Evaluation of groundwater sustainability in the arid Hexi Corridor of Northwestern China, using GRACE, GLDAS and measured groundwater data products

STOTEN-135829; No of Pages 13 Science of the Total Environment xxx (xxxx) xxx

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Evaluation of groundwater sustainability in the arid Hexi Corridor of Northwestern China, using GRACE, GLDAS and measured groundwater data products Sijia Wang a,b,c, Hu Liu a,b,⁎, Yang Yu d, Wenzhi Zhao a,b, Qiyue Yang a,b, Jintao Liu e a

Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou 730000, China Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China c University of Chinese Academy of Sciences, Beijing 100029, China d China Institute of Water Resources and Hydropower Research, Beijing 100038, China e State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China b

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• GRACE–GLDAS data and in situ observations were used to evaluate groundwater sustainability. • Groundwater in the HC experienced a general deterioration in both storage and sustainability. • Human activity was confirmed as the dominant factor driving the groundwater deterioration. • Limited positive effects of the water management projects were detected on the groundwater system.

a r t i c l e

i n f o

Article history: Received 1 July 2019 Received in revised form 26 November 2019 Accepted 27 November 2019 Available online xxxx Editor: Paulo Pereira Keywords: Groundwater sustainability Arid region GRACE GLDAS WTF method

a b s t r a c t The exploitation of groundwater resources is of great importance and has become crucial in the last few decades, especially in arid regions, where surface water resources are scarce and unreliable. The Hexi Corridor (HC) is one of the most agriculturally rich and densely populated areas of arid northwestern China. Increasing demand for water, due to rapid population growth, oasis expansion and urbanization, has increased groundwater use, resulting in wide-scale depletion in this region. Sustainable management of aquifers in the HC requires accurate estimates of the current situation of groundwater resource sustainability. In this work, groundwater storage anomaly (ΔGWS) were estimated using the Gravity Recovery and Climate Experiment (GRACE) satellite data, the Global Land Data Assimilation System (GLDAS) data and the water-table fluctuation (WTF) method based on in-situ groundwater level data. Combined with the groundwater sustainability index (SIGWS), groundwater sustainability in the HC was then evaluated. Potential factors that could affect regional groundwater sustainability were analyzed by including and testing climate and socio-economic variables during the period of 1981 to 2016. We found that (1) groundwater in the HC has experienced a general deterioration (except for a sudden and sharp increase observed around 2002) in both storage and sustainability, from ΔGWS = 16.79 cm/year and SIGWS = 0.46 (1985–1990) to ΔGWS = −28.96 cm/year and SIGWS = 0.008 (2007–2016); (2) the lowest value of groundwater sustainability in the HC appeared in the central and eastern regions (SIGWS = 0);

⁎ Corresponding author at: Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China. E-mail address: [email protected] (H. Liu).

https://doi.org/10.1016/j.scitotenv.2019.135829 0048-9697/© 2018 Elsevier B.V. All rights reserved.

Please cite this article as: S. Wang, H. Liu, Y. Yu, et al., Evaluation of groundwater sustainability in the arid Hexi Corridor of Northwestern China, using GRAC..., Science of the Total Environment, https://doi.org/10.1016/j.scitotenv.2019.135829

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(3) human activity was confirmed to be the dominant factor driving the processes of deterioration in groundwater sustainability in the HC, and during the research period, it is striking that relatively limited “positive” effects of the water management project were detected on the regional groundwater resource; this result indicates that damaged groundwater sustainability cannot be easily reversed unless a long-term management policy is implemented. This study also proves that GRACE gravity satellite data has great application potential in groundwater sustainability evaluation in arid regions, especially in developing countries where in-situ data are scarce, and highlights the importance of joint management of surface water and groundwater, in groundwater sustainability management. © 2018 Elsevier B.V. All rights reserved.

1. Introduction The exploitation of groundwater resources is of great importance and has become crucial in the last few decades, especially in arid regions, where surface water resources are scarce and unreliable (Alley et al., 2002). Indeed, groundwater is the most important water resource for both people and the environment, in arid regions (Alfarrah and Walraevens, 2018). It contributes to maintain ecosystem functions, achieve food security and even support economic growth, by providing an important buffer to water supply variability (Famiglietti, 2014). Yet despite these critical services provided by groundwater, regulations governing it are practically nonexistent in most arid regions of the world (Khan et al., 2017), including arid northwestern China, where groundwater has been facing the risks of quantitative depletion and quality deterioration (Mehta et al., 2018). It in turn may lead to the regional degradation of groundwater-dependent ecosystems and endanger local ecological security (Nanekely et al., 2017). The Hexi Corridor (HC) is one of the most agriculturally rich and densely populated areas of arid northwestern China, and increasing demand for water supply—due to rapid population growth, oasis expansion and urbanization —has increased groundwater use, resulting in wide-scale depletion in this region (Akiyama et al., 2018). Although many water resource projects have been launched in this region during the last decade (Chen et al., 2014a, 2014b; Zhao and Chang, 2014), few of them have dealt directly with groundwater resources, and almost no studies have been conducted on how groundwater sustainability has responded to the projects that have occurred in the HC. Because of the high reliance of both social and oasis systems on groundwater, this water should be considered a precious and scarce resource in the HC, and sustainable utilization of groundwater has proved to be critical to alleviating water shortages while at the same time maintaining ecosystem stability in the region (Konikow, 2015). Sustainable management of aquifers requires accurate estimates of the current situation of groundwater resource sustainability (Dou, 2016); however, detailed evaluations for the HC are still lacking (Abou et al., 2018). Although the basic idea of sustainable utilization of groundwater was promoted as early as the 1910s (Lee, 1915), the first concept of groundwater sustainability was put forward only in the last decade (Alley et al., 1999). It originally appeared in publications as an engineering concept, and has further evolved as management or systematic sciences concepts in recent years (Alley et al., 1999). The engineering concepts include safe yield (Mays, 2013), optimal yield (Woldeyohannes and Waqar, 2017), sustainable pumping (Devlin and Sophocleous, 2005), sustainable yield (Kalf and Woolley, 2005) and groundwater capture (Seward et al., 2015). Early versions of management concepts (i.e., groundwater sustainability) include the development and use of groundwater resources in a manner that can be maintained for an indefinite time without causing unacceptable environmental, economic, or social consequences (Alley et al., 1999). Subsequently, many more concepts of groundwater sustainability have been promoted (Gun and Lipponen, 2010; Sophocleous, 2005; Velis et al., 2017). These definitions of groundwater sustainability largely focused on the quantity of groundwater, and only the most recent works have begun to consider both quantity and quality (Sophocleous, 2005), partly

