小流域非点源污染管理措施的多目标优化配置模拟

基于"风险评价—规划分区—分别管理"的非点源污染管理思路,采用非点源污染风险评价模型、最佳管理措施(best management practices,BMPs)评估体系及非支配排序遗传算法相耦合的方式,对北京怀柔区北宅小流域非点源污染进行不同空间尺度下最佳管理措施空间优化配置模拟,为小流域非点源污染最佳管理措施的实施,提供决策支持。研究结果表明:1)非点源污染潜力高风险区为距离河道较近受人为活动影响明显的居民区、养殖场和耕地,为重点管理区;2)根据污染物污染控制功效、成本投入以及景观美学功效3个方面综合评价结果对拟实施的BMPs进行综合评分排序,人工湿地、入渗池、绿屋顶、植物蓄留池等以下渗过程为主要污染控制机制类措施,可作为BMPs情景配置的优选措施;3)不同空间尺度下最佳管理措施空间优化配置模拟表明,流域层面BMPs最优方案为为生物滞留池0,湿式滞留池105 000元,占总成本的8%,入渗沟469 560元,占总成本的92%,总氮、总磷年污染负荷量综合削减率45%;村庄层面BMPs优化配置方案为生物滞留池3 105元,占总成本的0.8%;湿式滞留池21 000元,占总成本的5.6%;绿屋顶216 306元,占总成本的64%;透水性路面11 0736元,占总成本的29.6%。总氮、总磷年污染负荷综合削减率能够达到46%;农户层面BMPs优化配置方案为绿屋顶0元;雨水罐38元,占总成本的2.5%;生物滞留池675元,占总成本的44.5%;透水性路面805元,占总成本的53%。总氮和总磷两种污染物的年污染负荷削减率65%。

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

Abstract: Eutrophication caused by the enrichment of nutrients from diffusing sources is degrading surface water quality throughout the world, while an increased loss of agricultural nutrients is a growing concern for water quality in drinking water areas of Beijing. Best management practices (BMPs) have been proven to actually reduce nitrogen (N), phosphorus (P) and sulfur (S) pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose the right combination of BMPs that provides maximum pollution reduction with least implementation costs. Several studies have shown that best BMPs are effective in controlling water pollution. However, those issues affecting water quality need water management plans that take into consideration BMPs selection, placement and affordability. 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. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LIDBMPs. The quantified indices were normalized and then integrated to obtain the score for each first-level index. The final evaluation score of each BMP was then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores, and furthermore the final scores could be served as a first screen and selective reference for the BMP placement and optimization in next step; 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. The results indicated that: 1) Potential risk evaluation of non-point source pollution in the study area proved that the potential of non-point source pollution was closely related with land use patterns affected by human activities; 2) Comprehensive index values for different measures in a descending order were constructed wetlands, infiltration basin, green roof, wet detention pond and porous pavement, and these could be used as the main practices for the BMP planning; 3) The pollutants loads were reduced by 45% while the total cost (TC) was 574 560 yuan for watershed scale, the pollutants loads were reduced by 46% while the TC reached to 374 660 yuan for the community scale, the total N and P load was reduced by 65% while the TC reached to 1 518 yuan for the farm scale. Therefore, this framework can be served as a decision-making support for non-point source pollution control in the upper watershed of Huairou Reservoir.