the reclamation of the project area. Furthermore, at the completion of the construction works, disturbed areas should be re-vegetated using native species that can grow fast and cover the exposed soil in easily erodible areas and at the same time the wildlife should not be exposed.

Erosion control measures must be implemented during any construction on wetlands to prevent introduction of sediment-laden runoff into surface waters and no material excavated for bridge approaches should be introduced into the stream (Gainey, 1998). For example, rising sea level, coastal subsidence, and erosion processes have been important factors affecting wetland loss and distribution globally (The Ramsar Convention on Wetlands, 2015). Coastal wetlands also appear to be vulnerable to saltwater inundation in areas of the northern to mid- Atlantic and the western Gulf of Mexico.

Exposed soils, particularly on slopes, must be compacted and stabilized with vegetation as soon as possible to prevent all kinds of erosion. Bloom (1998) stated that among different landscape conditions that contribute to differences in the stream environment, erosion plays a great role. Roise et al. (2005) confirmed that drainage control structures such as culverts, drop structures, energy dissipaters should be designed and constructed to prevent soil erosion and impacts to surface water quality.

Protective management involves maintaining important natural processes that

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operate within wetlands by monitoring and controlling human activities in the wetland environment (Dixon, 2003). Despite appreciation among plant ecologists of its important role, fire was always viewed as an entirely negative phenomenon in the early days of wetland management by land management agencies (Hansen and Gorbach, 1997). Garren (1943) identified fire as responsible for the development and maintenance of several wetland communities in the Southeast USA, while Welcomme & Brummet (200b) and Zedler & Kercher (2005) described the value of burning in Atlantic coast marshes and identified the need for further study of fire in marshes. Contrary opinions suggest that fire destroys the organic matter of soil, increases the weed population and reduces native plants (Tiedemann et al., 1979; Burrows, 1998; Horwitz et al., 1999). Many wetland types are adapted to periodic burns, but development avoids fire of any sort. Controlled burning is a management strategy that mimics the natural process in developed landscapes and promotes marsh plant diversity and eliminates undesirable vegetation (Klijn and Witte, 1999).

The sustainable use of wetlands for agricultural production according to Dixon (2003) needs a special management emphasis and critical thinking. Masiyandima et al. (2006) confirmed that a balance has to be found between the environmental functioning of wetlands and their use for livelihood purposes. Sustainable wetland management regimes are found in various situations. Usually they involve minimal conversion of the wetland and limited degradation of the catchment (Edwards, 1992). In general terms, sustainable management involves managing wetland functioning in order to get multiple benefits and it is clear that an integrated wetlands and catchment approach is needed to ensure that these two elements are linked (Wood, 2000b).

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Wetland protection and restoration require more attention in watersheds. Otherwise, there is a risk of reducing or losing the substantial ecological, commercial, economic, and recreational services they provide. Policymakers and water resources managers have been confronted with the daily task of finding a balance between benefiting from economic growth and mitigating the effects of growth on wetland environments. This task will become more challenging as the wetland farmers’ population continues to grow in a limited space, thereby pressuring on the other natural habitats (The Ramsar Convention on Wetlands, 2012, Costanza et al., 2014).

2.11 Summary and conclusion

This chapter has reviewed the available scientific literature about the importance of understanding the functions and value of wetlands and its hydrological processes, including threats, groundwater interactions, and management. The existing knowledge focuses on wetland and groundwater interaction and wetland managements aspects, because this information is needed by water resources and wetland managers. The different conclusions reached by various authors about both the functioning and the management of wetlands indicate that there is still more to know about wetlands. There seems to be general agreement that for an area to be defined as a natural wetland three main components must be included:

 Wetlands must have water present throughout the year or part of the year, either at the surface or within the plants root zone.  Wetlands must have unique soil conditions that differ from the adjacent upland.  Wetlands must support water tolerant plants (hydrophytes).

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Even though these individual component definitions (or requirements) are relatively straightforward, combining them to make one general definition is not that easy because the detail of the individual components vary from wetland to wetland. Perhaps more importantly, the three variables are not independent of each other. Each wetland’s hydrology, soil, and plants vary from season to season and from year to year, making it hard to define strict boundaries of any wetland. Each wetland also has its own unique hydrology, soil and plants according to its location. In addition, defining a wetland is subject to individual or professional interpretations. Thus a geologist, hydrologist, biologist or ecologist will each define a wetland according to their professional experience and understanding.

Wetlands were disturbed and reduced in the whole world, mostly in the United States, Western Europe and Africa. These threats were caused by humans, because they assumed that wetlands were lands to avoid in their natural state (Scoones, 1991a & b). Human activities like agriculture, road building, residential and industrial building, construction, etc. are the major reasons for the reduction of wetland areas in the world. Part of the process of establishing agricultural developments includes the construction of ditches or drainage channels to remove excess water, completely altering the hydrological water balance of a wetland. After destroying at least half of the world’s wetlands, the positive uniqueness of wetlands has caused scientists to understand their values in the ecosystem (Scott, 1993). Since people have gained a better understanding of wetlands and how they benefit the environment, today’s view is quite different and wetland rehabilitation has occurred in many countries.

Lack of natural wetlands and recognition of the beneficial role that they can play have led to the construction of man-made wetlands, particularly in urban

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environments. As with the definition of a wetland, managing both natural and constructed wetlands is not a simple task. According to McCartney et al. (2011) and Scott & Poole (1989), there is no uniformly applicable approach that can apply to all wetlands, because they are all different and located in different ecological, hydrological and climatological zones. Even though wetlands are hard to define because of the variations among the hydrology, hydric soil, and hydrophytic plants, most people have recognised that wetland protection and management is important.

In situations where ecological protection as well as community use is dual management objectives, the principles of adaptive management appears to be appropriate. This involves understanding the dynamics of a wetland, evaluating the results of management actions and adapting such actions to achieve a defined set of objectives. This can only be achieved by involving the local community who will be affected by the management decisions that are taken and must include a monitoring programme to assess the socio-economic, hydrological and ecological impacts.

Transport of water and solutes through interfaces between groundwater and surface water have for some time been acknowledged as an integral part of the hydrological cycle. Since these flow and transport processes are not easily observed and quantified, they have been neglected or, estimated as a residual component in the water balance studies. Describing and quantifying the flow and transport processes are further complicated by the fact that the physical and chemical conditions at the interface are very heterogeneous in a spatial and sometimes also in a temporal sense.

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Previous lake-groundwater studies have analysed the interaction with a variety of methods (seepage meter, hydraulic gradients from piezometers, stable and radiogenic isotopes, temperature, and numerical modelling). Many of these studies have either been theoretical numerical studies or small scale field studies.

Analysis of solute discharge showed high potential for loading of nutrients through groundwater to the lake. The focused groundwater discharge, combined with high concentrations of phosphorus observed in groundwater just beneath the lake, suggest that groundwater discharge could be the reason for several failed lake restoration attempts.

Within the research area of groundwater-surface water interaction there are still several challenges (Winter and Rosenberry, 2001). One of these involves quantification of the nutrient filtering potential of plant vegetation in the littoral zone with different discharge rates and solute concentrations. This is probably reasonable with thicknesses of several meters, but in the lake bed zone where the fine-grained sediments terminate toward coarser sediments, it is not necessarily true (Winter et al., 1998). Perhaps groundwater discharge is focused into groundwater springs in this zone and maybe lakes having only a thin fine-grained layer experience the same. This would on the other hand have implications on the loading of solutes via groundwater because more focused discharge will probably decrease the potential of removing the solutes before entering surface waters.

Groundwater-surface water interactions are very complex; and groundwater generally does not discharge from even areas like a stream or lake bottoms (Carter, 1996). Investigations based on chemical data have increased understanding of these processes, including that most storm runoff spends sometime in the

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subsurface, and most water discharging to streams during storms takes longer residence times. Mason (1990) defined residence time as a measure of the time it takes a given amount of water to move into, through and out of the wetland. Since chemical processes take time and follow one another sequentially, the degree to which wetlands can change water chemistry is determined to an extent by residence time. This is one reason why it is important not to create a channel across a wetland in the direction of flow, increasing outflow rate and decreasing residence time. Wetlands receiving inflow from groundwater are known as discharging wetlands because water flows or discharges from the groundwater to the wetland (Mason, 1990).

In these areas, surface water may be receiving groundwater discharge under some conditions but discharging into aquifers under other conditions: for example, when there is significant pumping of wells near the surface water body. A recent paper provides a method for quantifying surface water – groundwater interactions using thermal records. Moreover, water quality measurements can assist with estimating recharge to aquifers away from surface water connections. Measurements of ions/molecules such as chloride, bromide, or radiogenic and stable isotopes are valuable tools in determining areas of recharge and rates (Coplen, 1993).

Surface-water bodies are integral parts of groundwater flow systems. Groundwater interacts with surface water in all landscapes, ranging from small streams, lakes, and wetlands. The general fact is that topographically high areas are groundwater recharges areas and low areas. This is primarily true for regional flow systems. The superposition of local flow systems associated with surface-water bodies on this regional framework results in complex interactions between groundwater and surface water in all landscapes. Hydrologic processes associated with the surface

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water bodies are a major cause of the complex and seasonally dynamic groundwater flow fields associated with surface water. These processes have been documented at research sites in glacial, dune, coastal, mantled karst, and riverine terrains. Groundwater from local flow systems discharges into nearly all the lakes and wetlands, regardless of landscape patterns. These local flow systems are recharged in the uplands near the lakes and wetlands, mostly at small depressions (Lissey 1971; Winter and Rosenberry, 2001).

In USA, van Everdingen (1967) used piezometers to evaluate the effect of the formation of a large reservoir on groundwater flow in bedrock aquifers. Prior to construction of the dam, groundwater in the bedrock aquifers flowed towards the South Saskatchewan River. As the reservoir filled, the increased heads caused groundwater to reverse direction and flow away from the valley in part of the bedrock aquifers. This example indicates the close interaction of a major river with regional groundwater flow systems, and how changes in surface-water levels can affect relatively deep groundwater movement.

The interactions between GW and SW can be significantly affected by water use and management within the catchment. For example, in a stream system that is gaining water (Figure 2.1) from natural groundwater inflow, groundwater pumping may reduce the rate of inflow to the stream, or if the rate of groundwater pumping is sufficient the stream may become a losing stream (Figure 2.2) and provide recharge to the groundwater aquifer (Winter et al. 1998).

The interactions of streams, lakes, and wetlands with groundwater affect the positions of the water bodies with respect to groundwater flow systems, geologic characteristics of their beds and their climatic settings (Kelbe & Germishuye,

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2010). Therefore, for thorough understanding of the hydrology of these surface- water bodies, all three factors need to be taken into account. A study in North Dakota (USA) by Winter and Rosenberry (2001) indicated that the chemistry of lake waters reflects the magnitude of the groundwater flow systems that discharge to them. For many purposes of watershed and ecosystem management, this general knowledge could be acceptable. However, knowledge of local geology and the effects of climate on these prairie systems, as indicated by studies of the Cottonwood Lake area provide a more thorough understanding of the hydrologic processes that define these surface-water bodies. Furthermore, Winter and Rosenberry (2001) document substantial changes in the relation of these wetlands to groundwater that resulted from century-scale periods of drought and precipitation. For example, wetlands that normally contain bicarbonate water can become dominated by sulphate water during major droughts, and wetlands having sulphate water can become dominated by bicarbonate water during major wet periods (LaBaugh et al., 1997).

Studies of wetlands in the Indiana Dunes in USA also provide evidence that the integrated knowledge of regional position within groundwater flow systems, local geology, and climate is needed to understand and effectively manage these ecosystems. Furthermore, studies of temporary reversals in flow direction between wetlands and groundwater in the same wetland complex indicate the significant effect that climate-driven processes of focused recharge and transpiration directly from groundwater have on these ecosystems (Doss, 1993).

Moreover, a study by Winter (1981) in several parts of USA indicated that lakes and wetlands that lie along a regional groundwater flow system are largely flow- through with respect to groundwater. These situations could be observed directly

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adjacent to surface water, thereby causing temporary water-table mounds and enhanced seepage rates or reversals of seepage direction. In addition, transpiration directly from groundwater that affects seepage rates and direction also has been documented in these terrains (Lemaitre & Colvin, 2008).

Groundwater from local flow systems discharges into almost all the lakes and wetlands, whether topographically high or low. These local flow systems are recharged in the uplands near the lakes and wetlands, mostly at small depressions (Lissey 1971; Winter and Rosenberry 2001).

Human activities commonly affect the distribution, quantity, and chemical quality of water resources. The range in human activities that affect the interaction of ground water and surface water is broad. The effects of human activities on the quantity and quality of water resources are felt over a wide range of space and time scales. For example, agriculture has been the major cause of significant modification of landscapes throughout the world. Tillage of land changes the infiltration and runoff characteristics of the land surface, which affects recharge to ground water, delivery of water and sediment to surface-water bodies, and evapotranspiration.

All of these processes either directly or indirectly affect the interaction of ground water and surface water (Lerner, 1996; Lerner et al., 1990). Agriculturalists are aware of the substantial negative effects of agriculture on water resources and have developed methods to alleviate some of these effects. For example, tillage practices have been modified to maximise retention of water in soils and to minimise erosion of soil from the land into surface-water bodies. Two activities related to agriculture

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that are particularly relevant to the interaction of ground water and surface water are irrigation and application of chemicals to cropland.

Hornberger et al. (1998) stated that analysing and interpreting the chemistry of water can provide valuable insights into groundwater-surface water interactions. Kendal and Coplen (2001) and Mazor (2004) illustrated that dissolved constituents can be used as environmental tracers to track the movement of water. Environmental tracers can occur naturally or may be released into the general landscape by human activities (Winter et al., 1998). Several studies have used a combination of these tracers (for example major ions, stable and radioactive isotopes) to assess groundwater-surface water interactions (Epstein and Mayeda, 1953; Fontes and Edmunds, 1989; (Herczeg et al., 2001; Baskaran et al., 2004).

The use of tracers has advantages and limitations (Mueller et al., 2014; Pritchard et al., 2000; Crandall et al., 1999; Gonfiantini, 1986). Some of the advantages are the development of a conceptual understanding of groundwater flow near a stream and in the provision of information on groundwater evolution, residence times or mixing ratios that would otherwise be difficult to determine (Hornberger et al., 1998; Hannula et al., 2003). The range of hydrogeological processes that can be investigated under field conditions is probably the great strength of this method. In addition, Gonfiantini (1986) and Katz et al. (1997) demonstrated that measurements of an environmental tracer along the stream can be a powerful tool to map the spatial distribution of groundwater inflows.

Mazor (2004) further illustrated that water chemistry monitoring is commonly undertaken to complement hydrographical data collection and analysis. For example, Deuterium and 18O are the most commonly used isotopes to investigate

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groundwater-surface water interactions (Katz, 2000). However, Hooper and Shoemaker (1986) and Coplen (1991) noted that the use of such techniques has some limitations including costs related to the logistics of sampling (Mekiso & Ochieng, 2014b; Katz et al., 1997) and laboratory analysis and a requirement for a high level of expertise for sampling and interpretation (Mook, 2006; Pritchard et al, 2000; Gonfiantini, 1986). Moreover, tracers such as deuterium, 18O or tritium can have long lead times between sample collection and the final analytical results (Katz et al., 2000). Models used to quantify seepage flux from hydrochemical data can require estimates of parameters that are difficult to measure in the field (Katz et al., 2000).

Field surveys using other water quality parameters may also be useful in characterising groundwater discharge (Katz, 1997). Mazor (1991) showed that cations (such as calcium, magnesium, sodium and potassium) and anions (such as chloride, bicarbonate, sulphate and bromide) have been used as tracers to determine groundwater inputs to a stream during high and low flow periods. Mazor (2004) demonstrated that processes such as acid-base reactions, precipitation and dissolution of minerals, sorption and ion exchange, oxidation-reduction reactions, biodegradation of gases affect hydrochemistry. The key processes that could take place during the movement of water through aquifers and streams can only be interpreted by using hydrochemistry (Sprinkle, 1989).

De Groot et al. (2006) studied the ecology of the groundwater-surface water interface of large rivers in America, such as the Mississippi River for many years. Their studies indicated the importance of biological entities as indicators of the interaction of groundwater and surface water. Most studies of the interaction of groundwater and surface water, in which isotopes were considered, used the

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isotopes to determine the relative age of water or the proportion of water that had been exposed to evaporation. Coplen (1993) used tritium to determine the bulk of the contaminants, such as halogenated hydrocarbons, in water that seeped from the Rhine River in the Netherlands due to pumping of groundwater within the past two and half decades. Williams (1997) used a time series of data on deuterium and oxygen-18 to determine the amount of river water that contributed to groundwater pumped from an alluvial aquifer near Portland, Oregon. Williams (1997) used isotope tracers to locate occurrences and trace movements in a variety of naturally and anthropogenically recharged waters in aquifers of Orange County, California. In his four distinctive groundwater tracer studies, Williams (1997) compared potential recharge waters of natural and anthropogenic origin, and aquifer waters from Orange County wells. Stable isotope techniques, hydrochemical investigations as well as tritium measurements showed promise for tracing several distinctive recharge waters.

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CHAPTER 3: STUDY CATCHMENT

3.1 Site descriptions

This study was conducted at the Mohlapitsi/Mafefe Wetland, in the Capricorn District in the Limpopo basin (Figure 3.1). The study site is a palustrine wetland covering an area of 183 ha. It comprises predominantly reed beds (Phragmites mauritanus). The wetland is located in the B71C quaternary catchment within Oliphants catchment and geographically on coordinates 2406’0” South and 3006’0” East. Agricultural activities have extensively modified the ecological status of the wetland system under study.

Figure 3.1 Map showing the location of the study area in B71C Quaternary Catchment within the Oliphants Catchment (McCartney et al., 2011)

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The valley is narrow and confined; with steep hill slopes on the edges of the valley bottom (Figure 3.2); and the catchment altitude ranges from 740 m to 2050 m (where the river originates) above sea level (Figure 3.3).

Figure 3.2 Valley bottom wetland surrounded by mountains in east and west directions (Mekiso, 2011)

The wetland is about 5 km long, with an average width of approximately 600 m as shown in Figure 3.3.The entire study area was divided into seven transects (T) and the distance between them varied. Transect one (T1), transect two (T2), left bank of transect four (T4), the entire transect five (T5), transect six (T6) and transect seven (T7) are the wettest parts of the wetland. Transect three (T3) and right bank of T4 are the driest parts of the wetland (Figure 3.3). The wetland setting is characterised by moderately sloping alluvial fans and gently sloping river terraces transitioning southward into low-elevation bench lands (Kotze, 2005).

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Jordaan Spring

Figure 3.3 Locations of transects, water resources and sampling points in the study wetland during 2007 through 2013 (Mekiso, 2011)

Except between T1 and T2, river flow remains laminar and the average depth was 750 mm. In addition, water storage was observed in all parts of the transect (Figure 3. 4).

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Explanations: P=rainfall, E=evapotranspiration, T1-T7: transects, average flow depth=0.75 m

Figure 3.4 Longitudinal conceptualization of the Mohlapitsi River flow in the Mafefe wetland environment

The Mohlapitsi River originates in the Wolkberg Mountains, and is one of the tributaries of the Olifants River. It is a tributary of the Limpopo River with a total length of 50 kilometres at the confluence of Oliphants River and flows from north to south direction carrying sediments of different sizes as shown in Figure 3.5. The river is alluvial and begins branching and meandering approximately 350 metres downstream of Gabion Dam. Moreover, the river is known for shifting its routes after every flood, for example, its former route before 2000 devastating flood was 150 metres west of the current location in T3 environment. Numerous ex-bow lakes were observed in right bank of the river. The Mohlapitsi River is fed by baseflow, contributed from hillside slopes and perennial in nature. The river is incised between T1 and T2 and erosional land form is clearly seen in this part of the wetland environment.

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Figure 3.5 Sediments at T1 environment transported by the river during severe flood

Water marks on trees at Mashushu Village; about 3 km north of transect three (T3) and interviews with locals indicated that during a devastating flood of 2000, the river width was 30 m in both sides of the river. When the river was abnormally full, it flooded the wetland at T3 environment and transported boulders and gravels of many sizes. For about 75 m, the river experiences laminar flow (Figure 3.5) and then branches and flows turbulently until the beginning of T2. During the last 4 years (2010-2014), the river created 3 branches in T2 environment until it reaches T3 (Figure 3.6), where the flow is laminar.

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Figure 3.6 Laminar River Flow in T3 environment The upper catchment (above study area) comprises relatively natural grassland vegetation, contained within two nature reserves (Sarron 2005). The catchment area above the wetland is approximately 263 km2, with a population density of approximately 10.5 persons per km2 (Mekiso, 2013).

3.2 Climate of the study area

The Mohlapitsi River basin is within the summer rainfall region of South Africa and receives rain between October and April (Kotze, 2005). The mean annual rainfall in the uplands of the Mohlapitsi catchment exceeds 1000 mm (with ET of 1433 mm), while the long-term average annual rainfall over the wetland (Jogo et al., 2008; Adekola et al., 2007; Nell and Dreyer, 2005) is reported to be 511mm, of which 440.8 mm, or 86%, falls from November to March. Figure 3.7 illustrates the seasonal distribution of rainfall based on Midgley et al. (1994). The mean annual potential evaporation for the B71C quaternary catchment is 8.33 mm/day. Rainfall information on Figure 3.7 is based on all available gauged data; Potential Evapotranspiration (PE) as regionalised data and stream flow as simulated natural

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flow using a rainfall-runoff model. Averaged across the catchment, mean annual potential evapotranspiration (computed using the Penman-Monteith equation and gridded climate data provided in Schultz & Watson, 2002) is 1428 mm (McCartney, 2006).

180 9 PE 160 8

)

Rain 3

140 Stream Flow 7 6

120 6

100 5

80 4

60 3

Rainfall Rainfall and PE (mm) 40 2

20 1 Flow VolumeStream (10

0 0 Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Months

Figure 3.7 Seasonal distribution of rainfall, stream flow and potential evaporation for the period 1920 to 1990, based on data for quaternary catchment B71C taken from Midgley et al. (1994)

The entire Mohlapitsi/Mafefe Wetland has a typical valley climate with warm to hot summers (October-April) and cool winter days with cold nights. Temperatures at the study site vary from an average monthly maximum and minimum of 30.2 0C and 18.0 0C for January to 22.0 0C and 5.2 oC for June respectively (Nell and Dreyer, 2005). The climate of this part of South Africa is highly variable and the study site has experienced droughts and floods for many years (Nell and Dreyer, 2005).

