A scenario-based coupled SWAT-MODFLOW decision support system for advanced water resource management
Models provide invaluable visions to decision-makers for basin-scale management of water resources. However, decision-makers have difficulties in directly using these complex models. Water managers are primarily interested in user-friendly features allowing an integration of their judgments into the...
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Veröffentlicht in: | Journal of hydroinformatics 2022-01, Vol.24 (1), p.56-77 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Models provide invaluable visions to decision-makers for basin-scale management of water resources. However, decision-makers have difficulties in directly using these complex models. Water managers are primarily interested in user-friendly features allowing an integration of their judgments into the decision-making process, rather than applying detailed theories and methodologies. This knowledge gap between technical simulation models and policy-makers highlights the urgent need for developing an integrated water resource management decision support system (IWRM-DSS). This paper describes the main aspects of a new IWRM-DSS in which Microsoft Visual Studio under the C# language was employed to integrate the Microsoft SQL server as a database and ArcGIS Engine DLLs for pre/postdata processing for the SWAT and MODFLOW models. Two particular ‘module’ and ‘presentation’ shells are specifically designed for decision-makers to create four different scenarios, namely, ‘climatic’, ‘recharge’, ‘discharge’, and ‘coupled’ and to analyze the results. Decision-makers, without any detailed modeling knowledge and computer skills, can access the data and run models to test different management scenarios in an attractive graphical user interface. The IWRM-DSS, which was applied for the Neishaboor watershed, Iran, reveals that mean annual potential evapotranspiration increased to 8.2%, while runoff and recharge rates are reduced to 35 and 63%, which led to a decline of 13.5 m in mean groundwater level for the 13-year projected period. |
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ISSN: | 1464-7141 1465-1734 |
DOI: | 10.2166/hydro.2021.081 |