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Masters Degrees (Hydrology)

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    Assessing and improving the simulation of runoff and design flood estimation in urban areas using the ACRU and SCS-SA models.
    (2022) Ndlovu, Zama Sibahle.; Smithers, Jeffrey Colin.
    Urbanisation is increasing at a rapid rate. Pervious and vegetated land is increasingly being replaced by impermeable surfaces (roads, pavements, driveways, parking lots, etc.) resulting in large portions of total imperviousness in catchments. The expansion of urban areas alters the natural underlying surface condition affecting catchment characteristics. The most common impacts of urbanisation on the hydrology of a catchment are increased runoff volumes, reduced baseflows owing to less infiltration taking place and a decrease in catchment response time. These changes can result in increased flood risk and subsequent damage to urban infrastructure and affect livelihoods. Therefore, accurate modelling of runoff and estimation of design floods of highly urbanised areas is necessary, especially in the often neglected catchments with informal settlements and infrastructure and in peri-urban catchments. Peri urban areas are defined as those areas located adjacent to a city area and have a mix of both rural and urban characteristics. Two rainfall-runoff models, namely the ACRU and the Visual SCS-SA model, were selected for application on catchments with typical South African urban conditions. The models have been developed and tested in urban catchments, however not extensively. The study areas are located in the South African urbanised cities of Tshwane and Pietermaritzburg. ACRU is a daily time step conceptual and physically-based agro-hydrological model that is relatively more data intensive compared to the simpler SCS-SA model. Therefore, information systems such as Remote Sensing (RS) and Geographic Information System (GIS) have been explored to aid as data sources and tools for acquiring model input parameters, at a more accurate level. The ACRU default values by Tarboton and Schulze (1992) and impervious area estimations derived by Loots (2020) were initially used to estimate the ACRU impervious parameters. Additionally, the pixel-based land cover classification method using satellite images was carried out in detail for this study as an attempt to map impervious surfaces and obtain impervious ACRU parameters with improved accuracy. Impervious land use classes were also extracted from the 2018 South African National Land Cover Database (SANLC), 2018 Global Man-made Impervious Surface (GMIS) and the 2010 Global Artificial Impervious Areas (GAIA). In order to use the ACRU and SCS-SA models confidently, the simulated results need to be verified against reliable observed data for each impervious scenario, if observed data is available. QGIS was used to obtain and process data into information required for the selected models. Several model input data such as slope, elevation, and catchment rainfall were estimated through GIS. The models over simulated observed design floods for the urbancatchments. Obtaining reliable observed data (rainfall and runoff), and satellite images with good resolution proved to be a consistent challenge throughout the study and could have contributed to the poor performance of the models. Urban area data dating back to the1990s was extracted from the GAIA method for most of the simulation period and a trend in impervious area expansion linked to urbanisation was detected and analysed against simulated streamflow from the urban catchments.
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    Evaluation of soil moisture estimates from satellite based and reanalysis products over two network regions.
    (2022) Naidoo, Kivana.; Chetty, Kershani Tinisha.; Gokool, Shaeden.
    The soil is an important variable of the hydrological cycle. It plays a key role in the distribution of water and energy fluxes between the surface and atmosphere. Soil moisture data can be used to develop early warning systems for flood and drought monitoring, improve weather and climate forecasting and provide an indication of crop water requirements. Therefore, the regular monitoring of this variable can prove to be beneficial to various management applications. One of the main issues associated with estimating soil moisture is to adequately account for its spatial and temporal variability as it is influenced by factors such as climate, topography, soil properties and land cover. There are different methods available to derive soil moisture estimations such as in-situ, remote sensing and modelling-based approaches. In-situ methods generally produce reliable soil moisture estimates, however, are only suitable for small scale studies. Alternatively, remote sensing and modelled reanalysis methods can provide soil moisture estimates over a large spatial extent, however, they are generally limited by their coarse spatial resolutions and may not be suitable for localised applications. Therefore, the aim of this study was to implement and evaluate a downscaling technique across two regions (South Africa and USA) to ultimately produce finer scale soil moisture and address the scale mismatch between in-situ methods and coarse resolution products. This procedure was facilitated by two data processing platforms, Google Earth Engine (GEE) and R, which showed significant potential for data processing and analysis. Additionally, satellite-based and reanalysis products were also evaluated to determine which of these methods are more suitable for soil moisture estimation. The soil moisture products and the downscaled products were validated against the CRNS instrument, which was particularly chosen for its performance at an intermediate spatial resolution. The SMAP_25 km product performed best at the Two Streams site and was selected for downscaling, whilst the CFSV2 product performed best at the Mead CSP3 and York Benny catchments and was chosen to be downscaled at both these sites. The results from the study indicated that the downscaled products for the Two Streams and Mead CSP3 sites performed better than the original products when compared to the CRNS data. The data acquired for the York Benny site revealed that the downscaled product performed similarly to the CFSV2 product. Therefore, downscaling does not always result in an improved outcome. However, from the results acquired for the Two Streams and Mead CSP3 study sites, it is evident that downscaling shows significant potential in producing better soil moisture estimates, which could be used to improve planning and management operations for various purposes.