because quantity is the most limiting factor for arid environments, and partly because quantitative data on groundwater are more available than qualitative data. Hence many more methods have been developed, for studying groundwater quantity: the GRACE (Gravity Recovery and Climate Experiment) method, the WTF (water-table fluctuation) method, and several indexes (groundwater resource pressure index, groundwater drought index). Among these, the combined GRACE and GLDAS (Global Land Data Assimilation System) data have been widely used for arid regions where data are scarce, because of its advantages of long duration, free download and wide coverage (Henry et al., 2011; Strassberg et al., 2009; Scanlon et al., 2012; Liesch and Ohmer, 2016). However, these studies focus only on the groundwater storage anomaly (ΔGWS) and pay less attention to the sustainability assessment of groundwater. In this study, a widely accepted index of groundwater sustainability (SIGWS) was employed to evaluate groundwater sustainability in the HC. In preparation, we validated the GRACE-GLDAS-based groundwater storage anomaly by using in situ groundwater-level measurements collected during the period in which the two data sets overlap (2002–2010). GRACE-GLDAS-derived groundwater storage variations (ΔGWS) were compared against those derived from in-situ groundwater-level measurements collected from 196 observation wells distributed throughout the arid HC in northwest China. After confirming the consistency between the ΔGWS values derived from the two different datasets, we further evaluated the groundwater sustainability for this region with the combined data from both sources, then extrapolated the results beyond the range covered by each of them. The aim of the study was to test the potential of applying GRACE-derived data together with in-situ measurements, and to analyze the effects of climate change and human activities on regional groundwater sustainability, so as to understand the current situation and historical changes that have occurred in the groundwater sustainability during the past three decades, in the HC. Our major concerns include: (1) testing the consistency between groundwater storage anomalies derived from GRACE-GLDAS data and from in-situ groundwater-level measurements; (2) using the index of groundwater sustainability to quantitatively measure the groundwater sustainability of the HC during the period for which data are available; and (3) clarifying the response of groundwater sustainability to climate change, human activities and the major water resource management projects launched in the HC during the last decade. 2. Materials and methods 2.1. Study area The HC is located at the northern margin of the Qinghai-Tibet Plateau. It is morphologically divided into two zones: mountains in the south and north, and lowland in the middle. The mountainous zone includes the Qilian and Arkin mountains in the south, and the Mazong, Heli, and Longshou mountains in the north. From northwest to southeast, the lowland zone has been separated by tectonic uplifts into several deep basins of inland rivers (Li and Yang, 1998): the Shule, Heihe and Shiyang river basins (Fig. 1). Hydrologically, the southern mountain

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Fig. 1. Locations and boundaries of the three major inland river basins in the Hexi Corridor (Shule river basin, middle and upper reaches of Heihe river basin, and Shiyang river basin), and the lithology (downloaded from Global Lithologic Map v1.0: https://ccgm.org/en/) (Hartmann and Moosdorf, 2012) and distribution of groundwater-level monitoring wells in the study area, as well as epicenter locations of four major earthquakes (MS refers to magnitude on the Richter scale) in the study area, from 2001 to 2003 (the dataset is from China earthquake administration: https://www.cea.gov.cn/). The dotted grid represents GRACE-GLDAS pixels containing observation wells, which are used for consistency testing between GRACEGLDAS data and in-situ groundwater level data.

ranges (Qilian Mountains) are the most important source of water for these inland river basins, because they are all fed by runoff from precipitation and from melting snow and glaciers in this region (Mi et al., 2016). Since the lowland regions of the HC coincide well with an extensive faulting at the northern front of the Qilian Mountains, this area is also an important seismic zone responsible for high-magnitude earthquakes; more than five earthquakes greater than MS = 7 (magnitude on the Richter scale) have occurred in this area since 180 CE (Li and Yang, 1998). Above the fault, loose quaternary sediments have accumulated to a great thickness, providing beneficial conditions for groundwater preservation, so that groundwater resources are relatively abundant and can be recharged (Wang et al., 2009). Climatically, the HC is a continental arid region with short hot summers and long cold winters. Total annual rainfall ranges from b50 mm year−1 in the desert areas, and around 150 mm year−1 in the oasis regions, to N500 mm yr−1 in the Qilian Mountains, against total annual evaporation of 2100–3200 mm (Ji et al., 2006). Like other arid regions in the world, the HC is facing a very serious shortage of water resources. Well known as an irrigated agricultural area of China, the HC receives N90% of its total water demand from irrigation (Chen et al., 2014a, 2014b). The expanding agricultural land area, and thus irrigation water requirements, can be largely attributed to the continually increasing population during recent decades. According to Xie et al. (2018b), the average population density has reached 200 pop./km2, far exceeding the United Nations standard of 20 pop./km2 for critical population density in arid areas. Therefore, the water resources problem has become the core issue of ecological security maintenance and economic development guarantees in the HC. The local governments of China are increasingly realizing the importance of water resource management for the sustainable development of the regional society, and thus have initiated many projects to alleviate water-

related challenges in the HC, including the “Compulsory Water Division Regulation of the Heihe River Basin”, the “Key Management Plan for the Shiyang River Basin”, and the “Water Resources Rational Utilization and Ecological Protection Plan for the Shule River Basin” (Aarnoudse et al., 2019). Among these, the first was initiated in 2001, and was designed to resolve the conflicts and optimize the runoff water allocation among the upper, middle and lower reaches of the Heihe river basin through the management of catchment water resources (Dou, 2016). The second project was initiated in 2007, and it aimed to protect the Minqin Oasis, between the Badain and Tengger deserts, from being buried by drifting sand through catchment water management (Huang et al., 2017). The last project was initiated in 2011, and was mainly designed to restore the ecosystem of the Shule River (Hao et al., 2017). All the projects have been basically completed; however, none of them, to date, has achieved uniformly successful results, at least partly because of limited consideration of groundwater in the context of sustainable development goals (Yin et al., 2008). For instance, reduced use of surface water has also increased the rate of pumpage and thus lowered the groundwater table (Merritt and Bateman, 2012), and has also changed the vegetative composition in many areas with shallow groundwater, where groundwater-dependent vegetation forms the sub-dominant or partial cover of a habitat (Vest et al., 2013). 2.2. Groundwater storage anomaly based on GRACE-GLDAS data 2.2.1. Terrestrial water storage anomaly The terrestrial water storage anomaly (ΔTWS) can be derived from GRACE data products (Long et al., 2017). The products are now developed to the 6th generation (RL06) and can be divided into CSR (the Center for Space Research), GFZ (the GeoForschungs Zentrum) and JPL (the Jet Propulsion Laboratory) versions, according to the provider, or

