The further development, application and evaluation of a sediment yield model (WQSED) for catchment management in African catchments
- Authors: Gwapedza, David
- Date: 2021-04
- Subjects: Sedimentation and deposition -- South Africa , Sedimentation and deposition -- Zimbabwe , Watersheds -- South Africa , Watersheds -- Zimbabwe , Watershed management -- Africa , Water quality -- South Africa , Water quality -- Zimbabwe , Modified Universal Soil Loss Equation (MUSLE) , Water Quality and Sediment Model (WQSED) , Soil and Water Assessment Tool (SWAT)
- Language: English
- Type: thesis , text , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/178376 , vital:42934 , 10.21504/10962/178376
- Description: Erosion and sediment transport are natural catchment processes that play an essential role in ecosystem functioning by providing habitat for aquatic organisms and contributing to the health of wetlands. However, excessive erosion and sedimentation, mostly driven by anthropogenic activity, lead to ecosystem degradation, loss of agricultural land, water quality problems, reduced reservoir storage capacity and damage to physical infrastructure. It is reported that up to 25% of dams in South Africa have lost approximately 30% of their initial storage capacity to sedimentation. Therefore, excessive sedimentation transcends from an ecological problem to a health, livelihood and water security issue. Erosion and sedimentation occur at variable temporal and spatial scales; therefore, monitoring of these processes can be difficult and expensive. Regardless of all these prohibiting factors, information on erosion and sediment remains an urgent requirement for the sustainable management of catchments. Models have evolved as tools to replicate and simulate complex natural processes to understand and manage these systems. Several models have been developed globally to simulate erosion and sediment transport. However, these models are not always applicable in Africa because 1) the conditions under which they were developed are not as relevant for African catchments 2) they have high data requirements and cannot be applied with ease in our data-scarce African catchments 3) they are sometimes complicated, and there are little training available or potential users simply have no time to dedicate towards learning these models. To respond to the problems of erosion, sedimentation, water quality and unavailability of applicable models, the current research further develops, applies and evaluates an erosion and sediment transport model, the Water Quality and Sediment Model (WQSED), for integration within the existing water resources framework in South Africa and application for practical catchment management. The WQSED was developed to simulate daily suspended sediment loads that are vital for water quality and quantity assessments. The WQSED was developed based on the Modified Universal Soil Loss Equation (MUSLE), and the Pitman model is a primary hydrological model providing forcing data, although flow data from independent sources may be used to drive the WQSED model. The MUSLE was developed in the United States of America, and this research attempts to improve the applicability of the MUSLE by identifying key issues that may impede its performance. Assessments conducted within the current research can be divided into scale assessment and application and evaluation assessment. The scale assessment involved evaluating spatial and temporal scale issues associated with the MUSLE. Spatial scale assessments were conducted using analytical and mathematical assessments on a hypothetical catchment. Temporal scale issues were assessed in terms of the vegetation cover (C) factor within the Tsitsa River catchment in South Africa. Model application and evaluation involved applying and calibrating the model to simulate daily time-series sediment yield. The model was applied to calibrated and validated (split-sample validation) in two catchments in South Africa, two catchments in Zimbabwe and three catchments were selected from the USA and associated territories for further testing as continuous daily time-series observed sediment data could not be readily accessed for catchments in the Southern African region. The catchments where the model was calibrated and validated range in size from 50 km2 to 20 000 km2. Additionally, the model was applied to thirteen ‘ungauged’ catchments selected from across South Africa, where only long-term reservoir sedimentation rates were available to compare with long term model simulations converted to sediment yield rates. The additional thirteen catchments were selected from areas of different climatic, vegetation and soils conditions characterising South Africa and range in size from 30 km2 to 2 500 km2. The current research results are split into a) MUSLE scale dependency and b) WQSED testing and evaluation. Scale dependency testing showed that the MUSLE could be spatially scale-dependent, particularly when a lumped approach is used, resulting in simulations of up to 30% more sediment. Spatial scale dependence in the MUSLE was found to be related to the runoff and topographic factors used and how they are calculated. The current study resorted to adopting a reference