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    Assessing the water productivity of sweet potato (Ipomoea batatas (L.) Lam.)
    (2022) Mthembu, Thando Lwandile.; Kunz, Richard Peters.; Mabhaudhi, Tafadzwanashe.
    Abstract available in PDF.
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    An investigation of the impacts of Acacia Mearnsii plantations on secondary aquifer systems within the Two Streams catchment, KwaZulu-Natal, South Africa
    (2019) Ngubo, Caiphus Zimise.; Demlie, Molla Bekele.; Lorentz, Simon Antony.
    Abstract available in the PDF.
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    Assessing climate change impacts on productivity of sugarbeet and sugarcane using aquacrop.
    (2018) Mokonoto, Ofentse.; Kunz, Richard Peter.; Mabhaudhi, Tafadzwanashe.
    Globally, the use of biofuels has grown over the years and their importance in helping to reduce a) dependency on fossil-based fuels and b) greenhouse emissions has been widely recognised. Various feedstocks are used for biofuels, viz. sugar-based crops for bioethanol production and oil from vegetable crops for biodiesel production. The research presented in this study focused on sugar crops such as sugarcane and sugarbeet. The sugarcane industry is widely established in South Africa, whereas sugarbeet is still a new crop and hence, there is little information on its water use efficiency (WUE) and potential yields under South African growing conditions. Overall, there is a need to better understand the agricultural potential and water use requirements of these feedstocks, in order to grow the biofuels industry in South Africa in a sustainable manner. Furthermore, climate change poses a threat to global food security as well as to biofuel feedstock production. There are uncertainties regarding the potential impacts of climate change on the yield and WUE of agricultural crops. One of the main objectives of this study was to calibrate the AquaCrop crop model for sugarcane and sugarbeet using experimental datasets. This study then followed a modelling approach to estimate dry yields and WUEs of these two sugar feedstocks to add to the existing knowledge base for potential biofuel production in South Africa. Sugarbeet was planted at the Ukulinga research farm and field equipment was used to collect data for the calibration of the crop model to better estimate attainable yield and WUE. Growth and yield datasets were provided by the South African Sugarcane Research Institute to calibrate the model for sugarcane, as well as validate AquaCrop for both feedstocks. The performance of the crop model was tested using various statistical methods. The model’s performance was satisfactory after calibrating it for sugarcane. However, the calibration process was compromised by the lack of sufficient leaf area index data. For sugarbeet, AquaCrop simulated the canopy cover, yield and WUE well, but tended to over-estimate observations. For the validation process, simulations closely matched the observed yields for both feedstocks. However, the model’s ability to simulate soil water content at Ukulinga was considered unsatisfactory. The calibrated AquaCrop model was used for long term assessments of yield and WUE. Baseline simulations were undertaken using 50 and 30 years of climate data and the results indicated that the 30 years of data could adequately estimate the long-term attainable productivity of sugarcane and sugarbeet. According to the literature, an ensemble approach to climate change modelling reduces uncertainty in long-term assessments. Hence, climate projections from several global climate models (GCMs), that were downscaled using dynamical and statistical approaches, were obtained and used to assess the potential impacts of climate change on yield and WUE of the selected feedstocks. An increase in yield and WUE of both feedstocks is projected in the distant future. The statistically downscaled GCMs projected higher increases compared to the dynamically downscaled GCMs. Increases in future WUE are much higher compared to yields projections. The so-called “CO2 fertilisation” effect largely benefits C3 crops (sugarbeet) with regards to yield improvements. However, the results also show that C4 crops (sugarcane) also benefit from improved WUE. Both sugarcane and sugarbeet will benefit from the anticipated climate change when planted in February and May, respectively. However, it is recommended that other planting dates should be studied for sugarcane.
