4.6 Review

A Review of SWAT Model Application in Africa

期刊

WATER
卷 13, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/w13091313

关键词

SWAT model; Africa; review; applications; challenges

资金

  1. JSPS KEKENHI [JP20KK0242, JP18H02295]

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The SWAT model has been extensively used in various hydrological and environmental simulations, with studies focusing on water resources, erosion, land-use management, climate change, and model parameterization. The challenges and potential benefits of the SWAT model's applications, along with considerations for future simulations, are discussed in these studies.
The soil and water assessment tool (SWAT) is a well-known hydrological modeling tool that has been applied in various hydrologic and environmental simulations. A total of 206 studies over a 15-year period (2005-2019) were identified from various peer-reviewed scientific journals listed on the SWAT website database, which is supported by the Centre for Agricultural and Rural Development (CARD). These studies were categorized into five areas, namely applications considering: water resources and streamflow, erosion and sedimentation, land-use management and agricultural-related contexts, climate-change contexts, and model parameterization and dataset inputs. Water resources studies were applied to understand hydrological processes and responses in various river basins. Land-use and agriculture-related context studies mainly analyzed impacts and mitigation measures on the environment and provided insights into better environmental management. Erosion and sedimentation studies using the SWAT model were done to quantify sediment yield and evaluate soil conservation measures. Climate-change context studies mainly demonstrated streamflow sensitivity to weather changes. The model parameterization studies highlighted parameter selection in streamflow analysis, model improvements, and basin scale calibrations. Dataset inputs mainly compared simulations with rain-gauge and global rainfall data sources. The challenges and advantages of the SWAT model's applications, which range from data availability and prediction uncertainties to the model's capability in various applications, are highlighted. Discussions on considerations for future simulations such as data sharing, and potential for better future analysis are also highlighted. Increased efforts in local data availability and a multidimensional approach in future simulations are recommended.

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