基于坡位-地块单元的流域最佳管理措施空间优化配置方法

最佳管理措施（BMP）是治理流域土壤侵蚀、非点源污染等环境问题的有效途径,基于流域过程模拟的情景优化方法可得到综合效益近似最优的BMP空间配置方案集。目前用于配置BMP的空间单元（如子流域、水文响应单元、地块、坡位）均不能有效地综合体现BMP与地形部位间的空间关系以及同一地形部位内不同土地利用斑块上的BMP差异。本文提出将坡位单元与地块单元叠加生成的坡位-地块单元作为BMP空间配置单元,结合分布式流域建模框架SEIMS和多目标优化算法NSGA-II建立一套流域BMP空间优化配置方法。以江苏省溧阳市中田舍流域的非点源污染治理为例,选取减量施肥、退耕还林、封山育林和生态林草4种典型BMP,以最大化总氮削减率、最小化经济成本为优化目标,分别采用坡位单元、地块单元、坡位-地块单元进行情景优化。结果表明：相比坡位单元和地块单元,采用坡位-地块单元可获得最多具有近似最优综合效益的BMP情景,定量评价解集分布性和收敛性的Hypervolume指数分别提升了7%和4%,且BMP在空间上分布更加精细、配置更加灵活。本文方法可有效、合理地优化流域最佳管理措施的空间配置,为流域治理提供决策支持。

Spatial Optimization of Watershed Best Management Practices based on Slope Position-Field Units

Best Management Practices (BMPs) are effective ways to control environmental problems in watersheds such as soil erosion and nonpoint source pollution. BMP scenario optimization method based on watershed modeling and intelligent optimization algorithms can obtain near-optimal Pareto solutions with comprehensive cost-effectiveness. Existing spatial units used for BMP configuration in optimizing BMP scenarios (e.g., subbasins, Hydrological Response Units (HRUs), farms, and slope position units) cannot comprehensively represent spatial relationships between BMPs and topographical positions and differences of BMPs configured on various landuse units within the same topographical position. In other words, these spatial units cannot effectively consider both the characteristics of natural processes and the flexibility of BMP configuration during BMP scenario optimization in a watershed. In this paper, a composite type of spatial unit, the so-called "slope position-field" unit, is proposed to be the BMP configuration unit, which can incorporate the advantage of slope positions (i.e., effectively considering spatial allocation relationship between BMP and topographic position at the hillslope scale) and that of landuse fields (i.e., effectively considering the difference of BMP configurations on various landuse units within a topographical location). Based on a distributed watershed modeling framework named SEIMS (Spatially Explicit Integrated Modeling System) and a multi-objective optimization algorithm named NAGA-II ( Non-dominated Sorting Genetic Algorithm II), a methodological spatial optimization framework of BMP configuration based on the slope position-field units is designed. The method was examined by a case study of controlling nonpoint source pollution in the Zhongtianshe watershed, Liyang city, Jiangsu province, China. Four types of BMPs (e.g., reducing fertilizer application, returning farmland to forest, closed forest, and planting ecologic forest and grass) were selected. The optimization objectives are maximizing the reduction rate of total nitrogen output at the watershed outlet and minimizing the economic cost of the BMP scenario. The proposed BMP configuration unit was compared with two existing types of BMP configuration units such as slope position unit and field unit on the effectiveness of watershed BMP scenario optimization. The results present that: (1) compared with slope position units and field units, taking slope position-field units as BMP configuration units can obtain the largest number of optimized BMP scenarios that have the best comprehensive cost-effectiveness, which can be interpreted from the scatter plot of Pareto solutions, and proved by the quantitative Hypervolume index (with an increase of 7% and 4%, respectively); (2) BMP scenarios based on slope position-field units have more fragmented but finer spatial distribution of BMPs. Therefore, slope position-field units are more flexible for BMP configuration and hence maybe more beneficial for actual BMP implementation. In conclusion, the proposed method can optimize the spatial configuration of BMPs effectively and reasonably, so as to support decision making for watershed management.