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3.3 Population and unemployment

The study site contains 400 households with an average of seven people per household. Based on the classification provided by Statistics South Africa 2000 and 2001 Census (Statistics South Africa, 2014 & 2000), about 90% of households are classified as very poor. Livelihood activities in the catchment are centred on small-scale agriculture, mainly practiced by old and mature men and women. Unemployment is high, and many men between the ages of 25 and 65 migrate to neighbouring towns and mines in Limpopo Province to seek work. Engagement in subsistence farming is not considered employment. Local job opportunities come mainly from government programmes (e.g. the building of schools, road construction, a sanitation project, and construction of a tourism centre), which are limited (Tinguery, 2006).

3.4 Geology

The geology of the region comprises sediments of the Transvaal Sequence and the study area is underlain by the Malmani Subgroup of the Chuniespoort Group (Nell and Dreyer, 2005) which are Early Proterozoic dolomitic rocks of between 2 100 million years and 2 000 million years old (Miyano and Beukes, 1996). The material in this subgroup consists of grey to greyish blue and pink, compact and poorly bedded dolomites and limestone with chert layers (Figure 3.8). The general site geology of the study area was assessed from previous investigations (Miyano and Beukes, 1996) and during field visits. The hills flanking the valley consist of grey dolomite (Figure 3.9) with limestone, chert layers and interbedded quartzite of the Malmani Subgroup (Miyano and Beukes, 1996). It is assumed that the wetland is underlain by the same material. To the north, within the river catchment, is

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encountered fine to medium grained quartzites, gritty in places with pebble layers (Black Reef Formation), white grey, fine-grained quartzite with pebble fans and interlayered shale (Sadowa Formation), laminated micaceous and graphitic shale (Mabin Formation), and dark brown well-bedded micaceous shale with lenticular quartzite layers (Selati Formation) of the Wolkberg Group which are 2 600-2 500 million years old (Woodford & Chevalliere, 2002; Miyano & Beukes, 1996,). The groundwater resources assessment (GRAII) database (DWA, 2010; Dondo et al., 2010; Vivier et al., 2007; Vegter, 2001) suggests that the mean annual recharge to groundwater for B71C is between 24.08 mm y-1 and 86.50mm y-1 depending on the methods used to generate the estimates. Groundwater transmissivities are expected to be approximately 14.71 m2. d-1, while storativities have been estimated as 0.004 and aquifer thickness as 25 m (Scanlon et al., 2006; Siegel & Glase, 1987).

The geology underlying the catchment is a complex assemblage of compact sedimentary and extrusive rocks of the Godwan and Black Reef formations. In the north and east of the catchment, it comprises lava, tuff, quartzite, shale and conglomerates. In the south, west, and underlying the wetland, it comprises dolomite, chert and subordinate limestone (Watkeys, 2006).

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Wetland Boundary

Vbr: Fine-medium grained quartzites, gritty in places with pebble layers Black Reef Formation Vmd: Grey dolomite & limestone, chert layers, interbedded quartzite Malmani Subgroup Chenesproot Group

Vwm: White grey, fine drained quartzite with pebble fans & interlayered shales Sadowa Formation Vwe: Laminated micaceous & graphitic shale Mabin Formation Vws: Dark brown well bedded micaceous shale Wolkberg Group with lenticular quartzite layers Selati Formation Vti: Dark grey to black well bedded shale with conglomerate Timeball Hill Formation Pretoria Group Vd: Medium-grained quartzite with gritty & conglomeratic layers & occasional shale layer

Study wetland

Figure 3.8 Geological Map of the study catchment (Source: 2430 Pilgrim’s Rest), Scale: 1:250 000

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Figure 3.9 Dolomite rock at the study area roadside

3.5 Soils

The soils in the wetland are a mix of fine-textured, poorly drained areas away from the river bank, and less extensively sandy soils located close to the channel (Kotze, 2005). During floods, the Mohlapitsi River carries fine and coarse sediments from the steep catchment slopes with high velocity until it reaches the wetland with gentle slopes. A sudden reduction in flow velocity in the valley has created a changing pattern of braided channels, where it spreads and deposits coarse sediments or bed load (gravel, cobbles and boulders) during very high flood stages (Figure 3.5). These deposits are located near the base of the alluvium. Suspended load (fine materials or sediments such as sands, clays and silts) are deposited at the surface (Kotze, 2005).

Soils of the study site are hydric-wetland soils, which have greyish, dark brown to reddish brown, sandy loam soils and strongly sub-angular structured, sandy clay loam sub soils because of the long periods of saturation (Nell and Dreyer, 2005). Vegetation burning in the catchment is a common practice and this is likely to result in the depletion of soil organic matter (Balesdent and Mariotti, 1996).

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Chemical and physical properties of soil are influenced by the amount of organic matter in the soil (Balesdent et al., 1988). These properties include soil bulk density, porosity, structure; moisture holding capacity; diversity and activity of soil organisms. Moreover, Collins et al. (2000) demonstrated that burning vegetation caused a negative impact of soil organic matter and the environment through the oxidation of carbon into carbon dioxide, an anthropogenic greenhouse gas.

The progressive depletion of soil organic matter poses probably the greatest threat to the integrity and environmental security of the wetland (Sarron, 2005; UNEP, 2009 a & b). Drainage and cultivation could result in subsidence in wetland soil organic matter (Bossio et al., 2008), which is likely to considerably alter the morphology of the wetland and the pattern of flows through the wetland. This, in turn may potentially affect the hydrologic and geomorphic integrity of the wetland. However, it is not possible to predict the magnitude of this effect with any certainty (Faber-Langendoen et al., 2005). Most of the organic soils are elevated well above the main channel and, even in major floods, are not inundated by the river.

3.6 Hydrology of the wetland area

The Mohlapitsi River is a perennial stream, with peak flows generated during the rainy season between December and April. The river is gauged one kilometre south of T7, named as station B7H013 and stream flow records for the periods 1970 to 2008 are shown in Figure 3.10.The flow shows both seasonal and inter-annual variation, with mean annual flow is 37.96 Mm3, equating to about 144 mm of runoff (McCartney, 2006). The coefficient of runoff for the catchment is 0.18,

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which compares to an average of 0.06 for the whole of the Oliphants catchment (McCartney et al., 2004).

Cultivation within the wetland, although initiated several decades ago, expanded after 2000 following severe floods that damaged the small-scale irrigation infrastructure on which local people depended, and slightly modified the drainage within the wetland, making agriculture more feasible (Murgue, 2010).

) -1 10

Mean daily flow (m Mean daily flow

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Years (axis tick Yearsmarks at January 1)

Figure 3.10 Time series of observed stream flow for gauge B7H013 for the period 1970 to 2008 (Mekiso, 2011)

The Fertilis irrigation system, which is located to the north and west of the wetland and takes water from the Mohlapitsi upstream, was repaired in 2006. However, in the intervening years, the wetland was increasingly utilised for agriculture. As the crops grown in the wetland do not do well in saturated conditions, farmers have dug a large number of channels in an attempt to drain the wetland soils. Livestock

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grazing takes place in the areas of natural vegetation, some of which are subject to moderately heavy grazing (Kotze, 2005)

Minor stream flow reducing activities are present at Mashushu village- approximately 3 km north of the valley bottom; and flow in the channel can be inferred to be largely natural. Abstraction for irrigation has been practised since 1953 by a commercial farmer called Fertilis (Sarron, 2005). Two canals were constructed in order to convey water for crop production and none of them is functioning efficiently. The Mashushu village earth canal was destroyed by 2000 flood and the irrigation schemes were abandoned since then. In 2013, the Department of Agriculture through its extension agent delivered old and damaged PVC pipes in order to convey water to damaged irrigation schemes. The second canal is approximately 3 km long, which was made from mortar and masonry. However, at least 70% of water is lost due to lack of canal maintenance for decades.

Heavy grazing pressure and the associated reduction in vegetation cover in the wetland have potentially increased surface runoff and reduced infiltration in the catchment (Figure 3.11). This, in turn, would lead to less sustained sub-surface inputs to a wetland. However, much of the local catchments are very rocky, with many loose surface rocks. This renders the area fairly resilient and these catchments have not been greatly altered. Settlements, roads and cultivated lands are present in the local catchment.

The main catchment feeding the river channel remains predominantly natural, with much of it being a wilderness area (Sarron, 2005). Except T3 and right bank of T4, the rest of the wetland has been subjected to artificial drainage.

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Figure 3.11 Animals grazing at T1 (dominated by reeds) during 2006-2014 (Mekiso, 2011)

The hydrology of the wetland has also been adversely affected by artificial drainage of water by wetland farmers aimed at removing excess water (Figure 3.12) to create favourable growing conditions for maize, the main crop grown in the wetland (Adekola, 2007; Jogo and Hassan, 2010). Besides crop production, the wetland provides other services that support people’s livelihoods, such as dry season livestock grazing and watering, domestic water supply, fishing and natural products (reeds, sedges and other edible plants).

Figure 3.12 Artificial drainage ditch at the study wetland

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The hydrological and ecological functions of the study site are driven by wetland activities, and the magnitude of these impacts is not well understood (Kotze, 2005). Because the Mohlapitsi River contributes approximately 10% of the dry season flow in the Oliphants River (McCartney et al., 2005), external stakeholders have the perception that the wetland, regardless of its small size, provides an important regulating ecosystem service, in maintaining dry season flows downstream. At the catchment scale, Jogo et al. (2008) demonstrated that there is a potential trade-off between crop production and the Mohlapitsi River flow regulation and water supply downstream. Finally, in the long-term, continuous use of wetland for agriculture without mitigating management practices may result in irreversible loss of wetland functioning (depletion of organic matter, soil erosion, lowering of shallow water table and reduced contribution to base flow), thus impacting on the wetland ability to provide ecosystem services, including crop production (Adekola, 2007; Jogo et al., 2008).

3.7 Sources of water feeding the wetland

The present study is aimed at understanding the sources of water that contribute to the wetland, as these are important in understanding the ecological function and hydrological management of the wetland. There are six possible potential sources of water to the wetland: direct precipitation, river water infiltration from upstream, springs, and runoff from the surrounding uplands (eastward and westward), direct flow from the river channel during high river stage, and movement of ground water into the wetlands in response to river-stage changes and aquifer recharge. Furthermore, the catchment is built on karst terrain whereby subsurface and surface is dominated by sinkholes. Caves are good example of karst topography and already one big cave was discovered in 2014 on top of the valley. The river

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receives baseflow especially during low flows (May – September). The wetland acts like a conduit that receives water from mega watersheds and feeds the river. The river water assumed to be infiltrating and moving horizontally and percolating until it reaches right bank of the wetland environment (Figure 3.13).

Figure 3.13 River water above temporary gabion dam Losses of water occur through evapotranspiration, drainage to the river channel (natural and artificial) or deep drainage to the underlying aquifer if the water table drops below the base level of the wetland. Changes in wetland moisture from direct precipitation depend on the amount of rainfall and the proportion which is intercepted by vegetation and subsequently evaporated. Runoff from the surrounding uplands can provide water to the wetland and thus could increase water table levels in the valley. Direct flow from the river channel during flood can affect the wetland by water logging. Two major and several small springs contribute to the left bank section of the wetland. The water from the stream originating in the major Loumauwe Spring is mainly used for irrigation purposes and very little water flows at the confluence of the Mohlapitsi River, and its natural route is not visible during dry period. A significant input to the river on its left

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bank, a stream derived from the Jordaan Spring some 1.6 km north of the valley, occurs upstream of the wetland. It is assumed that this spring does contribute directly to the wetland and represents a component of the main channel flow. Both natural and artificial drains on the left and right banks of Mohlapitsi River drain the valley bottom/wetland. The size of the wetland is decreasing towards south (right bank) due to manmade drains (Figure 3.12). More than 7 springs were identified in the left bank of the wetland (T5 environment) in September 2005. The springs indicate the presence of regional groundwater contributing to inflows to the Middle Mohlapitsi Wetland (Kotze, 2005; McCartney et al., 2005).

Members of the households in the study site have access to piped water for drinking and sanitation facilities, and many have small gardens and kraals in which they keep small numbers of livestock. Except Ga Mampa village, all others are provided with boreholes that supply water to water points where each community member is served freely. The Ga Mampa village community is supplied by two springs that originate from mountains at the right bank.

3.8 Engineering structures

Two minor engineering works were installed in the river in order to assist the community that lost its entire irrigation infrastructure during the 2000 flood. The first is at gabion dam (Figure 3.14), which is located approximately 2.5 km north of T1 - the wetland. The purpose of this structure is to increase the head so that more water can be diverted to both Fertilis and Mashushu canals during base flow. During base flow, very little Mohlapitsi River water flows in the Fertilis irrigation canal. The second engineering structure is PVC pipes, that were installed within the right bank of T4 (Figure 3. 15). The purpose of installing these pipes was in

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order to convey the river water to a canal (adjacent to the main road). These structures were constructed by the Department of Agriculture in 2002. Both structures were constructed by not capable and experienced professionals, hence they do not operate. A

Figure 3.14 Gabion dam structure at the head of the valley (A=constructed after 2000 flood; B=renovated in 2006)

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Figure 3.15 450 mm PVC diameter pipe installed at right bank of T4 environment

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CHAPTER 4: METHODOLOGY

4.1 Instrumentation

The study site was instrumented to monitor groundwater, stream flow, and trace water dynamics and how the wetland receives water. A catchment-scale water balance was used to examine factors regulating spatial and temporal soil water distribution within the catchment. To gain insight into hydrological processes within the wetland and its contribution to river flow, hydrometric instruments were installed within the wetland.

The wetland boundary, locations of drains, the river course, springs and boreholes were determined by a Global Positioning System (GPS) and engineering surveying equipments. Field observations of the general geology, soils, topography, vegetation and an assessment of existing borehole characteristics were carried out.

4.2 Weather data

Five nearby South African Weather Service (SAWS) stations (Figure 4.1) were shut down in 1989 except Stellenbosch station. Hence, it was not possible to use rainfall data from these stations. In November 2005, five manual rain gauges were installed within the wetland on transects T1, T2, T4 and T6, two gauges were installed on T4 because it is the largest transect. These gauges were read after each rainfall by the field assistants and are shown on Table 4.1.

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Explanation: Rain gauges, River, Wetland, Catchment boundaries Figure 4.1 Location of rain gauges stations in the Mohlapitsi/Mafefe catchment (Sarron, 2005; Troy et al., 2007 and Mekiso, 2011)

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Table 4.1 Mean rainfall obtained from manual rain gauges in the Mohlapitsi/Mafefe from January 2006 to December 2014 Measurement Dates Rainfall (mm) 31/01/2006 49.0 28/02/2006 63.0 31/03/2006 48.0 31/01/2010 134.0 28/02/2010 176.0 31/03/2010 16.0 30/04/2010 30.0 31/06/2010 32.0 31/10/2010 12.0 30/11/2010 28.0 28/02/2011 17.0 31/03/2011 12.0 30/11/2011 48.0 28/02/2012 51.0 30/11/2012 28.0 31/12/2012 15.0 31/01/2013 46.0 28/02/2013 78.0 31/03/2013 47.0 30/04/2013 13.9 31/05/2013 18.0 30/06/2013 23.0 30/09/2013 19.0 31/10/2013 36.0 30/11/2013 42.0 31/12/2013 38.0 31/01/2014 73.0 28/02/2014 53.0 31/03/2014 28.0 30/04/2014 34.0 31/08/2014 27.0 30/09/2014 25.0 31/10/2014 44.0 30/11/2014 65.0 31/12/2014 63.0

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4.3 Piezometer installation and groundwater monitoring

Sixty five (65) mm diameter PVC piezometers were used to gain a better understanding of groundwater-surface water interactions as demonstrated by (Hattermann et al., 2008; Kirk et al., 2004). In 2005, 42 piezometers were installed at seven transects in the wetland catchment. At each transect, piezometers (Figure 4.2) were installed perpendicular to the stream channel, positioned approximately 4 m from the channel edge and 50 m between piezometers. However, the depth of each hole and the spacing were constrained by the occurrence of boulder beds beneath the surface. The lateral distance between transects differs due to the wetland orientation (left bank and right bank position). Piezometer holes were made using a Dutch Auger with extension as shown on Figure 4.3.

The piezometers were installed under three different land covers: reed beds and natural grass cover and corn field marshy land. T1, T2, T7 and parts of left bank of T4 are covered by reeds and natural grasses. T3, most part of T6, small portion of T5, most part of left bank of T4 and the whole area of right bank of T4 predominantly covered by corn crop. Most part of T5 is covered by marsh (approximately 22 ha). The number of piezometers in each transect differs depending on transect width. A cement-sand mortar with bentonite chips were added to provide a seal around piezometers, and ground surface elevation at each piezometer was obtained by a dumpy level to understand groundwater flow direction in each transect.

Daily water level measurements were collected at all seven transects in the wetland catchment. Continuous water level or hydraulic head measurements were made in all transects from November 2005 to December 2011 and the data was sent by

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technical assistants. The accuracy of the measurements was assumed to be about ±5 mm. This clearance was allowed due to the fact field measurement could not be perfect. The data was analysed in a spreadsheet and hydrographs were produced in order to understand groundwater fluctuations through time.

Measurements and monitoring of water levels in piezometers enable the researchers to develop an understanding of regional water quality as an aid to better capture knowledge of the groundwater regime for optimal management of groundwater resources (The United Nations World Water Development Report 4, 2012). Sufficient water supply of appropriate quality is a key ingredient in the health and well-being of humans and ecosystems, and for social and economic development. Water quality is becoming a global concern of increasing significance, as risks of degradation translate directly into social economic impacts (Famiglietti et al., 2009).

Polluted water that cannot be used for drinking, bathing, industry or agriculture may effectively reduce the amount of water available for use in a given area. The more polluted the water is, the greater the incremental cost of treatment required to return it to a useable standard (UNEP, 2010).

Furthermore, overuse of surface water, such as rivers and lakes, can lead to increased concentrations of harmful substances present in the water due to pollution or mineral leaching. For example, decreased flows in summer caused declines in water quality in Rio Grande River (Stellar, 2010).

Understanding groundwater and surface water will help to determine long-term trends in water quality and to relate observed trends to human activities as a basis

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for informed decision making to wise use of groundwater resources. Water level measurements from piezometers are important source of information about the hydrologic stresses acting on aquifers and how these stresses affect groundwater recharge, storage, and discharge (Famiglietti et al., 2009).

Monitoring is a crucial component of ecosystem management, to detect long-term ecosystem change, provide insights to the potential ecological consequences of the change, and help decision makers determine how management practices should be implemented (Kevin, 2009). Monitoring may be used as a starting point to define baseline conditions, understand the range of current variability in certain parameters and detect desirable and undesirable changes over time in the system.

This information will assist in solving water resources problems experienced by hydrologists, hydrogeologists, engineers, regulators, and resource managers (Sadashivaiah et al., 2008). This assists scientists, practitioners, managers and policymakers to provide some perspective as well as a stimulus for discussion with a goal toward developing a new direction for global wetland conservation in a dynamic environment (Kevin, 2009).

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Figure 4.2 Cross-section of a poly vinyl chloride (PVC) piezometer, not to scale, units given in mm

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Figure 4.3 Dutch Auger with extension

In order to monitor water level in the piezometers, a water level indicator was used (Durham Geo Slope Indicator, http://www.slopeindicator.com - Figure 4.4). It consists of a probe, a cable with laser-marked graduations, and a cable reel. LED located in the hub of the cable reel illuminates and a beeper sounds as soon as the probe contacts the surface of the water in the piezometer tube (Mekiso, 2011).

Figure 4.4 Water Level Indicator (Source: Durham Geo Slope Indicator, Website: http://www.slopeindicator.com)

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4.3.1 Conceptual Modeling for flow generation within each Transect

The main goal was to generate a conceptual model that would synthesise the relationships between groundwater (GW) and surface water (SW) interactions in each transect. In this model, groundwater inflow (Gwi), surface water inflow (SWi), overland flow to river (OF), capillary rise (CR), seepage from wetland and hillslope to the river (LR), rainfall (P), evapotranspiration (ET), recharge (R), springs and drainage from wetland to the river (D) were used. The conceptual model was used in order to show flow generation to relevant stakeholders and academic. The aim of this conceptual model was to aid in the implementation of the integrated management plan for the study of wetland ecosystem.

4.4 Stream flow measurements

Daily stream flow was measured at the gauging station on the Mohlapitsi River (B7H013), located about 1 km downstream of the wetland. The gauging station weir (Figure 4.5) is maintained by the Department of Water and Sanitation (DWS) and has been in operation since August 1970. Mean daily stream flow data available from the DWS website were used in the analysis. For this study, historical records from June 1990 – September 2014 were used for all calculations in the analysis.

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Figure 4.5 DWA weir site

Starting in the dry season of 2006, river flow has been measured upstream of the wetland by using a C2 current meter (OTT instruments). Measurements were taken for the months of July and August 2006. Unfortunately, the gauge was washed away during the November 2006 flood after which, no data was collected. Moreover, attempts at performing more accurate fluorescent dye tracing failed as no suitable sections of the river could be found along which the basic criteria for such tracing (complete mixing, no stagnant water, a single channel) could be satisfied.

