Masters Degrees (Environmental Hydrology)

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

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Assessment of satellite derived rainfall and its use in the ACRU hydrological model.
(2017) Suleman, Shuaib.; Chetty, Kershani Tinisha.; Clark, David John.
Many parts of southern Africa are considered water scarce regions. Therefore, sound management and decision making is important to achieve maximum usage with sustainability of the precious resource. Hydrological models are often used to inform management decisions; however model performance is directly linked to the quality of data that is input. Rainfall is a key aspect of hydrological systems. Understanding the spatial and temporal variations of rainfall is of paramount importance to make key management decisions within a management area. Rainfall is traditionally measured through the use of in-situ rain gauge measurements. However, rain gauge measurements poorly represent the spatial variations of rainfall and rain gauge networks are diminishing, especially in southern Africa. Due to the sparse distribution of rain gauges and the spatial problems associated with rain gauge measurements, the use of satellite derived rainfall is being increasingly advocated. The overall aim of this research study was to investigate the use of satellite derived rainfall into the ACRU hydrological model to simulate streamflow. Key objectives of the study included (i) the validation of satellite derived rainfall with rain gauge measurements, (ii) generation of time series of satellite derived rainfall to drive the ACRU hydrological model, and (iii) validation of simulated streamflow with measured streamflow. The products were evaluated in the upper uMngeni, upper uThukela (summer rainfall) as well as the upper and central Breede catchments (winter rainfall). The satellite rainfall products chosen for investigation in this study included TRMM 3B42, FEWS ARC2, FEWS RFE2, TAMSAT-3 and GPM. The satellite rainfall products were validated using rain gauges in and around the study sites from 1 January 2010 to 30 April 2017. The rainfall products performed differently at each location with high variation in daily magnitudes of rainfall. Total rainfall volumes over the period of analysis were generally in better agreement with rain gauge volumes with TRMM 3B42 tending to overestimate rainfall volumes whereas the other products underestimated rainfall volumes. The ACRU model was applied using satellite rainfall and rain gauge measurements in the aforementioned study catchments from 1 October 2007 to 30 September 2016. Streamflow results were generally poor and variable amongst products. Daily correlations of streamflow were poor. Total streamflow volumes were in better agreement with total volumes of observed streamflow. TRMM 3B42 and rain gauge driven simulations produced the best results in the summer rainfall region, whereas the FEWS driven simulations produced the best results in the winter rainfall region.
Development and assessment of rules to parameterise the ACRU model for design flood estimation.
(2015) Rowe, Thomas James.; Smithers, Jeffrey Colin.; Schulze, Roland Edgar.; Horan, Mark John Christopher.
Design Flood Estimation (DFE) is essential in the planning and design of hydraulic structures. Recent flooding in the country has highlighted the need to review the techniques used to estimate design floods in South Africa, where old and outdated methods are widely applied. In this study the potential of a Continuous Simulation Modelling (CSM) approach to DFE in South Africa is highlighted, identifying the benefits of a CSM approach over event based approaches. The daily time-step ACRU agrohydrological model has provided reasonable results for DFE in several pilot studies. A review on hydrological modelling and the links and similarities between the SCS-SA and ACRU models, however, highlighted that in terms of land cover information, the land cover classification used in the SCS-SA model accounts for different land management practices and hydrological conditions, which are not accounted for in the current versions of the ACRU land cover classification. Since the CNs used in the original SCS model were derived from observations, and the SCS-SA model is an accepted method of DFE in small catchments in South Africa (Schmidt and Schulze, 1987a; Schulze et al., 2004; SANRAL, 2013), it was assumed in this study that the design volumes simulated by the SCS-SA model are reasonable, and that the relative changes in design volumes simulated by the SCS-SA model as a consequence of changes in land management practice or condition are also reasonable. Based on these assumptions, the general approach to the study was to investigate how design volumes simulated by the SCS-SA model for various land management practices or conditions could be simulated by the ACRU model, and to derive classes in the ACRU hierarchical classification for land management practice and hydrological condition. Consequently, design runoff volumes and changes in design runoff volumes, for different management practices and hydrological conditions, as simulated by the SCS-SA model, were used as a substitute for observed data, i.e. as a reference, to achieve similar design runoff volumes and changes in design volumes in the ACRU model. This was achieved by adjusting relevant variables in the ACRU model to represent the change in management practice or hydrological condition, as represented in the SCS-SA model. After three initial attempts failed to produce comparable simulation results between the SCS-SA and ACRU models a sensitivity analysis of ACRU variables was conducted in order to identify which ACRU variables would represent SCS-SA Curve Numbers (CNs) best for selected land cover classes. The sensitivity analysis identified two ACRU variables best suited to achieve this task, namely QFRESP and SMDDEP. Calibration of QFRESP and SMDDEP values against CN values for selected land cover classes was performed. A strong relationship between these ACRU variables and CN values for selected land cover classes was achieved and consequently specific rules and equations were developed to represent SCS-SA land cover classes in ACRU. Recommendations, however, are suggested to further validate and substantiate the approach and developed rules and equations.
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.

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Browsing Masters Degrees (Environmental Hydrology) by Subject "ACRU."