Masters Degrees (Environmental Hydrology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6589

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Assessing techniques for selecting a climate driver station for a study catchment.
(2025) Xolo, Thobeka.; Kunz, Richard Peters.
The accurate assessment and modelling of hydrological processes relies heavily on comprehensive and reliable climate data. In South Africa, the alarming decline in the number of climate monitoring stations and the poor quality of observed data (i.e. missing records) present a significant challenge to reliable hydrological modelling. In addition, it is crucial to select climate driver stations as representative as possible of the catchment being studied. Climate driver stations are essential for capturing representative climate conditions necessary for water resources management and planning. This study assessed existing techniques used for selecting climate driver stations for a catchment. Available daily rainfall and temperature datasets were infilled and extended to create a 70-year record for quaternary catchments C41A to C41E, which are situated in the Lejweleputswa District Municipality (Free State Province, South Africa). The Inverse Distance Weighting method was used to infill rainfall data, whilst the Mean Temperature Difference method, Difference in Standard Deviation method and a ranking algorithm method were used to infill missing temperature data. Rainfall driver stations were selected using the common Driver Station (DS) method as well as the Adjustment Factor (AF) method which is closely related to the CalcPPTcor approach. Pseudo temperature driver stations were selected for each selected rainfall driver station using a revised ranking algorithm. The Dent et al. (1989) median, Lynch (2004) median, Lynch (2004) mean and Pegram et al. (2016) mean gridded rainfall datasets were compared for their performance in estimating rainfall adjustment factors using the R2 , Nash-Sutcliffe Efficiency and Root Mean Square Error statistics. Each gridded dataset was then used to verify the methods for selecting a climate driver station DS and AF methods. The ACRU model was used to simulate inflow to the Erfenis Dam, which was then compared to a dam water balance as a means of verifying which method performed better. Key findings showed that the Pegram mean gridded datasets (monthly and annual) perform better in enhancing the representativeness of station rainfall for the study catchment. The results for the AF and DS methods were inconclusive due to various challenges, i.e. having no observed streamflow for the study catchment. It is recommended that the Pegram mean grids be considered when deriving rainfall adjustment factors, which are applied to the rainfall driver station to improve the representativity of catchment rainfall. It is recommended that the DS and the AF methods be re-evaluated in another study catchment with more climate stations and a reliable streamflow monitoring network.
Investigating groundwater and surface water interactions in the Uthukela Catchment, KwaZulu-Natal, South Africa.
(2025) Tshikororo, Mutondi.; Kebede Gurmessa, Seifu.
Groundwater-surface water (GW-SW) interactions are not fully explored in South Africa. This study investigated the interaction between GW-SW in the uThukela Catchment, located in KwaZulu Natal, South Africa. Understanding the complex interactions of the GW-SW is very important for water resources and water quality management, thus making it essential to investigate the factors that control these interactions. The widely referred factors include topography, geology (lineament and dykes), climate and land use. The research employed stable isotopes of oxygen-18 (δ¹⁸O) and deuterium (δ²H), piezometric analysis, baseflow analysis, in situ measurements of radioactive radon isotope (222Rn), and hydrochemical parameter of Temperature, pH and electrical conductivity (EC). Rainfall δ¹⁸O and δ²H were sampled across altitudinal transect and precipiation gradient at five locations; Catchment 6 (1921 masl, 1273 mm), Mike Pass (1621 masl, 1236 mm), Winterton (1103 masl, 833 mm), Pietermarzitburg (627 masl, 825 mm), and Eshowe (522 masl, 800 mm). The δ¹⁸O and δ²H revealed a weak altitude effect limiting its use to trace regional scale movement of groundwaters.The role of groundwater was investigated across three spatial scales: hillslope, catchment, and regional. A total of 470 samples were collected and analysed during the dry and wet seasons. These included 39 groundwater samples, 28 wetland samples, 363 surface water samples, and 40 spring samples. At the hillslope scale, stable isotope data and EC measurements indicate that groundwater plays a dominant role in runoff generation both during rainfall events and periods of no rainfall. At the catchment scale, stable isotopes and EC measurements shows mountain front aquifers are recharged from losing streams. Additionally, at the regional scale, ²²²Rn and baseflow analysis indicate substantial groundwater contributions to streamflow in the upper uThukela Catchment. However, there is no clear evidence of deep regional groundwater flow.
Assessing the utility of drone technology in estimating surface water temperature, total suspended solids (TSS) and Chromophoric dissolved organic matter (CDOM) in reservoirs: a case study in the uMngeni Catchment.
(2025) Pillay, Shannyn Jade.; Mabhaudhi, Tafadzwanashe.; Bangira, Tsitsi.; Sibanda, Mbulisi.; Kebede Gurmessa, Seifu.