4.5 Water sampling for environmental isotope, hydrochemistry and field parameter analysis

4.5.1 Water sampling for stable isotopes analysis

Sampling was carried out between 2007 and 2013. The number of samples varied from year to year and a total of 128 water samples of one litre each were collected and transported to iThemba and University of Pretoria Laboratories. The Los Gatos Research (LGR) Liquid Water Isotope Analyser was used for the analyses. The analytical precision is estimated at 0.5‰ for Oxygen (O) and 1.5‰ for Hydrogen

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(H). The δ values (δ18O, δ2H) are calculated using the internationally accepted standard equation (Craig, 1961a) given as

푅푠푎푚푝푙푒−푅푣푠푚표푤 훿(0⁄ )= [ ] × 1000 (4.1) 00 푅푣푠푚표푤 where, R is the isotope ratio 2H/1H or 18O/16O. These delta values are expressed as per mil deviation relative to known standard, in this case standard mean ocean water (SMOW) for δ18O and δD or 2H. Stable isotope values of δ18O and δ2H were measured by isotope ratio mass spectrometry (IRMS), and were measured relative to international standards that were calibrated using V-SMOW (Vienna Standard Mean Ocean Water) and reported in 0 conventional δ ( /00 or per mil) notation.

The local meteoric water (LMWL) line equation for the Pretoria rainfall station was constructed in order to compare it with what is known as the global meteoric water line (GMWL) (Mekiso et al., 2013; Craig, 1961b).

δ2H = 8δ18O + 10 (4.2)

4.5.2 Water sampling for tritium analysis

A total of 50 water samples (from drainage, river, springs, boreholes and piezometers) were collected for tritium analyses during May 2010, December 2011, April 2012, and October 2013. Borehole samples were collected from Vallis and Mashushu villages during sampling times except May 2010 for isotopic analysis and both samples were taken from the 1taps. During May 2010, the pump failed and the community did not receive water when sampling was done. Samples

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were not taken directly from boreholes due to the fact that water line installation was completed and hence, there was no direct access to boreholes. All the samples were collected with polyethylene containers. The sample bottles were rinsed several times with water from the site as described by Rozanski et al. (2001).

As 3H enters groundwater systems and begins to radioactively decay, the noble gas 3He is produced. In the unsaturated zone, dissolved 3He generated from 3H decay can be lost to the atmosphere. Below the water table, dissolved 3He concentrations will increase as groundwater becomes older. Although groundwaters contain 3He from several sources other than ‘H decay, determination of both 3H and tritiogenic 3He have to be used as a residence time (Gusyev et al., 2013; Moran, 2007).

Tritium decays by electron emission with 12.43 years by β particle, and its λ is between 5.5 and 5.69 kev. For 3H, one tritium unit (TU) represents one atom of tritium in 108 atoms of hydrogen. Concentrations of tritium in the groundwater were measured by scintillation counting after electrolytic enrichment as described by Clark and Fritz (1997). Analytical uncertainties usually result in errors in age estimates of less than 10% (Visser et al., 2014).

Borehole samples were collected from Vallis and Mashushu villages and were taken from the taps (not directly from the boreholes). These are the only two villages where drinking water is supplied to the communities. All the samples were collected with polyethylene containers. The sample bottles were rinsed several times with water from the site.

The samples were distilled and subsequently enriched by electrolysis. The electrolysis cells consist of two concentric metal tubes, which are insulated from

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each other. The outer anode, which is also the container, is of stainless steel. The inner cathode is of mild steel with a special surface coating.

Five hundred (500) ml of the water sample, having first been distilled and containing sodium hydroxide, was introduced into the cell. A direct current of some 10–20 ampere was then passed through the cell, which was cooled because of the heat generation. After five days, the electrolyte volume was reduced to some 20 ml. The volume reduction of about 25 times produced a corresponding tritium enrichment factor of about 20. Samples of standard known tritium concentration (spikes) were run in one cell of each batch to check on the enrichment attained. Tritium concentrations were expressed as absolute concentrations, using tritium units (TU) and, no reference standard is required (Mekiso, 2011).

For liquid scintillation counting samples were prepared by directly distilling the enriched water sample from the highly concentrated electrolyte. Ten (10) ml of the distilled water sample was mixed with 11 ml Ultima Gold and placed in a vial in the analyser and counted 2 to 3 cycles of 4 hours. Detection limit was 0.2 TU for enriched samples.

4.5.3 Hydrochemistry

4.5.3.1 Alkalinity, electrical conductivity and major ions

Samples for alkalinity, pH and electrical conductivity, and major ion analysis were collected in polyethylene bottles, tightly capped and transported to TUT Science Faculty for analysis. Alkalinity, electrical conductivity and pH were measured using WM-22EP meter, while major ions were analysed using Inductly Couple

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Plasma Mass Spectrometer (ICP-MS) in the Chemistry Laboratory, Science Faculty.

Cation and anion concentrations for each water sample were converted to total meq/L and plotted as percentages of their respective totals in two triangles. The concentrations were calculated in milliequivalents per liter, meq/L. To facilitate the interpretation of the chemical analysis, Piper diagrams (Figures 4.6 & 4.7) were used. The cation and anion relative percentages in each triangle were projected into a quadrilateral polygon that describes the water type or hydrochemical facies. Finally, the cation-anion balance percentage was determined using the equation 4.3 (Milovanovic, 2007) {(∑cations − ∑anions) ÷ (∑cations + ∑anions)} (4.3) In the Piper diagram, the relative abundance of cations with the % meq/L of Na+, K+, Ca2+ and Mg2+ was first plotted on the cation triangle as described by Cea et al. - 2- - (2011) and Mazor (2004). Then the relative abundance of Cl , SO4 , and HCO3 + 2- CO3 was plotted on the Piper diagrams (Figures 4.6). Furthermore, the two cation and anion triangles were combined into the four-sided polygon that shows the overall chemical property of the water sample (Mazor, 1997 &1991).

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Figure 4. 6 The Piper Diagram with two simple triangular plots on the right and left side of a 4-sided diamond field. (Taken from Sun, 2010, Seraj et al., 2006, Piper, 1953 http://www.sciencedirect.com/science)

Water classification was done using anion and cation facies in the form of major- ion-percentages as shown by Tomar et al. (2012), Piper, 1953; Back and Hanshaw, 1965; Sadashivaiah et al., 2008 (Figure 4.7)

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Explanation: A = Calcium type, B = No Dominant type, C = Magnesium type, D = Sodium and potassium type, E = Bicarbonate type, F = Sulphate type, G = Chloride type

Figure 4.7 Classification diagram for anion and cation facies in the form of major-ion percentages (Piper, 1953; Back and Hanshaw, 1965; Sadashivaiah et al., 2008)

Concentrations of major ions were also plotted on Schoeller’s diagram (Figure 4.8) using Microsoft Excel. Both anion and cation values were plotted on the same plane and are visible to understand.

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Figure 4.8 Schoeller’s diagram (Schoeller, 1977; Hakim et al., 2009)

Major concentrations were plotted using GW Chart Software, which has been used by United States Geological Survey (2013).

4.6 Application of Darcy’s Law to understand groundwater

4.6.1 Wetland soil permeability The falling head permeability test (Figure 4.9) was used for measuring the permeability of soil taken from the study site. In this instrument, water was passed through a soil sample and the hydraulic gradient and quantity of water flowing into the sample were measured. The coefficient of permeability was calculated from the equation 4.5:

푞. 푙 푘 = (4.4) ℎ. 퐴

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where k = coefficient of permeability in cm/sec,

volume of water collected in cylinder (ml) q = (푚푙/푠푒푐) duration of test in seconds

l =length of sample between adjacent nipple points (cm) h = head difference between adjacent sets of manometer tubes (cm) A= cross-sectional area of sample (sq.cm)

Figure 4.9 Soil hydraulic permeability using falling head method

4.6.2 Other groundwater hydraulics components

Average piezometer hydraulic head (h) was calculated using the following simple equation

Surface elevation at piezometer − water level at piezometer (4.5) In addition, the average horizontal hydraulic gradient between the piezometers was estimated using equation (4.6) [(head at piezometer 2 – head at piezometer 1) / Distance between piezometers (L)

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ℎ2−ℎ1 Or 푖 = (4.6) 퐿 Finally, average groundwater velocity was calculated using equation (4.7). dh v = k x i = k (4.7) dl where v Darcy velocity of water [m/s] k hydraulic conductivity of soil [m/s] i hydraulic head gradient [-] dh difference of hydraulic head between piezometer point i+1 and point i [m] dl horizontal distance between piezometer point i+1 and point i [m]

The groundwater velocity is the product of hydraulic conductivity and hydraulic gradient, with adjustments for the porosity of the soil material.

4.7 Water Budget

4.7.1 Data collection

For this study, streamflow data was obtained from Department of Water and Sanitation (DWS), streamflow-gauging station B7H013. The annual change in ground-water storage was estimated from water-level records from observation wells. Data on ground-water withdrawals, surface-water withdrawals, returns of water to the ground-water system, and discharge to streams were provided by the DWS.

The hydrologic system in the watershed is dynamic because water is always in motion. In this undeveloped watershed, water is constantly added by precipitation and constantly leaving as surface water and evapotranspiration (Vallet-Coulomb et

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al., 2001). The common factor for all watersheds is that the total amount of water entering, leaving, and being stored in the system is conserved. An accounting of all the inflows, outflows, and changes in storage is called a water budget. Human activities, such as pumping ground water, change the natural system, and these changes must be accounted for in the calculation of the water budget. Human activities affect the amount and rate of movement of water entering the system, in the system, and leaving the system (Allen et al., 1998). Long term water level information from observation wells at the study site and streamflow data were collected from DWS. The information is too big to include in this study and only calculated quantities were used.

4.7.2 Study basin water-budget calculations

Under natural conditions, the hydrologic system is in long-term equilibrium. Averaged over a long period of time (tens of years), the amount of water entering the system is approximately equal to the amount of water leaving the system (Healy et al., 2007; Sloto and Buxton, 2005). Because the system is in long-term equilibrium, the quantity of water stored in the system is constant or varies about an average value in response to annual or longer term climatic variations (Schultz et al., 2004). Sloto and Buxton (2005) demonstrated the annual water budget of a natural system states water input (I) equals discharge (D) plus or minus changes in water in storage (ΔS): WE (Water entering system) = WL (Water leaving system) ± ∆S (4.8) In natural systems, water enters the system as rainfall (R) and leaves the system as streamflow (SF) (surface runoff plus ground-water discharge to streams) and evapotranspiration (ET) (USGS, 2002; Adeloye et al., 1999):

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In some areas, flow is upward from confined aquifers to unconfined aquifers; this upward flow is a negative leakage; while in other areas, flow is downward from unconfined aquifers to confined aquifers (Liang and Ding, 2004).

In the hydrologic system, storage can be ground water stored in an aquifer (∆GWs), surface water stored in impoundments (∆SWs), and water stored in the soil (∆SMs). As Kebede et al. (2006) and Kidd (1983) pointed out changes in ground-water storage are caused by changes in recharge to the ground-water system and discharge from the ground-water system to streams, ground-water pumping, or ET directly from ground water. The quantity of water stored in the soil depends on precipitation, temperature, and plant cover (Kusler, 1987). Soil moisture and changes in soil moisture are difficult to measure and may vary widely over a given area. Water budget in this report was calculated on an annual basis with the start and end in the wet season when soil moisture is at field capacity. In our situation, April is the month where the wet season ends. Due to the fact that the water budget in the study area begins and ends when the soil is saturated between March and April, the change in soil moisture is zero (Munthali, 1994).

Sloto and Buxton (2005) stated that human activity changes the natural hydrologic system in many ways. One way is by importing water into a watershed (Imp) and increasing the quantity available for use. They further demonstrated that imported water can be water imported as a source of potable supply or as wastewater imported for treatment and discharge in the watershed. Another change is by exporting water (GWexp, SWexp) from the watershed (Kumambala and Ervine, 2010). Some human activities result in the consumption of water (CoU), which can be viewed as an export from the watershed. According to Sloto and Buxton (2005), consumptive use includes water loss from irrigation (agricultural, golf-course, or

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land application of treated sewage effluent) and in bottled water or manufactured products. An equation describing the water budget for a watershed influenced by human activity, which is referred to as the basin water budget,

The basin water-budget equation was adjusted by trial and error method for conditions in the Middle Mohlapitsi watershed/catchment. This watershed does not have surface-water exports or leakage to underlying groundwater units; therefore, those terms are not included in the final equation.

Average rainfall over the watershed where data from multiple stations were available was estimated using the Thiessen polygon method of areal rainfall determination (Kogelbauer, 2010; Thiessen, 1911). The Thiessen method subdivides a watershed into polygonal subareas with the rainfall stations as centers. The polygonal subareas are used to assign a weight to the rainfall amount at the station in the center of the polygon (Figure 4.10). The Thiessen network is fixed for a given raingauge distribution. When a rainfall gauge is added, removed, or moved to a new location, the polygons must be recalculated. Average precipitation over the watershed where data from multiple stations were available was estimated by using the Thiessen polygon (Figure 4.10) method of areal rainfall determination (Kogelbauer, 2010; Thiessen, 1911).

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Figure 4.10 Thiessen Polygons of the piezometers

The annual ΔGWs were estimated from water-level records from DWS observation wells (Krasnostein and Oldham, 2004). Since monthly water levels were available, the annual change in water level was calculated by subtracting the water level from the previous year’s last month water level, and multiplying the result by the specific yield of the aquifer. Because the basin water-budget equation was solved for ET, errors in the measurement or estimation of the other terms affect the calculated ET. Therefore, the ET term is evapotranspiration plus errors.

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Long term water-level data from the study area observation wells (Table 4.2) were used to estimate the annual change in ground-water storage. The ΔGWs vary from year to year. Over the long term, the average ΔGWs is equal to zero. In the basin water budgets presented in this report, the long-term average change in groundwater storage does not equal zero because of the short period of record of some of the water budgets and because of the estimation of specific yield; it does not reflect a decline in aquifer storage over time. Table 4.2 Long term water level data from observation well at study area (negative values indicate that groundwater is below natural ground level) Year Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep 2006 -5.04 -5.48 -5.41 -5.47 -5.54 -5.68 -5.56 -6.61 -6.71 -6.78 -7.60 -9.84 2007 -5.20 -5.97 -5.75 -5.63 -5.75 -5.87 -5.91 -6.94 -6.65 -6.71 -8.85 -9.99 2008 -5,09 -5.87 -5.68 -5.75 -5.57 -5.45 -5.45 -6.52 -6.56 -6.63 -7.72 -9.81 2009 -5.42 -5.82 -5.61 -5.69 -5.48 -5.36 -5.38 -6.48 -6.49 -6.51 -7.69 -9.43 2010 -5.18 -5.73 -5.54 -5.60 -5.36 -5.30 -5.32 -6.40 -6.41 -6.45 -8.66 -9.88 2011 -5.16 -5.38 -5.42 -5.18 -5.09 -5.26 -5.53 -6.63 -6.59 -6.59 -8.65 -9.62 2012 -4.71 -5.64 -5.45 -5.38 -5.13 -5.26 -5.30 -6.31 -6.38 -6.40 -8.42 -9.99

All consumptive water use (CoU) was estimated. Most uses of water have a consumptive-use component, but consumptive use is not straightforward. If withdrawal and discharge data were available for a user, the difference was considered consumptive use. In the case of the middle Mohlapitsi Wetland, irrigation water (8-11 cm depth) has been conveyed to the study area by means of 3 km long main canal, made from masonry and concrete structures.

The watershed is undergoing a change from rural to suburban. Some residential developments are served by public-water systems and may be served by public- sewer systems, but many of the residents are self-supplied by springs from adjacent mountains. The period for which annual water budgets were calculated (2006-

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2012) was governed by the availability of water-use data. Data from DWS streamflow-gaging station B7H013 below wetland was used to calculate the streamflow component of the water budget. Water-level data used to estimate the annual change in groundwater storage were available from boreholes in the wetland. These wells were measured monthly.

The study watershed does not have surface-water impoundments, surface-water exports, or leakage to underlying confined units; therefore, those terms are not included in equation 4.9. Hence, equation 4.9 was used for the final calculation of the water budget of the study catchment. R + Imp − (SF + ∆GWs + ∆SWs + GWexp + CoU) = ET (4.9)

where

R = precipitation, Imp = water imported into the watershed (cm), SF = streamflow leaving the watershed (cm), ∆GWs = change in ground-water storage (cm), GWexp = ground-water withdrawals exported from the watershed (cm), CoU = consumptive use (cm), ET = evapotranspiration (cm)

4.8 Statistical analyses

The data was statistically analysed using STATA V13 statistical software. Data was summarised by means of the mean, standard deviation, maximum and the minimum values .One-way analysis of variance (ANOVA) was used to compare the effect of season (summer, autumn, winter and spring) on the average electrical conductivity (EC) concentration and to also compare the average EC at four

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springs of interest; namely: Jordan, right bank spring 2 (RB2), river upstream (rus) and river downstream (rds). Comparison of the average EC concentration between Mashushu and Vallis boreholes and the 200m south of T1 and 100m south of T1 grains was done through the independent T- test. Pearson’s correlation coefficient was used to test the relationship between EC and Alk at α= 0.05 level of significance. Regression analysis was also performed to compare the average EC concentration between the years under study.

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CHAPTER 5: RESULTS AND DISCUSSIONS

5.1 Rainfall and streamflow

The rainfall data plotted (Table 4.1) are obtained from the study area located at the five rain gauges installed as part of the study (Table 4.1). There were very small differences between the rainfall values measured at these gauges suggesting low spatial variability of rainfall inputs over the wetland area.

The flow of the Mohlapitsi River is seasonal in nature (Masiyandima et al., 2006). High flows were observed between January and March 2010, November 2010 and January 2011, January and February 2012, January and March 2013, November 2013 and February 2014, October and December 2014 (Figure 5.1). The flow is characterised by hydrographs with steep rising and falling limbs, indicating limited infiltration and retention in the catchment. Between January and February 2010 the first peak rainfall was observed, followed by October 2011 and February 2012, January and March 2013, November 2013 and February 2014, and October and December 2014.

Figure 5.1 depicts the relationship between rainfall measured over the wetland and stream flow at the DWS gauging station B7H013 downstream. The accuracy of the measured flow data at the hydrological station is 5% for flow lower than 5m3s-1 and 10% for flow higher than 5m3s-1 (Sarron, 2005; Troy et al., 2007).

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Rainfall Streamflow

120.0 12.0

100.0 10.0

/s) 80.0 8.0 3

60.0 6.0

40.0 4.0 Rainfall (mm) Rainfall

20.0 2.0 Streamflow (m

0.0 0.0

Dates of measurement

Figure 5.1 Rainfall over the wetland and daily streamflow observations at B7H013

5.2 Piezometer responses

The period of records for groundwater levels was 65 months. It included the 2005/2006 wet season and 02 January 2010 – 30 December 2014. In between April 2006 and January 2010, no data was recorded due to budget constraints. Groundwater hydrographs for piezometers along T1, T2, T3, T4, T5, T6, and T7 are shown in Figures 5.2, 5.5, 5.8, 5.11, 5.14, 5.17 and 5.20.

5.2.1 Piezometers in T1

A total of 1 169 measurements were taken and analysed during the entire study period. All piezometer levels showed a rapid response at the start of the wet season (from 18 November 2005 until 28 January 2006). However, water levels in Piezometer MRB101 (Figure 5.2) showed rapid response from 18 November 2005

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to 16 November 2006 and undulating pattern was observed between 16 January 2006 and 29 March 2006. The water table surface elevation along T1 did not drop significantly during the dry episodes that followed (Figure 5.2). Again after 02 January 2010 until the end of study period (30 December 2014), water level elevations in all piezometers in T1 environment showed positive increase. However, there is very little correlation with the patterns of local rainfall during the main part of the wet season.

Figure 5.2 depicts that none of the piezometers responded to the large amounts of rainfall recorded during the first three weeks of February 2010. Piezometers MRB103 and MRB105 show some response to the final stream flow event of the season (end of November 2010). Variations in groundwater levels in MRB101 show the closest relationship with variations in stream flow, an expected result given that this piezometer is the closest to the channel. The assumption is that the groundwater is draining towards the channel and that the wetland is probably contributing to stream flow.

The changes in the groundwater levels correlate well with periods of rainfall, with groundwater level increases observed immediately after rainfall. Rapid response by groundwater was observed in piezometers close to the river (MRB101, in Figure 5.2). In piezometers located further away from the river and closer to the hill slopes (MRB102, MRB103, and MRB105), rapid increases in the water levels were observed following rainfall, indicating lateral flow from the hill slope maintaining groundwater levels. In all the piezometers there was a gradual recession in the dry season after March 2006. Thereafter, it was impossible to mention anything since no groundwater monitoring record was available. Groundwater recording started on 31/01/2006 and all piezometers showed increase

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with minor undulations (Figure 5.2).

724 200

/s) 3 723 180

160 722 140 Rainfall 721 120 720 100 MRB101 719 80 MRB102 60 718 MRB103 Groundwater Groundwater level (m) 40 MRB104 717 20 Rainfall (mm) Rainfall (mm) & Streamflow (m MRB105 716 0 Streamflow

Dates of measurement

Figure 5.2 Groundwater table fluctuations January 2006 to December 2014 for T1

Piezometers in T1 do not show a great deal of variation at the end of the wet season and yet the groundwater levels (and hydraulic gradients toward the river) are substantially higher than at the start of the 2006 wet season.

T1 is dominated by reeds, artificial and natural drains; and not much agricultural operation has been observed. From 2010 to 2013, the wetland farmers burned the reeds in order to expand agricultural operation. T1 is the beginning of the wetland and is also located at the right bank of the Mohlapitsi River.

Water table profiles across transects T1 indicate groundwater flow from the wetland to the river and this is shown in Figure 5.3. The profiles for T1 in the north-end of the wetland, with organic soils and peat, showed a large response to

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rainfall between December and January at 100m, 150m, and 250m from the river bank. Adjacent to the river bank (MRB100), the water level did not increase as much as further upslope at MRB102, MRB103, and MRB105. Water levels in all piezometers increased from the end of 2006 until the end of study time. The water table surface elevation along T1 did not drop significantly during the dry episodes that followed. The possible reasons could be land clearance by burning the reed bed for cropping. This has been the usual practice by wetland farmers who occupy agricultural plots after 2000 year devastating flood. They keep on burning the wetland immediately after harvesting their crops. The second important reason for why water table level did not drop during dry time could be contributed from increased recharge from irrigation scheme close to T1 site. Approximately 150 hectares of irrigation scheme has been under irrigation. This small irrigation scheme has been developed by about 3 km long canal that conveys water from the Mohlapitsi River. The third reason could be that increased recharge from high rainfall that the wetland received. For example, on 28/02/2010 and 28/02/2013, the wetland received 176 mm and 78 mm rain respectively.