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alternatively, into three categories according to the processing level: Level 0, Level 1 (Level 1A and Level 1B) and Level 3 (Frappart and Ramillien, 2018). This study used the 5th generation (RL05) Mascons product provided by CSR (Save et al., 2016), which is a recently released local solution developed to minimize the common north-south striping error and spherical harmonic noise in the calculation of GRACE satellite data. This product provides monthly ΔTWS data with a spatial resolution of 0.5°×0.5°from April 2002 to December 2016 and can be used without post processing (http://www2.csr.utexas.edu/grace) (Save et al., 2016). 2.2.2. Anomaly of plant canopy surface water, soil water and snow water storage GLDAS is a model that parameterizes the land surface model based on (re)analysis data obtained from satellite observations, ground observations and model output, thus outputting land surface state and flux with high time resolution (Rodell et al., 2003). In this study, plant canopy surface water (parameter: plant canopy surface water), soil water content (parameter: soil moisture in layers of 0–10 cm, 10–40 cm, 40–100 cm and 100–200 cm) and snow water equivalent (parameter: snow water equivalent) were retrieved by using the product of the NOAH land surface model driven by the GLDAS-v2.1. Like TWS data obtained by GRACE satellite, the average value from January 2004 to December 2009 (Yin et al., 2015) was subtracted from the data obtained through the NOAH model to obtain the plant canopy surface water anomaly, soil water content anomaly and snow water equivalent anomaly. The time span of the GLDAS-NOAH-v2.1 products, which are monthly data with a spatial resolution of 0.25°×0.25°, is from January 2000 to the current time (https://search.earthdata.nasa.gov/) (Hiroko et al., 2016). 2.2.3. Groundwater storage anomaly The monthly change of ΔTWS obtained from GRACE data includes two parts (Frappart and Ramillien, 2018): the aboveground part (i.e., plant canopy surface water, soil water and snow water) and the underground part (i.e., groundwater), as shown in Eq. (1). ΔGWSGRACE can be calculated by removing the storage anomaly of the aboveground part from ΔTWS according to Eq. (2). ΔTWS ¼ ΔWcan þ ΔWsoi þ ΔWsno þ ΔGWS

2.3. Groundwater storage anomaly based on water table fluctuation method Groundwater levels in the major oasis regions of the HC have been monitored regularly during the last 30 years, and 196 borehole wells with monthly records of hydraulic heads over the period 1981 to 2010 were selected in this study to build the basic input for validating and extrapolating the GRACE-derived groundwater storage anomaly through the WTF method. In order to improve the accuracy, we only use the grid (Fig. 1) containing one or more monitoring wells to check the consistency between GRACE-GLDAS data and in-situ groundwater level data (Chen et al., 2019). The core principle of the WTF method used here is that the groundwater storage anomaly (ΔGWSWTF) is equal to the recharge of groundwater (R) over a long-time interval and can be calculated by Eq. (4): ΔGWSWTF ¼ R ¼ Sy Δh

ð4Þ

where Sy is the specific yield of the aquifer and Δh is the groundwater head anomaly within a specific time interval. The method skillfully associates groundwater storage with groundwater-level fluctuation, and uses relatively available groundwater-level data to obtain ΔGWS trends. Errors for ΔGWSWTF, in turn, can be calculated as the standard deviations of the mean value of all wells. The above formula can be used to evaluate the monthly and annual ΔGWSWTF time series of a single monitoring well, and can also be extended to the whole study area. The monthly Δh of a single monitoring well refers to the anomaly between the average water level of each month and the average water level of all months of the monitoring well, during the study period (Henry et al., 2011). Because of the lack of ready-made aquifer-specific yield distribution maps in the study area, the Sy of the aquifer corresponding to each monitoring well can be determined based on previous research results (Cao et al., 2012), the lithologic distribution of the HC (from Global Lithologic Map v1.0) (Hartmann and Moosdorf, 2012), and the empirical relationship between aquifer lithology and specific yield provided in Fig. 1; thus the monthly ΔGWSWTF of a single monitoring well can be determined.

ð1Þ 2.4. Groundwater sustainability assessment

where ΔWcan, ΔWsoi and ΔWsno represent the storage anomalies of plant canopy surface water, soil water and snow water, respectively. ΔGWSGRACE ¼ ΔTWS−ðΔWcan þ ΔWsoi þ ΔWsno Þ

ð2Þ

Since the different components of ΔTWS cannot be separated using GRACE data alone, auxiliary data sources (such as other remote sensing data, the outputs of hydrological models and in situ data) are needed. In this study, GLDAS data were used as the auxiliary data for estimating the above-ground water storage anomaly. However, due to the inconsistent spatial resolution between GLDAS data and GRACE data, GRACE data was interpolated before removing the above-ground water storage anomaly from ΔTWS to obtain ΔGWS with a spatial resolution of 0.25°×0.25°, and potential error rates were estimated on ΔGWS by using below equation: σΔGWSGRACE ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðσΔTWSÞ2 þ ðσΔWcan Þ2 þ ðσΔWsoi Þ2 þ ðσΔWsno Þ2 ð3Þ

where σΔGWSGRACE, σΔTWS, σΔWcan, σΔWsoi and σΔWsno represent the one-sigma error on the ΔGWSGRACE, ΔTWS, ΔWcan, ΔWsoi and ΔWsno, respectively (Voss et al., 2013).

The groundwater sustainability assessment in this study adopted the method of combining ΔGWS and the sustainability index, in which the sustainability index draws on the methods of Loucks (1997) and Sandoval et al. (2011); the formula is as follows: SIGWS ¼ RELGWS  RESGWS  ð1−VULGWS Þ

ð5Þ

where SIGWS is the groundwater sustainability index, and RELGWS, RESGWS and VULGWS represent the reliability, resilience and vulnerability of groundwater storage, respectively (Hashimoto et al., 1982). RELGWS is estimated as the quotient of the number of times that ΔGWS is N0 and the total number of ΔGWS data points; RESGWS is estimated as the quotient of the number of times when ΔGWS is N0 followed by b0, and the number of times when ΔGWS is b0 (if the number of times when ΔGWS is b0 is 0, the value of RESGWS is specified as 1); VULGWS is estimated as the quotient of the number of times ΔGWS is b0 and the total number of ΔGWS data points. RELGWS, RESGWS, VULGWS and SIGWS are all non-dimensional values between 0 and 1. 0 ≤ SIGWS≤0.2 means extremely unsustainable, 0.2bSIGWS≤0.3 means severely unsustainable, 0.3bSIGWS≤0.5 means slightly unsustainable, 0.5bSIGWS≤0.75 means moderately sustainable, and 0.75bSIGWS≤1 means highly sustainable.

