Spatiotemporal evolution of water conservation function and its driving factors in the Huangshui River Basin, China

doi:10.1007/s40333-024-0087-y

Journal of Arid Land

2024, Vol. 16

Issue (11): 1484-1504 DOI: 10.1007/s40333-024-0087-y

Research article

Spatiotemporal evolution of water conservation function and its driving factors in the Huangshui River Basin, China

YUAN Ximin¹^,², SU Zhiwei¹^,²^,³, TIAN Fuchang¹^,²^,^*(

), WANG Pengquan³

¹State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300350, China
²School of Civil Engineering, Tianjin University, Tianjin 300350, China
³School of Civil and Transportation Engineering, Qinghai Minzu University, Xining 810007, China

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Abstract

The Grain for Green project has had a substantial influence on water conservation in the Huangshui River Basin, China through afforestation and grassland restoration over the past two decades. However, a comprehensive understanding of the spatiotemporal evolution of water conservation function and its driving factors remains incomplete in this basin. In this study, we utilized the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to examine the spatiotemporal evolution of water conservation function in the Huangshui River Basin from 2000 to 2020. Additionally, we employed the random forest model, Pearson correlation analysis, and geographical detector (Geodetector) techniques to investigate the primary factors and factor interactions affecting the spatial differentiation of water conservation function. The findings revealed several key points. First, the high-latitude northern region of the study area experienced a significant increase in water conservation over the 21-a period. Second, the Grain for Green project has played a substantial role in improving water conservation function. Third, precipitation, plant available water content (PAWC), grassland, gross domestic product (GDP), and forest land were primary factors influencing the water conservation function. Finally, the spatial differentiation of water conservation function was determined by the interactions among geographical conditions, climatic factors, vegetation biophysical factors, and socio-economic factors. The findings have significant implications for advancing ecological protection and restoration initiatives, enhancing regional water supply capabilities, and safeguarding ecosystem health and stability in the Huangshui River Basin.

Key words： water conservation function Grain for Green project climate change Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model random forest geographical detector (Geodetector) Huangshui River Basin

Received: 20 June 2024 Published: 30 November 2024

Corresponding Authors: ^*TIAN Fuchang (E-mail: tianfuchang@tju.edu.cn)

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	YUAN Ximin
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Cite this article:

YUAN Ximin, SU Zhiwei, TIAN Fuchang, WANG Pengquan. Spatiotemporal evolution of water conservation function and its driving factors in the Huangshui River Basin, China. Journal of Arid Land, 2024, 16(11): 1484-1504.

URL:

http://jal.xjegi.com/10.1007/s40333-024-0087-y OR http://jal.xjegi.com/Y2024/V16/I11/1484

Fig. 1 Overview of the Huangshui River Basin based on digital elevation model (DEM)