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    An assessment of the critical source areas and transport pathways of diffuse pollution in the Umngeni Catchment, South Africa.
    (2018) Nsibirwa, Nantale Edith.; Jewitt, Graham Paul Wyndham.
    The difficulty in locating and managing diffuse pollution sources and their transport pathways is one of the reasons for the continued degradation of surface water in South Africa. Dealing with this problem is complex, as the sources and transport pathways of the pollutants are often not known because of the diffuse nature of the pollution. This study demonstrates the constraints of conventional diffuse pollution assessment approaches in identifying the Critical Source Areas (CSAs) and transport pathways of diffuse pollution, as applied in the uMngeni Catchment, South Africa. The use of various risk-based modelling approaches are reviewed for identifying the risk of diffuse pollution generation and transportation across a catchment landscape. The Sensitive Catchment Integrated Modelling and Analysis Platform (SCIMAP) Model is a risk-based tool that was developed to give a spatial representation of diffuse pollution sources. In this study, the SCIMAP Model was applied to identify and prioritise the protection and control of nutrient CSAs and transport pathways within the uMngeni Catchment. The results of the study were displayed in a catchment scale web map. The hydrological connectivity risk in the catchment was higher in the high-lying western areas and lower in the middle-eastern areas. The upper and middle parts of the catchment that are dominated by commercial agriculture and built-up urban areas were identified as the most impactful CSAs for intervention. The results are immediately applicable to water managers in the catchment and are strongly linked to the investment efforts in ecological infrastructure. A walkover survey revealed that the SCIMAP Model was able to direct the CSA investigations to the nutrient sources at four out of five locations. The survey also revealed that the accuracy of the modelled transport pathways increased with an increase in the elevation difference. The sensitivity of the SCIMAP Model to input land cover weightings was assessed, using an objective function. A high sensitivity of the modelled high-risk areas was observed on the intermediate diffuse pollution risk map, and a slight sensitivity of the modelled high-risk areas on the final diffuse pollution risk map, when the input landcover weightings were increased and decreased by 5%, 10% and 15%. This implies that caution should be practised in the formulation of the input land cover weightings, as they are a potential source of error in the model outputs. It is concluded that SCIMAP is a valuable tool for identifying the CSAs and transport pathways of diffuse pollution in a catchment. The results of the model can better inform the management of diffuse pollution and guide investments in the protection of the ecological infrastructure in the uMngeni Catchment. However, the establishment of input land cover weightings is very important and should receive priority in similar studies in the future.
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    Determination of below-ground vegetation and water use model parameters for a revised South African hydrological baseline land cover.
    (2018) McNamara, Megan Ann.; Toucher, Michele Lynn.
    The combination of both natural and anthropogenic activities have caused significant changes to the natural land cover which have impacted on the hydrological responses. The assessment of the magnitude of these land use change impacts on the hydrological response is important for sound water resource management, and is largely dependent on the baseline land cover used. The development of an updated natural vegetation map of South Africa by SANBI (2012), together with improved field based measurements of natural vegetation water use in recent studies, has led to the assessment of this map as a new hydrological baseline for South Africa. The proposed new baseline provides an opportunity to address the concerns raised about the current Acocks’ (1988) baseline used in South Africa. This study has provided estimates of the below-ground related vegetation and water use ACRU parameters for the proposed new baseline. These below-ground parameters estimated include the seasonal variations of the distribution of active roots in topsoil and subsoil horizons (ROOTA and ROOTB), the effective rooting depth (EFRDEP). The new and refined set of below-ground land cover ACRU input parameters will contribute to an improved and reliable baseline against which to assess any changes. As it was impractical to produce field-based measurements for the large number of natural vegetation species, and as it was not possible to form new spatial observations of theses below-ground root structures, the refined parameterisation of the below-ground component in ACRU was based primarily on review of measured values from past literature. The ROOTA values were estimated based on the vertical root distributions for various vegetation growth forms from previous studies together with the A-horizon soil depths of the vegetation clusters that constitute the baseline land cover. The effective rooting depth (EFRDEP) values were estimated by applying a linear regression relationship, relating rooting depths to Mean Annual Precipitation (MAP) for each baseline cluster. The study also involved a sensitivity analysis of the land cover input parameters to the ACRU Agrohydrological Model to determine the parameters to which the model is most sensitive.