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2.5. Driving force data and statistical analysis

3. Results

Before the groundwater sustainability assessment, statistical methods, the moving t-test, and the Mann–Kendall (MK) test were used to detect the existence of increasing or decreasing trends in the time series of ΔGWS. The moving t-test detects abrupt changes in series by assessing the significant difference between averages of two groups of samples (Liang et al., 2010). The MK trend is a rank nonparametric test, and the null (H0) and alternative hypotheses (H1) are equal to the nonexistence and existence of a trend in the time series of the observational data, respectively (Pingale et al., 2014). In this work, the abrupt change points of the water level series were firstly detected by the moving t-test, and then significance of the changing trend in each of the different periods was evaluated with the MK test. After the groundwater sustainability assessment, potential factors that could affect regional SI GWS were analyzed by including and testing climate variables (annual air temperature, precipitation) and socio-economic factors (population, regional gross domestic product, cultivated land area, gross output value of agriculture, forestry, animal husbandry and fishery, gross output value of planting industry and gross output value of animal husbandry) during the period of 1981 to 2016. Reanalyzed climate data of China with 1-km grid resolution were downloaded from the Scientific Data Center of China, and regional data of HC were then extracted from that and averaged for each year over the HC region (Wang et al., 2009). Socio-economic data were collected from the Gansu Provincial Bureau of Statistics and the Gansu Provincial Statistical Yearbook (Table 1). Principal component analysis (PCA) was used to reduce those variables that potentially affect groundwater sustainability to a small number of principal components that reflect the primary modes of variation (Jolliffe, 2002). The principal component can be expressed by the following linear equation:

3.1. Consistency test of GRACE-GLDAS data and in-situ data

Z aj ¼ ai1 x1 j þ ai2 x2 j þ ai3 x3 j þ … þ aim xmj

ð6Þ

where Z is the component score, a is the component's loading, x is the measured value, i is the component number, j is the sample number, and m is the total number of variables. Pearson's product moment correlation analysis was used to find out the relationship between estimated SI GWS and the potential factors affecting it. The significance of the correlation was assigned based on the 95% confidence level. All the statistical analyses were performed in MATLAB (R2016a, MathWorks, Natick, MA).

By comparing the time-overlapping parts of ΔGWS estimated from both the in-situ data and the GRACE data from 2002 to 2010, it is obvious that all the fluctuation trends in ΔGWS are generally similar (Fig. 2a), whereas the amplitude estimated from the in-situ data is slightly higher than that determined by the GRACE data. There is also a clear time lag between the derived ΔGWSGRACE and ΔGWSWTF (Fig. 2b), and the correlation between them receives the highest score (r = 0.75, P b 0.01) when the lag time is set to 3 months. To investigate the influence of seasonality on ΔGWS, ΔGWSGRACE and ΔGWSWTF were calculated for the four different seasons separately (Fig. 3). We found that the general trends of ΔGWSWTF and ΔGWSGRACE were much the same in most seasons: i.e., they seem to match well with each other in all the seasons except summer. However, considering the 3-month time lag (Fig. 4), the correlation between ΔGWSWTF and ΔGWSGRACE, for the four seasons, from 2002 to 2010, is autumn N summer N winter N spring, and the fitting lines are all very close to the 1:1 line, which also indicates that the ΔGWS values calculated from the two data sources are relatively consistent, but the time lag should also be carefully considered and evaluated. According to our calculation, about 56% (P b 0.01) or even more (if not including summer) of the observed variance in ΔGWSWTF can be explained by ΔGWSGRACE, suggesting that even though robust consistency was achieved, potential errors and uncertainties could still be introduced into the combined time series of ΔGWS by the extrapolation method adopted in this work (Fig. 5). 3.2. Spatial and temporal anomalies of GWS As indicated by the derived monthly ΔGWSWTF (1981–2010) and ΔGWSGRACE (2002–2016), groundwater storage anomalies in the HC regions increased significantly during the period of 1981–1989 (16.79 cm/ year, r = 0.81, P b 0.01), and then decreased significantly during the next period, 1990–2001 (−9.67 cm/year, r = 0.65, P b 0.01). A sudden and sharp increase in groundwater storage was observed in 2002, and after that, ΔGWS continuously declined until 2010. From 2010 onward, the storage has exhibited a general downward trend but with strong fluctuations (Fig. 5). The spatial patterns of groundwater storage in the HC regions during 2002–2016 are shown in Fig. 6. Clear monthly patterns were observed in this study throughout the entire period of available GRACE data (Fig. 6). The average highest ΔGWSGRACE was observed in July (−0.22 cm) and the lowest in December (−1.88 cm). The southeastern part of the HC regions experienced the most significant

Table 1 List of all datasets used in this study. Datasets Inversion datasets of groundwater storage anomaly

Climate datasets Socio-economic datasets

Time range Temporal and spatial resolution

Spatial range

Sources

GRACE-RL05-Mascon

2002–2016 Monthly 0.5°×0.5°

Global

GLDAS-NOAH v2.1 In-situ groundwater level measurements

2002-Now Monthly 0.25°×0.25° 1981–2010 Monthly

NASA (http://www2.csr.utexas. edu/grace/) NASA (https://search.earthdata.nasa.gov/)

Global Lithologic Map v1.0 Precipitation Air temperature Regional population Gross domestic product Cultivated land area Gross output value of agriculture, forestry, animal husbandry and fishery Gross output value of the planting industry Gross output value of the animal husbandry

– – 1981–2016 Yearly 1981–2016 Yearly

Global HC region Global 1 km×1 km China HC region

CCGM-CGMW (https://ccgm.org/en/) The Scientific Data Center of China (http://www.csdata.org/) The Gansu Provincial Bureau of Statistics (http://www.gstj.gov.cn/)

Note: NASA refers to National Aeronautics and Space Administration, CCGM-CGMW to Commission for the Geological Map of the World.