Over the past few decades, South Africa has faced severe water shortages, primarily due to the declining quality of its natural water supplies. This decline has further strained irrigation standards, directly impacting crop yields, livestock health and soil fertility. This has emphasised the need for advanced, near-real-time approaches to assess and monitor key water quality parameters affecting irrigation water quality, such as water temperature, total suspended solids (TSS), and Chromophoric dissolved organic matter (CDOM). This research explores the utility of UAV-based remote sensing for monitoring water quality parameters in small reservoirs to address the limitations of traditional remote sensing and ground-based methods, which are often labour-intensive, costly and lack sufficient spatial and temporal coverage. Chapter 1 introduces the research problem, highlighting the increasing pressure on water resources in southern Africa’s resources due to climate change, population growth and land-use changes. It outlines the study's objectives, which include developing a robust methodology for using UAV-derived data to monitor key water quality parameters and improving decision-making in water resource management at the farm scale. Chapter 2 presents a global systematic review of the literature for UAV-based remote sensing for water quality monitoring. It critically evaluates advancements in sensor technology, machine learning algorithms and statistical approaches, identifying key research gaps. The chapter emphasizes the potential of UAVs to provide high- resolution, real-time data but notes challenges such as cost, regulatory constraints and the lack of standardized validation protocols. Chapter 3 provides a case study of the High Flight Farm dam in the uMngeni catchment, illustrating the application approach of UAV-derived data in monitoring water temperature, TSS, and CDOM. The study demonstrates the integration of UAV-based observations with machine learning techniques and model development to produce high-accuracy predictive spatial maps that inform sustainable agricultural practices. Finally, Chapter 4 synthesises the findings, addressing limitations such as weather and operational constraints while offering recommendations for future research. These include expanding research on underrepresented water bodies and promoting interdisciplinary collaborations to enhance the accessibility and scalability of UAV technology in water quality monitoring.
Use of environmental isotopes to investigate groundwater and surface water interaction in the South Phuthiatsana Catchment, Lesotho.
(2025) Phori, Thabang Sehlolo Leo.; Kebede Gurmessa, Seifu.; Leketa, Khahliso.
Lesotho, often referred to as the "Water Tower of Southern Africa," plays a crucial role in regional hydrology due to its high-altitude water sources, which significantly contribute to the Orange-Senqu River system. Despite its importance, comprehensive data on the country's catchment hydrology remains limited. This underscores the need to enhance understanding of Lesotho’s water resources to support sustainable management under the pressures of population growth and climate change. Isotopic techniques provide valuable insights that complement conventional hydrological methods and are critical in identifying groundwater recharge, essential for effective policy development and implementation. This study investigates groundwater and surface water (GW-SW) interactions in the South Phuthiatsana catchment, addressing a significant knowledge gap in Lesotho’s hydrology. A multi-parameter, multiscale approach was applied, employing stable water isotopes (δ¹⁸O and δ²H), the radioactive isotope ²²²Rn, baseflow separation, and in-situ electrical conductivity (EC) measurements to systematically analyse flow dynamics. Over 21 months from April 2022 to January 2024, water samples were collected from 50 springs, five precipitation stations, four rivers, five wetlands, and 11 boreholes. These were supplemented by additional datasets collected between 2018 and 2023, offering a comprehensive hydrological snapshot of the catchment. Stable isotope analysis led to the development of Lesotho’s Local Meteoric Water Lines (OxLMWL, Ms-LMWL, and Abia-LMWL), which revealed key isotopic signatures associated with the amount effect, altitude effect, and seasonal variability in precipitation. These LMWLs served as essential baselines for assessing recharge processes and determining the origins of water sources. The results show that highland wetlands are recharged primarily by precipitation and groundwater (subsurface) inflows, playing a critical role in sustaining upstream rivers with baseflow. Downstream river segments exhibited significant evaporative fractionation, marked by enriched δ¹⁸O and δ²H values, indicating prolonged residence times, warmer temperatures, and wider channel areas. Moreover, river classification using δ¹⁸O, 222Rn and EC revealed a systematic altitudinal trend: isotopic depletion at higher elevations and enrichment downstream, alongside decreasing ²²²Rn concentrations, highlighting reduced groundwater discharge with decreasing elevation. However, elevated ²²²Rn near the confluence of the Liphiring and South Phuthiatsana Rivers suggests localised zones of increased subsurface inflow. Boreholes, plotting above the LMWL, displayed isotope signatures consistent with rapid recharge from meteoric water. In contrast, spring samples exhibited more varied isotope values and plotted below the Abia-LMWL, suggesting evaporation before recharge, possibly due to shallow flow paths or delayed infiltration. While ²²²Rn measurements were intentionally excluded from boreholes and springs to avoid groundwater contamination during isotope sampling, EC was measured across all water sources. Although no consistent spatial pattern emerged in EC values for boreholes and springs, some localised areas exhibited elevated EC levels, warranting further investigation. Importantly, all EC readings remained below 1000 µS/cm, indicating generally low mineralisation and limited salinity issues within the catchment. Overall, the study demonstrates strong interconnectivity between GW-SW in the catchment, with hydrological processes governed by elevation, geology and climate. Key contributions include the establishment of local isotopic baselines, enhanced understanding of wetland recharge mechanisms and identification of spatial variability in GW-SW interactions. The findings provide a robust scientific foundation for integrated water resource management in Lesotho. By illustrating the hydrological connectivity between GW-SW water systems, the research supports a shift from isolated to joint resource management approaches. The insights gained can inform catchment planning, protection of the highlands recharge zone and adaptive water allocation strategies in response to environmental change. This study thus strengthens the evidence base necessary for safeguarding Lesotho’s water security through informed decisionmaking and sustainable resource governance.
Assessing cyanobacteria in a small reservoir using unmanned aerial vehicle systems (UAVs): a case study of High Flight Farm Dam.
(2025) Ngwenya, Nobubelo.; Mabhaudhi, Tafadzwanashe.; Bangira, Tsitsi.
