Comprehensive Review on SWAT for Sustainable Agriculture and Climatic Solutions
Vinay Dhanda, Syed Arsalan, Shilpa Kaushal, Shubham
Journal of Scientific Research and Reports · pp. 773–784 · Published 14 Nov 2024
10.9734/jsrr/2024/v30i112604Abstract
Soil and Water Assessment Tool (SWAT), a popular hydrological model, created to impersonate how the land management techniques would affect the water availability, sediments transportation and nutrient transformations in region’s expansive and intricate watersheds. SWAT has evolved from its initial development state as a comprehensive modelling tool for agricultural systems, watershed management and climate change adaptation. SWAT predicts the effects of agricultural practices on water, sediment and nutrient loads. Moreover, over time, its functionality has broadened to include complex environmental processes, such as sediment transport, nutrient cycling, and land-use change dynamics. This review paper mainly focused on the literature collected on its relevance and applicability to agricultural sector and climate change. Moreover, the incorporation of SWAT into studies on climate change has broadened its scope by enabling it to simulate the possible consequences of fluctuating temperature patterns, unpredictable precipitation, and severe weather on worldwide water resources and farming systems. In addition to highlighting its practical applicability, case studies from India and other locations also highlighted in current review article. For policymakers, agricultural scientists, SWAT is an essential tool because of its capacity to model the long-term effects of land and water management at broad spatial and temporal dimensions. SWAT also found to help the stakeholders for creating plans to lessen the effects of climate variability by combining several climate models and scenarios and to provide better insights on future soil erosion, flood hazards and water availability. Overall, in light of the escalating environmental issues, SWAT is essential for sustainable management of water and agricultural resources due to its capacity to produce comprehensive and long-term projections.
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