Optimal Prioritization of Best Management Practices Through a Simulation-Optimization Model to Sediment Load Reduction

Watershed management practices are as appropriate solutions to control nonpoint sources of pollution at the watershed scale. Nevertheless, the best way to allocate limited resources is a challenge for watershed management efforts. Therefore, to achieve the most suitable strategies, the manager requires using mathematical techniques to prioritize management practices. In this regard, in the present study, an optimization-based Decision Support Tool (DST) was used to assign the optimal combinations of management practices at the Taleghan Dam Watershed, Alborz Province, Iran. Materials & Methods: To achieve the present research goals, the Soil and Water Assessment Tool (SWAT) was applied to determine the sediment yield at the outlet of the watershed under different combinations of management measures and was coupled with a genetic algorithm in MATLAB computer software, which provides as the optimization engine. Findings: the optimization results in the Taleghan Dam Watershed showed that implementation costs for 10% and 20% sediment reduction in optimal solution were obtained 110300$ and 235500$, respectively. The cost-effectiveness ratio of scenarios 10% and 20% sediment reduction obtained about 11030 and 11770.5 (dollars for 1% sediment reduction), respectively. The results also showed that filter strips and seeding are the most cost-effective option for sediment load control. Conversely, the grade stabilization structure and detention pond are the least cost-effective option. Conclusion: This tool is transferable to other watersheds and is one of the practical approaches to watershed management. The presented tool could provide better information on location, the BMPs area, and the effects of measures on NPS and flood reduction in the watershed. The developed DST can be easily used in any other watershed. Copyright© 2021, the Authors | Publishing Rights, ASPI. This open-access article is published under the terms of the Creative Commons Attribution- NonCommercial 4.0 International License which permits Share (copy and redistribute the material in any medium or format) and Adapt (remix, transform, and build upon the material) under the Attribution-NonCommercial terms.