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    The estimation and evaluation of a satellite-based drought index using rainfall and evapotranspiration.
    (2017) Mahomed, Maqsooda.; Chetty, Kershani Tinisha.; Clark, David John.
    Abstract available in PDF file.
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    The contribution of fog to the water balance along the eastern escarpment of South Africa.
    (2017) Aldworth, Tiffany Anthea.; Toucher, Michele Lynn.; Clulow, Alistair David.
    Fog is a frequent phenomenon in South Africa, occurring mostly on the west coast and along the mountains forming the southern and eastern escarpments. Fog measurements are, however, neglected in water balance studies, resulting in an underestimate of the precipitation input to catchments that experience frequent fog occurrences. World-wide, tropical montane cloud forest (TMCF) studies have proven that fog deposition, facilitated via the interception of fog droplets by vegetation, can represent a significant fraction of the total hydrological input. In South Africa, limited literature exists on the contribution of fog to the country’s water yielding catchments. In particular, information on fog patterns and its contribution to the water balance is extremely scarce in the mountains forming South Africa’s eastern escarpment, where only one study has been previously conducted. Additionally, no forestry studies in the country have attempted to quantify fog. Thus, the aim of this study was to determine the contribution of fog to the water balance of two research catchments of different land use types and altitudes, situated along South Africa’s eastern escarpment. These sites included the Cathedral Peak research catchments and Two Streams; Cathedral Peak is a high altitude montane grassland catchment, whereas Two Streams is at a lower altitude and afforested by exotic plantations. At Two Streams, fog and the climatic conditions were monitored over a 16-month period (July 2015 to October 2016) and additional measurements of throughfall, stemflow and soil water content were carried out in an Acacia mearnsii plantation, to further determine the fog contribution in a forest plantation. At the Cathedral Peak research catchments, fog and the climatic conditions were monitored at three sites, including Mike’s Pass Meteorological Station, Catchment VI and a High Altitude site. Monitoring was conducted over a 14-month period (September 2015 to October 2016) at Mike’s Pass and over a two-month period (August 2015 to September 2015) at Catchment VI and the High Altitude site. Fog was found to be prevalent, occurring frequently and for long durations, potentially contributing fairly substantial amounts of water to the water balance. It occurred all year round, but was predominantly a summer phenomenon, however, it comprised a greater proportion of the total precipitation during the dry winter season. At Mike’s Pass, fog represented a contribution of almost 30 % during several drier months. At Two Streams, during the driest month of August 2015, fog represented a contribution of approximately 38 % of the total precipitation. Fog increased with altitude as a whole, but changes in other topographic features (i.e. hillslope orientation and slope) over short distances, meant that the delivery of fog was not uniform from one point to another at the same altitude. Fog occurrence and water yield increased with wind speed, although this was not found to be a very significant relationship. A stronger relationship between wind direction and fog was observed, particularly at Mike’s Pass, the higher altitude site, which was better exposed to fog-bearing winds. At Two Streams, fog did not facilitate throughfall of rainfall or contribute to soil water. The indirect effects of limiting wet canopy evaporation and transpiration rates were suggested to be a more relevant effect of fog on the water balance. These findings further the understanding of the contribution of fog to the water balance along the eastern escarpment of South Africa and will assist in future long-term climatological studies of fog and low cloud occurrence in the region.
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    Modelling the impacts of changes in agricultural management practices on water resources with declining hydrometeorological data in the Uthukela Catchment.
    (2018) Shabalala, Mlungisi Maxwell.; Toucher, Michele Lynn.
