Browsing by Author "Gokool, Shaeden."

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An assessment of satellite derived total evaporation data as a data source to the ACRU hydrological model.
(2014) Gokool, Shaeden.; Chetty, Kershani Tinisha.; Jewitt, Graham Paul Wyndham.
Hydrological models and tools are often used as decision support systems to inform water resources management. The successful application of these systems is largely dependent on the quality of data being incorporated into them. Accurate information with regards to total evaporation is of paramount importance to water resources managers, as it is a key indicator in determining if water resources are being used for their specific purposes. Due to the inherent spatial limitations associated with conventional techniques to estimate total evaporation, the application of satellite earth observation as a tool to estimate total evaporation is being advocated more frequently. The focus of this Dissertation was to develop an approach which would allow for the incorporation of total evaporation estimates from an existing evaporation model that incorporates satellite earth observation data i.e. the SEBS model, into a hydrological simulation model i.e. ACRU, to simulate streamflow. The SEBS model was first validated in the Komatipoort study site against the surface renewal system. The results of this investigation indicated that the SEBS model over-estimated total evaporation by approximately 47% and produced R2 and RMSE values of 0.33 and 2.19, respectively, when compared to total evaporation estimates obtained from the surface renewal system. Once, the model had been validated, it was then applied to estimate total evaporation for quarternary catchment X23_A for the period 01st December 2011 to 25th November 2012. These estimates were used to create a continuous total evaporation time series, which was used as an input to ACRU to model streamflow. The EVTR3 approach was derived to allow for the incorporation of the aforementioned SEBS total evaporation estimates in ACRU and to estimate streamflow amongst other hydrological parameters. The simulated streamflow for this technique was under-estimated by approximately 10% and produced R2 and RMSE values of 0.41 and 1.05, respectively, when compared to observed streamflow. Although these results appear to be satisfactory at best, similar results were obtained when using the conventional evaporation routine in ACRU to estimate streamflow. This occurrence circuitously highlights the potential of utilizing satellite earth observation data as a data source for a hydrological model.
Evaluating the influence of the land surface and air temperature gradient on terrestrial flux estimates derived using satellite earth observation data.
(2020) Khan, Sameera.; Chetty, Kershani Tinisha.; Gokool, Shaeden.
Abstract available in pdf.
Evaluating the potential of using satellite earth observation data to quantify the contribution of riparian total evaporation to streamflow transmission losses.
(2017) Gokool, Shaeden.; Riddell, Edward Sebastian.; Chetty, Kershani Tinisha.; Jarmain, Caren.
Numerous perennial rivers which flow through arid and semi-arid environments in South Africa, have become severely constrained as water resources abstractions are close to exceeding, or have exceeded the available supply and ecosystem resilience. This is a common phenomenon, as river basins are increasingly developed and often over allocated, in order to maximize socio-economic benefits through consumptive water use, often at the expense of the environment. Thus, managing and maintaining environmental water requirement (EWR) flow allocations in these circumstances becomes increasingly important but all the more challenging, especially during periods of water scarcity. The Letaba River situated in the semi-arid north-eastern region of South Africa is a typical example of a river system in which water governance challenges and infrastructural development have resulted in flows within the river no longer resembling the natural flow regime. This situation has improved to some extent after the establishment of river operating rules and an adaptive operational water resources management system. However, one of the major challenges with successfully implementing and managing EWR flows to date has been the uncertainty regarding the magnitude and influence of streamflow transmission losses (TL’s) on flows within the river system. TL’s along the Letaba are thought to be a significant proportion of streamflow during dry periods and this therefore constrains the ability to meet target EWR flows, as it is often the case that specified EWR releases from the Tzaneen dam are not adequately met further downstream at EWR target gauges. To ensure that water provisions and in particular EWR flows can be managed more effectively and efficiently in the future, it is imperative that the hydrological processes contributing to TL’s are quantified at various spatial and temporal scales. Considering this statement as a point of departure, the overall objective of this thesis was to reduce the uncertainty associated with TL’s by attempting to acquire an improved hydrological process understanding of the natural drivers of loss in this system, so that TL’s along the Letaba River can be more accurately quantified. This research involved, conducting detailed characterizations of hydrological processes along a 14 km reach of the Groot Letaba River which has similar land use activities and hydrological characteristics to the broader river system. Particular emphasis was placed upon establishing the influence of riparian total evaporation (inclusive of open water evaporation) on TL’s, as this process is a major contributing factor to the water balance of arid and semi-arid environments, yet has seldom been incorporated or adequately represented into TL’s estimation procedures. These investigations were centred on evaluating the potential of using a satellite-based approach