MIKE-SHE integrated groundwater and surface water model used to simulate scenario hydrology for input to DRIFT-ARID: The Mokolo River case study

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1 juillet 2016

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Water SA

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Pattern Model

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Bob Prucha et al., « MIKE-SHE integrated groundwater and surface water model used to simulate scenario hydrology for input to DRIFT-ARID: The Mokolo River case study », Water SA, ID : 10670/1.png389


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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 ecosystem-based 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.

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