Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services

doi:10.1007/s40333-022-0059-z

Journal of Arid Land

2022, Vol. 14

Issue (2): 115-138 DOI: 10.1007/s40333-022-0059-z CSTR: 32276.14.s40333-022-0059-z

Research article

Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services

LI Feng¹^,²^,³, LI Yaoming¹^,²^,³, ZHOU Xuewen⁴, YIN Zun⁵, LIU Tie¹^,²^,³, XIN Qinchuan¹^,²^,³^,^*(

)

¹State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
²Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
³University of Chinese Academy of Sciences, Beijing 100049, China
⁴School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China
⁵Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey, NJ 08542, USA

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Abstract

Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas. As the impacts of climate change and human disturbance intensify across time, uncertainties in both water resource supplies and demands increase in arid and semi-arid areas. Taking a typical arid region in China, Xinjiang Uygur Autonomous Region, as an example, water yield depth (WYD) and water utilization depth (WUD) from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and socioeconomic data. The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference (WSDD) and water supply rate (WSR). The internal factors in changes of WYD and WUD were explored using the controlled variable method. The results show that the supply- demand relationships of water resources in Xinjiang were in a slight deficit, but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation. WYD generally experienced an increasing trend, and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin. WUD had a downward trend with a decline of 20.70%, especially in oasis areas. Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased. The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang, and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×10⁸ m³. This study analyzed water resource supplies and demands from a perspective of ecosystem services, which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation. The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.

Key words： ecosystem services water resources climate change human activities arid and semi-arid areas InVEST model Xinjiang

Received: 23 November 2021 Published: 28 February 2022

Corresponding Authors: *XIN Qinchuan (E-mail: xinqinchuan@ms.xjb.ac.cn)

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Cite this article:

LI Feng, LI Yaoming, ZHOU Xuewen, YIN Zun, LIU Tie, XIN Qinchuan. Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services. Journal of Arid Land, 2022, 14(2): 115-138.

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http://jal.xjegi.com/10.1007/s40333-022-0059-z OR http://jal.xjegi.com/Y2022/V14/I2/115

Fig. 1 Digital elevation model (DEM) and rivers in Xinjiang (a) and land cover types and main cities in Xinjiang (b). Note that the figures are based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified. Altay, Tacheng, Karamay, Shihezi, Changji, Urumqi, Turpan, Hami, Bole, Yining, Korla, Aksu, Kashgar, Artux, and Hotan are the capitals of Altay Prefecture, Tacheng Prefecture, Karamay City, Shihezi City, Changji Hui Autonomous Prefecture, Urumqi City, Turpan City, Hami Prefecture, Bortala Mongolian Autonomous Prefecture, Ili Kazak Autonomous Prefecture, Bayangol Mongolian Autonomous Prefecture, Aksu Prefecture, Kashgar Prefecture, Kizilsu Kirgiz Autonomous Prefecture, and Hotan Prefecture, respectively.