to acquire spatially explicit estimates of evapotranspiration (ET) during the low flow period in this river system (May to October), which typically represents a critical period with regards to water shortages. For this purpose, the satellite-based surface energy balance (SEBS) model and satellite earth observation data acquired from Landsat and Moderate-resolution imaging spectroradiometer (MODIS) were used to estimate ET. However, the trade-off between the spatial and temporal resolution associated with these data sets can limit the reliability of satellite-based ET modelling (except where occasionally correct). Consequently, the SEBS ET estimates from these data sets were used as inputs to two relatively simplistic approaches (actual crop coefficient or Kcact and output downscaling with linear regression or ODLR) to quantify ET at a moderate spatial resolution (30 m) on a daily time step. These ET estimates were compared against in-situ ET estimates using a one sensor Eddy Covariance system to quantify any uncertainties associated with the satellite-derived estimates. To further investigate spatial and seasonal variations in source contributions to plant water uptake during the investigation period, stable isotope analysis (of 18O and 2H) and a Bayesian mixing model were coupled with the satellite derived ET estimates. The insights acquired from these investigations, were then used to derive baseline estimates of TL’s. This involved using the satellite-derived daily ET time series in conjunction with data obtained from a parallel investigation focusing on quantifying the rapport between surface and sub-surface water storage processes. Initial comparisons of ET estimates acquired using the Kcact and ODLR approaches against ECET were fairly poor yielding RMSE values of; 1.88 and 2.57 mm d-1 and 1.10 and 2.39 mm d-1 (for two replicate transects), respectively. The poor performance of these techniques was largely attributed to the SEBS ET estimates used as inputs to these techniques, as SEBS may overestimate evapotranspiration during conditions of water stress. This limitation was overcome using an evaporative calibration factor (termed the environmental stress factor or ESF) into the original SEBS formulation (SEBS0), to correct for the overestimation of the latent heat flux (LE) and the evaporative fraction (EF). The ESF calibration factor was empirically derived and then integrated into SEBS0, so as to better represent the influence of water stress on the EF and consequently LE. The implementation of the modified version of SEBS (SEBSESF) was shown to significantly improve the estimation of energy fluxes, which in turn resulted in an improved correlation and an increase in the percentage of modelled ET estimates within an acceptable accuracy range (± 15 to 30 %) when compared against in-situ observations. Through the application of this modified version of SEBS (SEBSESF), the ability of the ODLR and Kcact approaches to develop a time-series of daily moderate spatial resolution ET estimates could now be demonstrated. The use of SEBSESF ET estimates as inputs to the Kcact approach was shown to compare most favourably to ECET, yielding correlation coefficient and Nash-Sutcliffe efficiency values of 0.79 and 0.60, respectively. With the ability of this satellite-based approach to adequately represent ET within this environment now confirmed. Stable isotope analysis (of 18O and 2H) and a Bayesian mixing model were coupled with the Kcact derived ET estimates, to further investigate spatial and seasonal variations in plant water uptake dynamics. The results of these investigations showed that soil water was the main contributing source to ET. While stream and groundwater use during transpiration was also prevalent within the study area and increased with aridity, the magnitude of the contribution of these sources to transpiration was fairly minimal and not as significant as generally reported in literature. The insights gained from these investigations, as well as those obtained from the quantification of surface and sub-surface water storage processes, assisted in deriving baseline estimates of TL’s along the length of river reach studied. In general, it was found that during the latter stages of the dry season (August to October) TL’s accounted for approximately 5 to 15 % of the flow in the river system, with riparian total evaporation and in particular transpiration the dominant contributing processes to this loss. Through linkages with the recent gazetting of the Letaba Management Class (resource objective setting) and the mandatory implementation of EWR flows, it was shown that flows within the river system were unable to meet low flow targets and are required to be increased in order to fulfil this requirement, whilst simultaneously accounting for TL’s. It should be noted that while the various investigations undertaken in this study enabled the estimation of TL’s and the contribution of processes viz. riparian ET to TL’s, the estimates provided could not be verified due to the lack of reliable upstream (inflow) flow gauge data. Although the investigations and observations detailed in this study provide an understanding of the system for a limited period in time, they would substantially benefit from longer-term monitoring, so that the assumptions and related uncertainties that had to be factored into the analysis could be reduced. Overall the study has detailed key hydrological processes influencing TL’s along the Groot Letaba River, providing invaluable insights on existing knowledge gaps and contributing new knowledge to this research area. It is envisaged that this will enable the establishment of an improved conceptual understanding of the system, which may prove to be beneficial for future hydrological modelling applications in this region.
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.
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.
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.