Synergetic Integration of SWAT and Multi-Objective Optimization Algorithms for Evaluating Efficiencies of Agricultural Best Management Practices to Improve Water Quality

Abstract

Nitrate is one of the most complicated forms of nitrogen found in aquatic surface systems, which results in the eutrophication of the water. During the last few decades, due to agriculture and animal husbandry activities, as well as urban development, a significant amount of pollutants have accumulated in the Jajrood river in northern Iran. In this research, we simulated nitrate load in a rural watershed to assess the outlet stream’s qualitative status and evaluate the influence of best management practices (BMPs). To accomplish this, we prepared, processed, and integrated different datasets, including land-use land-cover (LULC) maps, physiographic layers, and hydrological and agricultural datasets. In the modeling section, the Soil and Water Assessment Tool (SWAT) was used to simulate nitrate load over 28 years (1991–2019). Additionally, the multi-objective optimization algorithm (MOPSO) was implemented to reduce the intended objective functions, including the number of best management practices and the nitrate concentration considering different scenarios. The calibration of the basin’s discharge and nitrate indicated that the SWAT model performed well in simulating the catchment’s streamflow (R2 = 0.71) and nitrate (R2 = 0.69). The recommended BMPs for reducing nutrient discharge from the basin are using vegetated filter strips on river banks and fertilizer reduction in agricultural activities. According to the results from this investigation, the integrated model demonstrates a strong ability to optimally determine the type, size, and location of BMPs in the watershed as long as the reduction criteria change. In a situation of water scarcity, the studies reported here could provide useful information for policymakers and planners to define water conservation policies and strategies.

Monitoring, Modeling and Planning Best Management Practices (BMPs) in the Atwood and Tappan Lake Watersheds with Stakeholders Engagements

“…The alarming rate of TN and TP loading entering water bodies has posed critical challenges, notably the escalating issue of eutrophication in lakes, compromising the quality of drinking water and impacting various water-related activities [20][21][22]. In order to minimize the adverse effects of nutrient pollution in water bodies, many researchers in recent studies suggested that conservation methods, also known as Best Management Practices (BMPs), including vegetative filter strips (VFS), grass waterways (GWW), fertilizer reduction (FR), crop rotation (CR), and cover crop (CC) have been widely recommended as viable mitigation measures to reduce non-point pollution and improve water quality in impaired waterbodies [23][24][25]. However, the efficacy of BMPs is case by case and mostly limited to site-specific locations.…”

“…For example, several studies reported that VFS could potentially reduce the nutrient level by 31% to 90% [33,34]. Additionally, several investigations have demonstrated that crop rotation can lead to a significant decrease in nutrient load, with reductions ranging from 15% to 32% [7,25,35]. The application of cover crops has been proven to be effective to decrease nitrogen and phosphorus by 20% to 38% [36,37].…”

Parallelization of AMALGAM algorithm for a multi-objective optimization of a hydrological model

“…Therefore, the choosing an efficient and effective optimization framework in a complex model (e.g., SWAT) is becoming a critical issue to decrease the running model time. For instance, Hashemi Aslani et al (2023) established a connection between the SWAT model and MOPSO as a multi-objective optimization algorithm. Their study aimed to minimize various objective functions, such as the number of best management practices and nitrate concentration, while considering different scenarios.…”