    In order to meet the country’s growing demand for food, and to transform the economy of rural communities, the South African Government aims to develop the agricultural sector in the uThukela Catchment, KwaZulu-Natal Province. Intensification of agriculture will depend on the availability of water resources, with subsequent impacts on the quality and quantity of water resources. Therefore, the aim of this study was to investigate the impacts of proposed agricultural developments on the water flows in the upper uThukela Catchment using the multi-purpose, multi-soil-layered, daily time step ACRU model. The first phase of the study was to confirm the model’s ability to simulate flows in three, relatively small, gauged subcatchments of the uThukela catchment (Quaternary Catchments V11K, V14C and V31F), using current land cover and climate information extending to present day. However, the documented decline in the number of, and quality of data from, hydrometeorological stations, particularly since the year 2000, was concerning. Therefore, the impact of this decline on model performance was investigated in the selected subcatchments by comparing simulated flows to available observed flows in a confirmation study. Configuration of the model to present day conditions was restricted by the unavailability of rainfall stations. In cases where stations were available, there were no nearby stations to patch or compare to, when the record had missing or suspicious values. Given this, the model was set to run from 1960 to the latest record date available for catchments V14C and V31F. For V14C, the model performance decreased when the model was run from 1960 to 2012, compared to 1960-1999. Although a slightly better performance was obtained at V31F, the simulation time period was reduced to 1960-1999 for both catchments due to uncertainties with post 2000 rainfall and streamflow data. However, V14C continued to prove problematic and further investigation using of the Indicators of Hydrological Alteration software revealed a marked change in the flow characteristics between 1980 and 1981. No documentation of developments or substantial changes in the catchment could be sourced. Therefore, Quaternary Catchment (QC) V14C was excluded from further analysis. The ACRU model adequately simulated the flows for V11K and V31F, with the simulated flows being more representative of the observed flows in V31F. With the ability of the ACRU model to simulate the flows in the upper uThukela catchment under various land uses confirmed, the model could be used to investigate the impacts of agricultural land management scenarios on water flows. The agricultural land management scenarios were developed from the national and local government’s plan to expand agriculture to transform the socioeconomic status of the uThukela catchment. To develop scenarios for larger scale modelling, numerous scenarios were tested at QCs V31F and V11K. However, V11K was not responsive to changes in land use; therefore, results from the catchment were not used. For large scale modelling, the Upper uThukela (V1) Secondary Catchment was selected. The scenarios considered were: (i) increasing the fraction of irrigated commercial agriculture into currently dryland commercial fields, (ii) increasing subsistence agriculture through reduction of commercial agriculture (i.e. land reform), (iii) conversion of dryland commercial agriculture into crops with biofuel potential (iv) increased burning, (v) intensified land degradation and (vi) rehabilitation of degraded areas. These were developed from current land cover and compared to a simulation assuming natural conditions. The runoff components of interest were baseflow, quickflow and streamflow, as well as the low, median and high streamflows. Irrigation resulted in the highest flow reductions, with permanent cropping and planting two crops per year resulting in the largest decrease in streamflow at V31F and V1, when compared to natural conditions. These scenarios also had the greates impact on low flows. Plantation of biofuels increased flows, with soya beans having a higher impact on baseflows. Intensified burning and degradation increased quickflow and streamflow, while increasing subsistence agriculture and rehabilitation of degraded areas had little impact on flows. These results were generated from poor climate and land cover input information. Therefore, these results cannot be used at a definite decision-making tool, rather as an indication of the possible impacts of land use change on flows at the uThukela Catchment and similar regions. Efforts should be made to improve and maintain hydrometeorological monitoring stations. In addition, there should be more initiatives to collect land cover and water use data at various catchments in order to improve the quality of input data. Lastly, the current version of the ACRU model requires high computational power for large catchment simulations, lowering the model performance. Investigation into better versions or possible development of the current version should be conducted to enable modellers to finish large projects in allocated time.
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    Estimating water use and yield of soybean (glycine max) under mulch and fertilizer in rainfed conditions in KwaZulu-Natal.
    (2017) Lembede, Lungile Phumelele.; Kunz, Richard Peter.; Mabhaudhi, Tafadzwanashe.
