Journal of Geographical Sciences ›› 2020, Vol. 30 ›› Issue (6): 1005-1020.doi: 10.1007/s11442-020-1767-y

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Attribution analysis for water yield service based on the geographical detector method: A case study of the Hengduan Mountain region

DAI Erfu1,2, WANG Yahui*()   

  1. 1. Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2020-01-05 Accepted:2020-02-22 Online:2020-06-25 Published:2020-08-25
  • Contact: WANG Yahui E-mail:wangyah.15b@igsnrr.ac.cn
  • About author:Dai Erfu (1972-), PhD and Professor, specialized in research on the impact of land use and climate change on ecosystems. E-mail: daief@igsnrr.ac.cn
  • Supported by:
    National Basic Research Program of China(No.2015CB452702);National Natural Science Foundation of China(No.41571098);National Natural Science Foundation of China(No.41530749);National Key R&D Program of China(No.2017YFC1502903);Major Consulting Project of Strategic Development Institute, Chinese Academy of Sciences(No.Y02015003)

Abstract:

Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the InVEST software was used to simulate the spatial distribution of water yield. Also, quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method. Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First, water yield spatial heterogeneity is influenced most by climate-related factors, where precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most influential factor. Evapotranspiration is the most influential factor in a plateau climate zone, while in the mid-subtropical zone, precipitation is the main controlling factor. Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slope <5° and 25°-35° should be recognized as water yield important zones, while the corresponding elevation values are different among different geomorphological and climatic zones. Therefore, the spatial heterogeneity and influencing factors in different zones should be fully considered while planning the maintenance and protection of water yield services in the Hengduan Mountain region.

Key words: water yield service, Hengduan Mountain region, InVEST software, geographical detector, attribution analysis