Abstract
A fully integrated, physically-based MIKE SHE/MIKE11 model was developed for the Mokolo River basin flow system to simulate key hydraulic and hydrologic indicator inputs to the Downstream Response to Imposed Flow Transformation for Arid Rivers (DRIFT-ARID) decision support system (DSS). The DRIFT-ARID tool is used in this study to define environmental water requirements (EWR) for non-perennial river flow systems in South Africa to facilitate ecosystembased management of water resources as required by the National Water Act (Act No. 36 of 1998). Fifty years of distributed daily climate data (1950 to 2000) were used to calibrate the model against decades of daily discharge data at various gauges, measurements of Mokolo Dam stage levels, and one-time groundwater level measurements at hundreds of wells throughout the basin. Though the calibrated model captures much of the seasonal and post-event stream discharge response characteristics, lack of sub-daily climate and stream discharge data limits the ability to calibrate the model to event-level system response (i.e. peak flows). In addition, lack of basic subsurface hydrogeologic characterisation and transient groundwater level data limits the ability to calibrate the groundwater flow model, and therefore baseflow response, to a high level. Despite these limitations, the calibrated model was used to simulate changes in hydrologic and hydraulic indicators at five study sites within the basin for five 50-year land-use change scenarios, including a present-day (with dam), natural conditions (no development/irrigation), and conversion of present-day irrigation to game farm, mine/city expansion, and a combination of the last two. Challenges and recommendations for simulating the range of non-perennial systems are presented. Keywords : hydrology, non-perennial, MIKE SHE, integrated surface and groundwater modelling
Highlights
Physically-based, distributed-parameter integrated hydrologic codes, such as MIKE SHE/MIKE11, that simulate fully coupled groundwater and surface water flows, represent the best available tools to simulate hydrologic flow systems for environmental water requirements (EWR) studies and water management, because they can readily reproduce results obtained using simpler methods, and offer the most rigorous physically-based equations which solve for hydrologic and hydraulic variables at spatially and temporally variable distributions of interest
The Mokolo River lies in the Limpopo Water Management Area (WMA1) (Fig. 2), and is a tributary of the Limpopo River which flows along the border between Botswana and South Africa
A generalised hillslope flow model with key structural features and flow processes that explains much of the integrated groundwater–surface water flow processes was developed (Fig. 4)
Summary
Physically-based, distributed-parameter integrated hydrologic codes, such as MIKE SHE/MIKE11, that simulate fully coupled groundwater and surface water flows, represent the best available tools to simulate hydrologic flow systems for EWR studies and water management, because they can readily reproduce results obtained using simpler methods (i.e., analytic, lumped), and offer the most rigorous physically-based equations which solve for hydrologic and hydraulic variables at spatially and temporally variable distributions of interest. In data-limited systems, it is important to recognise it is not so much the integrated hydrologic codes that fall short of producing desired output accuracy, but rather the inability to adequately characterise often complex surface and subsurface hydrologic parameter distributions, or processes which typically result in greater uncertainty in conceptualisation of flows within a system. It is the greater uncertainty in flow conceptualisation that directly translates into higher degrees of error/uncertainty in calibration and model predictions. The level of this study is at a detailed level, though some inputs such as subsurface data are limited, which results in the subsurface part of the model being more conceptual than, for example, the surface hydraulic part, where stream locations and cross-sectional profiles are known reasonably well
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