Spatial-temporal variations of ecological vulnerability in the Tarim River Basin, Northwest China

doi:10.1007/s40333-021-0079-0

Journal of Arid Land

2021, Vol. 13

Issue (8): 814-834 DOI: 10.1007/s40333-021-0079-0

Spatial-temporal variations of ecological vulnerability in the Tarim River Basin, Northwest China

BAI Jie¹^,²^,³, LI Junli¹^,²^,³^,^*(

), BAO Anmin¹^,²^,³, CHANG Cun¹^,²^,³

¹ State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
² Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China
³ University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

As the largest inland river basin of China, the Tarim River Basin (TRB), known for its various natural resources and fragile environment, has an increased risk of ecological crisis due to the intensive exploitation and utilization of water and land resources. Since the Ecological Water Diversion Project (EWDP), which was implemented in 2001 to save endangered desert vegetation, there has been growing evidence of ecological improvement in local regions, but few studies have performed a comprehensive ecological vulnerability assessment of the whole TRB. This study established an evaluation framework integrating the analytic hierarchy process (AHP) and entropy method to estimate the ecological vulnerability of the TRB covering climatic, ecological, and socioeconomic indicators during 2000-2017. Based on the geographical detector model, the importance of ten driving factors on the spatial-temporal variations of ecological vulnerability was explored. The results showed that the ecosystem of the TRB was fragile, with more than half of the area (57.27%) dominated by very heavy and heavy grades of ecological vulnerability, and 28.40% of the area had potential and light grades of ecological vulnerability. The light grade of ecological vulnerability was distributed in the northern regions (Aksu River and Weigan River catchments) and western regions (Kashgar River and Yarkant River catchments), while the heavy grade was located in the southern regions (Kunlun Mountains and Qarqan River catchments) and the Mainstream catchment. The ecosystems in the western and northern regions were less vulnerable than those in the southern and eastern regions. From 2000 to 2017, the overall improvement in ecological vulnerability in the whole TRB showed that the areas with great ecological improvement increased by 46.11%, while the areas with ecological degradation decreased by 9.64%. The vegetation cover and potential evapotranspiration (PET) were the obvious driving factors, explaining 57.56% and 21.55% of the changes in ecological vulnerability across the TRB, respectively. In terms of ecological vulnerability grade changes, obvious spatial differences were observed in the upper, middle, and lower reaches of the TRB due to the different vegetation and hydrothermal conditions. The alpine source region of the TRB showed obvious ecological improvement due to increased precipitation and temperature, but the alpine meadow of the Kaidu River catchment in the Middle Tianshan Mountains experienced degradation associated with overgrazing and local drought. The improved agricultural management technologies had positive effects on farmland ecological improvement, while the desert vegetation in oasis-desert ecotones showed a decreasing trend as a result of cropland reclamation and intensive drought. The desert riparian vegetation in the lower reaches of the Tarim River was greatly improved due to the implementation of the EWDP, which has been active for tens of years. These results provide comprehensive knowledge about ecological processes and mechanisms in the whole TRB and help to develop environmental restoration measures based on different ecological vulnerability grades in each sub-catchment.

Key words： ecological vulnerability ecological improvement ecological degradation AHP-entropy method climate change human activities Tarim River Basin

Received: 26 January 2021 Published: 10 August 2021

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	Jie BAI
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Cite this article:

BAI Jie, LI Junli, BAO Anmin, CHANG Cun. Spatial-temporal variations of ecological vulnerability in the Tarim River Basin, Northwest China. Journal of Arid Land, 2021, 13(8): 814-834.

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http://jal.xjegi.com/10.1007/s40333-021-0079-0 OR http://jal.xjegi.com/Y2021/V13/I8/814

Fig. 1 Overview of the Tarim River Basin (TRB) as well as the area percentage of land use/land cover (LULC)

Table 1 Variance inflation factors for the selected ecological vulnerability indicators

Table 2 Weights of the selected ecological vulnerability indicators

Fig. 2 Spatial distribution of ecological vulnerability grades in 2000 (a), 2010 (b), and 2017 (c), and the area proportion of ecological vulnerability grades distributed in 2000, 2010, and 2017 (d)

Fig. 3 Statistics of ecological vulnerability values at each catchment of the TRB in 2000 (a) and 2017 (b). Note that the pie charts show the proportion of different ecological vulnerability grades, and the ecological vulnerability values at each catchment represent the mean ecological vulnerability value of that catchment.

Fig. 4 Statistics of ecological vulnerability values in 2000, 2010, and 2017 based on LULC (a), elevation (b), and slope (c). Note that the black circles are outliers on each box; the central black line is the median; and the edges of the box are the upper and lower quartiles.

Fig. 5 Spatial-temporal distributions in the changes of ecological vulnerability in the TRB during 2000-2010 (a), 2010-2017 (b), and 2000-2017 (c), as well as the proportion of changed values for ecological vulnerability during 2000-2010, 2010-2017, and 2000-2017 (d).

