Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Abstract

Implementing agricultural best management practices (BMPs) is influenced by a balance of desired environmental outcomes, economic feasibility, and stakeholder familiarity, the latter taken to be related to BMP acceptability. To explore this balance, we developed a multi-objective decision support system for allocating BMP type and placement by coupling the Soil and Water Assessment Tool with a nondominated sorted genetic algorithm that minimizes total phosphorus (TP) yields from agricultural hydrologic response units (HRUs) and costs, while using stakeholder BMP familiarity as a constraint; conventional tillage, no tillage, nutrient management, riparian buffers, and contour cropping were explored. Using constraints representing current conditions, the optimization resulted in 59.6 to 81.0% reduction in agricultural TP yield from HRUs at costs ranging between US $0.8 and US $5.3 million. The constrained optimization tended to select mostly single BMPs or at most two BMPs for a given HRU due to these BMPs having higher acceptability to stakeholders. In contrast, the unconstrained case, representing full familiarity, selected 2-and 3-BMP applications. There was little difference in costs between the constrained and unconstrained cases below an 80% TP yield reduction; however, significant differences were found at larger reductions, supporting the value of stakeholder education and extension efforts. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.(KEY TERMS: soil and water assessment tool; best management practice optimization; stakeholder familiarity; total phosphorus; agricultural nonpoint sources.)

Evaluation of best management practices for sediment and nutrient loss control using SWAT model

“…Implementation of agricultural BMPs is influenced by a balance of desired economic feasibility and environmental outcomes. Many studies have been conducted to couple multiobjective optimization methods to the SWAT model to optimize the selection and placement of BMPs from both economic and environmental points of view (Chiang et al, 2014;Herman et al, 2015;Pyo et al, 2017). However, in India, very few studies were conducted using the hydrologic and water quality models to evaluate the effects of BMPs on nutrient losses from a watershed (Tripathi et al, 2005;Behera and Panda, 2006;Tripathi et al, 2013).…”

Spatial optimization of watershed best management practices based on slope position units

“…In the late phase of the optimization, the random approach can generate scenarios beyond the search space of the proposed approach and could reach a higher hypervolume index value (figures 8 and 9d). This phenomenon is common in similar comparison studies, such as Pyo et al (2017). Although this means a better set of near Pareto optimal solutions from the mathematical perspective, the scenarios in this set might not be practical in terms of their spa- Near Pareto optimal solutions derived from the first to 100th generation by (a) the proposed approach and (b) the random approach.…”

Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions

“…When applying new water quality improvement measures, such as BMPs, it is necessary to consider trade-offs such as the effectiveness of BMPs in improving water quality, expected costs, and familiarity of the stakeholders with the BMPs [18]. Therefore, many researchers have applied methodologies specializing in multi-objective optimization to address these complex problems and resolve the tradeoff problems attributed to the application of BMPs [19][20][21][22][23][24][25]. Pyo et al [20] conducted a study on the application of BMPs for the Lake Erie watershed, considering total phosphorus (TP) removal efficiency, stakeholder familiarity with BMPs, and costs.…”