Monitoring water quality, particularly chlorophyll-a (chl-a) concentrations, is critical for managing irrigation water, as excessive chl-a can degrade aquatic ecosystems and reduce water availability. While multispectral satellite-based remote sensing is widely used, its spatial resolution is inadequate for small water bodies, which are crucial to smallholder farmers. Unmanned Aerial Vehicles (UAVs) offer high-resolution, near-real-time data, presenting a promising solution. This thesis investigates UAV-based multispectral imaging for chl-a estimation in small reservoirs through an empirical study in South Africa, supported by a background systematic review of existing literature. The empirical study integrates UAV-based multispectral data from April, June, and July 2024 with in-situ measurements of chl-a, total nitrogen (TN), total phosphorus (TP), and dissolved oxygen (DO). The machine learning models tested include Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boost (XGBoost), K-Nearest Neighbours (KNN), with ANN consistently outperforming the others and achieving the highest R² values across the three sampling periods: 0.949 (April), 0.991 (June), and 0.734 (July). The green, red, and red-edge bands were the most sensitive for chl-a estimation. Seasonal patterns emerged, with high chl-a concentrations in April and June, followed by a decline in July due to reduced water levels. Strong correlations were found between chl-a and nutrient parameters, particularly TP (R² = 0.879) and TN (R² = 0.711) in July. This study highlights the potential of UAV-based remote sensing for high-resolution chl-a monitoring in small water bodies. This study demonstrates the potential of UAV-based remote sensing for accurate, localized, and detailed chl-a monitoring in small water bodies, offering valuable insights for water resource management in smallholder agricultural systems worldwide.
Role of groundwater in runoff generation at a hillslope scale using environmental tracers.
(2025) Cahi, Joss Alexander.; Kebede Gurmessa, Siefu.
Understanding surface water–groundwater interactions is essential for effective water resource management, particularly in the context of land use and climate change. This study investigates these interactions at two contrasting sites in KwaZulu-Natal, South Africa: the near-pristine Cathedral Peak Catchment 6 (CP Catchment 6) in the Drakensberg Mountains and the agriculturally impacted Fountainhill Estate (FHE) catchments near Wartburg. These catchments are representative of different climatic, topographic and anthropogenic conditions, offering insights into how land use and land use change influence hydrological connectivity. At CP Catchment 6, intensive field-based monitoring was conducted over two years using a combination of hydrometric measurements, stable isotopes, electrical conductivity (EC), radon (222Rn) and satellite-derived soil moisture modelling (OPTRAM). Sampling occurred across multiple temporal scales (event-based and seasonal scales) to capture both baseline and dynamic hydrological processes. The catchment exhibited stable groundwater contributions facilitated by steep topography, connected wetlands and limited disturbance. Baseflow was sustained by meteoric-origin groundwater, while significant rainfall events rapidly mobilised pre-event water stored in wetlands due to groundwater ridging. These findings validate and expand upon existing conceptual models (e.g., Harrison et al., 2022), highlighting the critical buffering role of wetlands and subsurface flow systems in maintaining perennial streamflow. In contrast, at FHE, hydropedological desktop assessments, historical soil surveys, OPTRAM modelling and EC monitoring data revealed fragmented hydrological connectivity driven by agricultural land use. Practices such as irrigation, soil compaction and fertiliser application in the surrounding farms have resulted in elevated solute loads and episodic flushing during storm events. The presence of farm dams moderated downstream water quality but altered natural flow regimes. The OPTRAM model proved effective in identifying active flow paths and subsurface recharge zones, even in the absence of extensive in-situ data. A comparative analysis underscores how natural and anthropogenically altered systems diverge in their hydrological responses. CP Catchment 6 illustrates efficient, topography-driven hydrology with strong wetland-groundwater interaction, while FHE displays disrupted, highly variable flow paths shaped by land use activities. This research refines conceptual models of runoff generation across diverse landscapes and emphasises the need to incorporate subsurface flow processes into hydrological models. These findings have practical implications for catchment management, especially in balancing water supply, land development and ecosystem sustainability in South Africa’s heterogeneous environments.
Using water isotopes, geochemistry, and unmanned aerial vehicles to investigate the origin of the Shu-Shu thermal springs and their role in affecting surface water/groundwater heat and chemical exchange: uThukela River.
(2025) Buthelezi, Gugu Happiness.; Kebede Gurmessa, Seifu.
The Shu-Shu thermal springs are located in Nkandla, KwaZulu-Natal, emerging underneath and at the margin of the uThukela River. This work aimed to determine the geothermal energy potential of the Shu-Shu thermal springs, their origin, and their role in heat and chemical exchange with the uThukela River. The specific objectives of the investigation included determining the origin, the extent of discharge, the depth of circulation of the thermal springs, and assessing the impact the Shu-Shu thermal springs have on the surrounding surface water of the uThukela River. The Shu-Shu thermal springs were investigated using; isotopic, physiochemical, and Unmanned Aerial Vehicles (UAV) methods. Water samples were collected from the thermal springs, surrounding surface waters, and rainfalls across different altitudes during wet and dry seasons. The stable isotope (δ 18O, δ 2H) analysis confirms the meteoric origin of the thermal waters with a positive 18O shift. The Shu-Shu thermal springs are regionally sourced as they have a similar isotopic signature to the rainfall in the Drakensberg Mountains. A hydrochemistry analysis performed indicates that the Shu-Shu thermal springs are Na-Cl waters that are dominated by ions such as SO4 2- , Na+ , Cl- , Ca+, and SiO2. The major ions signify a rock-water interaction and the leaching of amphibolites, gneiss, and pyrite. From the numerous geothermometers used, only the Silica (quartz and chalcedony) geothermometers provide a reliable estimation (76-80 °C) of the reservoir temperature, and the estimated depth of 1.8-2 km. Mineral saturation states calculated from GWB 11 software indicate that thermal waters are supersaturated (SI>0) with respect to quartz, tridymite, chalcedony, cristobalite, and undersaturated (SI<0) with respect to amorphous silica, anhydrite, gypsum, bassanite, halite and many more. The thermal map produced from the UAV images shows that the Shu-Shu thermal springs discharge zone extends to an area of 3100 m2 along the faultline that strikes at N 63° E. The metamorphic rocks underlying the thermal springs have a low hydraulic conductivity, causing a low discharge rate. Based on the reservoir temperature estimations using geothermometry, it can be concluded that the Shu-Shu thermal springs have a low-enthalpy (temperature) energy potential. The origin of the springs is controlled by faults and fractures. The use of geophysics is recommended to further investigate the subsurface extent of the springs. The association of the springs with dykes/fractures indicates the need to investigate the geothermal energy potential associated with the other dense network of fractures and dykes in South Africa.