grid in applying the MUSLE, followed by scaling up the outputs to the total catchment area. Using a reference grid resulted in a general avoidance of the problem of spatial scale. The adoption of a seasonal vegetation cover factor was shown to significantly account for temporal changes of vegetation cover within a year and reduce over-estimations in sediment output. The temporal scale evaluation demonstrated the uncertainties associated with using a fixed vegetation cover factor in a catchment with variable rainfall and runoff pattern. The WQSED model evaluation showed that the model could be calibrated and validated to provide consistent results. Satisfactory model evaluation statistics were obtained for most catchments to which the model was applied, based on general model evaluation guidelines (Nash Sutcliffe Efficiency and R2 > 0.5). The model also performed generally well compared to established models that had been previously applied in some of the study catchments. The highest sediment yields recorded per country were 153 t km-2 year-1 (Tsitsa River; South Africa), 90 t km-2 year-1 (Odzi River; Zimbabwe) and 340 t km-2 year-1 (Rio Tanama; Puerto Rico). The results also displayed consistent underestimations of peak sediment yield events, partly attributed to sediment emanating from gullies that are not explicitly accounted for in the WQSED model structure. Furthermore, the calibration process revealed that the WQSED storage model is generally challenging to calibrate. An alternative simpler version of the storage model was easier to calibrate, but the model may still be challenging to apply to catchments where calibration data are not available. The additional evaluation of the WQSED simulated sediment yield rates against observed reservoir sediment rates showed a broad range of differences between the simulated and observed sediment yield rates. Differences between WQSED simulated sediment and observed reservoir sediment ranges from a low of 30% to a high of > 40 times. The large differences were partly attributed to WQSED being limited to simulating suspended sediment from sheet and rill processes, whereas reservoir sediment is generated from more sources that include bedload, channel and gully processes. Nevertheless, the model simulations replicated some of the regional sediment yield patterns and are assumed to represent sheet and rill contributions to reservoir sediment in selected catchments. The outcome of this study is an improved WQSED model that has successfully undergone preliminary testing and evaluation. Therefore, the model is sufficiently complete to be used by independent researchers and water resources managers to simulate erosion and sediment transport. However, the model is best applicable to areas where some observed data or regional information are available to calibrate the storage components and constrain model outputs. The report on potential MUSLE scale dependencies is relevant globally to all studies applying the MUSLE model and, therefore, can improve MUSLE application in future studies. The WQSED model offers a relatively simple, effective and applicable tool that is set to provide information to enhance catchment, land and water resources management in catchments of Africa. , Thesis (PhD) -- Faculty of Science, Institute for Water Research, 2021
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- Date Issued: 2021-04
Understanding and modelling of surface and groundwater interactions
- Authors: Tanner, Jane Louise
- Date: 2014
- Subjects: Groundwater -- South Africa , Water-supply -- Management , Integrated water development , Hydrogeology , Water resources development -- South Africa , Water -- Analysis , Groundwater -- Management , Watersheds -- South Africa , Hydrologic models
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:6043 , http://hdl.handle.net/10962/d1012994
- Description: The connections between surface water and groundwater systems remain poorly understood in many catchments throughout the world and yet they are fundamental to effectively managing water resources. Managing water resources in an integrated manner is not straightforward, particularly if both resources are being utilised, and especially in those regions that suffer problems of data scarcity. This study explores some of the principle issues associated with understanding and practically modelling surface and groundwater interactions. In South Africa, there remains much controversy over the most appropriate type of integrated model to be used and the way forward in terms of the development of the discipline; part of the disagreement stems from the fact that we cannot validate models adequately. This is largely due to traditional forms of model testing having limited power as it is difficult to differentiate between the uncertainties within different model structures, different sets of alternative parameter values and in the input data used to run the model. While model structural uncertainties are important to consider, the uncertainty from input data error together with parameter estimation error are often more significant to the overall residual error, and essential to consider if we want to achieve reliable predictions for water resource decisions. While