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Fig. 2. (a) Estimated ΔGWSGRACE (only grids containing one or more monitoring wells were included in this analysis) and ΔGWSWTF for the period from April 2002 to December 2010; (b) Pearson correlation coefficient between ΔGWSGRACE and ΔGWSWTF when setting the lag time between them to different intervals.

fluctuations, ranging from the lowest value of −6.02 cm in June to the highest value of 2.05 cm in August. The western part of the study area showed a gradual increase in groundwater storage from April to July, and a clear decrease from September to March. The central part of the study area experienced a decrease in groundwater storage all year round except July and August (Fig. 6). 3.3. Groundwater sustainability in the HC regions We used SIGWS to evaluate groundwater sustainability within the time span of 1981–2016 (the data sources from 1981 to 2001 are insitu data, and from 2002 to 2016, GRACE-GLDAS data) in the HC regions (Fig. 7). The results show that although improvement was observed at some levels during some periods (i.e., 2000–2004), the groundwater system in the HC has experienced a general deterioration in sustainability, from SIGWS=0.48 to SIGWS=0.004 (Fig. 7e). We also analyzed the spatial patterns of groundwater sustainability, and found that the groundwater system in the HC showed a wide range of extreme unsustainability during the entire period of 2002–2016 (Fig. 7d). The

lowest SIGWS were found in the middle part of the HC regions (including the middle HRB and part of the SLRB), followed by those in the eastern part (the middle and lower reaches of the SYRB). Groundwater in the Qilian Mountains (the southern part of the HC regions) shows the highest sustainability. We also analyzed the reliability (Fig. 7a), resilience (Fig. 7b) and vulnerability (Fig. 7c) of the groundwater, and found that the extremely low SIGWS appeared in the middle part of the HC (HRB), most likely due to the combined low reliability, low resilience, and high vulnerability. However, the unsustainability of the northeastern part of the HC (the lower reaches of the SYRB) could be due to high vulnerability in the groundwater system. Because water resource management plans were launched in the three inland river basins of the HC region during the past decade, we also compared the groundwater sustainability before and after the implementation of such plans for each of the river basins. For instance, the Water Resources Plan was initiated in 2011 for the SLRB, and the SIGWS before (2002–2011) and after the initiation of the project (2012–2016) were evaluated (Fig. 8). It was found that the groundwater sustainability in the SLRB evolved in a similar pattern; the entire

Fig. 3. Influence of season (spring, summer, autumn and winter) on the correlation between ΔGWSGRACE (partial grid containing monitoring wells) and ΔGWSWTF during the period of 1980 to 2016.

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regression model for the independent variable SIGWS, i.e., SIGWS = − 0.552 × PC1 + 0.003 × PC2. The significance level of the coefficient of PC1 is P b 0.01 and that of the coefficient of PC2 is P N 0.05, suggesting that PC1 or the socio-economic factors have much more significant effects on the groundwater sustainability than climatic factors (PC2) over the HC region during the period of 1980–2016. Since precipitation and temperature exert opposite influence on PC2 (Fig. 9), the net effect might therefore be to further reduce the joint effects of climate change, and thus their relative contributions to the variances in groundwater sustainability should be trivial in the HC region when compared with the contribution from human activities. 4. Discussion 4.1. Observed time lag between ΔGWSGRACE and ΔGWSWTF

Fig. 4. Scatter plot of ΔGWS based on in-situ data (ΔGWSWTF) and GRACE-GLDAS data (ΔGWSGRACE, partial grid containing monitoring wells) in the four seasons.

HC: groundwater system was moderately sustainable during the period of 2002–2006, and then declined rapidly, and remained extremely unsustainable until 2016. In general, the groundwater development was slightly unsustainable (SIGWS=0.35) before the project kickoff, and the overall trend was not improved, and was even aggravated after that (SIGWS=0.002). Further analysis suggested that the revealed extreme unsustainability in the eastern part of the basin before the project was induced by the extremely low resilience of the groundwater system (Fig. 8). However, the subsequent loss of groundwater sustainability should be attributed to the decreased reliability and increased vulnerability of the groundwater system (Fig. 8). Very similar patterns also occurred in the HRB and SYRB (Fig. 8). 3.4. Analysis of the potential factors affecting groundwater sustainability Principal components analysis (PCA) suggested the selection of two components with eigenvalues N1.0, which explain 87.8% of the variability in the original data (see Fig. 9). The first component (PC1), which explains 72.1% of the total variances within the dataset, is characterized by high positive loadings with a combination of socio-economic indicators. The second component (PC2), which explains a further 13.3% of the variance, is characterized by high loadings of climatic indicators (Fig. 9, Table 2). The two components are further used to construct a multiple

Time lags between the ΔGWSGRACE and the ΔGWSWTF have been reported by many previous works, e.g., Abou et al. (2018), Cao et al. (2012) and Thomas et al. (2017), although there are also some studies that did not find any obvious time lags, e.g. Toure et al. (2016), Iqbal et al. (2017), Katpatal et al. (2018) and Xie et al. (2018a). In cases where there was a time lag, differences were also reported in its length. Several causes could be responsible for these differences: (1) Climate features may affect the observed time lag between ΔGWSGRACE and ΔGWSWTF, which is more likely to occur in arid environments. For example, Thomas et al. (2017) reported a time lag of 2 months in the Central Valley of California, in the United States; Abou et al. (2018) and Cao et al. (2012) reported a time lag of 3 months in southwestern Iran and the middle HRB, respectively. However, most of the researches conducted in wetter climates did not observe any obvious time lags, e.g., Toure et al. (2016)'s work in the Canadian Prairies, Iqbal et al. (2017)'s work in the Indus Basin, Katpatal et al. (2018)'s work in central India and Xie et al. (2018a)'s work in the Loess Plateau of northern China. The existence of time lags in researches of arid areas may be due to more frequent exchanges and interactions between groundwater and vegetation, and between soil water and surface water in arid environments, and greater interference by climate change and human beings as well [due to the fact that summer is the growing season with the greatest water demand for irrigation ended, and thus the in-situ measurements based ΔGWSWTF are more sensitive but less accurate given the relatively limited spatial representation of individual wells, i.e., Mi et al. (2016)]. Therefore, although the retrieved results of groundwater in arid environments are more prone to showing such a time lag, the specific responsible mechanism still needs professional in-depth study. (2) Different versions of GRACE data, different types and processing methods of auxiliary hydrological data (the datasets of surface water, soil water and snow water) will affect the existence