Advancing precision water management in smallholder sugarcane farming: leveraging unmanned aerial vehicle-based remote sensing and machine learning for evapotranspiration and water stress assessment.
(2024) Yacoob, Ameera.; Gokool, Shaeden.; Clulow, Alistair David.
This thesis addresses the imperative of optimising water resource management within smallholder sugarcane cultivation in Swayimane, KwaZulu-Natal, South Africa—a region contending with the dual pressures of escalating food demand and increasingly volatile climatic dynamics. Smallholder farmers are indispensable to advancing food security and socio-economic development, underpinning up to 80% of the region's agricultural output. Nevertheless, their capacity to mitigate food insecurity is hindered by restricted access to vital resources, including reliable water supplies and advanced tools. These limitations necessitate innovative and economically viable strategies to enhance productivity and optimise resource allocation. Precision agriculture (PA) methodologies, supported by cutting-edge technologies such as unmanned aerial vehicles (UAVs), hold promise for smallholder farmers. By enabling data-driven, resource-efficient cultivation practices, UAVs emerge as an instrument to foster sustainable agricultural systems tailored to the unique challenges of these communities. Sugarcane, a high-value commodity crop, is integral to the socio-economic fabric of smallholder farming communities, substantially contributing to employment and subsequent regional economic advancement. However, the absence of irrigation infrastructure within smallholder systems and escalating water deficits driven by rising temperatures and prolonged dry spells present formidable challenges to sustainable production. This reliance emphasises the need for resource-efficient agronomic strategies that maximise water use while safeguarding yields. By harnessing the potential of PA methodologies, including UAVs equipped with advanced multispectral sensors, farmers can acquire high-resolution insights into crop water dynamics and evapotranspiration processes. To this end, this research pioneers integrating UAV technology with machine learning (ML) to refine water management practices, focusing on enhancing evapotranspiration (ET) estimation and monitoring crop water stress. Chapter 2 undertakes a bibliometric analysis of UAV applications in precision water management, employing Biblioshiny and VOSviewer to identify key research trends and highlight potential strengths, limitations, and future opportunities. The findings reveal UAVs' potential to address the limitations of traditional ground-based and remote sensing (RS) methods, which are often labour-intensive, expensive, and lack sufficient spatial and temporal resolution for effective water management in smallholder farming systems. UAV technology, driven by advancements in high-resolution data acquisition and the proliferation of cost-effective, open-source processing platforms, offers accessible, scalable solutions tailored to smallholders. While certain factors may moderate their adoption, continuous technological progress and decreasing costs present significant opportunities for UAV applications to enhance policy formulation, strategic planning, and operational decision-making, ultimately strengthening resilience in sustainable water management for smallholders. Chapter 3 presents an empirical evaluation of vegetation index (VI)-based ET estimation methods. Using data from a smallholder sugarcane field equipped with an eddy covariance (EC) system for ground-truthing, the study assessed five actual ET (ETa) models—ET-NDVI, ET-NDVIscaled, ET-NDVIKc, ET-EVI, and ET-EVI2—alongside an ML-derived crop coefficient (Kc) prediction model correlating in-situ NDVI with Kc values. The EVI2 model demonstrated superior performance, achieving moderate to strong correlation (R² = 0.63) with lower Root Mean Square Error (RMSE = 0.67) and Mean Absolute Error (MAE = 0.52) compared to competing models. EVI2's resilience against NDVI saturation—a persistent challenge in mature sugarcane—translates to improved water use assessment, while reduced reliance on extensive in-situ data enhances its scalability for smallholder systems. Furthermore, high-resolution ETa maps derived from these models offer potential insights for optimising irrigation and improving productivity in resource-limited agricultural contexts. Chapter 4 presents a novel ML-based predictive model for the Normalised Difference Water Index (NDWI), utilising correlations with structural VIs (SVIs) from UAV and Sentinel-2 data. The Random Forest (RF) ensemble model achieves exceptional accuracy (R² = 0.95, RMSE = 0.03, MAE = 0.02), offering a precise and efficient tool for monitoring sugarcane water stress. Validated against ETa and the Water Deficit Index (WDI), the model confirms NDWI's reliability as a proxy for assessing sugarcane water status. A Principal Component Analysis (PCA) reveals complex interactions between NDWI, SVIs, and physiological parameters, further enhancing insights into sugarcane water status. Additionally, temporal analysis highlights NDWI's responsiveness to rainfall, with marked fluctuations pinpointing critical stress periods. By minimising dependence on in-situ measurements, the model offers a scalable, cost-effective solution tailored to the needs of resource-constrained smallholder farmers. In conclusion, this thesis advances PA by integrating UAV technology and ML to revolutionise water management in smallholder sugarcane farming. The VI-based ET estimation models and NDWI prediction framework deliver customised, high-resolution insights to optimise irrigation and enhance water efficiency during critical growth phases. Beyond showcasing these innovations, the study emphasises the necessity of capacity-building initiatives and user-friendly tools to enable farmer adoption, addressing climatic and socio-economic constraints. This work establishes a foundation for scalable, context-specific solutions despite its limited scope. Future research should prioritise decision support systems integrating UAV data and predictive models for real-time water stress monitoring and adaptive irrigation. By empowering smallholders, this study contributes to resilient agricultural systems, enhanced food security, and sustainable sugarcane production, laying the groundwork for global efforts against water scarcity and climate variability.
