Multi-objective optimization modeling for non-point pollution management measures in small watershed

• Published in: Nong ye gong cheng xue bao Vol. 31; no. 2; pp. 211 - 220
• Main Authors: Geng, Runzhe, Wang, Xiaoyan, Duan, Shuhuai, Yang, hua, Nan, Zhe
• Format: Journal Article
• Language: Chinese
• Published: 01.01.2015
• Subjects: Agricultural engineering; Genetic algorithms; Management; Optimization; Pollutants; Pollution abatement; Risk assessment; Water pollution; Watersheds
• ISSN: 1002-6819
• DOI: 10.3969/j.issn.1002-6819.2015.02.030

In this study, a framework of "Risk assessment - Planning and zoning - differentiated management" was developed, and it included three tools: 1) A new "risk assessment" tool was introduced for potential loads estimation of N, P and S pollution in BeiZhai small watershed by analyzing social economic data, land use, soil type, water and soil conservation practices and agricultural management measures under current conditions, and then the critical source area was identified according to the pollution loads based on GIS technology; 2) A multi-criteria index ranking system for the BMPs was devised. 3) Three typical areas with different spatial scales were extracted from the BeiZhai small watershed, and a Non-dominated Sorting Genetic Algorithm (NSGA-II) was selected as an optimization engine to evaluate the optimal fitness of each BMP combination based on the initial pollutant loadings, targets of pollutant reduction and the costs of BMPs implemented at different spatial scales.