Parameter type	Unit	Time period	Resolution	Description
LULC	m	2000-2020	30 m	Based on the CLCD land cover dataset from 1985 to 2021 with an overall accuracy of 80.00% (Yang and Huang, 2021) and reclassified into six LULC types (cropland, forest land, grassland, water body, construction land, and unused land)
DEM	m	2013	30 m	Based on the SRTM DEM data from the Geospatial Data Cloud (http://www.Gscloud.cn)
Soil properties	-	2009	1 km	Sourced from the HWSD dataset (http://www.fao.org/statistics/en)
Soil depth	mm	1980	1 km	Based on China Soil Dataset for Land Surface Simulation (http://westdc.westgis.ac.cn/)
PAWC	mm	2020	250 m	Taking the weighted average of all soil depths within the study area based on the global dataset provided by ISRIC (https://www.isric.org/)
Evaporation coefficient	-	2000-2020	1 km	Calculated from LAI according to vegetation type and quoted from the InVEST manual and existing research results
Z	-	2000-2020	-	Obtained by comparing the water yield calculated in the InVEST model in each year with the annual average runoff in the Qinghai Provincial Water Resources Bulletin (http://slt.qinghai.gov.cn) and trial calculation
Precipitation	mm	2000-2020	1 km	Based on the data from China Meteorological Data Network (http://data.cma.cn)
Annual average runoff	mm	2000-2020	-	Based on the data from the Qinghai Provincial Water Resources Bulletin (http://slt.qinghai.gov.cn)
SDI	-	2000-2020	1 km	Calculated using the precipitation and PET data
NDVI	-	2000-2020	1 km	Based on MOD13A3 data (https://search.earthdata.nasa.gov)
GDP	10⁴CNY/km²	2000-2020	1 km	Sourced from China 1 km gridded GDP distribution dataset (http://www.geodata.cn/)
NLI	-	2000-2020	1 km	Sourced from Institute of Tibetan Plateau Research Chinese Academy of Sciences (http://data.tpdc.ac.cn)
R_depth	cm	2020	250 m	Sourced from global soil data (https://www.isric.org/)
Slope	°	2013	30 m	Based on DEM data and processed in ArcGIS
PET	mm	2000-2020	1 km	Sourced from the National Tibetan Plateau Scientific Data Center (https://data.tpdc.ac.cn/zh-hans/)
TI	-	2013	30 m	Based on DEM data and processed in ArcGIS
Velocity	-	2016	30 m	Determined by referring to USDA-NRCS and InVEST instructions
K_sat	mm/d	2009	1 km	Calculated using clay, sand, and other data in the HWSD (https://www.fao.org/land-water/databases-and-software/hwsd/en/)

Table 1 Data sources and processing methods used in this study

Fig. 2 Research framework of this study. PET, potential evapotranspiration; PAWC, plant available water content; LULC, land use/land cover.

Table 2 Criteria for factor interactions in this study

Fig. 3 Calibration of the parameter Z and validation of the simulated water yield depth in the Huangshui River Basin from 2000 to 2020. Z, seasonal constant; RMSE; root mean square error.

Fig. 4 Temporal variation in water conservation depth of the Huangshui River Basin from 2000 to 2020

Fig. 5 Spatial variation in water conservation depth (a and b) and area transfer among different water conservation levels (c and d) in the Huangshui River Basin from 2000 to 2020

Fig. 6 Spatial variation in LULC (a and b) and changes in area of each LULC type (c and d) in the Huangshui River Basin from 2000 to 2020. CL, cropland; FL, forest land; GL, grassland; WB, water body; CSL, construction land; UL, unused land.

Table 3 LULC transfer matrix of the Huangshui River Basin from 2000 to 2020 (unit: hm²)

Fig. 7 Structure chart (a) and area percentage (b) showing the transfers among different LULC types in the Huangshui River Basin from 2000 to 2020

Table 4 Variation in total water conservation with the transfers among different LULC types in the Huangshui River Basin from 2000 to 2020 (unit: ×10⁶m³)

Table 5 Variation in proportion of total water conservation for each LULC type in the Huangshui River Basin from 2000 to 2020

Fig. 8 Correlation of water conservation depth with precipitation (a1 and a2), PET (b1 and b2), and temperature (c1 and c2) in the Huangshui River Basin during 2000-2020

Fig. 9 Importance ranking of driving factors and corresponding cross-validation curve (a and b) and results of Pearson correlation analysis (c and d) in 2000 and 2020. NLI, nighttime light index; TI, topographic index; R_depth, plant root depth; NDVI, normalized difference vegetation index; SDI, spatial drought index; PRE, precipitation; GDP, gross domestic product; WC, water conservation depth; IncMSE, percentage of increase of mean square error. ^*, P<0.05 level; ^**, P<0.01 level.

Table 6 Explanatory power (q) of driving factors concerning the spatial differentiation of water conservation in the Huangshui River Basin in 2000 and 2020

Fig. 10 Results of interaction detection showing the combined effect of any two driving factors on the spatial differentiation of water conservation in the Huangshui River Basin in 2000 (a) and 2020 (b). q-value represents the explanatory power of driving factors.


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