Fig. 5. Monthly ΔGWS time series based on in-situ groundwater level data (ΔGWSWTF) and GRACE-GLDAS data (ΔGWSGRACE). The time span of the in-situ data set is from January 1981 to December 2010, of the GRACE-GLDAS data, from April 2002 to December 2016. The red shaded area represents the ΔGWSWTF error (calculated as the standard deviations of the mean value of all wells), and the blue shaded area represents the ΔGWSGRACE error (which is the monthly one-sigma error from the combined GRACE-based ΔTWS, and GLDAS-based ΔWcan, ΔWsoi and ΔWsno errors). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 6. The monthly average ΔGWSGRACE. The data set covers the period from April 2002 to December 2016 with a spatial resolution of 0.25° × 0.25°. It should be noted that the colour of each grid represents the change of groundwater storage in this location relative to the 14-year average of groundwater storage in this location, in each month. Therefore, the actual groundwater storage in the blue grid may be higher than that in the red grid. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

and length of a time lag. For instance, a time lag of 3 months was determined between ΔGWSGRACE and ΔGWSWTF in our study (Fig. 2) which agrees well with Cao et al. (2012), who found a similar time lag for the HRB, and believed it to be related to the lower spatial resolution of

GRACE data or the limited representatives of in-situ measurements. Thomas et al. (2017) also reported a time lag of 2 months, and considered it to be due to auxiliary hydrological data (provided by North American Land Data Assimilation Systems), which lacks consideration

Fig. 7. Groundwater storage reliability (a), resilience (b), vulnerability (c), and groundwater sustainability (d, e) of the HC regions with a spatial resolution of 0.25° × 0.25°.

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Fig. 8. Groundwater storage reliability, resilience, and vulnerability, and groundwater sustainability of Shule (SLRB), Heihe (HRB), and Shiyang river basins (SYRB).

of irrigation and deep soil moisture. The GLDAS data used in our research had similar problems, which may be another potential reason for the observed time lag in our study. (3) The size of study area and the spatial representation of the measured data will also affect the time lag. Since the study area is about 11° to 7°, there is not a good resolution in some parts due to having the boundaries and most of the monitoring wells were set in or around the oasis, the observed time lag in our study is also at least partly due to the same cause. 4.2. Groundwater storage dynamics during the past decades The ΔGWS in the HC from 1981 to 2016 can be divided into four stages according to the moving t -test and MK test conducted at the 0.05 significance level: (1) 1981–1989 (stage 1): the storage continued to increase significantly (P b 0.01). The 1980s was a period of accelerated retreat of glaciers in the Qilian Mountains (about 7 m/year) and was a wet period for the whole northwestern region (Guo et al., 2018). Glacier melt water and extreme precipitation may increase the recharge of groundwater. At the same time, the oasis area expansion

in the HC was relatively stable (59.90 km2/year) during this period (Xie et al., 2018b), causing the recharge to be greater than the discharge. (2) 1990–2001 (stage 2): groundwater storage decreased significantly (P b 0.01). In the 1990s, the oasis area in HC expanded steadily and rapidly (193.80 km2/year) (Xie et al., 2018b), because of ecological immigration into the SLRB and even into the entire northwest region during this period. The local government encouraged groundwater irrigation to maximize immigrants' income (Bao and Fang, 2007). (3) 2002–2004 (stage 3): abnormal increase in storage due to earthquakes and other factors. (4) 2005–2016 (stage 4): storage decreased slightly. During this period, the oasis area in the HC was at a low growth stage (109 km2/year) (Bao and Fang, 2007), and the fluctuation of groundwater storage in the three major watersheds was greatly affected by the comprehensive watershed management project initiated by the government (Mi et al., 2016). A sharp increase of about 4 cm was detected in groundwater storage in 2002, and continued until 2004. Previous works conducted in this region have also reported the same phenomenon, e.g., Chen and Wang (2009) and Hochmuth et al. (2015). Chen et al. (2014a, 2014b) analyzed the cause of a large-scale rise in the groundwater level in the HC around 2003 using the isotope method, and found that this phenomenon was probably due to the increase of glacial melt water in the Qilian Mountains caused by climate warming, thus increasing the amount of groundwater recharge (Zhang et al., 2017). However, other researches were more likely to attribute the phenomenon to earthquakes occurring in this region during 2001–2003. According to Chen and Wang (2009) and Hochmuth et al. (2015), four earthquakes with magnitudes above 5 were recorded in the HC, which could potentially increase the permeability of the aquifer, and result in the fluctuation of the water level (Fig. 1). For example, Chen and Wang (2009) found that groundwater recharge always exists at the fault where the base of the Zhangye Basin connects with the Qilian Mountains, and the earthquake intensified the activity at the fault, thus causing the recharge speed and water volume to increase rapidly. Mi et al. (2016) also found similar phenomena in the SLRB and the HRB, and believed that in addition to the above two reasons, the inland rivers in the HC region have entered a 100-year-scale flood period, and the Heihe riverbed's water-passing time has increased in the 21st century, thus increasing the supply of Table 2 Correlation coefficients between the principal components of driving factors in the HC region.

Fig. 9. Principal component load diagram of various climate and socio-economic factors. The red circle part (including PRE and TEM) is mainly distributed along the longitudinal direction (i.e., the dimension of PC2), while the blue circle part (including POP, GDP, CLA, GV, GVP and GVA) is mainly distributed along the transverse direction (i.e., the direction of PC1). Note: abbreviations are similar to those in Table 2. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Principal component

PRE

TEM

POP

GDP

CLA

GV

GVP

GVA

PC1 PC2

0.224 0.888

0.661 −0.453

0.719 −0.228

0.966 0.074

0.970 0.043

0.981 0.049

0.982 0.045

0.982 0.060

Note: PRE refers to precipitation, TEM to air temperature, POP to total population, GDP to regional gross domestic product, CLA to cultivated land area, GV to gross output value of agriculture, forestry, animal husbandry and fishery, GVP to gross output value of the planting industry, and GVA to gross output value of the animal husbandry.

