JOURNAL OF NATURAL RESOURCES ›› 2020, Vol. 35 ›› Issue (2): 371-386.doi: 10.31497/zrzyxb.20200210

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Spatiotemporal and influencing factors analysis of water yield in the Hengduan Mountain region

WANG Ya-hui1,2, DAI Er-fu1,2, MA Liang1,2, YIN Le1,2   

  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:2018-12-18 Revised:2019-06-20 Online:2020-02-28 Published:2020-02-28

Abstract: In this study, we evaluated the water yield in the Hengduan Mountain region from 1990 to 2015 using the water yield module in the InVEST model; we further analyzed the corresponding spatial and temporal characteristics and influencing factors. The results show the following. First, water yield decreased with increasing altitude and tended to decrease from the southern to the northern areas. Second, water yield increased slightly from 1990 to 2000, decreased significantly from 2000 to 2010, and then increased slightly again from 2010-2015. Third, the average water yield varied greatly across different land use types: the water yield capacity of construction lands was the strongest, for about 550-920 mm; that of forests and grasslands were moderate, for about 438-650 mm and 412-580 mm, respectively; that of unused land and water areas were the weakest, for about 273-457 mm and 56-237 mm, respectively. Lastly, there exists a significant negative relationship between the water yield spatial pattern with elevation and grasslands proportion, while there is a positive relationship with precipitation and forests proportion. The temporal changes were attributed to the positive relationship with precipitation. Overall, this study promotes the development of mountain ES (ecosystem services) research, and the results provide scientific support for water resource management and sustainable development in the Hengduan Mountain region.

Key words: InVEST model, spatiotemporal pattern, ecosystem services, water yield, Hengduan Mountain region