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Figure 5.3 Lithological sections of piezometers at T1(modified from Mekiso, 2011)

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Figure 5.4 depicts that the river receives flows from surrounding catchments, natural and artificial drainage systems, direct rainfall, base flows (groundwater from Mega watersheds). In this part of the wetland, river water surface elevation is higher than that of T2, T3, T4, T5 and T6 environments. When the river was full, it transported sediments of different sizes drops in T1 area. Report from locals confirmed that the river overtopped its bank for a few minutes only. During dry season, flow depth in the channel does not exceed 750 mm. It was observed that the locals easily pass using their boots.

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Explanations: Gwi = groundwater inflow, SWi = surface water inflow, OF = overland flow to river, CR = capillary rise, LR = seepage from wetland and hillslope to river, P = rainfall, E = evapotranspiration, R= recharge, D = drainage from wetland to river

Figure 5.4 Conceptual Model of flow generation in T1

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5.2. 2 Piezometers in T2

Piezometers in T2 showed relatively small responses throughout the wet season, although MRB205 responded rapidly to the high rainfalls that started at the beginning of February 2006. Piezometer MRB201 approximately followed the patterns of stream flow variation (Figure 5.5). Piezometer MRB206 also showed similar response during the end of March 2006.

725 200

724 180

723 160 /s)

722 140 Rainfall 721 120 MRB201

720 100 MRB202 MRB203 719 80 MRB204

Groundwater Groundwater levels (m) 718 60 MRB205 717 40 Rainfall (mm) Rainfall (mm) & Streamflow (m MRB206 716 20 MRB207 715 0 Streamflow

Dates of measurement

Figure 5.5 Groundwater table fluctuations January 2006 to December 2014 for T2

In T2 environment, except piezometer MRB205, no boulders were found while augering. This part of the wetland is dominated by peat and dark clay soil as shown in Figure 5.6.

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Figure 5.6 Lithological sections of piezometers at T2(modified from Mekiso, 2011)

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Figure 5.7 depicts conceptualization of flow in T2 environment and wetland contributing flow to the river, the groundwater is draining towards the channel and that the wetland is probably contributing more flow to stream channel.

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Figure 5.7 Conceptual Model of flow generation in T2

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5.2.3 Piezometers in T3

Piezometer MRB306 fluctuates less in response to precipitation than that of MRB303 due to low water level. Figure 5.8 showed that the water level in MRB302 seems to be less affected by precipitation. It is true that the water level in a piezometer in which the depth to water is great will not readily respond to precipitation.

724 200

180 723 160 722 140 721 Rainfall

120 /s), Rainfall /s), Rainfall (mm)

3 MRB301 720 100 MRB302 80 719 MRB303

60 MRB304 Streamflow Streamflow (m Groundwater Groundwater levels (mm) 718 40 MRB305 717 20 MRB306

716 0 Streamflow

Dates of measurement

Figure 5.8 Groundwater table fluctuations January 2006 to December 2014 for T3

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The wetland in T3 portion is more elevated than the rest of the wetland environments. Furthermore, high water table (3.19 m) was observed in T3 site. On the other hand, the deepest water table in T4 environment was 1.42 m. Figure 5.9 depicts that overland flow (OF), drainage (D) and groundwater gradient are towards the river channel, because water level elevation in this part of the wetland is higher than that of the river. There is no evidence that the river contributes flow to the river. The demonstration by Darradi et al. (2006) that the river contributes to the sustainability of the wetland was incorrect.

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Figure 5.9 Conceptual Model of flow generation in T3

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The lithology of transect three (T3) is more complicated than the rest. Its top (surface) material is loamy clay; followed by approximately 0.3-0.4 m deep boulders and 0.3 m thick sand bed (Figure 5.10). The gradient of the water table is generally towards the depression at MRB304 and the river at MRB301.

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Figure 5.10 Lithological sections of piezometers at T3 (modified from Mekiso, 2011)

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5.2.4 Piezometers in T4 A total of 2 175 measurements were taken and analysed during the entire study period. Figure 5.11 depicts that piezometers responded to peak rainfalls recorded between 31/01/2010-28/02/2010. Piezometers did not show any significant undulations until the end of December 2014 (Figure 5.11). There was no correlation among groundwater levels, rainfall and river gauge heights throughout most of the study period, indicating river flow was majorly influenced by baseflow contributed from surrounding mountains, caused by precipitation events that occurred far from B7H013 gauge. Hence, the river in the wetland environment is gaining stream. There was insignificant correlation with the patterns of local rainfall during the main part of the wet season. The reason for insignificant fluctuations in all piezometers could be that during installation piezometers were clogged with peat so that water was blocked from entering the piezometer.

T4 is the widest of all transects and its left bank is dominated by reeds. Piezometers in T4 do not show a great deal of variation at the end of the wet season and yet the groundwater levels (and hydraulic gradients toward the river) are substantially higher than at the start of the 31/01/2006 wet season.

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Rainfall MRB401 MRB402 MLB403 MLB404 MLB405 MLB406 MLB407 MLB409 Streamflow

723 200 180

722 160 721 140 720 120

100 /s) /s) & Rainfall (mm) 719 80 3 718 60 40 Groundwater Groundwater levels (m) 717 20

716 0 Streamflow (m

Dates of measurement

Figure 5.11 Groundwater table fluctuations January 2006 to December 2014 for T4

Figure 5.12 depicts wetland in T4 environment contributing flow to the river, the groundwater is draining towards the channel and that the wetland is probably contributing more flow to stream channel. In addition, the wetland elevation is higher than that of the river. The river’s discharge at approximately 3 km north of the wetland was measured as 2.5 m3/s; while in the wetland environment (T1-T7) it was 1.8 m3/s, indicating the river is an effluent stream. In gaining streams, groundwater seeps out into the streams.

In T4, groundwater moves both towards the river channel and depressions shown on Figure 5.13. For example water table in piezometers MRB408 and MRB406 move to MRB407 depression; while water table from MRB401 up to 405 and partly from MRB406 flows to the natural channel.

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Explanations: Gwi = groundwater inflow, SWi = surface water inflow, OF = overland flow to river, CR = capillary rise, LR = seepage from wetland to river, P = rainfall, E = evapotranspiration, R= recharge, D = drainage from wetland to river

Figure 5.12 Conceptual Model of flow generation in T4, located both sides of the river

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Figure 5.13 Lithological sections of piezometers at T4 (modified from Mekiso, 2011)

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5.2.5 Piezometers in T5

T5 site is located at the left bank of the Mohlapitsi River and at the foot of the mountain, where it is fed by numerous springs originating from the dolomite hill. About 20 hectares of it was marshy area and at least 150 mm deep water was observed ponded. Farmers created artificial drainage close to the river. There is no much agricultural practice due to groundwater seepage all over the site.

A total of 2 037 measurements were taken and analysed during the whole study time. The water table level with respect to the groundwater level of the piezometers in T5 is shown in Figure 5.14 to highlight the seasonal pattern of the water table behaviour during the period of study. Piezometers showed distinct increase between 31/01/2006 and 28/02/2010 after receiving a total of 470 mm of rain water. Piezometers showed neither increase nor decrease between 28/02/2010 and 31/03/2013 even after receiving 460 mm rainfall. Then they showed a slight decrease from 31/03/2013 to 31/08/2013, and the wetland received little rainfall compared to other times. From 31/08/2013 until the end of study period, piezometers showed minor increase. During the study period, piezometers showed an average water level increase of 1.65 m.

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Rainfall MLB501 MLB502 MLB503 MLB504 MLB505 MLB506 MLB507

722.00 200

721.50 180

721.00 160

720.50 140 720.00 120

719.50 100 /s & Rainfall (mm) 3 719.00 80

718.50 60 Groundwater Groundwater levels (m) 718.00 40

717.50 20 Streamflow m in 717.00 0

Dates of measurement

Figure 5.14 Groundwater table fluctuations January 2006 to December 2014 for T5

Several springs were identified within T4, T5 and T6 environments in September 2010 dry season. The springs indicate the presence of regional groundwater contributing to inflows to the Mohlapitsi wetland (McCartney et al., 2011; McCartney, 2006).

Wetland in T5 environment (Figure 5.15) keeps water from rainfall and groundwater and slowly releases to the natural channel. Furthermore, water surface elevation in the river is much lower than that of wetland. Hence, there is no reason to show in the conceptual model that there is seepage from the river to wetland as Masiyandima et al. (2011) and McCartney (2004) indicated. The explanation made

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by the above authors is misleading, since water does not flow from lower to higher elevation.

T5 is located at the left bank and is 451m wide with eight piezometers. Dark brown clay dominates T5 with 300 mm thick boulders beneath (Figure 5.16).This portion of the wetland is located at the foot of a dolomite hillside and is within approximately 20 ha of marshy land. Several springs were observed to exist at the foot of the hillside, even during dry seasons.

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Figure 5.15 Conceptual Model of flow generation in T5

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Figure 5.16 Lithological sections of piezometers at T5 (modified from Mekiso, 2011)

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5.2.6 Piezometers in T6

During the entire study period 764 measurements were taken from piezometers MLB601, MLB602 and MLB603 (Figure 17). Groundwater table levels in T6 showed fluctuations until the beginning of January 2010 and revealed distinct increase between January and February 2010. The highest rainfall that occurred during these periods could have affected these results. The mean water table surfaces in transects within T4, T5 and T6 (Figures 5.13, 5.16 and 5.19) show gradients in the water table along transects towards the channel, suggesting inflow from the slopes.

724 200

180

723

160 722 140 721 120

720 100 Rainfall /s) /s) & Rainfall (mm) 3 MLB601 80 719 MLB602 60 718 MLB603 Groundwater Groundwater Table levels (m) 40 Streamflow Streamflow (m Streamflow 717 20

716 0

Dates of measurement

Figure 5.17 Groundwater table fluctuations January 2006 to December 2014 for T6

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Figure 5.18 depicts that T6 are elevated compared to streamflow that the river is fed by groundwater in the wetland environment, hence the river is an effluent stream. The groundwater table in T5 and T6 is higher than the river, and water moves towards the river. Even when the river rises suddenly due to the fact that ground water levels are higher than the river, groundwater flow further from the river would move towards the river while water in the river would begin moving into bank storage (Figure 5.18). Hence, seepage, overland flow and drainage were contributed from wetland to the river.

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Figure 5.18 Conceptual Model of flow generation in T6, located left bank of the river

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Figure 5.19 depicts that groundwater gradient is towards the river channel. The entire portion is marshy and several non-identified springs were observed even during dry season. Farmers who occupied this site are unable to run their farming activities during rainfall event. Water logging and forest-like weeds do not allow them to work. Field assistants found it difficult to collect data due to the above reasons.

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Figure 5.19 Lithological sections of piezometers at T6 (modified from Mekiso, 2011)

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5.2.7 Piezometers in T7

This site is located at the extreme end of the wetland and is always wet throughout the year even during dry season. It is located at the left bank of the Mohlapitsi River and just at the foot of the mountain, where it is fed by numerous springs originating from the dolomite hill. About 70% of T7 is utilised for agricultural purposes and no artificial drainage was observed. It is in this part of the wetland that the river creates several branches and meanders. One of the branches flows close to the road.

A total of 759 measurements were taken and analysed during the whole study period. The water table level with respect to the groundwater level of the piezometers in T7 is shown in Figure 5.20 to highlight the seasonal pattern of the water table behaviour during the period of study. During 2006, water table levels in all piezometers showed increase with undulations. However, from 2010 to 2014 water table levels neither increased nor decreased in all piezometers and the hydrograph remained horizontal. Even after 17 February 2010, when the study area received the highest rainfall (176 mm), none of the water table levels changed but remained horizontal (Figure 5.20). The reason for this water table level pattern is not known.

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722 200

180

721 160

140 720 120

100 /s) /s) & rainfall (mm) 3 Rainfall 719 80 MLB701

60 MLB702 Groundwater Groundwater levels (m)

718 40 MLB703 Streamflow Streamflow (m 20 Streamflow 717 0

Dates of measurement

Figure 5.20 Groundwater table fluctuations November 2005 to December 2014 for T7

No Lithological section was drawn for T7 section for the following reasons: During preparation of holes to install piezometers, the site was saturated and no geologic materials (soil and rocks) were obtained. It was not possible to collect soil samples due to the fact that the auger carried only loose material. However, it was observed that the soil material removed as mud was black cotton soil, which is different from the rest of the piezometers. In addition to this, one day after installing piezometers, the shallow GW level was above ground level. Hence, the three wells are artesian type. This shows that T7 environment is built on confined aquifer.

Wetland in T7 environment (Figure 5.21) keeps water from rainfall and groundwater and slowly releases to the natural channel. Furthermore, the river created several branches, ok-bow lakes and meanderings and water surface

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elevation in the river is higher than that of other sections of the wetland. However, since this site is saturated the lateral seepage is assumed negligible.

The variables which influence water table rise and the occurrence of saturation include topography, antecedent catchment conditions, soil characteristics, and rainfall intensity and duration (Cheng et al., 1975). These variables may act alone or together in influencing water table rise at a specific point. For example, in a forested catchment in the United States of America, Pierson (1980) found that over 90% of variance in piezometric response was explained by rainfall depth, catchment area, and antecedent soil moisture. Although it is difficult to separate the influence of one variable from another, an attempt will be made to describe individual variables and their influence on water table rise (Cheng, 1988).

The role of topography in influencing soil moisture levels was investigated by Dunne and Black (1970 a &b) and Anderson and Burt (1978) who both revealed that water table levels were generally higher in hollows (surface concavities) than in spurs (surface convexities). Although the effect of topography on water table levels was with topographic variables (Sinai et al., 1981).

Anderson & Kneale (1982) suggested that on low-angle slope (≤ 10%), saturation may occur downslope from concave areas, as precipitation inputs will influence soil moisture distribution more than topography. Moreover, these authors concluded that topographic variables should only be used in steep topographies. However, this finding was contradicted by Petch (1988), who found that the highest probability of saturation existed in areas of strong topographic convergence regardless of slope, as well as in areas of low slope close to stream channels.

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Topography is an important influence on water table behaviour and the development of saturated zones, especially in zones of flow convergence with large upslope contributing areas (Burt & Butcher, 1985, Moore et al., 1986b). However, as predictors of water table levels, topographic variables do not account for all aspects influencing water table response.

Many studies have suggested that topography and soil characteristics are intrinstically linked, which has led to the development of the catena theory. This theory states that soils derived from the same parent material and of the same age may have varying characteristics due to differences in topographic relief and drainage. The physical basis of the theory is that lateral movement of soil water in a downslope soil development (McCaig, 1984). According to Birkeland (1984), topography is the primary factor in explaining soil variation. Proponents of the catena theory have found that many soil characteristics vary with topographic position, including organic matter content (King et al., 1983, Kreznor et al., 1989).

The occurrence of high moisture levels has been correlated with specific soil characteristics (Cogger & Kennedy, 1992). Highly fluctuating water tables and the occurrence of long-term soil saturation have also been linked to soil colour and the presence of mottles and gleying (Mokma & Sprecher, 1994).

Soil parameters influencing water table behaviour include saturated hydraulic conductivity, the moisture release curve, organic content, and depth to restricting layers (Moore & Foster, 1990). In predictive indices, transmissivity is usually the only incorporated soil variable. However, questions still remain regarding the use of transmissivity in predictive indices, given the possible larger influence of topography on water table response.

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More immediate influences on water table behaviour and the development of saturation are hydrologic variables, including storm volume, intensity, and antecedent moisture conditions (Ragan, 1967; Dunne et al., 1975). Whereas topographic and soil characteristics influence the magnitude and and timing of this response. In general, water table response will be higher under high intensity storms of large volume, and response will be quicker under wet antecedent soil conditions (Pierson, 1980).

The influence of rainfall intensity and volume on water table response has been found in a number of studies, although a consensus on the importance of each variable has not been reached. On a Virginian coastal plain, Eshleman et al. (1993) used chemical separation techiniques to conclude that high intensity rainfall enabled the production of stormflow and the occurrence of soil saturation due to high vertical flow velocities in upper soil layers. During low intensity storms, low horizontal flow velocities led to equilibration and the water table did not rise as quickly, resulting in a smaller area of surface saturation. Pierson (1980) found out catchment response was affected rainfall intensity, while Jordan (1994) found storm volume more influencial than storm intensity.

When rainwater infiltrates the soil profile, it is initially stored in soil pores, causing the soil moisture content to rise. Dunne & Leopold (1978) demonstrated that with increasing moisture, the soil will be able to transmit water as a wave of downward percolation. If an impermeable layer exists at depth, the percolating water will reach the barrier and a perched layer, allowing water to be transmitted downslope laterally through shallow subsurface paths to the stream channel (Hewlett & Hibbert, 1963 and Dunne, 1978). This subsurface stormflow dominates in areas of dense vegetation and permeable soils on steep hillslopes (Dunne, 1983).

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Subsurface stormflow may be delivered to the stream channel more quickly through macropores. After passing the unsaturated soil matrix, this water will reach the saturated zone more quickly (Bonell, 1993). Beven and German (1982) have stated that the most effective macropore systems will develop in undisturbed forested sites. The rapid rise and fall of water table levels in forested catchments has been partially attributed to the presence of macropore systems (Burch et al., 1987).

When lateral subsurface flow and vertical infiltration of precipitation exceed the soil’s ability to transmit this water flux, the water table will rise. In areas where the water table rises to intersect the soil surface, overland flow may be generated from zones of saturation by continued precipitation inputs (Ward & Robinson, 1990). This flow is called saturation overland flow. Dunne & Black (1970 a & b) found that saturation overland flow developed from small portions of the watershed. These zones were generally topographically low, with higher antecedent moisture levels than catchment averages. The development of saturated zones in soil permeable areas has been confirmed by Taylor (1982), Burt & Butcher (1985) and Cheng (1988).

Since the capillary fringe extends to the ground surface, soil storage capacity is limited and water table will respond quickly to infiltrating precipitation (Novakowski & Gillham, 1988). This will lead to a concentration of flow lines toward the stream the rapid development of saturated zones. Gillham (1984) has stated that the groundwater ridging mechanism will have particular importance in complex topographies.

Antecedent moisture levels and the intensity, duration, and volume of precipitation will influence the magnitude of water table rise and increase the

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likelihood of saturation due to faster water table response and the initiation of lateral subsurface flow. The lack of research in describing water table behaviour and assessing the strength of the relationship between water table levels is one of the focus areas of the current study.

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Figure 5.21 Conceptual model of flow generation in T7

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5.3 Hydraulic characteristics of groundwater in the wetland environment

The average hydraulic permeability (K) was estimated as 10-6 m/s. The 24 hour soil permeability test indicated that the soil is not permeable even though its texture is silty-clay loam. Clay related soils usually have low permeability due to small grain sizes with large surface areas, which results in increased friction, and their pore spaces are not well connected. Clay usually creates confining layers in the subsurface zone. Permeability is mostly influenced by the size of fractures in rocks, degree of interconnectedness and the amount of open space in sediments. The study wetland soil has low porosity, since it contains very few openings, so water cannot easily pass through.

Average hydraulic head (h) between piezometers, horizontal hydraulic gradient (i) and groundwater flow velocity (v) were 1.49 m, 6.46 x 10-5 and 6.46 x 10-10 m/s respectively.

High permeability will allow fluids to move rapidly through rocks. Permeability is affected by the pressure in a rock. Permeability is the property of rock or soil that permits water to pass by flowing through interconnected voids or spaces. For a given hydraulic head gradient, a higher the permeability means a higher fluid velocity. Permeable bedrock makes a good aquifer, a rock layer that yields water to wells.

Cracks and joints that interconnect in the soil and bedrock allow the water to reach a zone below the surface of the land where all the fractures and void spaces are completely filled with water. This water-rich zone is called the saturated zone and its upper surface is called the water table. The volume of void space in soil or bedrock is termed porosity (Baird, 1997). The larger the proportion of voids in a given volume of soil or rock the greater the porosity. When these voids are interconnected, water can migrate from void to void. Thus

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the soil or bedrock is said to be permeable because fluids with contaminants can easily move through them. Permeable bedrock makes a good aquifer, a rock layer that holds and conducts water. If the ground water that flows through the underlying permeable bedrock is acidic and the bedrock is soluble, a distinctive type of topography, karst topography, can be created.

Mekiso (2014) demonstrated that karst landforms created by downward movement of water accompanied by dissolution of rock and mass transport of sediments in stream channels could contaminate the groundwater system. In tropical areas with thick massive limestones, a remarkable hilly area and narrow gorges completely dominate the landscape. Movement of solution along fractures and joints etches the bedrock and leaves limestone blocks as isolated structures. These structures range from small features of few inches tall to intermediate forms a few feet tall to large materials-hundreds of feet tall. In addition, sheets of flowing water with pollutants move down sloping surfaces creating a variety of etched surface features.

Karst topography dominated by sinkholes or dolines usually has several distinct surface features, which is associated with karst landscape. Sinkholes are surface depressions formed by either: 1) the dissolution of bedrock forming a bowl- shaped depression, or 2) the collapse of shallow caves that were formed by dissolution of the bedrock. These sinkholes or shallow basins may fill with water forming lakes or ponds. The existence of different types of springs make the study area created convenience to the communities. Springs are locations where ground water emerges at the surface of the earth. Disappearing streams are streams which terminate abruptly by flowing or seeping into the ground. Disappearing streams are evidence of disrupted surface drainage and thus indicate the presence of an underground drainage system. Caves may reflect a complex underground drainage system (ASTM, 1997c).

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Moving water may transport earth materials into and through caves physically or chemically. Caves contain interesting features as a result of the physical and chemical processes that form them. Among these features are breakdown blocks of rock formed by collapse of cave ceilings. Also seen are sediments containing boulders, sand, silt, and clay deposited from water flowing in and through cave passages and conduits.

Karst springs supply drinking water to millions of people. Knowledge of karst terrain and the movement of water in underground drainage systems is important for maintaining good quality and safe drinking water. Pollution of ground water is a major problem in karst terrain.