    South Africa is classified as a semi-arid country characterized by low and erratic rainfall. This poses major limitations to crop productivity, especially for smallholder farmers who rely on rainfed agriculture. This is worsened by lack of knowledge regarding best management practices that can improve crop yields attained by smallholder farmers. In addition, smallholder farmers lack access to markets and do not participate in the agricultural value chain. The Biofuel Regulatory Framework (DoE, 2014) seeks to include smallholder farmers in the biofuel feedstock value chain. However, a prerequisite to their meaningful participation in the value chain would be to increase their current levels of crop and water productivity. The main aim of this study was to estimate the yield and water use of soybean (Glycine max L.) under rainfed and smallholder farming conditions using the AquaCrop model. Secondary to this, the effect of mulch and fertilizer on soybean water use efficiency was assessed. Lastly, the Soil Water Balance model (SWB) was used to compare simulations made by AquaCrop for the non-mulched, full fertilizer treatment. Thereafter, the water use efficiency of soybean was calculated from crop water use and the final yield. The soybean trial was carried out at Swayimane, KwaZulu-Natal. The model simulations of crop water use and reference crop evapotranspiration were also used to calculate crop coefficients under non-standard conditions. Crop growth and yield parameters were measured to calibrate and evaluate model performance. Soil water content was monitored using Watermark sensors, along with climatic variables. An analysis of variance (ANOVA) was used to detect significant interactions between treatments, while statistical indicators were used to evaluate model performance of AquaCrop and the SWB model. Mulching improved soil water content and reduced soil water evaporation, although the final yield and total water use efficiency was reduced. It is believed the yield reduction in mulched plots was mostly affected by nitrogen immobilization as a result of decaying straw mulch. Increasing soil fertility improved crop yield and water use efficiency in both mulched and non-mulched treatments. The AquaCrop model simulated the final yield and biomass fairly well, except in mulched treatments. The model simulated the highest yield in the mulched, fully fertilized plots, which is contrary to what was observed. This is because the model only accounts for improved soil water content and does not account for the complex interactions between the soil and mulch residue that resulted in nitrogen deficiency. The SWB model simulated fairly similar crop water use and yield to AquaCrop. The water use efficiencies obtained in this study were compared to that derived by Mengistu et al. (2014) for the same cultivar grown in a commercial farming environment at Baynesfield, KwaZulu-Natal. In comparison to commercial farmers, smallholder farmers tend to produce lower water use efficiencies. The modelled water use efficiency reported for Baynesfield was 1.277 kg m-3, compared to 0.359 kg m-3 obtained in this study for the non-mulched, full fertilizer treatment. According to AquaCrop, the mulched, full fertilizer treatment had a water use efficiency of 0.485 kg m-3. It is believed that the latter water use efficiency could have been achieved had enough nitrogen been available to the crop. In conclusion, implementing best management practices can help narrow the yield gap between smallholder and commercial farmers. It was evident from this study and others that agronomic practices have a significant impact on crop yield and ultimately, water use efficiency.
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    Detection and attribution of long-term climatic and hydrological trends in the Cathedral Peak catchments.
    (2016) Majozi, Sibusisiwe N.; Toucher, Michele Lynn.
    It has become accepted that global change is a considerable threat to vulnerable environments such as mountains. Various studies highlight the importance of change detection in long term climatic and hydrological data in understanding the catchment responses to various environmental changes. Long term trend detection of rainfall, temperature and streamflow has shown to be of practical importance to water resources management and planning. More especially in mountainous regions which have highly variable microclimates and are vulnerable to climate change impacts. In mountainous regions, the lack of data as a result of sparse observation networks often leads to a poor understanding of the climatic systems and amplifies the degree of uncertainty in trend detection. Given this need, the area of interest to this study was the intensively monitored Cathedral Peak catchments which are representative of the uKhahlamba Drakensberg region where a significant amount of water is generated for the KwaZulu-Natal and Gauteng provinces. In this context, the aim of the study was to detect trends in the historical hydroclimatic data of the Cathedral Peak catchments and gain understanding about the causes of change. To accurately detect and attribute the hydroclimatic trends in rainfall, temperature and streamflow the study was carried out using three methods. The first method investigated the data for historical trends (1948 - 2000), followed by a comparative analysis which investigated the differences between the historical and current records (2012 – 2015). The third method was an attribution study which investigated the influence of rainfall and land use to determine which of the two considered factors contributed as the cause of change. The Mann-Kendall and Sen’s slope estimator non-parametric tests were used to detect trends in the data and determine magnitude of the trends detected while the Mann-Whitney test was used to detect the difference between the historical and current records. The results across all times scales showed a few statistically significant trends in rainfall. However, the majority of the rainfall analyses showed no statistically significant trends with the expectation of a decline autumn rainfall detected in the seasonal analysis. The comparative analysis showed a few significant differences indicating increased rainfall between the historical and current period. The short current record was seen to have restrained the ability to detected definite differences in the rainfall. The significant positive trends detected in the historical temperature records and the comparative analysis provided more evidence of an increase in the temperature between the historical and current period. Furthermore, the positive trends found in the daily maximum and average temperatures were consistent with those from previous studies, which can be used to establish that there has been a general increase in the temperature between 1955 and 2000. Significant negative trends were detected in both the historical streamflow and the comparative analysis which showed evidence of a distinct decline in streamflow between 1949 and 2000. The results from the attribution study indicated that both land use change and rainfall appear to have a noticeable impact on streamflow. The complexity and highly variable nature of rainfall in the Cathedral Peak area as well as the difference in record length largely contributed to the lack of significant trends detected from the historical records and the inconclusive results obtained from the comparative study. However, despite this shortfall detection and attribution studies remain a useful tool in providing valuable information on the effects of global change in sensitive and vulnerable environments such as mountains.