Investigating groundwater and surface water exchange in the Umgeni Catchment, Kwazulu-Natal, South Africa.
(2024) Mpungose, Thobeka Silindile.; Kebede-Gurmessa, Seifu.
The understanding of the role of groundwater in river basin hydrology and its contribution to the water resources base is limited. Past studies have focused on quantifying and modelling surface water. Recent South African policies emphasise the need for conjunctive use of water resources, including adding groundwater into the national water security mix and water balance accounting. Groundwater and stream networks fed by groundwaters are proven to be resilient against global climate change. The current study aims to shed light on groundwater recharge processes and its connection to the stream network in the Umgeni Catchment of KwaZulu-Natal province in South Africa. The groundwater recharge-flow-discharge processes are examined across altitudinal gradients and scales with specific emphasis on the role of wetlands, lithology, geomorphology, dykes, land use and land cover in controlling the connection between groundwater and surface water. Proven isotope tracers (Oxygen-18 (18O) and Deuterium (2H) and Radon (222Rn)), piezometry, electrical conductivity and baseflow separation were employed to investigate groundwater recharge processes and the connection between groundwater and surface waters. About 220 rainwater samples have been collected on a daily to monthly basis between March 2022 and January 2024 at three locations (Durban, Pietermaritzburg and Howick). In addition, we collected 180 samples, including streams (105), springs (18), wetlands (15) and boreholes (43), representing both the wet and dry seasons. The results showed that rainfall predominantly recharges the groundwaters. 222Rn data from the stream network revealed that the headwater streams of the Umgeni catchment are dominated by groundwater inflow, while the stream network downstream shows little sign of groundwater inflow. The findings highlight the critical role of rainfall in recharging groundwater and the strong influence of geology on groundwater contributions to surface waters in the Umgeni Catchment. The identification of groundwater-dominated headwaters and surface water-dependent downstream areas underscores the need for regionspecific water management strategies. Protecting recharge zones, implementing sustainable groundwater abstraction, and integrating groundwater-surface water management will be essential for ensuring long-term water security.
Quantifying the hydrological benefits of investing in ecological infrastructure through the use of ecological and hydrological models.
(2024) Srikissan, Sayuri Tasha.; Gokool, Shaeden.; Chetty, Kershani Tinisha.
Ecosystems are vital for the survival of all life on earth. Healthy ecosystems in turn provide invaluable goods and services that contribute to sustainable growth. Therefore, in order to produce and deliver goods and services at an optimum, ecosystems need to be managed, maintained and protected to remain within functioning capacity. There are many stresses that impact ecosystems functioning, examples of these include, growing population, climate change and land use/land cover (LULC) changes. These stressors alter ecological infrastructure (EI), which is the base from which ecosystem services (ES) are derived. EI is the natural equivalent of built infrastructure, e.g. dams, and provides beneficial services to society. Previously, attention had been centred on supply-sided interventions which focused mainly on built infrastructure investments. Despite their importance, the focus needs to shift to integrate investments between both built infrastructure and EI, this owes to built-infrastructure sites becoming scarce, and the majority of water resources already being allocated. The benefits of EI investments are generally not easily or explicitly demonstrated therefore there remains a reluctance to adopt EI investment approaches. To inform investment decisions pertaining to water resources management, tools such as ecological and hydrological models can be used. Thus, the aim of the study was to demonstrate how both ecological and hydrological can be used in tandem with each other to result in making more well-informed water resources management decisions. The novelty of the research was thus twofold: (1) demonstrating how LULC changes impact EI functionality in producing and delivering HES, (2) identifying how both ecological and hydrological models can be applied synergistically to reveal the full potential benefits of investments in EI. The study was conducted across the uMkhomazi catchment with a focus on the proposed Smithfield. A major concern within the catchment is the high degree of soil erosion which could potentially impact the functionality of the dam. Based on the dominant LULC within the catchment, i.e., grasslands, the targeted land management intervention selected was grassland restoration of degraded surfaces, with the protection/management of grasslands currently in good health. Grasslands provide a wide array of ecosystem benefits but are often disregarded in value therefore, it was assumed that changes to this LULC would result in significant impacts on HES.
Physicochemical characterization and applicability of the mini stream assessment scoring system and the South African scoring system version 5 in the Upper Awash Basin, Ethiopia.
(2024) Jele, Zizile Yoliswa.; Kebede Gurmessa, Seifu.; Taylor, Jim.
