土地利用优化和空间防控策略对非点源污染风险控制及水环境质量的改善具有重要意义。本文以太湖流域典型平原河网地区一上海市青浦区为研究对象,将灰色线性规划模型与最小累积阻力模型相结合,以控制非点源污染风险和增加经济效益、生态效益为目标,进行土地利用结构优化与空间分区防控研究,在空间上划设了水资源保育区、水资源重点防护区、非点源污染一般阻控区、非点源污染中等阻控区及非点源污染重点阻控区,并针对不同分区提出具有针对性的防控措施。与2012年相比,预测2020年优化防控方案下,可减少总氮、总磷的输出10.96%和41.33%。由此表明,优化土地利用结构和构建空间差异化防控机制是有效调控非点源污染风险,实现区域可持续土地利用,促进经济发展和保证生态环境安全的有效途径。
Land-use optimization and spatial countermeasures are of great significance to control of non-point source pollution and improvement of water quality, In this paper, the gray linear programming method (GLP) and a minimum cumulative resistance model (MCR) were coupled to carry on risk control of non-point source pollution. (1) Taking the economic and ecological service value as the objective function, the gray linear programming model was built for the land use structure optimization at the regional scale. (2) The spatial zoning and countermeasure oriented to non-point source pollution risk control was discussed based on theMCR model. The Qingpu District located in the Taihu Lake Basin in a plain river network region was selected as a study case for this approach. The results showed that the Qingpu District could be divided into five parts, i.e., the delimiting water conservation zone, the key protection area of water resources, the general non-point source pollution control zone, the medium non-point source pollution control zone, and the core non- point source pollution control zone. According to the results of spatial-division, the specific countermeasures were put forward to lower the environmental risk. The annual load of total nitrogen will be reduced by 10.96%, and the load reduction of total phosphorus will be 41.33%. The economic benefits will be 46.13 billion yuan in 2020. Compared with 2012, the economic benefit will increase by 28.12%. In order to ameliorate the ecological environment and promoting the local social and economic development in area, land-use optimization and spatial zoning regulation mechanism were effective approach in risk control of non-point source pollution.