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groundwater. The surge in groundwater storage in this study is reflected in all the inland basins (SLRB, HRB and SYRB), of which SYRB has seen the most obvious increase. The more intense response observed in the groundwater storage of SYRB could be a result of the suppression effect of the earthquakes and an ecological conservation policy initiated by the central government of China, i.e., the “three prohibitions” policy (prohibition of grazing, prohibition of digging wells in wasteland and prohibition of over-exploitation of groundwater in the lower reaches of SYRB) (Huang et al., 2017). 4.3. Impact of climate change and human activities on regional groundwater sustainability 4.3.1. Human activity dominantly drove the processes of regional groundwater deterioration Factors that could affect the groundwater sustainability include climate change and human activity (Rakhmatullaev et al., 2010; Sophocleous, 2010). In the scenario of climate change, the precipitation and temperature in the HC have increased synchronously in the past few decades, and the increased precipitation and evaporation caused by temperature rise almost offset each other (Fig. 9, Table 2). Consequently, human activity has been the dominant factor driving the processes of deterioration in groundwater sustainability in the HC, at least during the study period of 1980–2016, i.e., the expansion of irrigation, the switch toward more profitable crops which often had higher water needs, and the development of well drilling and groundwater irrigation rate (Bao and Fang, 2007; Xie et al., 2018b). Indeed, HC regions have been undergoing significant changes due to social-economic development and expanded irrigation for agricultural production during the past decades. Fig. 10a shows the evolution of irrigated area in the three inland river basins in HC regions, and it is obvious that the irrigation has been continuously increased during the whole period of investigation (1980–2016) and over all the river basins of the HC. The switch toward more profitable crops also caused the increased water consumption, which in turn threatens groundwater sustainability by increasing groundwater abstraction when surface water for irrigation is limited. For instance, Zhang et al. (2014) reported that during the period of 1987–2007, the annual total crop water consumption in Dunhuang City (the middle SLRB) increased by N25% from 1987 to 2007, because of both the substantially expanded agricultural land area and the significantly increased proportion of cash crops (with high value and profitability). A similar situation has been reported for many other regions of the HC, e.g., Hao et al. (2017) and Zhou et al. (2017). The increased water consumption in HC regions was largely driven by the highly

intensified groundwater extraction, which is evidenced by the everincreasing bore well drilling during the past decades, i.e., the Minqin oasis in the SYRB, the Linze oasis in the HRB, and the Dunhuang oasis in the SLRB (Huang et al., 2017; Qi, 2017) (Fig. 10b). Consequently, we confirmed that overexploitation of groundwater resources caused by groundwater-fed irrigation was the main driver of the deterioration in groundwater sustainability in the HC. This was consistent with the conclusion drawn from many other researches conducted in this region, e.g., Zhou et al. (2017). Similar reasons were found in other regions of groundwater resources deterioration, such as the Gangetic Plain in India (Buvaneshwari et al., 2017), the North Plain in China (Von et al., 2010), and the High Plains and California Central Valley in the USA (Scanlon et al., 2012).

4.3.2. Response of regional groundwater sustainability to water resource management All the above discussions are related to the negative impacts of human activities on groundwater sustainability; however, groundwater over-abstraction has been increasingly recognized since the late 1990s in the HC regions, and many water management projects were launched to alleviate environmental challenges since then, in light of severe water scarcity issues and advancing desertification. We compared the groundwater sustainability before and after the implementation of watershed management initiatives in the HC, and found that the groundwater sustainability was lowered rather than raised by these treatments in all the three watersheds involved (Fig. 8). Taking the HRB as an example, the compulsory water division regulation limited water withdrawals by Zhangye City in the middle reach of the HRB to protect the extremely fragile ecological conditions in the lower reach. Although the policy helped improve the ecosystem conditions in the lower reach, but 40,000 ha of cropland annually in Zhangye City could not obtain sufficient surface water for irrigation. As a result, farmers turned to groundwater for supplementation, leading to the overpumping of groundwater (Yin et al., 2008). According to Zhao and Chang (2014), the number of wells in the middle reaches of the HRB increased sharply, from 5282 in 2000 to 14,685 in 2013. It is obvious that even the management of water resources designed to help face the general challenges in environmental sustainability could worsen the groundwater situation by neglecting the importance of including groundwater in the water management paradigm (Aarnoudse et al., 2019). Similar cases have also been reported in other regions of the world, e.g., the Murray-Darling River Basin in Australia (Ross, 2012), the High Plains Aquifer in the United States (Sophocleous, 2010), the

Fig. 10. Time series of socio-economic indicators in typical areas of the three major river basins in the HC. (a) irrigated area; (b) changes in the number of motor wells (which was normalized with the recorded maximum in order to be comparable with each other) in three representative regions in the HC during the period of 1966 to 2016. Data was collected from Huang et al. (2017) and Qi (2017).

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Amu Darya River Basin in central Asia (Rakhmatullaev et al., 2010), and the Yinchuan Plain in northwestern China (Chen et al., 2018). One of the most important reasons for this phenomenon is that joint management of surface water and groundwater is almost completely absent in most catchments, and the spontaneous and unplanned use of groundwater results in aquifer depletion to water-table levels that could further jeopardize local plant communities and thus ecosystem functioning, potentially at a larger scale (Yu et al., 2018). Although this situation is changing, and joint management has been explored in various forms around the world and successfully implemented in a few developed countries—e.g., the Sustainable Groundwater Management Act issued in California, United States (Jacobs and Holway, 2004)—there is still a long way to go for most countries, including China, to widely implement comprehensive groundwater management, under the current water management paradigm (Aarnoudse et al., 2019). For instance, the conjunctive use and joint management of surface and groundwater was also explored in the SLRB as part of the catchment water resources strategy, but very limited effects on groundwater sustainability were seen, at least during the short-term treatment (Fig. 8), partly because of the fact that the surface water and groundwater management departments are independent of each other and their powers and responsibilities are separated. The coordination between departments is insufficient and the management interest is low. For example, the price of groundwater is significantly lower than that of surface water, farmers are more inclined to exploit groundwater for irrigation, so that without more structural interventions such as price control and department cooperation, it has been impossible to substantially improve groundwater management in the region (Dou, 2016). Compared with the SLRB and HRB, a much stricter groundwater management regime was adopted in the SYRB since 2007, and the joint management of surface water and groundwater has been in operation for several years, however, groundwater sustainability there has been dropping during the period of record. We found that although the groundwater level in many parts of the basin stopped falling because of the treatment, high vulnerability caused by overdraft still hampered an improvement of groundwater sustainability in the SYRB (Fig. 8), indicating that damaged groundwater sustainability cannot be easily reversed unless a long-term management policy is implemented (Aarnoudse et al., 2019; Xie et al., 2018b; Buvaneshwari et al., 2017). Given the limited data (with respect to the water resources management problems) currently available in the HC, it is worth to note that just comparing the groundwater sustainability before and after the implementation of such plans either cannot fully distinguish the effects the water management projects on the groundwater system, or completely reflect the response of groundwater sustainability to water resource management. More researches are needed in this regard in the future. 4.4. Limitations and implications The accuracy of any findings depends upon the authenticity of the source and on information used in analyzing secondary data (Kapur, 2018). The present study used GRACE, GLDAS and in-situ measured groundwater data products. GRACE data itself has north-south band noise, spherical harmonic coefficient noise and errors generated when eliminating high-frequency short-term aliasing caused by tides and atmospheric conditions (Bhanja et al., 2016). As a data assimilation product, the estimation accuracy and effectiveness of GLDAS also relies largely on the quality of the forcing data (Frappart and Ramillien, 2018). Even the in-situ data are not always measured, so that the interpolation of missing values could also result in uncertainty of the results (Fig. 5), and the benefits of improving data management are not well understood. Consequently, our results are potentially suffering from limitations due to the errors on the data used, the non-consideration of some hydrological compartments, fluxes, and abstractions (Voss et al., 2013). The unmatched spatial resolution of the dataset and the processing methods for each dataset could result in substantial