The Sustainable Development Goal (SDG) 6, introduced by the United Nations in 2015, focus on ensuring the availability and sustainable management of water, also encompassing the quality and sustainability of freshwater resources. Central to achieving SDG 6 is target 6.3, which aims to improve water quality by 2030. An essential indicator for this goal is SDG 6.3.2, tracking the proportion of water bodies with good ambient water quality. SDG 6.3.2 requires monitoring programmes based on relevant and measurable parameters. However, Africa faces challenges in implementing conventional physico-chemical water quality monitoring due to limitations such as scarce testing facilities, resource constraints, and expensive logistics. Therefore, a complementary approach is needed and in the context of this study, Biomonitoring is regarded as a necessary strategy. Biomonitoring involves assessing river health using aquatic macroinvertebrates. Research indicates successful applications of Biomonitoring in various countries, particularly in South Africa, where Biomonitoring tools like the South African Scoring System version 5 (SASS5) and the simplified Stream Assessment Scoring System (miniSASS) have been developed, tested and used. SASS5 is a standardized method that evaluates the presence and richness of macroinvertebrates, acting as sensitive indicators of water quality. MiniSASS is designed for non-experts, supports citizen science initiatives and aligns with SDG 6. b. The study aims to test the applicability of SASS5 and miniSASS in intermittent rivers and ephemeral streams in the Upper Awash River in Ethiopia. This region, situated in the Ethiopian highlands, represents a tropical area with high biodiversity and prominent water quality challenges. The research site choice is strategic, considering tropical rivers and more especially intermittent rivers and ephemeral streams which are often overlooked in water quality assessments. The study employs both Biomonitoring and physicochemical monitoring, including heavy metals. Principal Component Analysis (PCA) results highlight an inverse correlation between Biomonitoring metrics and heavy metals. The clustering of heavy metals in opposite end of the cluster of Biomonitoring scores reveals that Biomonitoring could be a good index for water quality even in relation of pollution with heavy metals. This research contributes to advancing scientific knowledge and addresses the applicability of South African Biomonitoring tools in diverse environmental contexts beyond their country of origin.
Groundwater recharge mechanism, groundwater-surface water connection and groundwater dynamics around Lake Sibaya, north eastern KwaZulu-Natal.
(2023) Nsibande, Thobeka Nomfundo.; Kebede Gurmessa, Seifu.; Janse van Rensburg, Susan.
Abstract available in PDF.
Understanding the fate and mobility of zinc in contaminated shallow groundwater and vadose zone with clay rich soils.
(2023) Terrell, Christie Lynn.; Lorenz, Simon Antony.
Abstract available in PDF.
The evaluation and quantification of the drought propagation process using satellite earth observation products.
(2022) Sukhdeo, Trisha.; Chetty, Kershani Tinisha.; Gokool, Shaeden.
Droughts can be categorized in four types namely, meteorological, agricultural, hydrological and socio-economic drought. Droughts have the potential to occur either as an isolated event, mutually exclusive event or through the progression from one form to another. The use of drought indices were recognized as an approach capable evaluating and monitoring the characteristics of the different drought types. The aim of this study is to evaluate and quantify drought characteristics as it evolves and propagates form meteorological to agricultural drought, within two climatically different regions within South Africa, namely the uMngeni Catchment and the Breede-Overberg Catchment. These areas generally have insufficient networks of ground-based observations to provide continuous and long-term data. Therefore, Satellite Earth Observation (SEO) data and Google Earth Engine (GEE) were utilized. The Standardized Precipitation Index (SPI) was selected to quantify meteorological drought, whilst the Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Health Index (VHI) was chosen to assess agricultural drought at both of the selected sites. The methodology undertaken firstly involved validating the SEO data against in-situ data. Thereafter, historical droughts were calculated by the SPI and SPEI indices at various timescales. Assessments were then conducted to determine the applicability of satellite based drought index VHI on quantifying agricultural drought conditions. The final assessment involved conducting propagation analysis between the drought indices. The findings of this study indicated that SEO have the potential to be utilized in the collection and monitoring of drought conditions. VHI was recognized to be scale dependent index, especially when considering averaging values. The findings of this study further suggested that the uMngeni region was more susceptible to the impacts associated with meteorological droughts characteristics whilst the Breede-Overberg region was more susceptible to the impacts associated with agricultural drought characteristics. Understanding the impacts and characteristics associated with the drought propagation process may further provide theoretical knowledge that can be used to facilitate more informed disaster, water and agricultural management and mitigation strategies to be implemented. If decision makers were to only consider drought using meteorological assessments for management decisions, the resulting strategies produced may be misleading as the impacts of an agricultural drought event may still be persistent.
An assessment of the use of remote sensing to estimate catchment rainfall for use in hydrological modelling and design flood estimation.
(2022) Khakhu, Khodani.; Smithers, Jeffrey Colin.
The accurate estimation of catchment rainfall is crucial, especially in hydrological modelling and flood hydrology which is used for the planning and design of hydrological infrastructures such as dams and bridges. Traditionally, catchment rainfall is estimated by making use of ground-based point rainfall measurements from rain gauges. The literature review conducted in this study supports that there is evidence of a decrease in the number of operational groundbased rainfall stations in South Africa which presents a challenge when estimating catchment rainfall for use in hydrological modelling and design flood estimation. Thus, innovative ways are required to estimate catchment rainfall and to improve the estimation of catchment design rainfall. This study investigated the use of remote sensing as an alternative way to estimate catchment design rainfall. To do this, a pilot study was first used to develop and test the methodology using a quaternary catchment that was selected based on the raingauge density. This was followed by the application of a refined methodology in another quaternary catchment which was used to verify the results that were obtained in the pilot study. After a comprehensive review of the literature, the remote sensing product selected for this study was the CHIRPS rainfall product. The methodology adopted first validated the remotely sensed rainfall data using the observed rainfall data and the estimated remotely sensed rainfall values were bias corrected using the observed rainfall data. The statistics that were used for validating are MAE, MBE, RMSE and D. The method that was used for bias correction was empirical quantile mapping Issues encountered, and as documented in the literature, include the unavailability of long periods of observed quality rainfall data and the limited and uneven spatial distribution of rainfall stations. Catchment rainfalls were estimated using observed rainfall, and this was assumed as the best estimate and was compared to the catchment rainfalls that were estimated using the biascorrected remotely sensed rainfalls. The performance of CHIRPS rainfall was varied among the approaches and the selected catchments. Nevertheless, the results from this study still show the potential of the use of remotely sensed rainfall to estimate catchment design rainfalls. At the daily timescale, satellite-derived and observed rainfall were poorly correlated and variable among locations. However, monthly and annual rainfall totals were in closer agreement with historical observations than the daily values. Despite the varied performance , the result of the study shows that CHIRPS rainfall product can be used to estimate catchment rainfall for hydrological modelling and flood frequency analysis. By acknowledging that the performance of remote sensing products is robust, it is of importance to note that the performance of the results presented is strictly for the catchments and stations selected for this project as well as the methods selected to validate and correct the bias in remotely sensed rainfall. The recommendations from the study are that a similar study is conducted in another region where there is even distribution of stations and a long record of quality observed rainfall beyond the year 2000 and consideration of the methods to identify outliers before making any meaningful estimations such as catchment rainfall from rainfall data.
