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

doi:10.1007/s11442-020-1767-y

Abstract

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

DAI Erfu, WANG Yahui. Attribution analysis for water yield service based on the geographical detector method: A case study of the Hengduan Mountain region[J].Journal of Geographical Sciences, 2020, 30(6): 1005-1020.

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Category	Indicators	Data type	Category	Indicators	Data type
Climate	Annual average temperature	Continuous	Land use	Land use types	Discrete
	Precipitation	Continuous		SHDI	Continuous
	Solar radiation	Continuous		CONTAG	Continuous
	Actual evapotranspiration	Continuous		MESH	Continuous
Topography	Elevation	Continuous		PLAND (cultivated land)	Continuous
Topography	Slope	Continuous		PLAND (forests)	Continuous
Soil	Soil type	Discrete		PLAND (grassland)	Continuous
Vegetation	NDVI	Continuous

Regions	Dominant interactions
Entire mountain region	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩soil type
Plains	Precipitation∩actual evapotranspiration, precipitation∩land use type, actual evapotranspiration∩soil type/elevation
Platforms	Precipitation∩actual evapotranspiration, precipitation∩land use type, actual evapotranspiration∩MESH metric
Hills	Precipitation∩actual evapotranspiration, actual evapotranspiration∩elevation, precipitation∩land use type
Small relief mountains	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩soil type
Medium relief mountains	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩soil type
Large relief mountains	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩soil type
Extreme relief mountains	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩PLAND(grassland)
Qamdo region	Precipitation∩actual evapotranspiration, actual evapotranspiration∩other factors
Bomê-western Sichuan region	Precipitation∩actual evapotranspiration, precipitation∩land use type, actual evapotranspiration∩other factors
Sichuan region	Precipitation∩actual evapotranspiration, actual evapotranspiration∩land use type
Jinsha river-Chuxiong, Yuxi region	Precipitation∩actual evapotranspiration, actual evapotranspiration∩land use type
Northern Yunnan region	Precipitation∩actual evapotranspiration, precipitation∩land use type, precipitation∩soil type

Regions	Elevation (m)	Slope (°)	Soil type	NDVI	Land use type
Entire mountain region	1591-2484	25-35	Primarosol	0.78-0.94	Shrub
Plains	2069-2484			0.72-0.78	Shrub
Platforms	2069-2484		Primarosol	0.78-0.94	Shrub
Hills	3377-3797		Primarosol	0.78-0.94	Woods, shrub
Small relief mountains	2069-2484	25-35	Primarosol	0.78-0.94	Shrub
Medium relief mountains	2069-2484	25-35	Primarosol	0.78-0.94	Shrub
Large relief mountains	2069-2484		Primarosol	0.78-0.94	Shrub
Extreme relief mountains	2924-3377	25-35		0.78-0.94	Shrub
Qamdo region	3797-6808	0-5	Primarosol	0.78-0.94	Shrub
Bomê-western Sichuan region	347-1591	0-5	Primarosol, anthropogenic soil	0.78-0.94	Shrub
Sichuan region	347-1591	0-5	Primarosol, anthropogenic soil		Shrub, other forests
Jinsha river-Chuxiong, Yuxi region	1591-2069	0-5	Primarosol	0.72-0.78	Shrub
Northern Yunnan region	3797-4548	25-35	Primarosol	0.78-0.94	Sparse grass