Nature Environment and Pollution Technology (Dec 2022)

An Assessment of Ongoing Developments in Water Resources Management Incorporating SWAT Model: Overview and Perspectives

  • S. K. Verma, A. D. Prasad and M. K. Verma

DOI
https://doi.org/10.46488/NEPT.2022.v21i04.051
Journal volume & issue
Vol. 21, no. 4
pp. 1963 – 1970

Abstract

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Land and water are the most necessary natural resources because the entire life system depends on them. It requires proper management to achieve maximum utilization. When used in conjunction with Arc GIS, the Soil and Water Assessment Tool (SWAT) is a promising model for simulating the agricultural watershed since it can forecast runoff, sediment and nutrient transport, and erosion under various management scenarios. Furthermore, the model is better at evaluating both the spatial and non-spatial variation of hydrological methods under a very large watershed. This study uses the methodology employed by the SWAT model for the estimation of surface runoff and sediment yield and discusses in detail the setup of the model computer file needed by the model sensitivity analysis parameter and validation area unit. SWAT is a well-known hydrological modeling method used in many hydrologic and environmental simulations. Over 17 years (2005-2021), 212 studies were found from various peer-reviewed scientific publications listed on the SWAT online database (CARD). Applicability studies were divided into five categories: water resources, streamflow, erosion, land-use planning and agricultural settings, climate change scenarios, and model parameterization. Hydrologic phenomena and adaptations in various river basins have been investigated. They mostly examined environmental impacts and preventive techniques to ensure an understanding of effective environmental regulation. Streamflow susceptibility to climatic changes was shown in climate change studies. Modeling streamflow parameters, model modifications, and basin-scale calibrations were investigated. Future simulation aspects such as data sharing and the opportunity for improved future analysis are also discussed. A multimodal approach to future simulations, as well as more efforts to make local data available, are both very good ideas.

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