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    An assessment of the water quality of the Baynespruit River and its linkages to the health of the Sobantu community.
    (2016) Govender, Jédine.; Stuart-Hill, Sabine Ingrid.
    Worldwide, water quality degradation is rife. Rivers are amongst the most susceptible water bodies to this reality. In South Africa, the use of polluted river water for activities such as crop irrigation, washing clothes and recreation, is a common practice in many rural and urban communities. The Baynespruit River, in the province of KwaZulu-Natal, South Africa, is a typical example as it serves as a vital water source to the Sobantu community. There have been numerous reports of extremely poor water quality in this river and suggestions that this may pose health risks to the community. Thus, the aim of this study was to assess the water quality of the Baynespruit River and its linkages to the health of the Sobantu community. This was achieved through analyses of river water quality, river sediment, soil and crop samples, as well as an investigation of the pathways through which community members are exposed to the polluted river and finally, an analysis of urine from a sample of volunteers who are regularly exposed to the river water. The water quality assessment considered pH, electrical conductivity, As, Cd, Cu, Hg, Pb, Zn and E.coli, while the analysis of river sediment comprised of 23 elements including the aforementioned heavy metals. Using microwave acid digestion (EPA 3052) and Inductively Coupled Plasma – Optical Emission Spectrometry (ICP-OES), soil and crop samples from farming sites in Sobantu were analysed for Cd, Cr, Cu, Pb and Zn, and compared against the South African Water Quality Guidelines for Crop Irrigation. These results showed that E.coli contamination was high, there were extremely low concentrations of the heavy metals apart from infrequent elevated detections of Cu and Pb, as well as infrequent occurrences of acidic water. While the heavy metal concentrations of surface water were low, the sediment analysis suggested elevated concentrations of As, Cd, Cr, Cu, Ni, Pb, Zn, Fe, Mn and Ag. Analyses of soils and irrigated crops showed concentrations of heavy metals in excess of national and international guidelines, respectively. It is suggested that these soil and crop results indicate historical flooding events, which mobilized heavy metals in the river sediments and transferred them onto the floodplain where the farming sites are located. Furthermore, long-term irrigation with low concentrations of heavy metals may have also resulted in the build-up of these contaminants in the soil and eventually the crops. A workshop was held in the Sobantu community which included a questionnaire and separate open-ended conversations conducted with various community members, in order to determine the exposure pathways to the river and the associated health issues of participants. The questionnaire and open-ended conversations indicated that the most common exposure pathways to the river included using river water for crop irrigation, consuming irrigated crops, washing clothes and children swimming in the river. The questionnaire and open-ended conversations also highlighted many cases of skin rashes, as a result of being in direct contact with river water, with one reported case of diarrhoea. The confirmation of the presence of heavy metals in the Baynespruit River and its surrounding environment gave rise to a urine analysis, which used microwave digestion and ICP-OES to determine whether community members who volunteered for the study incurred heavy metal toxicities. However, the analysis did not show any severe cases of heavy metal toxicities to exposed volunteers and the high levels of Pb noted could not be attributed to exposure to the Baynespruit River and/or its surrounding environments, since similar levels of Pb were found in the control volunteers. It was therefore unclear as to whether the health of the exposed people of Sobantu was compromised by heavy metal toxicities. The persistent mention of skin rashes in the questionnaire and open-ended conversations suggests that water-related health issues in the community require further investigation. It was concluded overall that the water quality of the Baynespruit River is severely degraded however, a clear link between this poor water quality and the perceived health issues in the Sobantu community, could not be established. A key recommendation from this study would be for further investigation, i.e. through a detailed health monitoring programme, confirming the health issues that community members have associated with polluted river water.
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    Towards an improved understanding of the influence of rainguage design, slope and aspect on rainfall measurements : a cross-calibration study.
    (2017) Gray, Byron Andrew.; Toucher, Michele Lynn.
    Abstract available in PDF file.