Data type		Unit	Reference/Website
Administrative divisions vector borders	National Catalogue Service for Geographic Information	-	https://www.webmap.cn/main.do?method=index
Land cover data	European Space Agency	-	https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc
Precipitation data	TRMM 3B43 V7	mm	https://disc.sci.gsfc.nasa.gov/datasets?keywords=trmm3b43&page=1
GRACE gravity satellite data	German Research Center for Geosciences	cm	https://isdc.gfz-potsdam.de/grace-isdc/grace-gravity-data-and-documentation/
Soil texture data	Resources and Environmental Science Data Center of Chinese Academy of Sciences	%	http://www.resdc.cn
Soil organic carbon data	Harmonized World Soil Database Version 1.1 in National Tibetan Plateau Data Center	%	https://data.tpdc.ac.cn/zh-hans/search_index/?q=HWSD
Maximum buried depth of the root	Canadell et al. (1996); Zeng (2001)	mm	Canadell et al. (1996); Zeng (2001)
Potential evapotranspiration	CRU TS4.04	mm	https://crudata.uea.ac.uk/cru/data/hrg/
Biophysical parameter table	The InVEST model document	-	https://crudata.uea.ac.uk/cru/data/hrg/
Runoff	Measured data of Hydrological Station	m³
DEM	Resources and Environmental Science Data Center of Chinese Academy of Sciences	m	http://www.resdc.cn
Irrigated cropland maps	European Space Agency	-	https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc
Spatial distribution of GDP	Resources and Environmental Science Data Center of Chinese Academy of Sciences	×10⁴ CNY/ km²	http://www.resdc.cn/data.aspx?DATAID=252
Population density	Landscan	person/km²	https://www.satpalda.com/landscan
Agricultural comprehensive water utilization depth	Xinjiang Water Resources Bulletin	m³/m²	Water Resources Department of Xinjiang Uygur Autonomous Region (2002-2018)
Water utilization depth per 10,000 CNY of industrial value	Xinjiang Water Resources Bulletin	m³ per 10,000 CNY	Water Resources Department of Xinjiang Uygur Autonomous Region (2002-2018)
Domestic water depth per capita	Xinjiang Water Resources Bulletin	m³/capita	Water Resources Department of Xinjiang Uygur Autonomous Region (2002-2018)
Actual water supply volume of each city	Xinjiang Water Resources Bulletin	m³	Water Resources Department of Xinjiang Uygur Autonomous Region (2002-2018)
Ecological water utilization volume	Xinjiang Water Resources Bulletin	m³	Water Resources Department of Xinjiang Uygur Autonomous Region (2002-2018)

Table 1 Details of the used data

Fig. 2 Mean relative bias error between observed runoff data and modeled results without considering glacial meltwater (red violin boxes) and with considering glacial meltwater (blue violin boxes). The hollow white dots represent the median. The upper and lower horizontal lines represent the maximum and minimum values, respectively. The bottom and top lines of the box represent the 25.00% and 75.00% quartiles, respectively. The width of the violin represents the frequency of the data.

Fig. 3 Spatial distribution of water yield depth (WYD) in Xinjiang from 2002 to 2018 (a1-a5) and the corresponding cold and hot spot analysis results from 2002 to 2018 (b1-b5). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 4 Temporal analysis on averaged WYD in Xinjiang from 2002 to 2018 (a) and the Sen trend analysis and Mann-Kendall (MK) test of WYD in Xinjiang from 2002 to 2018. Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang. tianditu.gov.cn/ main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 5 Spatial distribution of water utilization depth (WUD) in Xinjiang from 2002 to 2018 (a1-a5) and the corresponding cold and hot spot analysis results from 2002 to 2018 (b1-b5). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 6 Temporal analysis on averaged WUD in Xinjiang from 2002 to 2018 (a) and the Sen trend analysis and MK test of WUD in Xinjiang from 2002 to 2018. Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu. gov.cn/main/ bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the base map has not been modified.

Fig. 7 Spatial distribution of water supply rate (WSR) in Xinjiang from 2002 to 2018 (a1-a5) and the corresponding cold and hot spot analysis results from 2002 to 2018 (b1-b5). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 8 Temporal analysis on averaged WSR in Xinjiang from 2002 to 2018 (a) and the Sen trend analysis and MK test of WSR in Xinjiang from 2002 to 2018 (b). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang. tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 9 Spatial distribution of water supply-demand difference (WSDD) in Xinjiang from 2002 to 2018 (a1-a5) and the corresponding cold and hot spot analysis results (b1-b5). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 10 Temporal analysis on averaged WSDD in Xinjiang from 2002 to 2018 (a) and the Sen trend analysis and MK analysis of WSDD in Xinjiang from 2002 to 2018 (b). Note that the figure is based on the standard map (新S(2021)023) of the Map Service System (https://xinjiang.tianditu.gov.cn/main/bzdt.html) marked by the Xinjiang Uygur Autonomous Region Platform for Common Geospatial Information Services, and the standard map has not been modified.

Fig. 11 Contributions of precipitation, potential evapotranspiration (PET), and land cover to WYD (a), contribution of irrigated WUD (WUD_irr), industrial WUD (WUD_ind), domestic WUD (WUD_dom), and ecological WUD (WUD_eco) to the total WUD (b), and changes in precipitation (c) and PET (d) in Xinjiang from 2002 to 2018

Table 2 Land cover transfer matrix in Xinjiang from 2002 to 2018 (unit: km²)


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