Under unsaturated conditions, the ability of peat to hold water within its structure may help support wetland ecosystems. Pumping during drought periods should be managed so that the capillary fringe does not fall below the peat-sand interface any longer than this period (Baird, 1997).

When surface water exists, the water table can be close to the top surface of the soil for a period of time, depending on surface water depth and water table depth, without causing all the surface water to drain or evaporate. When surface water does not exist, a maximum long-term water table drawdown must be considered so that there will not any major changes in wetland hydrology. This drawdown may be exceeded for periods of time short enough to prevent soil moisture from reaching a new equilibrium (Chason & Siegel, 1986).

When the soil is saturated, the hydraulic conductivity determines how much surface water is present and how long it can persist. When the soil is unsaturated, the capillary properties of the soil pores determine the ability of the

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soil to maintain sufficient moisture in order to support plant life. The hydraulic properties of a soil are determined by that soil's physical properties.

5.4 DISCUSSIONS

Three active springs and five drains were identified within T1 and T7 environments in August 2010 dry season. Drains are like springs, but were not found in the field when we first visited the study site in 2006. The springs indicate the presence of regional groundwater contributing to inflows to the Mohlapitsi/Mafefe wetland. Although the wetland is located in the channelled valley, the overflow from the river does not contribute significantly to the water balance of the wetland.

At the beginning of water level monitoring period (2006 - wet season) the variation in water levels across transects was relatively low. Almost all transects showed flow gradients towards the river, while in some cases there are local gradients towards depressions in the wetland surface. Transect 4 showed the greatest variations (between 1.0 m for MLB406 and 2.47 m for MLB404), while T6 showed the least variations (between 0.82 m for MLB603 and 1.34 m for MLB601). Sites closest to the river channel showed the highest variations. The soils near the river channel in T4, T5 and T6 are loamy clay and not well drained in nature.

The fluctuations in water level appear to be more strongly associated with the stream flow variations reflected at the gauge B7H013 located downstream of the wetland. There are several observations leading to this situation. For example, at the head of the valley, river flow measurement suggested that there was a reduction of flow rate approximately 700 m south of gabion dam (Figure 3.3). In addition, during 2006, the river had stopped flowing in its channel altogether for approximately 1.5 km southward and the flow recommenced only

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about 900 m north of T1. Furthermore, in 2006 only a single drain with little flow was observed, while during 2007 to the end of the study period (30 December 2014) four springs with significant amount of flow were observed.

Water table levels in T1 and T2 showed similar trend and increased with slight undulation until the end of measuring period. Rainfall events did not impact these results. The main reason for the above results could be that the wetland is built on karst aquifer. For example, when the site was last visited in September 2014, new three drainage systems were observed between T2 and T3. These drainage systems were formed by karst topography. Karst is a landscape formed from the dissolution of soluble rocks including limestone, dolomite, and gypsum. Over time, water flowing through the network continues to erode and enlarge the passages; this allows the plumbing system to transport increasingly larger amounts of water. This process of dissolution leads to the development of the caves, sinkholes, springs, and sinking streams typical of a karst landscape (Gunn, 2004).

The wetland farmers and extension agent confirmed that the drains were observed at the middle of 2012 when the wetland area did not receive rain. For example, a cave was discovered on top of the wetland (2 km north of the wetland), indicating the wetland is built on karst topography. Approximately 20-25% worldwide population largely depends on groundwater from karst aquifers (Cook, 2003).

South African dolomites are subdivided into smaller compartments by thin vertical dyke intrusions, which act as barriers to the lateral drainage of groundwater. This gives rise to the occurrence of springs at the topographical lowest point where these dykes force the groundwater to overflow as springs (Cook, 2003; Bredenkamp and Vogel, 2007).

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The mean water table surface in all transects show gradients in the water table along transect towards the channel, suggesting inflow from the slopes (Figures 5.3, 5.6, 5.10, 5.13, 5.16 and 5.19). As shown in Figures 5.20 and 5.21, T7 tends to illustrate uniform GW level than the drained site of T1. In addition, Figure 5.20 suggests that non-drained site demonstrates a gentle, more predictable hydrological response to rainfall events indicating their ability to store and regulate water. On the contrary, drained sites experience more erratic, non- predictable fluctuations in their water table level (Figures 5.2 and 5.5). Groundwater fluctuation at the end of 2013 was mapped using ArcGIS 9.0 and the result is shown in Figure 5.22.

Figure 5.22 Mean groundwater flow patterns in 2013 210

Geographical Information Systems (GIS) have been used in modeling groundwater for resources management, including groundwater recharge. Thematic layers for slope, infiltration rate, depth to groundwater, alluvial sediments, and land use were integrated into the GIS environment (ESRI, 2001). Extensive hydrogeological survey exploration required for characterizing groundwater conditions was replaced by integrating remote sensing data into a GIS environment to identify suitable sites for groundwater recharge in hard rock areas in part of the Vidisha District in India (Saraf and Choudury 1998).

A GIS software package ArcGIS 9.0 and Arc-GIS Geostatistical Analyst extension were used to map, query, and analyze the data in this study for the assessment of groundwater quality (Healy & Cook, 2002). Moreover, ArcGIS proves an ideal platform for the cross-analyzing approach to estimate initial recharge and discharge maps. Fast initial recharge and discharge estimation and mapping help decision makers and modellers design more accurate and cost- effective models before initiating labour-intensive field measurements (Lin et al., 2006).

The importance and use of GIS have benefited natural resources and environmental concerns, including groundwater studies. Typical examples of GIS applications in groundwater studies are site suitability analyses, managing site inventory data, estimating vulnerability of groundwater to pollution potential from nonpoint sources of pollution, modeling groundwater movement, modeling solute transport and leaching, and integrating groundwater quality assessment to create spatial decision support systems (Engel et al. 1999). Hudak (1999, 2000, and 2001) and Hudak and Sanmanee (2003) have reported a number of studies about Texas groundwater quality. ArcView GIS was used to map, query, and analyze the data in these studies. Vinten and Dunn (2001) studied the effects of land use on temporal changes in well water quality.

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Mean water level variations during the entire study period is summarised in Table 5.1 clearly shows a brief site characteristics, land use and water table trendlines.

Table 5.1 Summary of water level variations in the study area during November 2005 to December 2014 Transects Water table characteristics Location characteristics

T1 Showed an increase with fluctuations at the beginning of Drained by three natural drains; dominated by reeds at the wet season, after which the levels are variable. western side, the river is very close to the ground MRB101, close to the river show low variations but has a surface, farming towards, the river, and subsurface recession until the end of 2011 wet season, relative to material with many cobbles and boulders. other piezometers. Piezometers showed progressive increase until the end of 2014. T2 Initially undulating except MRB205, then gentle increase Highly waterlogged portion; two natural and two followed by not significant variable increase until the end drainage ditches, reeds dominate, undulating terrain; of 2014 dark brown (peat) soil. T3 Water level increased sharply in piezometers except This is the drier portion of the wetland MRB302 at the start of the wet season, then all showed progressive increase until the end of the study period T4 Initially, piezometers showed variable increase and sharp Right bank: Boulders and other sediments; reeds, no increase until 30/04/2010. Then, all piezometers showed drainagess, bank erosion, farming, river braiding and neither increase nor decrease until 30/06/2013. This could branching, domestic fishing be drying tendency with fluctuations thereafter. Finally, Left bank: receives runoff from dolomite hill, very gentle increment was shown in all piezometers. dominated by reeds and water logging, farming. Numerous springs were observed even during dry time T5 Piezometers response in T5 is similar to T4. All Left bank of the river, boulders underneath, bank piezometers, between 28/02/2010 and 31/03/2013 showed erosion, farming close to the river, many springs and neither increase nor decrease. Groundwater levels do not about 20 ha marshy land at the foot of dolomite show an obvious response to two instances of surface mountain. inundation. Finally, they showed the similar response to T4, T6 Similar to T4 and T5, groundwater levels in all three Left bank: farming dominates; not many reeds, totally piezometers did not respond between 31/03/2010 and waterlogged, boulders and pebbles towards the river, 28/02/2013. From 28/02/2013 until the end of study no drainages, stagnant water, hence, domestic fishing period, all piezometers showed gentle increase. T7 For a short period of time, all three piezometers of T7 Left bank: end of wetland, river branches tremendously showed rapid increase until they responded the same as to the extent of seeing one of the branches flowing very those of T4, T5 and T6. After 30/01/2013 showed close to the untarred road undulating and gentle increase

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5.5 Environmental Isotopes

5.5.1 Stable isotopes

A total of 128 water samples were collected to measure deuterium and oxygen- 18 isotopic values from 2007 to 2013 (Tables 5.2, 5.3 and Figure 5.23). The δ18O and δD values of water samples are listed in Table 5.2. The δ18O and δD values of these water samples and the global meteoric water line (GMWL), with the equation δD = 8δ18O + 10 as described by Craig (1961a) and the local meteoric water line (LMWL) as δD = 6.63 δ18O + 5.44.

Table 5.2 δD and δ18O isotopic concentrations from 2007 to 2009 at the Mohlapitsi/Mafefe Wetland

May.2007 Dec.2008 Jun.2009

18 0 18 0 18 0 Sample Description δ O /00 δD ‰ δ O /00 δD ‰ δ O /00 δD ‰ SMOW SMOW SMOW SMOW SMOW SMOW River upstream -4.71 -24.62 -4.7 -24.25 -4.69 -24.72 River downstream -4.85 -24.88 -4.8 -19.34 -4.88 -24.9 River T2, downstream -4.82 -23.96

River 3, T1 -4.74 -23.72

Upstream LB Spring -4.8 -25.41 -4.8 -25.44 LB Spring 2 -5.22 -28.76 -5.26 -28.67 LB Spring 3 -5.21 -28.81 -5.24 -28.56 RB Spring 1 (Ditolong) -4.56 -26.56 -4.45 -26.14 RB Spring 2 -5.75 -34.96 -5.92 -34.23 RB Spring 3 -5.37 -31 -5.43 -31.13 RB drain 1 -4.71 -24.12

RB drain 2 -4.84 -25.6

Auger hole at T501 -5.19 -27.43 -5.22 -27.6

Table 5.3 demonstrates that drainage at 200 m south of T1 is enriched. Furthermore, Table 5.3 indicates that the river upstream (δD = -16.24, δ18O = - 2.48) during December 2012 is enriched, while river at Fig trees environment (δD = -21.70, δ18O = -5.08) during November 2013 depleted. In addition to this, drainage at T206 and another drainage at 50m south of T1with isotopic

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fingerprints of δD = -26.60, δ18O = -5.14 and δD = -22.90, δ18O = -4. 56 showed depletion and enrichment, respectively. Auger holes at Transect two (T2) having an isotopic values of δD = -23.0, δ18O = -4 60 and δD = -28.70, δ18O = -5 32 showed enrichment and depletion, respectively.

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Table 5.3 δD and δ18O isotopic concentrations from 2011 to 2013 at the Mohlapitsi/Mafefe Wetland Jun.2011 Nov.2011 Jul.2012 Dec.2012 Nov.2013 Sample Description δ18O % δD ‰ δ18O % δD ‰ δ18O % δD ‰ δ18O % δD ‰ δ18O % δD ‰ SMOW SMOW SMOW SMOW SMOW SMOW SMOW SMOW SMOW SMOW River upstream -4.69 -24.72 -4.77 -34.5 -4.73 -24 -2.48 -16.24 -4.61 -22.2 River downstream -4.88 -24.9 -4.81 -19.3

River T2, downstream -4.87 -23.89 -3.5 -18.71 -4.62 -21.1

River 3, T1 -4.78 -23.56

River at Fig Trees -3.43 -18.4 -5.08 -21.7

River after Jordaan Spring -4.75 -24.4

River100m above Jordaan -2.69 -16.25 -4.49 -22.1

spring -4.56 -22.5 -4.74 -22.5

River water under bridge 2 -3.37 -18.56 -4.61 -21.1

River upstream from

Vallis crossing -4.88 -21.98 -4.41 -23.6 -4.99 -26.6

River upper crossing T1 -5.02 -22.65 -4.72 -23.9 -4.24 -18.7

River at Vallis crossing -3.03 -16.81 -4.73 -21.3

Mohlapitsi R water T6 envir -3.15 -18.16 -4.8 -22.7

Upstream LB Spring -4.8 -25.44

LB Spring 2 -5.26 -28.67 -5.88 -28.3

LB Spring 3 -5.24 -28.56 -4.63 -21.7

RB Spring 1 (Ditolong) -4.45 -26.14

RB Spring 2 -5.92 -34.23 -2.51 -14.16

RB Spring 3 -5.43 -31.13 -4.71 -23.38

Jordaan Spring -4.71 -24.2 -3.85 -20.28

Loumauwe Spring -5.31 -28.4 -4.2 -24.54 -5.28 -23.4

T5 Spring -5.49 -29.2

RB drainage 1 -4.7 -24 -4.57 -23.2 -4.65 -22

RB drainage 2 -4.85 -25.4 -4.65 -24.5 -4.49 -20.1

Drainage 200m south of T1 -4.61 -23.2

Drainage 400m S of T1 -4.72 -23.2 -4.74 -22.4

Drainage 50 m S of T1 -4.56 -22.9

Drainage 400m S of T1 -4.56 -22.9

Drainage 200m S of T1 -4.61 -23.4 -3.65 -18.4

Drainage at T206 -5.14 -26.6

Auger hole at T501 -5.22 -27.6 -5.32 -28.7

Auger hole at T101 -4.7 -23.8 -4.24 -20.59

Auger hole near T104 -4.9 -25.3

Auger hole at T302 -5.19 -29

T2 Auger hole -4.6 -23

Vallis borehole -5.67 -33 -3.64 -18.41 -5.56 -27.2

Mashushu borehole -5.08 -27.7 -5.01 -25.68 -5.25 -24.3

River at 1st HW bridge -4.74 -22.1

River at T7 environment -4.78 -22.7

DWS weir site -4.68 -22.2

River at Gabion dam -4.86 -21.5

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June 2011 water samples lie above both local meteoric water line (LMWL) and global meteoric water line (GMWL) except Right Bank Spring 1 (RB Sp1) with δD = -26.14, δ18O = -4.45 plot at right of both meteoric lines; indicating there is evaporation and showed enrichment (less negative); while Left Bank Spring 3 (LB Sp3), having δD = -28.5, δ18O = -5.24 is depleted (Table 5.3 and Figure 5.23). The rest of samples lie left of the lines; indicating there is no evaporation.

During November 2011, all except river downstream samples (δD = -34.5, δ18O = -4.77) lie left of GMWL and LMWL; indicating no evaporation. In addition, during July 2012, Vallis borehole (δD = -33.0, δ18O = -5.67) showed depletion in isotopic fingerprint and plots between the two lines (Figure 5.23). Transect five (T5) springs, drain 50m south of Transect one (T1) and MLB502 auger hole samples plot on LMWL. The rest of samples lie left of both lines. Also, half of December 2012 samples plot left of both meteoric lines. Except river 100 m above Jordaan Spring (δD = -22.50, δ18O = -4.56) and drain 200 m south of T1 (δD = -18.40, δ18O = -3.65), other samples lie left of both meteoric lines. All November 2013 samples plot left of both LMWL and GMWL and river samples cluster together.

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0.0

-5.0

-10.0

LMWL May.2007 -15.0 Dec.2008 δD = 7.0518O + 7.6 SMOW Jun.2009

00 00 R² = 1

/ 0

-20.0 Jan.2010 D

δ Jul.2010 Jun.2011 -25.0 Nov.2011 Jul.2012 -30.0 GMWL Dec.2012 δD = 818O+ 10 Nov.2013 R² = 1 GMWL -35.0 LMWL -7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 18 0 δ O /00 SMOW

Figure 5.23 Deuterium and Oxygen-18 plot for water samples during, June 2010, November 2011, July 2012, December 2012 and November 2013 (Vienna-Standard Mean Ocean Water is used as the accepted zero point standard for expression of hydrogen and oxygen isotopes of water samples in delta units)

The isotopic composition of water samples in the study area during dry season (June 2011 and July 2012) and wet season (November 2011 and December 2012) periods were similar (Figure 5.23) and no seasonal variations were observed as shown on Table 5.4. Table 5.4 Details of δD and 18O during May 2007 through November 2013 Sampling dates Equation Regression line (r2) May 2007 δD = 8.15 18O + 13.30 0.84 December 2008 δD = -2.89 18O – 37.28 0.006 June 2009 δD = 6.55 18O + 5.46 0.84 January 2010 δD = -14.35 18O – 93.92 0.03 July 2010 δD = 7.72 18O + 12.19 0.93 June 2011 δD = 6.55 18O+5.46 0.84 November 2011 δD =-13.55 18O-89.91 0.04 July 2012 δD =7.72 18O+12.19 0.93 December 2012 δD = 4.16 18O-4.44 0.91 November 2013 δD = 5.04 18O+1.89 0.84

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In this study, the isotopic compositions of SW and GW during the wet and dry seasons were examined in order to see seasonal variations. The statistical analysis showed that the average 18O between wet and dry seasons was significantly (p = 0.0026) different. For example, wet season had lower oxygen values than dry season. Hence, the isotopes in the study site basin are depleted more in wet seasons than is the case in dry seasons. The empirical equation found by Craig (1961b) was used to analyse the composition of the isotopes of oxygen and hydrogen in samples of precipitation, snow water, and river water from all over the world. This equation is known as Global Meteoric Water Line (GMWL): δD = 8 δ18O + 10 (shown in equation 4.2, Methodology Chapter) This equation is used to describe the relation between Oxygen-18 and Deuterium. Similar result was obtained by the IAEA (International Atomic Energy Agency) after collecting samples worldwide (equation 5.1): δD = (8.17 ± 0.08) δ18O + (10.56 ± 0.64) (5.1) In order to compare the result, Pretoria Meteoric Water Line was established as equation 5.2. δD = 7.05 δ18O +7.6 (5.2) The intercepts in most places around the world are approximately 10‰. However, the value of the intercept is based on the evaporative conditions in the water source region. Higher intercepts indicate faster evaporation rate. The dry season precipitation was found to have an intercept of 13.30 (Table 5.4), which is higher than that of the GMWL of 10 due to the different air masses affecting the study area.

No significant isotopic composition was observed between wet and dry season sampling, indicating that there was no difference between winter and summer temperatures.

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The clustering of stable isotope values of water samples from drainages, river, and auger holes in the wetland and all of the river water samples, indicated that all water samples are derived from a similar source of water.

The average intercept values of the local meteoric water lines (LMWLs) of 128 samples for May 2007, December 2008, June 2009, January 2010, July 2010, June 2011, November 2011, July 2012, December 2012 and November 2013 were 13.30, -37.28, 5.46, -93.92, 12.19, 5.46, -89.91, 12.19, -4.44 and 1.89 respectively. These results indicate that the datasets do not define coherent regional meteoric water lines (MWLs).

June 2009 and June 2011 appeared to have approximately similar slopes and intercepts (Table 5.4), suggesting that the waters draining the basins have a similar origin. In addition to this, isotopic signatures for July 2010 and July 2012 were similar, indicating both samples have a similar origin (Coplen and Kendall, 2000).

Figure 5.24 depicts the different isotopic signatures according to the source of water. The springs and groundwater samples appear to form a distinct group, while the drainages and river water generally cluster together; indicating they are from the same source. The auger hole samples are quite variable with those associated with upstream transects grouping with the drains, while those associated with the downstream transects are more similar to the spring signatures (Figure 5.25). The indications are that the springs have highly variable signatures which may suggest that there are different types of springs to be found in the area, some that are directly associated with groundwater and some that are associated with the drainage of sub-surface water circulating above the general level of the regional water table (Kotze, 2005).

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0.0

-5.0

-10.0

-15.0

SMOW -20.0

00 00

0 D D

δ River samples -25.0 Spring samples

-30.0 Drain samples

Auger holes -35.0 samples Boreholes samples -40.0 -7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 δ18O 0/ SMOW 00 Figure 5.24 Deuterium and Oxygen-18 plot for water samples based on water source

0.0

-5.0 -10.0 May.2007 Dec. 2008 -15.0

Jun. 2009 SMOW

-20.0

Jan. 2010 00 / -25.0 0 Jul. 2010

D D -30.0

δ Jun. 2011 -35.0 Nov.2011 -40.0 Jul. 2012 Dec.2012 Nov.2013

Sampling source

0 Figure 5.25 Plot showing δD /00 SMOW (Standard Mean Ocean Water) versus source of water

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5.5.2 Tritium

Table 5.5 and Figure 5.26 present the tritium-specific activities (TU) for all water samples during sampling periods of May 2010, December 2011, April 2012 and October 2013. There was no noticeable trend within tritium values across the various springs that were sampled, which was consistent with the variability in the isotopic signatures of the spring water. Also, during April 2010, the three left bank springs (Jordaan Spring, Loumauwe Spring and another spring at T5 environment) did not show significant variation. The higher tritium values (TU=1.4) and the smaller (TU=0.6) periodic oscillation observed for Piezometer T510, during April 2012 and December 2011 respectively, could be due to the small amount of rainfall during April 2012. Furthermore, during April 2012, five piezometer samples did not show significant variation. The tritium values for the river water samples were much more consistent, but did not show any strong seasonal variations, while it might have been expected that the dry season river samples would show up as older water originating from sources with long residence times.