Fig. 6 Spatial-temporal distributions in the changes of ecological vulnerability grade in the TRB during 2000-2010 (a), 2010-2017 (b), and 2000-2017 (c), as well as the proportion of changed grades for ecological vulnerability during 2000-2010, 2010-2017, and 2000-2017 (d)

Table 3 Contribution (q-values) of ten driving factors influencing ecological vulnerability in the TRB

Fig. 7 Spatial distribution of the annual maximum MODIS enhanced vegetation index (EVI) trend from 2000 to 2017. (a), spatial distribution of the changed rates of EVI in the whole TRB; (b)-(d), statistical results for the change trends of EVI in grassland, cropland, and forestland in different catchments, respectively. Note that the positive value indicates increasing trend of vegetation growth, and negative value means decreasing trend of vegetation growth.

Fig. 8 Aggregated total area of grassland (a), cropland (b), and forestland (c) in different catchments in 2000, 2010, and 2017, as well as aggregated total area of land transformation in different catchments (d). F-C, transformation of forestland to cropland; G-C, transformation of grassland to cropland; C-F, transformation of cropland to forestland; C-G, transformation of cropland to grassland.

Fig. 9 Crop yield and nitrogenous fertilizer utilization (a) as well as water consumption for different uses (b) in the TRB from 2000 to 2017

Fig. 10 Spatial changes in above-freezing temperature (AFT; a), precipitation (b), potential evapotranspiration (PET; c) and water density (WD; d) in the TRB from 2000 to 2017

Vulnerability index	Indicator	Calculation formula	Formula description
Climate indicator	Above-freezing temperature (AFT) (unit: °C)	$\text{AFT}=\frac{\sum\nolimits_{i=1}^{n}{{{T}_{i}}}}{n}$	T_i is the daily temperature above zero (°C); and n is the number of corresponding days.
	Precipitation (PRE; unit: mm)	$\text{PRE}=\sum\nolimits_{i=1}^{n}{\text{PR}{{\text{E}}_{i}}}$	PRE_i is the daily precipitation on the i^th day (mm); and n is the day number (n=365).
	Potential evapotranspiration (PET; unit: mm)	$\text{PET}=\frac{0.408\Delta ({{R}_{n}}-G)+r\frac{900}{T+273}{{U}_{2}}({{e}_{s}}-{{e}_{a}})}{\Delta +r(1+0.34{{U}_{2}})}$	R_n is the net radiation (MJ/(m²•d)); G is the soil heat flux (MJ/(m²•d)); r is the psychrometric constant (kPa/°C); T is the temperature (°C); U₂ is the wind speed (m/s); e_s is the saturation vapour pressure (kPa); e_a is the actual vapour pressure (kPa); and ∆ is the slope of vapour pressure curve (kPa/°C).
Ecological indicator	Vegetation cover (VC)	$VC=\frac{EVI-EV{{I}_{0}}}{EV{{I}_{s}}-EV{{I}_{0}}}$	EVI_s is the value at highly dense vegetation fraction; and EVI₀ is that value for bare soil.
	Soil erosion (SE; unit: t/hm²)	$\text{SE}=R\times K\times LS\times C\times P$	R is the rainfall erosivity factor (t/hm²); K is the soil erodibility factor; LS is the topographic factor; C is the vegetation cover factor; and P is the erosion control practices factor.
	Landscape diversity (LD)	$\text{LD}=-\sum\nolimits_{i=1}^{m}{({{P}_{i}}\times \ln {{P}_{i}})}$	P_i is the proportion of the area for the patch type i in the landscape (%); and m is the number of patch types in the landscape.
	Water density (WD; Unit: mm)	$\text{WD}=({{L}_{r}}+{{S}_{l}}+{{Q}_{w}}\times {{W}_{Q}})/3$	L_r is the length of river (m); S_l is the area of water body (m²); Q_w is the available water resource (m³); and W_Q is the weight of available water resource.
Socioeconomic indicator	Population density (POP; unit: person/hm²)	$\text{POP}=\frac{\text{PO}{{\text{P}}_{\text{total}}}}{A}$	POP_total is the urban and rural population (person); and A is the area of county (hm²).
	Food production (FOOD; unit: calorie/hm²)	$\text{FOOD}=\frac{\sum\nolimits_{i=1}^{n}{(100\times {{M}_{i}}\times E{{P}_{i}}\times {{E}_{i}})}}{A}$	i is the production category numbered from 1 to n; M_i is the product yield per category i (t); EP_i is the edible percentage of the product by category (%); E_i is the calories per 100 g of the product (calorie/g); and A is the area of county (hm²).
	Livestock density (LS; unit: head/hm²)	$\text{LS}=\frac{\sum\nolimits_{i=1}^{n}{(}\text{L}{{\text{S}}_{i}}\times {{L}_{i}})}{A}$	i is the livestock type numbered from 1 to n; LS_i is the livestock of type i (head); L_i is the converted ratio of standard sheep; and A is the area of county (hm²).

Table S1 Indicator system of ecological vulnerability in Tarim River Basin


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