Integrated sediment transport process modeling by coupling Soil and Water Assessment Tool and Environmental Fluid Dynamics Code
Reservoir sedimentation is a major environmental issue, and integrated sediment modeling provides a holistic picture of the sediment transport processes in watershed management planning. This study proposes a sediment modeling framework by coupling a watershed loading model, Soil and Water Assessmen...
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Veröffentlicht in: | Environmental modelling & software : with environment data news 2019-06, Vol.116, p.26-39 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Reservoir sedimentation is a major environmental issue, and integrated sediment modeling provides a holistic picture of the sediment transport processes in watershed management planning. This study proposes a sediment modeling framework by coupling a watershed loading model, Soil and Water Assessment Tool (SWAT), with a receiving water-body model, Environmental Fluid Dynamics Code (EFDC). In the proposed framework, upstream sediment load estimates made by SWAT are dynamically linked to EFDC to predict sediment deposition in a reservoir, facilitating multiple model runs required for what-if scenario analyses in developing sediment management plans and for optimization using sampling-based search algorithms. The modeling framework was applied to predict the spatial distributions of sediment depositions in an agricultural reservoir and quantify their uncertainty. This article introduces how the two models, SWAT and EFDC, are linked for integrated sediment modeling and demonstrates how the proposed framework can be applied in a case study.
•We propose a coupled modeling tool for integrated sediment transport analysis.•The proposed tool links SWAT outputs to the EFDC boundary conditions.•The tool facilitates iterative sediment transport modeling practices.•The spatiotemporal dynamics of reservoir sedimentation are illustrated using the tool.•The quantification of flow, sediment load, and deposition uncertainty is demonstrated. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2019.02.002 |