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Table 5.5 Tritium values during May 2010, December 2011, April 2012 and October 2013

May2010 Dec.2011 Apr.2012 Oct.2013 Sample description TU TU TU TU Left Bank (RB) Spring 1 3.2 Left Bank (LB) Spring 2 0.8 LB Spring 3 0.7 RB Spring 4 1.4 RB Spring 5 1.0 RB Spring 6 1.7 River Upstream 1.9 River downstream 1.2 Groundwater at piezometer T510 0.8 River below downstream new bridge 1.9 Rive at downstream new bridge 1.6 River upstream culvert, north of Fertilis village 2.1 River at Transect 1(T1) environment 1.4 Right Bank Spring 1 1.7 Right Bank Spring 2 1.3 Right Bank Drain at T1 environment 2.3 Right Bank Drain at T2 environment 1.6 Vallis Borehole 0.2 Mashshu Borehole 0.7 Groundwater at piezometer T510 0.6 River downstream of Jordaan Spring 1.4 River upstream of Jordaan Spring 2.4 River at Vallis village crossing 1.7 River upstream 1.7 Piezometer T510 1.4 Piezometer T101 1.6 Piezometer T201 1.6 Piezometer T104 1.7 Piezometer T302 1.2 Jordaan Spring 1.3 Loumauwe Spring 0.6 Left Bank Spring at T5 environment 0.7 Mashushu Borehole 0.9 Vallis Village Borehole 0.3

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Table 5.5 continued

May2010 Dec.2011 Apr.2012 Oct.2013 Sample description TU TU TU TU River below downstream new bridge 1.4 Right Bank Spring 1 1.9 Piezometer T201 1.2 RB Spring 4 1.1 Rive at downstream new bridge 1.4 River at Vallis village crossing 1.7 Piezometer MRB302 1.2 River upstream 1.3 River downstream 0.8 Mashushu bore hole 0.6 Right bank spring, LBS 3 1.2 Loumauwe Spring 0.9 Jordaan Spring 1.3 Piezometer MRB 101 0.9 Drain T1 1.3 Valis borehole 0.7

The highest value for tritium was observed at Left Bank Spring 1 (TU=3.2, during May 2010), located at the top extreme end of the study area as compared to the least value from Vallis Borehole (TU=0.2, during Dec. 2011). This result is in agreement with the result obtained by Thatcher (1962) that the atmospheric concentration of tritium in western Washington was estimated to range from 3 to 5 TU. The cause for high concentration of tritium in the study area during May 2010 could be that during the study period, new rainfall water entered the spring storage and mixed with old water. This further strengthens the argument that the spring waters come from different sources with different residence times and ages.

The Vallis borehole sample appears to be the oldest water (0.2 TU); indicating its age is about 40 years. This would be expected as the concentration of tritium in groundwater decreases by radioactive decay Poreda et al. (2008). The results of Vallis Borehole during December 2011 and April 2012 were consistent

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(Table 5.5 and Figure 5.26). The next old waters after Vallis borehole are Loumauwe Spring, Piezometer MLB510 and Mashushu bore hole each having the same tritium concentration (TU=0.6). Loumauwe Spring and Piezometer MLB510 located at left bank environment (Table 5.5 and Figure 5.26), while Mashushu bore hole is situated 3 km north of Valis village. Hence; indicating its age is less than 45 years. All other water samples plotted between 0.8 TU and 4 TU; indicating a mix of sub-modern and modern water (Sawodni et al. 2000).

May 2010 Dec.2011 April 2012 Oct.2013 3.5

3.0 2.5 2.0 1.5 1.0 0.5

Tritium conc. conc. (TU) Tritium 0.0

Sampling Sites

Figure 5.26 Tritium concentrations from May to October 2013

Also, samples that fall below 0.8TU indicate sub-modern water (prior to 1950s). The drain sample is of the same order of magnitude as the river water suggesting that the drainage water has a short residence time in the wetland. The majority of the piezometer water samples are also similar to the river water and have relatively high tritium values. However, the sample taken at T5 had low tritium value during April 2012, while the sample from the same site during December 2011 (0.6 TU) was more consistent with the other piezometer sites.

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This may suggest that some spring water is contributing to the wetland subsurface water content during the dry season.

Estimates of ground-water residence time were determined from the concentrations of environmental tracers measured in samples of ground water collected at selected locations. The measured concentrations of environmental tracers in the ground-water samples initially were used to classify the ground waters as either modern (recharged after 1953), pre-modern (recharged prior to 1953), or indeterminate (Stamoulisa et al., 2011).

The absence of tritium in ground-water samples clearly indicates recharge prior to the period of bomb testing. Such ground water is designated either as pre- modern or older ground water. Conversely, ground water containing tritium concentrations greater than 1 TU is considered modern or young. Ground water containing tritium concentrations between the detection limit and 1 TU may be considered to have been recharged prior to the bomb testing period (Mazor, 1991) or is predominantly older water that may have mixed with a smaller fraction of modern ground water recharged after 1953 (Clark and Fritz, 1997). In ground-water samples that were determined to be pre-modern, are older than about 45 years.

Ground-water samples with concentrations less than 0.4 TU are considered to contain insignificant amount of bomb tritium, indicating that ground water in these samples was recharged prior to 1953 (Cox, 2003).

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piezometer T510, Mashshu Borehole, Loumauwe Spring, Left Bank Spring at T5 environment, River downstream, Piezometer MRB 101 and Valis borehole. This indicates that except River downstream, all groundwater (boreholes, piezometers and springs) samples fall in this range.

Ground-water samples from the Left Bank Spring 1 contained tritium at concentrations of 3.4 TU, suggest that ground water in the spring was largely recharged after 1953 (Cornaton, 2004).

Only comparative ages of water samples are referred to and no absolute aging of water based on tritium has been attempted. While these comparative values have provided some information about the age and possible movements of water in the wetland environment, a more intensive and better planned programme of tritium analysis would have provided a complete assessment. It may be concluded that this study has therefore demonstrated potential for the use of tritium water analyses in wetland studies (Hsin-Fu et al., 2014), but that the sampling scheme used within this study does not provide conclusive answers about different ages (and residence times) of different water sources.

Groundwater can either be very young, representing recent recharge to the subsurface, or it can exist as very old water that has been interacting with the rock and sediments that host it. Ground water is vulnerable to contamination from the land surface, and many contaminants in the water would follow the same paths and have similar travel times from recharge areas to points of use as the chemical substances analyzed. The effects of contamination may not be seen for several years after a contaminant is introduced into the groundwater system.

For environmental tracer investigation, age applies to the date of introduction of the chemical substance into the water and not to the water itself. The accuracy

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of a determined age depends in part on the estimate of the initial concentrations at the time of recharge and how perfectly the tracer substance moves with water. The concentrations of all substances moving with water through the unsaturated zone and beneath the water table are affected, to some extent, by transport and chemical processes, including dispersion, mixing, degradation, and sorption.

5.6 Water quality

5.6.1 Electrical Conductivity (EC) and Alkalinity (ALK)

The electrical conductivity (EC) and alkalinity (ALK) results from May 2007 to November 2013 are depicted in Figure 5.27. During each sampling time, EC and ALK were measured for EC 24 samples. A total of 272 samples were collected for the analysis. EC was high in the Vallis borehole during the wet period (November 2010, 681µS/cm and April 2009, 554µS/cm); indicating that significant amount of salt entered the groundwater system. However, Mashushu Village borehole (3 km from Vallis borehole upstream) showed an EC of 307 and 291µS/cm during April 2009 and November 2010, respectively (Figure 5.28). This site shows the opposite seasonal trend to the Vallis borehole but the seasonal differences are small and possibly not significant. During May 2007, the lowest electrical conductivities (78 and 83 µS/cm) were observed in the upstream left bank spring1 (Figure 5.28) and river upstream respectively. The highest EC value (461µS/cm) was observed in the left bank spring. In December 2008, the lowest EC (120 µS/cm) was observed in T101 drainage; and the highest (381 µS/cm) was in the right bank spring 2 (Figures 5.27 and 5.28).

Higher electrical conductivities were observed during the start of the rainy season (November 2010) than the dry season (May 2007 and April 2009), although this is not evident from the December 2008 data. A possible

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explanation is that during the early part of the wet season surface runoff dissolves ions from surface soils (Ecos Environmental Consulting & Dodo Environmental, 2009).

450 400

350 May.2007 300 Dec.2008 250 Apr.2009 200 Nov.2010 150 Aug.2012

Alkalinity Alkalinity (meq/l) 100 Dec.2012 50 Jul.2013 0 Nov.2013 0 200 400 600 800 Electrical conductivity (mS/cm)

Figure 5.27 Total alkalinity against electrical conductivity during May 2007- November 2013

In addition, salts from individual septic tanks (because there is no common septic tank in the area) and roads during high flows could contribute to the increase in EC. Moreover, agricultural drainage and local catchment runoff could be contributing salts (Fetter, 1994). Evaporation of water from the surface of a wetland concentrates the dissolved solids in the remaining water contributing to higher EC values (Ecos Environmental Consulting & Dodo Environmental, 2009). After the Vallis borehole sample, the next highest EC values are measured in the two right bank springs (381 µS/cm and 416 µS/cm) suggesting that deeper sub-surface flows have the highest salt concentrations.

Figure 5.28 also depicts that electrical conductivity increases with alkalinity for all water samples. The results of May 2007, December 2008, and April 2009

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show very similar trend lines. However, the slope relationship between total alkalinity and electrical conductivity during November 2010 is higher compared to the other samples, and the highest electrical conductivity is observed for Vallis borehole, indicating that groundwater is more saline than other water samples.

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800

700

S/cm) 600 μ

500 May-07 Dec.2008 400 Apr.2009 300 Nov.2010 Aug.2012 200

Dec.2012 Electrical Conductivities ElectricalConductivities ( 100 Jul.2013 Nov.2013

of T1 of

tap watertap

RiveratT1

LB spring LB 2 spring LB 3

Drainat T2

RB springRB 2 springRB 3

b/nT2&T3

RB drain,RB T1 drain,RB T2

LB Spring, LB T5

Drainat T206

Auger hole,T1

JordaanSpring JordaanSpring JordaanSpring

Riverupstream

Auger hole,T202

LoumauweSpring

River, 100m ds River, of

Riverdownstream

Auger T104holeat

River,100m above

U stream U LB Spring1

Auger hole,T510, LB

Vallisborehole, from

RB springRB 1 (Ditolong)

RiveratValis crossing,

Drain,50m south of T1

Drainbetween T2 & T3

Drain,200mSouth of T1

Drain,300-400m south Drain,200m south of T1

Riverds (below bridge1)

Riveratupper causeway

Riveratupper crossing, T1

Mashushuborehole, tap-water Auger T302,holeat depth=2.80m Sampling Sites

Figure 5.28 Electrical conductivity against sampling sites during May 2007- November 2013

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5.6.1.1 Analysis of variance (ANOVA)

A one–way analysis of variance showed that the effect of season was significant; F (3,268) =6.04, p=0.0005.There was a significant difference in the average EC concentration between the following seasons ;summer (M=272.88, SD=124.67) and winter (M=217.41, SD=84.11), autumn (M=223.57, SD=97.98) and spring (M=278.22,SD=117.54) and winter(M=217.41,SD=84.1) and spring (M=278.22, SD=117.54).No significant differences were observed between summer and autumn, summer and spring and autumn and spring. The results of the study indicate that there was no significant increase or decrease in EC during all seasons. Reasons for the trend may be due to no land use change in the wetland environment during the last seven years. In addition, there was no significant urban development such as road and building construction in the area. Furthermore, there has never been effluents from industries and runoff from domestic and other human activities into the river during all seasons.

Significant differences in the EC concentration between Jordaan Spring, RB2, rds and rus were also observed; F (3, 28) =29.87, p=0000). Specifically the concentration at Jordan (M=-184.25, SD=35.32) was significantly different to that at RB2 (M=308.62, SD=48.67) and rus (M=120.62, SD=41.24), the concentration at RB2 was significantly different to that at rds (M=211.25, SD=34.99) and rus (M=120.62, SD=41.24) and finally the concentration at rus and rds were significantly different.

The T-test results show that there was a significant difference in the average EC concentration at Mashushu borehole (M=288.25, SD=41.00) and Vallis borehole (M=503, SD=123.12) boreholes; t (14) =-4.6805, p = 0.0004. This means that geology and soil composition in both sites are different. Valis

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borehole is located at the edge of the wetland (left bank, south), while Mashushu borehole (north) is three km upstream of the wetland. The wetland is built on dolomite rock, which leads to higher EC because of the dissolution of carbonate minerals in the watershed.

The EC concentration at drain 200m south of T1 (M=220. 37, SD=67.70) and 100m south of T1 (M=175.62, SD=25.24) was not significantly different (14) =1.7518, p=0.1017. The non-significant difference can be attributed to similarity in geological and soil chemistry as well as topography, since both sites very close to each other.

The results of regression analyses in table 5.6 shows that the difference in the average EC concentration between 2007 and 2008 was not significant (B=50.97, p=0.056); similar results were observed for the other subsequent years being compared, i.e.2008 and 2009(B=-50.35, p=0.060), 2009 and 2010(B=52.29, p=0.050), 2010 and 2012(B=-31.22, p=0.1770) and 2012 and 2013(B=3.39, p= 0.857).The results do not show evidence of neither an increasing nor a decreasing trend. Table 5.6 Table 3: Summary of Regression Analysis (N=272) Variables B SE P-value Year 2008 50.97059 26.60671 0.056 Year 2009 -50.35294 26.60671 0.060 Year 2010 52.29412 26.60671 0.050 Year 2012 -31.22059 23.04208 0.177 Year 2013 3.397059 18.81378 0.857 Constant 248.4779 7.011482 0.000

The results of the correlation analysis indicated a significant positive correlation between EC and alk (r = 0.8294, p < 0.001).This means that a high alk concentration is associated with a high EC concentration.

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5.6.2 Major ion chemistry

Concentrations of major ions present in the water samples are presented in Table 5.6. Both Schoeller and Piper diagrams were used to analize the results (Figure 5.29 and 5.30). Schoeller and Piper plots include cations and anions. Piper diagram include two triangles, one for plotting cations and the other for plotting anions. Anion and cation fields are combined to show a single point in a diamond-shaped diagram. These tri-linear diagrams are useful in bringing out chemical relationships among water samples in more definite terms.

November 2010 samples were subjected to more detailed ionic analyses (Cl,

SO4, NO3, HCO3, Ca, K, Mg and Na ions) and these results are presented in Figures 5.29, 5.30, 5.31, 5.32, and 5.33. The ion chemistry result shows that

HCO3 is the dominant anion (5.57 meq/l) followed by chloride (0.63 meq/l). The dominant cation is calcium (3.63 meq/l) closely followed by Mg (3.31 meq/l) (Table 5.7 and Figure 5.29). Overall, it was observed that Vallis borehole contains relatively elevated HCO3, calcium, magnesium, chloride, sodium and

SO4. Since groundwater mostly occurs in association with geological materials (such as carbonate rocks) containing soluble minerals, high concentrations of dissolved salts are normally expected in groundwater relative to surface or near- surface waters such as rivers, wetlands, lakes, drains (UNESCO/WHO/UNEP, 1996; Sadashivaiah et al., 2008).

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Table 5.7 Mean values of anion and cation analysis from November 2007 to November 2010 at the middle Mohlapitsi/Mafefe Wetland

Sample Cl SO4 NO3 HCO3 K Mg Ca Na Description (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) River us 0.12 0.05 0 0.9 0.02 0.4 0.41 0.12 T1 drain 0.13 0.04 0 1.03 0.02 0.61 0.66 0.14 T2 drain 0.15 0.04 0 2.67 0.02 1.51 1.63 0.17 Jordaan Spring 0.13 0.03 0.02 1.4 0.03 1.13 1.17 0.14 Valis borehole 0.63 0.34 0 5.57 0.08 3.31 3.63 0.77 River ds 0.13 0.05 0.02 0.93 0.02 0.82 0.84 0.13

Figure 5.29 Mean Schoeller diagram for River upstream, Drain T1, Drain T2, Jordan Spring, Vallis borehole, and River downstream samples for May 2007, December 2008, April 2009 and November 2010 (modified from Mekiso, 2011)

If the springs are associated with perched aquifers or fracture zone flow above the general water table (Hughes & Munster, 2010) they might be expected to have intermediate ionic signals related to short residence times. The latter types of springs appear to dominate within the study area based on the chemistry data, although the isotopic data suggested a mixture of spring types. The type and

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concentrations of salts in all sub-surface water will depend on the geological environment, the source and residence time of the water (Mazor, 1991). Mean nitrate concentration values were found to be below the detection limit in four of the six samples. However, the Jordaan Spring and River downstream sites both had nitrate values of 0.02 meq/l each indicating possible contamination.

Figure 5.30 depicted that Ca-Mg-HCO3 type of water dominated, with the exception of the Transect 1 (T1) drainage sample. The samples were clustered together in the cation triangle and fall under Ca-Mg-HCO3 type of water indicating the same source of origin. It also indicates that this water is a typical shallow, fresh groundwater (Tomar et al., 2012). The drainages reflect river water rather than dolomite water (Figures 5.30).

Figure 5.30 Mean Piper diagram of May 2007, December 2008, April 2009 and November 2010 for selected water samples

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0.7 0.6 0.5 0.4

0.3 Chloride, Cl (meq/l) Cl Chloride, 0.2 0.1 0.0 -6 -5 -4 18 δ O ‰ Figure 5.31 Mean chloride versus δ18O plot for May 2007, December 2008, April 2009 and November 2010.

Table 5.6 and Figure 5.31 depicts that chloride concentrations for all water samples remain nearly the same (0.12, 0.13, and 0.15 meq/l) except Vallis borehole (0.63 meq/l). The reason for an elevated concentration of chloride 18 0 when δ O /00 value is depleted is not clear.

Figure 5.32 shows that for surface waters, as calcium values increase, sulphate concentrations remain almost the same, while the highest concentrations of both calcium and sulphate were observed in the Valis borehole. The relationship between chloride and sodium is very similar for all the sources of water (Figure 5.33).

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18 16 14

12 River upstream (mg/l) 4 4 10 T1 drain 8 T2 drain Jordan Spring 6 Valis bore hole

Sulfate, SO Sulfate, 4 River downstream 2 0 0 20 40 60 80 Calcium, Ca (mg/l)

Figure 5.32 Mean sulphate versus calcium plot for May 2007, December 2008, April 2009 and November 2010

Cl Cl (mg/l) 10

0 0 5 10 15 20 Na (mg/l)

Figure 5.33 Mean chlorides versus sodium plot for May 2007, December 2008, April 2009 and November 2010

Mean chemical data of 16 representative samples (Table 5.8) from the study site were plotted on Schoeller and Piper-tri-linear diagram for 2011, 2012, 2013 and 2014. Figure 5.34 depicts Schoeller diagram, where anions and cations concentrations were plotted.

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Table 5.8 Mean values of anion and cation analysis from 2011 to 2014 at the Mohlapitsi/Mafefe Wetland Cl HCO3 SO4 NO3 K Ca Mg Na Sample description (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) (meq/l) River us 3.6 4.23 2.2 0.34 2.95 3.65 3.12 2.15 T1 drain 4.1 4.25 2.6 0.49 3.01 3.68 3.32 2.18 T2 drain 4 4.28 2.6 0.15 2.88 3.95 3.45 2.22 Jordaan Spring 0 8.12 2.64 0 2.9 3.86 3.85 2.78 Valis borehole 5.63 9.25 6.96 0.19 4.21 6.65 6.58 3.45 River ds 3.7 8.52 1.7 0.22 5.25 7.85 6.85 3.85 RBSp1 3.98 5.15 2.5 1.25 2.95 3.55 5.55 2.22 RBSp2 3.95 4.85 2.48 0.22 2.85 3.15 4.95 2.1 LBSp3 3.98 5.15 2.48 1.78 3.12 4.95 5.25 2.5 River at T4 4.16 8.23 2.04 0.31 3.45 4.26 4.95 2.85 River at T5 3.97 8.75 2 0 3.75 4.12 4.26 3.1 River b/n T2 & T3 3.75 7.23 1.63 1.12 3.45 5.15 5.2 3.15 Mashushu borehole 5.29 8.48 10.12 0.3 6.23 7.95 7.28 3.25 Piezometer MRB206 5.61 4.55 5.18 0.17 5.25 7.45 6.54 3.75 Piezometer MLB404 5.23 5.15 4.15 0.07 5.15 7.2 6.25 3.5 Loumauwe Spring 3.34 4.65 3.2 1.36 3.54 6.92 5.25 3.87

There was no significant change in chemical results during the study period, indicating that the major ions are from the same source. Na-HCO3 type water pre-dominated in water samples analysed from 2011 to 2014, indicating typical fresh groundwaters influenced by ion exchange (Tomar et al., 2012). This result is in agreement with that of Anwar et al., (2011), where they subdivided the tri- linear diagram (Figure 5.35) based on compositions of constituents. The dominant anion was SO4 (Mashushu borehole) with a concentration of 10.12 meq/l and HCO3 (Valis borehole). HCO3 showed the least concentrations, although percent composition has increased compared to the first sampling period (2007-2010).

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Figure 5.34 Mean Schoeller diagram for 16 different water resources samples from 2011, 2012, 2013 and 2014

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Figure 5.35 Mean Piper diagram of from 2011 to 2014 for 16 selected water samples

18 0 Figures 5.36, 5.37 and 5.38 showed chloride vs δ O /00 SMOW, calcium vs sulphate and sodium vs chloride concentrations, respectively.

6.0 5.0 4.0 3.0 2.0 1.0 0.0

-6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 Cl concentrations concentrations (meq/l) Cl 18 O δ O /00 SMOW

Figure 5.36 Mean chloride versus δ18O plot from 2011 to 2014

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) 10

8 y = 0.78x - 0.73 6 R² = 0.36

concentration (mg/l concentration

SO 2

0 0 2 4 6 8 10 Ca concentration (mg/l)

Figure 5.37 Mean sulphate versus calcium plot from 2011 to 2014

7 y = 0.51x + 2.51

6 R² = 0.07 5

2 Cl concentration (mg/l) concentration Cl 1

0 0 1 2 3 4 5 6 7 8 Na concentrations (mg/l)

Figure 5.38 Mean chlorides versus sodium plot from 2011 to 2014

Water hardness is caused mainly by the presence of ions namely calcium, magnesium, potassium, sodium, chloride, sulfate, nitrate, and fluoride. Hard water is not suitable for domestic use. In South Africa, the adopted specification for domestic water use is shown in Table 5.8.

