Sedighkia, Mahdi, and Datta, Bithin (2023) Mitigating Nitrate Concentration Using an Optimal Cropping Pattern Developed by Linking a Soil and Water Assessment Tool with Evolutionary Optimization. Applied Sciences, 13. 13183.

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Abstract

The unplanned development of agricultural land and urban areas poses threats to water quality, which can lead to the death of the aquatic species in rivers. The present study developed a novel framework by combining a soil and water assessment tool (SWAT) and evolutionary algorithms to optimize the cultivation pattern at the catchment scale in the Tajan River basin, with the aim of mitigating the environmental impacts of surface runoff from farms. This river basin is located in northern Iran, where quick agricultural development is one of the environmental challenges. We utilized a SWAT to simulate the nitrate concentrations for different crops at the river basin scale by applying the Nash–Sutcliffe model efficiency coefficient (NSE) as a measurement index. Then, a novel model was developed to optimize the cultivation pattern by applying different metaheuristic algorithms. Fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was applied as a decision-making system to select the best optimization algorithm. The results demonstrated that using a SWAT in the optimization model structure is a robust method for the design of an optimal cultivation pattern. The Nash–Sutcliffe model efficiency coefficient (NSE) was 0.74, demonstrating the robust predictive skills of the water quality model. The decision-making system indicated that particle swarm optimization and shuffled complex evolution were the best evolutionary algorithms to optimize the cultivation pattern using the proposed method. The proposed method opens a new window regarding the optimization of cultivation patterns in agriculture and provides an environmental-based optimization to design cultivation patterns on the catchment scale.

Item ID:	82770
Item Type:	Article (Research - C1)
ISSN:	2076-3417
Copyright Information:	© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)
Date Deposited:	15 May 2024 02:11
FoR Codes:	40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes:	18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180301 Assessment and management of freshwater ecosystems @ 100%
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