new philosophies and theories on modelling and results validation have been developed (Beven, 2002; Gupta et al., 2008), in many cases models are not only still being validated and compared using sparse and uncertain datasets, but also expected to produce reliable predictions based on the flawed data. The approach in this study is focused on fundamental understanding of hydrological systems rather than calibration based modelling and promotes the use of all the available 'hard' and 'soft' data together with thoughtful conceptual examination of the processes occurring in an environment to ensure as far as possible that a model is generating sensible results by simulating the correct processes. The first part of the thesis focuses on characterising the 'typical' interaction environments found in South Africa. It was found that many traditional perceptual models are not necessarily applicable to South African conditions, largely due to the relative importance of unsaturated zone processes and the complexity of the dominantly fractured rock environments. The interaction environments were categorised into four main 'types' of environment. These include karst, primary, fractured rock (secondary), and alluvial environments. Processes critical to Integrated Water Resource Management (IWRM) were defined within each interaction type as a guideline to setting a model up to realistically represent the dominant processes in the respective settings. The second part of the thesis addressed the application and evaluation of the modified Pitman model (Hughes, 2004), which allows for surface and groundwater interaction behaviour at the catchment scale to be simulated. The issue is whether, given the different sources of uncertainty in the modelling process, we can differentiate one conceptual flow path from another in trying to refine the understanding and consequently have more faith in model predictions. Seven example catchments were selected from around South Africa to assess whether reliable integrated assessments can be carried out given the existing data. Specific catchment perceptual models were used to identify the critical processes occurring in each setting and the Pitman model was assessed on whether it could represent them (structural uncertainty). The available knowledge of specific environments or catchments was then examined in an attempt to resolve the parameter uncertainty present within each catchment and ensure the subsequent model setup was correctly representing the process understanding as far as possible. The confidence in the quantitative results inevitably varied with the amount and quality of the data available. While the model was deemed to be robust based on the behavioural results obtained in the majority of the case studies, in many cases a quantitative validation of the outputs was just not possible based on the available data. In these cases, the model was judged on its ability to represent the conceptualisation of the processes occurring in the catchments. While the lack of appropriate data means there will always be considerable uncertainty surrounding model validation, it can be argued that improved process understanding in an environment can be used to validate model outcomes to a degree, by assessing whether a model is getting the right results for the right reasons. Many water resource decisions are still made without adequate account being taken of the uncertainties inherent in assessing the response of hydrological systems. Certainly, with all the possible sources of uncertainty in a data scarce country such as South Africa, pure calibration based modelling is unlikely to produce reliable information for water resource managers as it can produce the right results for the wrong reasons. Thus it becomes essential to incorporate conceptual thinking into the modelling process, so that at the very least we are able to conclude that a model generates estimates that are consistent with, and reflect, our understanding (however limited) of the catchment processes. It is fairly clear that achieving the optimum model of a hydrological system may be fraught with difficulty, if not impossible. This makes it very difficult from a practitioner's point of view to decide which model and uncertainty estimation method to use. According to Beven (2009), this may be a transitional problem and in the future it may become clearer as we learn more about how to estimate the uncertainties associated with hydrological systems. Until then, a better understanding of the fundamental and most critical hydrogeological processes should be used to critically test and improve model predictions as far as possible. A major focus of the study was to identify whether the modified Pitman model could provide a practical tool for water resource managers by reliably determining the available water resource. The incorporation of surface and groundwater interaction routines seems to have resulted in a more robust and realistic model of basin hydrology. The overall conclusion is that the model, although simplified, is capable of representing the catchment scale processes that occur under most South African conditions.
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- Date Issued: 2014