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Table 5.9 South African Bureau of Standard (SABS) specification for domestic water (Wilson & Deborah, 2009) Ions unit Recommended operational Maximum allowable for limit limited duration Ammonium as N mg/l < 1.0 10 -20 Calcium as Ca mg/l < 150 150 -300 Chloride as Cl mg/l < 200 200 – 600 Magnesium as Mg mg/l < 70 70 - 100 Nitrate & nitrite as N mg/l < 10 10 – 20 Potassium as K mg/l < 50 50 – 100 Sodium as Na mg/l < 200 200 – 400 Sulphate as SO4 mg/l < 400 400--600

The study site communities has been using irrigation water since 1960s (Sarron, 2005), which does not include the wetland portion. Therefore, sodium composition in different sampling years and percent water classification were analysed and included in this report (Tables 5.10 & 5.11). Table 5.10 also depicts that Na concentration increased for all samples from the first to the second sampling point. For example, river upstream (us) sample showed an increment from 13% (2007-2010 sampling period) to 18% (2011-2014 sampling time), although the results were in the specified limit (Table 5.11). Within four years, Na increased by 46 %. Also, T2 drain jumped from 5% during first sampling to 18% in second sampling. Hence, Na composition showed 360% increment between two sampling periods. Na composition in Jordaan Spring was already in second level (Table 5.11). Na composition jumped from 6% (2007-2010) to 21% (2011-2014) for the Jordaan Spring. Therefore, according to Table 5.11 specification, Na percentage increment in Table 5.10 is indicating that the catchment could be polluted with salts in the near future.

5.6.3 Pollution by water

As global population continues to grow, people are putting ever-increasing pressure on the earth's water resources. Furthermore, pollution has become a human problem because it is a relatively recent development in the planet's 242

history. As industrialization has spread around the globe, so the problem of pollution has spread with it. Hence, pollution is one of the signs that humans have exceeded those limits. The protection of water resources from pollution is fundamentally related to their use, development, conservation, management and control (WHO, 2006).

When flowing water reaches any surface body of water, it will contain a variety of chemical compounds dissolved within it from the air and from the rocks and soil through which it has percolated. These compounds may be completely harmless, naturally occurring substances, but they may also include pollutants (Boulding & Ginn, 2003).

Pollution can be defined as the introduction into the natural environment (air, water or land) of pollutants that are liable to cause harm to human health or to animals, plants and the entire ecosystem environment (Lapham et al., 1997). Water pollution occurs when a river, lake or other body of water is adversely affected due to the addition of pollutants by human intervention.

Water quality can be affected by pollution from point sources and non-point sources. Point sources are identifiable points or places, such as a pipe or channel, which discharge directly into a body of water (WHO, 2006). This might be from wastewater treatment plants, factories and industrial plants, latrines, septic tanks or piped discharge from barnyards and other places where livestock are confined. Non-point sources are those where pollution arises over a wider area and it is often difficult to locate the exact place of origin. For example, fertiliser or pesticide washed from a field by rain may seep into a river or stream at many places both on the surface and through the soil. Pollution from non-point sources, also known as diffuse pollution, contributes most of the contaminants in rivers and lakes (Kolaja et al., 1986 & Hadfield & Smith,

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1997). Other non-point sources are pollution from construction sites and other land disturbances. The problems in identifying the exact point of origin make non-point sources much more difficult to control.

5.6.3.1 Causes of water pollution

Aquifers feed our rivers and supply much of our drinking water. They too can become polluted, for example, when weed killers used in the agricultural area drain into the ground. Groundwater pollution must be given emphasis like surface-water pollution. Groundwater pollution unlike others is very critical, as once an aquifer becomes polluted, it is very difficult, expensive and time consuming affair to clean it up and may remain unusable for decades (Juergens- Gschwind, 1989).

Many soils have the ability to remove certain types of pollutants, including phosphorus, heavy metals, bacteria and suspended solids. However, pollutants that dissolve in water, like nitrate and ammonia from fertilisers and animal wastes, can pass through soils into the groundwater (NGWA, 2010). This may cause high concentrations of pollutants in local drinking water wells. Leaking from underground storage tanks, solid waste landfills, improperly stored hazardous waste, careless disposal of solvents and hazardous chemicals on ground surfaces are other potential sources of groundwater pollution (Wallender et al., 2013).

Construction of pit latrines are governed by the local geology, since liquid from the pit could flow through rock and soil into the groundwater and to the well. If the latrine is at a lower level than the well, the effect of gravity will make groundwater contaminated from the pit flow away from the well.

Sediments consist of fine particles of mostly inorganic material such as mud and silt washed into a stream as a result of land cultivation and construction. They

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may also arise from demolition and mining operations where these activities take place. The presence of solid particulate material suspended in the flowing water is the reason why many rivers look brown in colour, especially in the rainy season. WHO (2006) called these particles as suspended solids while they are carried in flowing water.

Organic matter means anything that is derived from living organisms, for example plants and animals. Inorganic matter has a mineral, rather than biological, origin meaning it comes from rocks and other non-living sources (Lapworth et al., 2012 and Graham, & Polizzotto, M.L. 2013).

Large quantities of inorganic matter, in the form of suspended solids, may reduce light penetration into the water which can affect the growth of plants. Sediments may even suffocate organisms on the river bed. River water may also contain organic matter, such as human and animal wastes, which can deplete the oxygen in the water if the river is slow-flowing. This can lead to anaerobic conditions which may create unsightly conditions and cause unpleasant odours (Bauld, 1994 and Appleyard et al., 1997).

When organic pollutants such as human and animal wastes are released into a water body, bacteria will use the waste as food and break it down into simpler, less harmful substances. As they do this, the bacteria will use up the dissolved oxygen from the water. If the quantity of organic pollution is high, then all the oxygen from the water may be used up leading to anaerobic conditions (Addis et al., 1986 and Lawrence & Kumppnarachi, 1986). This is unlikely in a river where the water is moving but can happen in lakes or slow-flowing channels.

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Agricultural wastes are generated from livestock and poultry farming and from growing crops. They can be the source of many organic and inorganic pollutants in surface waters and groundwater (Andreoli, 1999 & Agriculture Western Australia, 2000).

In practice, sewage contains many kinds of chemicals/materials for example; the pharmaceutical drugs, paper, plastic, and other wastes people flush down their toilets. The sewage and waste water that is produced by each household is chemically treated and released in to sea with fresh water (Kreutzwiser et al., 2011). Microorganisms in water are known to be causes of some very deadly diseases and become the breeding grounds for other creatures that act like carriers. When people are sick with viruses, the sewage they produce carries those viruses into the environment. It is possible to catch illnesses such as hepatitis, typhoid, and cholera from river and sea water. Around half of all ocean pollution is caused by sewage and waste water.

A small leakage from the sewer lines can contaminate the underground water and make it unfit for the people to drink. Also, when not repaired on time, the leaking water can come on to the surface and become a breeding ground for insects and mosquitoes (Morris & Tyson, 2003).

Biological pollutants are microorganisms such as bacteria, viruses, protozoa and helminths that are harmful to humans and other forms of life (Ramirez et al., 2010). Infectious diseases caused by biological pollutants, such as typhoid and cholera, are the most common and widespread public health risks associated with drinking water.

Microorganisms may get into water with dust from the air as rain falls, and when water passes through soil which is polluted with human and animal wastes

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(Close et al., 2008). The contamination of water supplies with raw sewage (human and domestic wastes generated from residential areas) is the most common route for biological pollutants to enter water (Ramirez et al., 2010).

Hynds et al., (2012) stated that when contaminated river water moves downstream it is possible that any pollutant will be diluted as more water flows in and so increase the total volume of water in the river. This dilution may be enough to reduce the contaminants sufficiently to minimise the possible health effects but this process may not work for all pathogens.

The presence of faecal coliform bacteria in drinking water, and E.coli in particular, can indicate a possible presence of harmful, disease-causing organisms (Smith & Grimason, 2003). Viral contamination may come from sewage effluent discharged into a river or from open defecation by an infected person that may be washed by rainwater to a river or stream (Gerba & Smith, 2005).

There are several protozoa that can be discharged into water bodies from infected persons. A home sand filter is appropriate for removing protozoa from drinking water. The layers of sand and gravel will trap the protozoa (Mawdsley et al., 1995 &Baum et al., 2013).

Helminths or parasitic worms can also cause ill health in humans. Infection occurs through ingestion of the helminth eggs which may be present in food (Aramini et al., 2000). For example, helminth eggs may be present in the meat of cattle grazing on land contaminated by faeces.

Fertilizers return important nutrients to the environment, such as nitrogen and phosphorus, which plants and animals need for growth. The danger is that sewage is often released in much greater quantities than the natural environment can cope with. Phosphorus and nitrogen are common pollutants generated from

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residential areas and agricultural runoff, and are usually associated with human and animal wastes or fertiliser. Nitrogen and phosphorus are plant nutrients required by plants to grow. They are spread on farmland in the form of fertilisers. Rain washes these nutrients into rivers, streams and lakes (Gowd et al., 2010). If the nutrients are present in large quantities, they can encourage excess plant growth in the water causing the phenomenon known as an algal bloom, which means a sudden increase in the population of microscopic algae. If a water body has high nutrient levels it is said to be eutrophic; the process is called eutrophication. The main problem of eutrophication is that the suddenly increased population of aquatic plants can die off equally quickly (Ullah et al., 2009). The decay of the plant material by bacteria can cause deoxygenation of the water.

Eutrophication is more likely to be a problem in lakes than in rivers due to the fact that moving water in a river will disperse the nutrients; in the still water of a lake, the nutrients will accumulate (Malik et al., 2010).

Highly toxic chemicals such as polychlorinated biphenyls (PCBs) were once widely used to manufacture electronic circuit boards, but their harmful effects have now been recognized and their use is highly restricted in many countries (Adam, 2010). Nevertheless, an estimated half million tons of PCBs were discharged into the environment during the 20th century. In a classic example of transboundary pollution, traces of PCBs have even been found in birds and fish in the Arctic. They were carried there through the oceans, thousands of miles from where they originally entered the environment (Juliette, 2010).

Industries produce huge amount of waste which contains toxic chemicals and pollutants which can cause water and air pollution. They contain pollutants such as lead, mercury, sulphur, asbestos, nitrates and many other harmful chemicals

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(BBC, 2006). Many industries do not have proper waste management system and drain the waste in the fresh water which goes into rivers, canals and later in to sea. The toxic chemicals have the capability to change the color of water, increase the amount of minerals, also known as Eutrophication, change the temperature of water and pose serious hazard to water organisms (Azizullah et al., 2011).

The best known example of heavy metal pollution in the oceans took place in 1938 when a Japanese factory discharged a significant amount of mercury metal into Minamata Bay, contaminating the fish stocks there. It took a decade for the problem to come to light (IMO, 2011). By that time, many local people had eaten the fish and around 2000 were poisoned. Hundreds of people were left dead or disabled.

These heavy metals can harm aquatic organisms and humans (WHO, 2006). Farmers who use river water polluted by urban wastes for irrigation of fruits and vegetables may find their crops affected by the accumulation of these chemicals.

At high enough concentrations radioactive waste can kill; in lower concentrations it can cause cancers and other illnesses. For example, the biggest sources of radioactive pollution in Europe are two factories that reprocess waste fuel from nuclear power plants: Sellafield on the north-west coast of Britain and Cap La Hague on the north coast of France (IMO, 2011). Both discharge radioactive waste water into the sea, which ocean currents then carry around the world.

The nuclear waste that is produced by radioactive material needs to be disposed of to prevent any nuclear accident. Nuclear waste can have serious

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environmental hazards if not disposed of properly. Few major accidents have already taken place in Russia and Japan (Harrison, 2006).

Mining is the process of crushing the rock and extracting coal and other minerals from underground. These elements when extracted in the raw form contain harmful chemicals and can increase the amount of toxic elements when mixed up with water which may result in health problems (WHO, 2004). Mining activities emit several metal waste and sulphides from the rocks and is harmful for the water.

The garbage produced by each household in the form of paper, aluminum, rubber, glass, plastic, food if collected and deposited into the sea in some countries and enter the sea, they not only cause water pollution but also harm animals in the sea (IMO, 2011).

Large amount of oil enters into the sea and does not dissolve with water. For example, ships carrying large quantity of oil may spill oil if met with an accident and can cause varying damage to species in the ocean depending on the quantity of oil spill, size of ocean, toxicity of pollutant.

Fossil fuels like coal and oil when burnt produce substantial amount of ash in the atmosphere. The particles which contain toxic chemicals when mixed with water vapor result in acid rain. Also, carbon dioxide is released from burning of fossil fuels which result in global warming (WHO, 2005).

There are several thousand different types of pesticides in the environment and almost all of them are possible causes of water pollution (WHO, 2006). Pesticides include insecticides, herbicides and fungicides. For example, DDT, malathion, parathion, delthametrine and others have been sprayed in the

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environment for long periods of time for the control of disease vectors such as mosquitoes, and to control the growth of weeds and other pests.

Herbicides and Pesticides are used by farmers to protect crops from insects and bacteria/viruses. Fertilizers are useful for the plants growth and good production. However, when these chemicals and fertilizers are mixed up with water they become harmful for plants and animals (Environment Canada, 2013). Also, when it rains, the chemicals mix up with rainwater and flow down into rivers and canals and eventually in to groundwater system, which pose serious damages for aquatic animals.

As more cities and towns are developed, they have resulted in increased use of fertilizers to produce more food, soil erosion due to deforestation increase in construction activities, inadequate sewer collection and treatment, landfills as more garbage is produced, increase in chemicals from industries to produce more materials (Bishop et al., 1998).

During wet season, the landfills may leak and the leaking landfills can pollute the underground water with large variety of contaminants. It gets mixed up with other harmful chemicals and causes various water borne diseases like cholera, diarrhea, jaundice, dysentery and typhoid.

5.6.3.2 Measures to prevent water pollution in the catchment

The control of pollution should ideally take place at the point of generation, or, in other words, it should be prevented at source (Barrett et al., 1996b). Farmers must receive on-site training about good agricultural practices that will help reduce water pollution from agriculture. For example, the amount of fertiliser used and the timing of its application can make a significant difference. It would be better to spread the fertiliser before rain because if the fertiliser was spread beforehand then much of it would probably be washed away. This would not

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only pollute the nearest river but would, of course, also reduce the effectiveness on the crop (Day, 2001).

Pollution prevention is best achieved by ensuring that each potential point source is properly sited, designed, constructed and managed; the aim being to contain the pollutants and prevent their uncontrolled release to the environment (Burston et al., 1993). Sources of pollution should be sited as far from watercourses as possible (at least 15 m away) and below any water sources on the site. Appropriate use of excreta disposal, solid waste disposal and animal waste disposal will help prevent contamination of both surface and groundwater (Alley et al., 1999).

Springs usually become contaminated when latrines, animal yards, sewers, septic tanks, cesspools or other sources of pollution are located on higher land nearby. In areas with limestone rocks, contaminated material can enter the water-bearing channels in the rock and descend through cracks and holes or other large openings and may be carried along with groundwater for long distances (Alley et al., 2002). Other rock types can have a similar effect so it is important to have knowledge of the local geology to assess the probability of groundwater contamination. Key preventive measures that will help to ensure that spring water is of a consistently high quality are:  Digging a diversion ditch above the spring that will take surface water away from it,  Building a fence to keep animals away from the spring,  Designing and build a protection box for the spring that will prevent contamination, and  Monitoring the condition of the spring and the quality of the water regularly.

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For rainwater harvesting, pollution control means proper maintenance of the roof and gutters and careful cleaning at the beginning of every wet season. Some form of mesh should be placed between the guttering and the pipe that leads to the storage tank to prevent the entry of coarse debris; it then becomes important to clean the screen regularly to prevent blockage (WHO, 2006).

Water can become polluted from sources in the catchment even though they may be some distance away. Ideally, the whole catchment area should be protected to avoid pollution and erosion (WHO, 2006). Preserving the vegetation in the surrounding area can help protect the spring from pollution and from siltation caused by soil erosion.

Industries and factory set-ups must be restricted from contaminating the water bodies and are advised to treat their contaminated waste through filtration methods.

When soil gets eroded and ends up in streams, rivers and other waterways, chemicals that exist in soil mix with the water and create problems for plant and animal life. The best way to prevent erosion is to keep the soil in place by planting plenty of native trees, shrubs, grasses and groundcover. The plants' roots hold the soil in place and keep it from falling into the water. Compost should be contained in a bin or barrel to prevent the materials from being washed away.

Learn about local and national laws against water pollution and join up with groups working to protect water in your area. The person who owns/occupies or uses the land in question is responsible for taking measures to prevent pollution of water resources. If these measures are not taken, the catchment management agency concerned may itself do whatever

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is necessary to prevent the pollution or to remedy its effects, and to recover all reasonable costs from the persons responsible for the pollution.

Burning practices in the catchment must be controlled or avoided. The amount of chemicals (phosphorus) transported to the catchment will decrease. Construction activities for example, roads, buildings, bridges, et cetera must be done without wastage of resources and exposure of soil. If the construction environment is controlled, the amount of salts (ions) coming to the catchment will be reduced and pollution decreased Table 5.10 Na composition in different sampling times in the study area % Sodium (Na) composition 2007-2010 2011-2014 Sample description (mean values) (mean values) River us 13 18 T1 drainage 10 18 T2 drainage 5 18 Jordaan Spring 6 21 Valis borehole 10 17 River ds 7 16 RBSp1 16 RBSp2 16 LBSp3 16 River at T4 18 River at T5 20 River b/n T2 & T3 19 Mashushu borehole 13 Piezometer MRB206 16 Piezometer MLB404 16 Loumauwe Spring 20

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Table 5.11 Sodium percent water classification (Sawyer & McCarthy, 1967 & Wicox, 1995; Kumaresan, 2006) Sodium (%) Water class Mean between Mean between 2007 & 2010 2011 & 2014 < 20 Excellent All 6 samples 15 samples 20-40 Good - 1 sample from Jordaan Spring 40-60 Permissible - - 60-80 Doubtful - - > 80 Unsuitable - -

5.6.4 Cation-Anion Balance Analyses Figure 5.39 depicts that percent difference is 63.2, which is not acceptable results; while mean cation-anion concentration from 2011 to 2014 percent difference improved. Even this result (51.1 %) is not acceptable by professional water quality laboratories. Hence, water analysis during study period was not of sufficient accuracy (Figures 5.39 & 40). The possible causes for poor accuracy could be that mistake occurred due to faulty laboratory equipments or human error.

Figure 5.39 Cation-anion balance table from 2007 to 2010

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Figure 5.40 Cation-anion balance from 2011 to 2014

5.7 Study wetland water balance

5.7.1 Wetland water balance conceptual model

Contributions to the shallow groundwater levels within the study wetland soils were assumed to come from different sources depending on the wetland locations. In the upstream part, river some water is lost from artificial diversion (Figure 5.41). The artificial diversion (earth canal) is meant for small scale irrigation scheme in Mashushu Village (approximately 3 km north of T1. While local rainfall clearly plays a contributing role, there are some sites where additional contributions from the local catchments draining the valley sides appear to be important.

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Figure 5.41 Water losses at Mashushu earth canal, approximately 200 m below temporary gabion dam that could contribute to wetland drains and groundwater (Mekiso, 2011)

In most transects the piezometers closest to the river showed patterns of water level variations that are similar to the patterns of stream flow variation. This could be due to drainage from the wetland contributing to river flow and the variation in the amount of drainage closely follows patterns of runoff generation in the rest of the catchment (both processes labelled as C-W in Figure 5.42).

Over-bank flooding (O-BF in Figure 5.42) from the main channel does not seem to contribute a great deal to the water balance of the wetland and local knowledge suggests that inundation is not a common occurrence. This could be due to the fact that the wetland is more elevated than the river bed elevation and related to the small size of the study area, and steep topography that suggests that flood events would not be long lived.

The study wetland is fed by several springs or seeps, which reach the surface from some underground supply, appearing as small water holes or wet spots on

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hillsides or along river banks. Seeps mostly occur in lower elevation areas due to water runs downhill. The flow of water from springs and seeps may come from small openings in porous ground or from joints or fissures in solid rock.

Moreover, fracture springs discharge from faults, joints, or fissures in the earth, in which springs have followed a natural course of voids. For example, the sources of the three right bank springs and Jordaan Spring are from faults. Therefore, Jordaan Spring is one of fracture springs designated as S3 type spring.

In addition, tubular springs exist in the wetland. In tubular springs, the water flows from underground caverns. For example, in 2006-2007, the wetland environment experienced few springs, while between 2008 and 2014 several springs were observed. Year after year the wetland moisture increases and in some portions ponds and potholes were seen. These ponds are not caused by rainfall. It was also observed that caves of different sizes were found. This indicates that the wetland is built on karst topography.

Figure 5.42 is designed based on theoretical background and field observations, showing three different spring types. For example, S1 type represents springs occurring at the topographic gradient change between the valley slopes and the flatter wetland surface and sourced from the regional groundwater. S2 represents spring flow rising into the lower sediments of the wetland and therefore not visible. S3 represents springs occurring as flow from fracture zones (for example, Jordaan Spring), or perched water tables, above the general level of the regional groundwater table (Mekiso, 2011; Hughes & Munester, 2010). The field observations suggest that all three types of springs exist in the Mohlapitsi/Mafefe wetland.

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Explanations: P = Precipitation, E = Evapotranspiration, S1, S2 and S3 = springs Figure 5.42 Conceptual Model of the study site water balance (modified from Mekiso, 2011)

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Fluctuations in the piezometers that are remote from the channel in T6 are very similar to those close to the channel and while the variations are similar to the measured downstream stream flow, they are not always well correlated.

Observations were made of the regional groundwater table levels and their variations (the water supply boreholes were accessed and readings were taken), which helped to further develop ideas about the links between the regional groundwater and the shallow groundwater in the wetland.

Reports from locals and field observations indicate that in 2006 the river had stopped flowing altogether in the northern part of the study area and that flow recommenced approximately 100 m above the Jordaan Spring (Figure 4.3 in methodology). When the river stopped the Jordaan Spring contributed the downstream flow. It is assumed that the river water was infiltrating to the wetland under boulder beds, but no significant flow was observed in the drains at the right bank side. However, in 2007 the volume of flow in drains increased significantly and additional drainages were observed.

The close clustering of stable isotope values of water from drains and auger holes in the northern part of the wetland (T2 and T3) and river water samples taken over a period of more than a year indicate that they are fed by one type of water. These values are distinct from those observed in dolomite springs discharging into the valley on both the right bank and the left bank (Vallis area). Tritium values in almost all samples except those from boreholes (could be deeper dolomite water) indicate recent water. Field parameter measurements on samples on all water sources taken throughout the study period and major ion analysis of selected samples proved a low mineralisation CaMg-HCO3 dominant type.