Applying the social-ecological systems framework to understand impacts of flooding in the Palmiet River catchment.
(2021) Dlamini, Londiwe Zola.; Stuart-Hill, Sabine Ingrid.; Sutherland, Catherine Grace.
Accelerating urbanization in African cities is impacting the ability of urban ecosystem services to provide services to contribute to the wellbeing of people. Additionally, climate change presents increased urban risks such as the increased frequency and intensity of flooding. This thereby threatens human life and built infrastructure; and challenges the resilience of communities already strained by socio-economic challenges. Ecosystem services in urban catchments are poorly understood which further adds to the lack of understanding the value of natural resources in urban catchments and subsequently how to restore and protect vital natural resources in order to ensure ecosystem services delivery. The aim of the study is to understand how impacts of flooding decrease the resilience of the communities in the Palmiet River catchment located in Durban, South Africa, through applying the social-ecological system (SES) framework. The Palmiet River catchment is a dynamic and heavily urbanized catchment in which the Palmiet River extends 26km through its headwaters at an elevation of 510m flowing through the lower informal settlement at 18m elevation. The SES framework is an interdisciplinary approach to understanding biophysical and social aspects in a relational landscape – both of which can no longer be studied in isolation. The methodology of the study uses data collected from public community engagement forums to identifyspecific issues occurring within the catchment and understanding the roles of interested and affected stakeholders. Further, aerial photography images of the Palmiet River catchment from 1981 to 2016 were used to identify the rate of urbanization and terrestrial impacts; this data was additionally supported by drone images. A SES framework was applied for sub-sections of the Palmiet River catchment in order to develop a narrative for the total river catchment to improve understanding of societal actions of urbanization that impact the functionality of the Palmiet River. The findings of the study reflect that: 1) Flood events are occurring more frequently, and more peopleare at risk as the influx of people within the catchment increases and the land use/cover changes. 2) A collaborative social system with a strong governance unit exists within the Palmiet catchment. This has facilitated conversations amongst resources users and actorsin the rehabilitation of the resource system. This could potentially serve as a springboard for identifying viable areas for ecological infrastructure investments. 3) The social system has increased resilience within the catchment – however, this may change as flood events continue to increase in intensity and frequency. 4) The Palmiet River is a dynamic social-ecological system that presents challenges as well as opportunities for sustainable and integrative catchment management. The SES framework provided a tool to evaluate the social and ecological systems through which to assess thecurrent limitations for the Palmiet River to regulate flood events. 5) It was lastly necessary to identify ways in which sustainable urban design systems and ecological infrastructure could be used as a part of catchment management strategies to rehabilitate and enhance ecosystem services. It was concluded that the ecosystem services once offered by the Palmiet River catchment have been compromised byunprecedented rates of urbanisation, particularly impacts of growing informal settlements in the lower parts of the catchment as well as industrial areas in the upper parts of the catchment.
Detecting and assessing the impacts of outlier events and data availability on design rainfall and flood estimation in South Africa.
(2021) Singh, Keanu Reeve.; Smithers, Jeffrey Colin.; Johnson, Katelyn Ann.
Accurate Design Rainfall Estimation (DRE) and Design Flood Estimation (DFE) require long periods of quality-controlled data for the planning, design, operation, and improved flood risk assessment of hydraulic structures. However, observed hydrological data frequently include outlier events and there is a decline of hydrological monitoring in South Africa which may impact DRE and DFE. It is therefore necessary to assess the impact of outlier events and reduced data availability on DRE and DFE. The aims of this study were to: (a) assess the impact of outlier events on DRE and DFE in South Africa, (b) assess the performance of outlier detection methods under South African conditions, and (c) assess the impact of reduced data availability on DRE and DFE in South Africa. The impact of synthetic Low Outlier (LO) and High Outlier (HO) events on DRE and DFE from observed and synthetically generated data series were assessed. The performance of the BoxPlot, Modified Z-Score (MSZ) and Multiple Grubbs-Beck Test (MGBT) outlier detection methods were assessed. Record length and network density were reduced to assess the impact of reduced data availability on DRE and DFE. Results from the analysis of observed data show that design rainfall is impacted by up to 22% and design floods by up to 45% in the presence of LOs. Design rainfall is impacted by up to 16% and design floods by up to 46% in the presence of HOs. For synthetically generated data series, design rainfall and floods are impacted by up to 2% and 1% respectively in the presence of LOs and by up to 13% in the presence of HOs. At best, LOs in observed rainfall and streamflow data are under-detected by up to 6% and 30% respectively by the MGBT method, whereas HOs are over-detected up to 50% and 150% respectively by the MZS method. Design rainfall and flood events are impacted by up to 4% and 24% respectively by reduced record lengths, and by up to 4.5% and 60% respectively from a reduced gauged network. This study indicates that outlier detection be adopted as regular practice in South Africa and that additional national resources must be directed towards maintaining and improving the hydrological monitoring networks in South Africa.
