地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (4): 564-575.doi: 10.12082/dqxxkx.2021.200335

• 地球信息科学理论与方法 • 上一篇    下一篇

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

史亚星1,3,4(), 朱良君1,2,*(), 秦承志1,2,5, 朱阿兴1,2,5,6,7,8   

  1. 1.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    2.中国科学院大学资源环境学院,北京 100049
    3.中国-丹麦科研教育中心,北京 100190
    4.中国科学院大学中丹学院,北京 100190
    5.江苏省地理信息资源开发与利用协同创新中心,南京 210023
    6.南京师范大学地理科学学院,南京 210023
    7.虚拟地理环境教育部重点实验室(南京师范大学),南京 210023
    8.威斯康星大学麦迪逊分校地理系,麦迪逊 WI53706
  • 收稿日期:2020-06-29 修回日期:2020-08-04 出版日期:2021-04-25 发布日期:2021-06-25
  • 通讯作者: 朱良君
  • 作者简介:史亚星(1993— ),女,山西阳泉人,硕士生,主要从事流域系统综合模拟与情景分析研究。E-mail: shiyx@lreis.ac.cn
  • 基金资助:
    国家自然科学基金面上项目(41871362);中国科学院A类战略性先导科技专项课题(XDA23100503)

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

SHI Yaxing1,3,4(), ZHU Liangjun1,2,*(), QIN Chengzhi1,2,5, ZHU Axing1,2,5,6,7,8   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    3. Sino-Danish Center for Education and Research, Beijing 100190, China
    4. Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
    5. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    6. School of Geography, Nanjing Normal University, Nanjing 210023, China
    7. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
    8. Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA
  • Received:2020-06-29 Revised:2020-08-04 Online:2021-04-25 Published:2021-06-25
  • Contact: ZHU Liangjun
  • Supported by:
    National Natural Science Foundation of China(41871362);Chinese Academy of Sciences(XDA23100503)

摘要:

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。

关键词: 最佳管理措施, 流域过程模拟, 情景优化, 空间配置单元, 土地利用, 坡位, 地块, 智能优化

Abstract:

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.

Key words: best management practice, watershed process simulation, scenario optimization, spatial configuration unit, landuse, slope position unit, field unit, intelligent optimization