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The present understanding on wetland suggests that its hydrology is likely to be dominated by local rainfall, surface runoff from the valley sides, and spring flow from recharge on the surrounding hills, evapotranspiration and lateral flow from the wetland to the river (McCartney el al., 2011). Acreman et al. (2007) demonstrated that contributions from channel flow appear to affect the upstream parts of the wetland (via boulder beds) and artificial drains also play an important role. However, field measurements clearly showed that the wetland receives flow from mega catchments (adjacent hills and mountains) and feeds the river as baseflow in the wetland environment (Bonell, 1998). In fact, baseflow is the primary source of running water in any stream during dry weather. Artificial drainage of the wetland soils plays an important role in some transects (notably T1 and T2).

5.7.2 Analysis of water balance of the study site

Workable and site specific water budgets for the study area were calculated using equation 4.9 in methodology: R + Imp − (SF + ∆GWs + ∆SWs + GWexp + CoU) = ET

The result was presented in Table 5.12. The ET term, which includes evapotranspiration plus all errors in measurement or estimation of the other water-budget terms, ranged from 8.30 cm in 2006 to 0.12 cm in 2012 and averaged 5.29 cm. The average annual potential ET estimated by Midgley et al. (1994) for the study wetland was about 14.33 cm. This finding was greater than wet year (2010, 12.32 cm) ET of the current study.

Years representing dry, average, and wet years were chosen from the water budgets presented in Table 5.12. The year 2011 represents a dry year. Precipitation during this year was 7.7 cm, which was less than the 7-year

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average for the annual water budgets (Table 5.12 and Figure 5.43). The previous year (2010) had received the highest precipitation, but change in ground-water storage decreased. Drainage of this stored groundwater to the stream as base flow kept SF higher than would be expected in 2011 and was followed by 2012 with below-average precipitation (14.1 cm), and SF (5.6 cm) for 2006 was the lowest of the 7 years. The estimated ET in 2011 was 2.63 cm and the highest was 12.32 cm in 2010. The year 2008 nearly represented an average rainfall year, but ET value (8.22 cm) was greater than that of the 7-year average ET (Table 5.12).

Rainfall in 2009 was 32.8 cm greater than the 7-year average. Streamflow in

2009 was the highest (30.3 cm) for the period 2006-2012. The estimated ET during 2010 was 12.32 cm, which was 7.03 cm greater than the average ET. The

ET was the lowest in 2012 with less rainfall (14.1 cm), indicating rainfall is directly correlated to ET when there is no human intervention.

Table 5.12 and Figure 5.43 also showed that in 2006, when the study site received 11.3 cm rain, streamflow was 5.6 cm; while in 2011(dry year) when the rain water was 7.70 cm, the streamflow was 8.1 cm. This situation could be explained as follows: The site is built on dolomitic aquifer, which has distinct flow characteristics produced primarily by the dissolution of mainly dolomite by percolating groundwater. Carbonate rocks are soluble in water rich in carbonic acid. In some carbonate rocks, dissolution of matrix material by water flowing through fractures can result in large conduits for groundwater flow and leading to the development of karst topography (Cook, 2003). Recharge of dolomitic aquifers is often very high. Thus, water can flow to the Mohlapitsi River from different directions. Karstification results from geochemical, climatological and geomorphological processes that affect and expose soluble rock, soil and alluvium (Atapur and Aftabi, 2002).

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Streams transport water and sediment and they are characterized by water moving under gravity that flows through defined channels to progressively lower elevations (Darby & Simon, 1999). Streamflow is always changing daily and the major influence on them is runoff created by rainfall in the watershed (Gordon et al., 2004). Rain water from far place can move to low places through fractured rocks in the surrounding hills and mountains. Water seeping into the stream beds from the surrounding ground is responsible for the water flowing in streams when no rainfall has occurred in a while (base flow). However, in an urban environment when the amount of impervious surfaces increase, the water that infiltrates into the ground during rain decreases, thus, there is less water in the surrounding ground to supply base flow. Appearance of drainages/springs during 2007, 2013 and 2014 in the right bank portion of the wetland are good examples.

However, a streamflow can rise even if it only rains very far up in the watershed (UKEA, 2012; Salvati & Sasowsky, 2002). For example, the study site experienced a devastating flood in 2000, when the site did not receive much rain (McCartney et al., 2011). In addition, it must be clear that water that falls in a watershed will eventually drain by the outflow point (Allan, 1995). For example, there are many cases whereby people experience flood without rain. People lost their lives and property without any notice. For example, flood caused the hospital in a place called Kasese in Uganda that damaged many homes and property. But there was no rain in Kasese that day (GNDR, 2015). However, it did rain in a hillside village few kilo meters away. As the rain fell in the hilly areas and travelled down to lower elevations, it never found a place to drain away. The drainage in Kasese is particularly poor due to inappropriate construction. This area of Uganda has seen a rising trend in the construction of roads and buildings without consideration for passages for rain water. This

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results in the rain hitting concrete with nowhere to go, leading to flooding miles downstream from where it rained.

Table 5.12 Water budget for the Mohlapitsi/Mafefe Wetland Catchment (all units are given in cm) Year Precipitation Imported Streanflow Change Change GW Consu. Evapotrans. (R) water (SF) in GW in SW exports use (Et) & (Imp) storage storage (GWexp) (CoU) errors (ΔGWs) (ΔSWs) 2006 11.3 0.0 5.6 -4.80 -7.80 0.0 10.0 8.30 2007 15.9 0.0 7.7 -4.78 -0.62 0.0 10.0 3.60 a2008 19.6 0.0 9.1 -4.72. -2.00 0.0 9.0 8.22 2009 32.8 0.0 30.3 -4.01 -4.32 0.0 9.0 1.83 w2010 45.1 0.0 25.3 -4.70 1.18 0.0 11.0 12.32 d2011 7.70 0.0 8.1 -4.46 -6.57 0.0 8.0 2.63 2012 14.1 0.0 18.4 -5.28 -8.14 0.0 9.0 0.12

Mean 20.93 0.0 14.93 -4.68- -4.04 0.0 9.43 5.29 wWet year, dDry year, aAverage year.

Although the wetland is located in the channelled valley, the overflow from the river did not contribute significantly to the water balance of the wetland. Figure

5.43 clearly indicated that ET was less than rainfall during study period. The evapotranspiration peaked in 2010; and reduced drastically in 2011 and 2012. During the year 2010 when the rainfall was higher than the evapotranspiration, the soil gained water.

Streamflow, change in groundwater storage, change in surface water storage as well as rainfall in the Middle Mohlapitsi Wetland are not correlated and the reason is as follows: The Middle Mohlapitsi Wetland is built on dolomite rock, which is characterized for having potholes and caves due to folds and faults. Rainwater from far country moves through mega catchments until it reaches the wetland. The wetland was formed with the upwelling of the groundwater (baseflow), not by the river flow.

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50 45 40 35 30 25 20 Rainfall 15 Evapotranspiration 10 5

Rainfall and Evapotranspiration Evapotranspiration and Rainfall 0

Hydrological year

Figure 5.43 Rainfall versus Evapotranspiration plot A comparison of the median monthly rainfall and the mean monthly Penman- Monteith potential evapotranspiration for the whole of the Oliphants catchment by Schulze et al. (1997) showed that there were no months when rainfall exceeds potential evapotranspiration (Figure 5.44). The study area is situated in the lower Oliphants Catchment. Consequently, rainfall conditions are not ideal for the growth of crops and, irrigation is necessary to reduce the risk of water shortages upstream of the wetland.

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180.0

160.0

140.0

120.0

100.0

80.0

60.0

Rainfall & Pot. ET (mm) ET & Pot. Rainfall 40.0

20.0 Rainfall Pot. Evap 0.0 Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Months

Figure 5.44 Median monthly rainfalls and mean monthly potential evapotranspiration for the whole of the Oliphants catchment (Source: Computed from data in Schulze et al. 1997

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CHAPTER 6: CONCLUSIONS, RECOMMENDATIONS AND SUGGESTIONS FOR FUTURE STUDY

6.1 Conclusions

This study attempted to reveal whether there were relationships between groundwater, surface water and rainfall at the study site. In addition, environmental isotopes and hydrochemistry were used to understand water flow generations and wetland dynamics.

Wetlands are complex ecosystems in which ground water and surface water interact, but because ground water cannot be easily observed, its role in the hydrology of wetlands is difficult to understand than that of surface water. The application of artificial drainage by the wetland farmers led to deep water table and has reduced the wetland area.

There was no relationship between piezometers and rainfall measured in the wetland. The reason for such result could be that other processes were contributing to the study site. These processes could include inflows from the adjacent hill slopes, the effects of artificial drains and et cetera. One of the important observations that have been made is that the research resources required satisfactorily quantifying and understanding wetland processes are substantial (Dixon and Wood, 2002; Conly and Wood, 2000; Meinzer, 1943; Theis, 1935).

Water-table measurements confirm that the hydraulic gradient is generally towards the river, in both the wet and the dry season, indicating that groundwater moves from the wetland to the river. Water table elevations in all

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transect is higher than the river, hence ground water moves downward toward the river’s lower elevation.

Measurements of electrical conductivity (EC) and total alkalinity (Talk) on all water sources collected throughout the study period and major ion analysis on six selected samples taken from 2007 to 2010 proved low mineralization CaMg-

HCO3 type of water.

Higher ECs were observed during the start of the high-flow season (November 2010) than the low-flow season (May 2007 and April 2009) for all water resources, except December 2008 data. A possible explanation is that during the early part of the wet season surface runoff dissolves ions from surface soils. Furthermore, mean value for major ion concentrations for water samples taken from 2011 to 2014 showed Na-HCO3 type water, indicating its source is shallow fresh groundwater.

Concentration of tritium in water samples shows seasonal variations. The maximum concentrations occur in late April 2012 (end of wet season); the next maximum concentrations occur in December 2011 (wet season). All samples that lie below 0.8TU indicate the existence of sub-modern water (prior to 1950s); while those that fall between 0.8 and 4TU indicate a mix of both modern and sub-modern waters (Schlosser et al., 1988). The cause for elevated concentration of tritium during May 2010 measured at left bank spring located about 3 km north of T1could be that during the study period, underground testing of atmospheric tritium from nuclear plants evaporated and fall down and mixed with surface water (Moram & Hudson, 1986; Ostlund and Mason (1974) (Ostlund and Mason, 1977, Ostlund and Mason, 1985; Happell et al., 2004; Mook, 2006; Morgenstern & Taylor, 2009).

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Tritium concentrations between 0.4 and 1.0 TU were considered to fall in a range where a clear distinction between modern and pre-modern groundwater could not be assigned based on tritium data alone (Stewart & Morgenstern, 2001). In general, the presence of tritium in groundwater sample means that the groundwater was recharged after post bomb-tritium era (Rozanski et al., 2001; Moran, 2007; Morgenstern et al., 2010; Clark & Fritz, 1997; Seitzinger, 1994).

Both radioactive and stable isotopes can provide information about a groundwater’s age, which refers to the last time the water, was in contact with the atmosphere. Younger water is more susceptible to contamination; therefore, it requires close monitoring.

One drawback of using age to assess vulnerability is that old groundwater may contain a small fraction of very young water that is highly contaminated

Drainage and burning of drained soils are common practices in the cultivated areas of the wetland (Kotze 2005). Hence, the wetland area is clearly decreasing, for example, the permeability test in the southern part of T2 and the entire T3 was 8.28 m/day, while that of T1 and T2 was 9.46 cm/day, indicating T3 portion of the wetland is already dry.

The Mohlapitsi River is not a major source of water for the wetland. Instead, the wetland exists primarily as a result of groundwater upwelling, which supports the river flow downstream of the wetland (McCartney et al., 2011). Hence, report by Darradi et al (2006) that the wetland supports dry-season flow in the Mohlapitsi River is not realistic.

This study attempted to examine the feasibility of using available data to develop annual water budgets in the study area. Therefore, it tackles with the

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second objective of the study, which is using Conceptual Water Balance model in order to develop a water budget for the wetland.

Water budgets account for the inputs, outputs, and changes in the amount of water by breaking the water cycle down into components. They provide scientific measurements and estimates of the amount of water in each component and calculate the movement of water among the different components – the flux or flow of water. The result is a budget that is a hydrologic record comparable to deposits, withdrawals, and changes in the balance of a checking account.

The time period for which the water budget is calculated is also critical for understanding scientific measurements and drawing appropriate conclusions about water availability. For example, we have to think of the difference between knowing the amount of water that flows through a gage each year versus knowing how much water flows past daily. Averages are insufficient for understanding many important management issues, which require managers to understand and address extremes in water availability.

Water budgets provide a helpful metaphor for the hydrologic aspects of water supply, but examining water availability as it pertains to ecosystems and natural resource management issues adds an additional layer of complexity. One key challenge is the need to assess availability at the same temporal and spatial scales to which aquatic and riparian species respond. This means hydrologic data must be measured or estimated at ecologically relevant scales and intervals. Future research should focus on advancing scientific techniques for quantifying ecological responses to patterns in water availability to provide objective information for resource managers on how key species of interest or overall

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ecological assemblages are affected by variation and alteration of hydrologic regimes.

Uncertainty is an inherent factor in hydrologic data collection, estimation techniques, and modeling. Errors associated with measurement techniques arise from the inability to accurately measure specific aspects of the hydrologic system, such as streamflow, the water level in a well, or soil properties that control evapotranspiration and runoff. Uncertainty arises from the inadequacy of our data collection networks to fully characterize natural spatial and temporal variability associated with hydrology, geology, climate, and land use. Therefore, future investigation must strive to estimate or quantify uncertainty associated with water availability and provide quantitative/qualitative information to end users.

Water availability is an important concern in the study wetland. Ensuring sustainable water supplies requires an understanding of the study wetland hydrologic cycle—how water moves through its atmosphere, land surface, and subsurface. Water budgets must be understood as important tools that water users and managers use to quantify the hydrologic cycle. It is important for the public and decision makers to have an appreciation of the uncertainties that exist in water budgets and the relative importance of those uncertainties in evaluating how much water may be available for human and environmental needs.

The water budget study conveyed the level of complexity inherent in conducting water balance studies and shows that results from even the most detailed studies of water budgets in natural hydrologic systems contain some uncertainty. This uncertainty arises from the natural variability in hydrology,

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geology, climate, and land use and inaccuracies in the techniques used to collect and interpret data.

The current study attempted to inform the public and decision makers about a scientific basis for water-resources and environmental management and to broaden awareness and understanding of water budgets and the hydrologic cycle so as to promote wise use and management of a most precious resource—water.

6.2 Recommendations

Groundwater – surface water interactions quantification has significance for the Resource Directed Measures (RDM) needed by DWS, which is in line with the requirements of the South African National Water Act of 1998.

The importance of long-term monitoring of GW table levels in the study wetland must be encouraged to analyse the processes and dynamics of water generation and retention within wetland. The quantification of groundwater recharge is a prerequisite for efficient and sustainable groundwater-resource management in arid regions.

Lack of awareness of wetland functions, uses and values of wetland ecosystems has caused their continued degradation, conversion and negligence in policy circles.

It is the responsibility of water resources managers to know how much water is stored in groundwater, lakes, and wetlands. Understanding the movement of water to, within, and from watersheds is a greater challenge.

Department of Water and Sanitation, Department of Agriculture and other interested parties within the watersheds need to be involved in the development of the water budgets. A special group that is responsible for maintaining the

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knowledge gained from water budgets must be formed to update the issue to the departments and the public at large.

With an increasing emphasis on watersheds as a focus for managing water quality, coordination between watershed-management and groundwater- protection programs will be essential to protect the quality of drinking water.

Isotope hydrology is of prime interest for water resource managers because fresh water is replenishing the isolated underground system. By understanding the age of the groundwater, water resources manager can determine how frequently the water is being replenished and how much of the resource is available for use. Knowing how water moves and is replenished will help minimize the risk of contamination.

The importance of environmental isotope tracers in tracing water dynamics in the Mohlapitsi Wetland is emphasized in the current research. On the other hand, there are limitations related to the costs and logistics of sampling and the cost of laboratory analysis. Secondly, a high level of expertise could be required for sampling and interpretation of the analysis. Hydrochemical investigations, electrical conductivity, and water isotopes (e.g. deuterium, Oxygen-18 and tritium), provided simple approaches for determining water sources and hydrological pathways within catchments (McCartney et al. 1998, McCartney and Neal 1999). Therefore, both hydrochemical and environmental isotope analyses have addressed third objective, which discusses the use of environmental tracers and water chemistry to trace water flow dynamics in the study area.

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Comparison of water quality analyses in the study area indicates that major ion concentration has increased. This trend line shows that water resources managers must critically think to further the study in the wetland environment.

In future studies, researchers should choose wetlands with small catchment areas to simplify investigations and to precisely quantify hydraulic functions.

Future study must concentrate on groundwater dependent wetlands. Groundwater dependent wetlands are vulnerable to development pressure such as agricultural operation and groundwater withdrawal.

Department of Water and Sanitation and Department of Agriculture through their policymakers are urged to take immediate action to meet the Ramsar Convention’s objective to stop and reverse the loss and degradation of wetlands and services to people. Policymakers and relevant departments have sufficient scientific knowledge to understand the need to take appropriate actions to conserve wetlands, wise use and their services to people.

6.3 Suggestions for future study

International Water Management Institute (IWMI) and French-South Africa research collaborations deployed postgraduate students from South African, Mozambiquean, Nigerian, French, Spanish, Portuguese and Austrian universities to prepare their academic theses. From these studies, about thirty two manuscripts were published on accredited international and national journals and quite good recommendations were made. Unfortunately, none of these recommendations were tried by the Departments of Agriculture, Water Affairs and Sanitation as well as Environmental Affairs. On the contrary, erosion at T2 environment reached climax and in five years’ time, the river width quadrupled as well as sediments of different sizes were transported by

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flood. During erratic rainfall, it was observed that T3 site was exposed to erosion at the right bank. The locals informed us that the river migrated to 130 m to the east during 2000 devastating flood.

Furthermore, the wetland area is decreasing at T3 site. In fact, except negligible amount of reeds, there is no any other symptom of wetland. It is in this portion of the wetland were low water table was observed. The soil is sandy loam and permeable (828 cm/day), while in T2 was 9.46 cm/day. In addition, T1 and T2 portions of the wetland are degrading since the length of man-made drainage ditches is increasing daily and reed-bed burning intensified by the farmers.

Before 2000 devastating flood, settlers in the Middle Mohlapitsi Wetland Catchment only used 120 hectares of irrigated scheme. When irrigation infrastructure was destroyed, the farmers occupied the wetland, which is now encroached by agriculture. However, none of the wetland farmers show responsibility to protect and properly manage the wetland. The farmers were not aware of wise-use of wetland concept since they assumed they are not owners of the portion they make use of it.

The Departments of Agriculture and Water and Sanitation must make use of the outcome of this study and upcoming studies and work on transferring knowledge to their extension agents. The extension agents in turn must implement the main outcomes and follow-up agricultural operation in the wetland. In addition, the same agencies should be designated to maintain and provide an additional level of assessment of the knowledge gained from water budget. This will assist in building general understanding of how much water is moving within the catchment.

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Water-budget equation was calculated for evapotranspiration (ET), the value of which was affected by errors of missing data. These errors are caused by overestimated/underestimated quantities, and poor measurements. Most of the inflow into the wetland was lost through evapotranspiration, either by agricultural crops or natural vegetation. However, the wetland functioning could play a role in the processes that affect flow in the river. Because of its linkage with the regional groundwater system, the Middle Mohlapitsi wetland is a complex hydrological system. Detailed water balance analysis is required to ascertain the contribution of the wetland to downstream flow in the Mohlapitsi River. This would require more accurate estimation of the evapotranspiration component of the water balance. Remote sensing technologies, such as the use of the Surface Energy Balance Algorithm for Land (SEBAL) can be explored to estimate seasonal evapotranspiration for inclusion into the water balance and more accurate determination of the unknown component of groundwater inflow from the hill slopes.

In the middle Mohlapitsi catchment where water resources are increasingly stressed, successful management requires detailed understanding of the hydrology and environmental factors. Lack of information about the hydrology and present utilization of water resources has been identified as being one of the most likely impediments to the success of the Catchment Management Agency (CMA).

Hydrological data and models are required to evaluate local resources, current utilization and the impacts of future use. This should include river and bulk distribution losses as well as water requirements for different sectors. In particular, there is a need for better understanding of water use for irrigation including information on abstractions, return flows and impacts on water quality. More quantitative information is required to evaluate the impacts of the

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elimination of prescribed flow reduction activities such as the removal of alien vegetation within the catchment.

Assessment needs to be made of the impact of water conservation and demand management strategies within the catchment.

Much more understanding is required of water quality issues within the catchment. In particular, there is need to incorporate water quality within evaluations of water productivity. In addition, high productivity may be achieved at the cost of much reduced water quality, which can have severe socioeconomic as well as environmental implications downstream.

Interactions between the high consumption of water for future industry sector and small scale farming need to be evaluated. The socioeconomic and equity implications of re-allocating quality water between sectors need to be assessed.

The consequences of water utilization and resource management within the study catchment on downstream users need to be considered. Of particular interest are the quantity and quality implications for the water resources and the impact of the Ecological Reserve when this is fully implemented.

Adequate information is needed about the extent, sustainable yield and current utilization of groundwater resources as well as understanding of groundwater and surface water interactions, and the implications of increased groundwater exploitation in the future.

Further research is needed to understand and evaluate the hydrological functioning of the wetland, its links to the regional groundwater system, to understand the variety of ecosystem services that it provides and the long-term consequences of agriculture. Despite the importance of agriculture within the wetland, there is currently little technical advice to support the farmers. Greater

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understanding of the hydrological functioning of the wetland, in conjunction with better understanding of the socio-economic factors influencing its use, would assist in better management.

There is a need for additional monitoring and continued improvement of science to understand the impacts of climate change on wetland and build climate change into watershed management decisions.

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