Assessing the performance of techniques for disaggregating daily rainfall for design flood estimation in South Africa.
(2020) Ramlall, Ryshan.; Smithers, Jeffrey Colin.
Design Flood Estimation (DFE) and other hydrological modelling methods are used to limit the risk of failure and ensure the safe design of infrastructure and for the planning and management of water resources. The temporal distribution of rainfall has a significant impact on the magnitude and timing of flood peak discharges. Rainfall temporal distributions are therefore an important component of DFE approaches. In order to improve DFE methods which are based on event or continuous simulation rainfall-runoff models, it is generally necessary to use sub-daily time step rainfall hyetographs as input. However, the number of recording raingauges which provide sub-daily timesteps in South Africa is relatively scarce compared to those which provide daily data. Rainfall Temporal Disaggregation (RTD) techniques can be used to produce finer resolution data from coarser resolution data. Several RTD approaches have been applied in South Africa. However, application of RTD approaches locally is relatively limited, both in terms of diversity of approaches and cases of application, compared to those developed and applied internationally. Therefore, a need exists to further assess the performance of locally applied approaches as well update the list of available approaches through inclusion of internationally developed and applied RTD techniques. A pilot study was performed in which selected locally applied and internationally applied approaches were applied to disaggregated daily rainfall data. Some approaches were applied in their original form while others were modified. Temporal distributions of rainfall were represented by dimensionless Huff curves, which served as the basis for comparison of observed and disaggregated rainfall. It was found that for daily rainfall, the SCS3, SCS4 and Knoesen model approaches performed considerably better than the other approaches in the pilot study. The RTD approaches were further assessed using data from 14 additional rainfall stations. For the additional stations, the Knoesen model disaggregated depths provided the most realistic temporal distributions overall, followed by the SCS-SA approach. In additional, an adapted form of the Triangular distribution was found to show potential for disaggregation when a generalised value for the timing of the peak was utilised.
Water-use of commercial bamboo species in KwaZulu-Natal, South Africa.
(2020) Gumede, Mxolisi Percyval.; Clulow, Alistair David.; Everson, Colin Stuart.; Everson, Theresa Mary.
Abstract available in pdf.
Assessing the effects of site preparation treatments on erosion processes and sediment yield on a commercial Eucalyptus plantation: case study at Two Streams, KwaZulu-Natal.
(2020) Bull, Jordan Michael.; Hill, Trevor Raymond.; Everson, Colin Stuart.
Soil erosion monitoring and modelling is critical in the face of climate change, as erosion is detrimental to environmental and human health. It reduces soil productivity through degradation, compromises water quality through nutrient loading freshwater sources, and decreases reservoir capacity through sedimentation. This is a global challenge which is being amplified by increased levels of soil erosion on cultivated lands (e.g. commercial forestry), the combined effects of which hinder the success of several United Nations Sustainable Development Goals. However, commercial forestry is essential for human survival, providing a host of resources for human consumption, and expanding in its global coverage each year; although, this expanding need for commercial forestry creates a paradox, as it has the potential to damage environmental health and biodiversity (systems which humans rely on for survival), particularly through soil erosion and sedimentation of freshwater systems. Afforestation of plantations has been widely considered a land-use activity which reduces soil erosion; although, this is dependent on the management of the commercial plantations, where certain commercial forestry management techniques exacerbate soil erosion, such as the well-used site preparation technique of burning. Therefore, an investigation into the effect of commercial forestry site preparation techniques such as burning (at different severities) and mulching on soil erosion and the modelling thereof is required, as only a paucity of research has reported on this. Soil erosion measurements were conducted on a newly planted Eucalyptus dunnii stand, which consisted of three different site preparation techniques, namely a hot burn, a cold burn and a mulch treatment, in the Two Streams catchment, Kwa-Zulu Natal, South Africa. Micro-runoff and runoff plots were used to respectively measure splash and rill erosion of sediment, nitrogen, phosphorous, dissolved organic carbon, particulate organic carbon loss and runoff on each treatment at different slopes. In addition, soil erosion and runoff of this catchment and treatments were modelled using the ArcSWAT model, and the observations were used to validate the simulated outputs. The mulch treatment had the most consistent reduction in runoff and erosion, while the burn treatments of different severities generated greater respective runoff and erosion quantities through different erosional processes (splash vs rill). The ArcSWAT model over-simulated runoff on the hot burn and mulch treatment, while under-simulating on the cold burn treatment; however, the model consistently over-simulated sediment and nutrient loss on all treatments, indicating the model’s inability to simulate soil erosion on the defined land-use treatments. The reduced runoff and erosion produced by the mulch treatment is attributed to the protection that the mulch provides to the soil from splash erosion and the resistance posed to overland flow reducing rill erosion. The burn treatments generating more erosion and runoff through different erosional processes was attributed to the differing nature of debris produced by each burn severity. This research will contribute towards the data sets necessary to refine the land-use management tools of the ArcSWAT model to better model soil erosion on different land-use treatments. Furthermore, this research demonstrates the erosion processes that differing site preparation treatments are susceptible to, and what this means for future research and protecting soil and downstream water quality in the face of climate change.

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