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uncertainty in the results. The limited spatial representation of the insitu data may also result in uncertainty of the results; for instance, the monitoring wells are largely set in the oasis areas so that few in-situ data were collected for the deserts and mountainous areas, which constitute N90% of the HC area. To overcome these data issues, we made every effort to minimize potential bias. For example, the Mascon data product was used in this study to minimize the potential noises of the GRACE data; and the Thiessen polygon method was used to improve the spatial representation of the measured data and to eliminate the extreme values, to improve data accuracy. Through these efforts, consistency between the GRACE-GLDAS and the in-situ measurements was enhanced significantly in terms of correlation, especially when a time lag of 3 months was considered. This approach highly supports the application of the GRACE-GLDAS database in estimating regional groundwater sustainability (Tangdamrongsub et al., 2018). However, no matter how theoretically correct a database may be, when it is applied in the field, “uncertainty” is always an important factor that cannot be neglected, for example, even the Mascon data product cannot be assured to be free of error, although which has been suggested to greatly reduce the signal loss (Sultan et al., 2019; Werth et al., 2017). Given the groundwater sustainability evaluation is largely based on the trend rather than specific points in time, the errors introduced from GRACE and GLDAS data can be considered small for the results upon groundwater sustainability in this work. Aside from the uncertainties induced by source data, more limitations may be placed upon the groundwater sustainability estimation by parametric structural estimation. For example, the WTF method used in this work relies heavily on specific yield, but there is no readymade high-resolution specific yield distribution map for the HC (Henry et al., 2011). We used a hydrogeological map and the empirical relationship between lithology and specific yield to derive a site-specific yield map, and this process requires certain human classifications, which in turn could also produce errors. Although such uncertainty is inevitable, we adopted GLiM v1.0 (Global Lithologic Map, Hartmann and Moosdorf, 2012), which is 100 times more detailed than the commonly used lithologic map, to ensure the accuracy and objectivity of the data source; and used a widely accepted relationship between lithology and specific yield, to ensure that the calculation of ΔGWSWTF remained realistic. For instance, we adopted more objective procedures such as laboratory tests, comparative verification with related papers, and consulting relevant experts, to make the results close to reality to the maximum extent possible, and to reduce the uncertainty of parameter setting. Overall, we are confident about the estimation accuracy of ΔGWSWTF and SIGWS, which provide useful information for the design of more sustainable strategies to reduce the environmental impacts of groundwater utilization and water resources. This study also proved the reliability of GRACE-GLDAS data and the feasibility of the evaluation method of groundwater sustainability in arid areas in combination with a groundwater sustainability index, which provides a relatively universal and complete approach for future related researches in other arid areas around the world. 5. Conclusion GRACE-GLDAS data and the WTF method based on in-situ groundwater-level data were used to estimate the groundwater storage anomaly (ΔGWS) and groundwater sustainability (SIGWS) in the arid HC of Northwestern China. The derived ΔGWS from the two datasets were compared, and good agreement and consistency were obtained between them during the period in which the two data sets overlapped (2002–2010). We found that ΔGWS in the HC regions increased substantially during 1985–1990 (16.79 cm/year) and decreased greatly during 1991–2001 (−9.67 cm/year). A sudden and sharp increase in groundwater storage was observed in 2002, and after that, ΔGWS continuously declined until 2010. From 2010 onward, the storage has exhibited a general downward trend but with strong fluctuations. Clear

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monthly patterns of ΔGWS (highest in July: −0.22 cm; lowest in December: −1.88 cm) were observed throughout the entire period when GRACE data were available, and was most significant in the southeastern HC. A widely accepted index of groundwater sustainability (SIGWS) was employed to evaluate the temporal and spatial characteristics of groundwater sustainability in the HC. Our results suggested that although improvement was observed in some levels during some periods (i.e., 2000–2004), the groundwater system in the HC has experienced a general deterioration in sustainability, from SIGWS=0.48 to SIGWS=0.004. The lowest SIGWS were found in the middle part of the HC region, followed by those in the eastern part. The extremely low SIGWS appeared in the middle part of the HC (HRB) and was most likely due to the combination of low reliability, low resilience, and high vulnerability. However, the unsustainability of the northeastern part of the HC (the lower reaches of the SYRB) is potentially due to high vulnerability in the groundwater systems. Our results suggested that human activity was the dominant driver of the processes of groundwater deterioration in the HC regions, and limited positive effects (or even negative impacts) were associated with the water management project in the short term, although the project may deliver stronger positive benefits in the long term if conjunctive use and joint management of surface and groundwater are more often included in a future water regime. This study proves that GRACE gravity satellite data has great potential in groundwater sustainability assessment in arid regions, especially in developing countries where measured data are scarce, and highlights the importance of joint management of surface water and groundwater, in groundwater sustainability management.

Declaration of Competing Interest There is no conflict of interest. Acknowledgements This research was jointly supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA2003010102), the West Light Foundation of the Chinese Academy of Sciences (29Y929621), the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology (2017–2019, awarded to Dr. Yang Yu), and the National Natural Science Foundation of China (41630861). We would like to thank Editor (Prof. Paulo Pereira) and anonymous referees for their helpful comments. A special thank is also given to Marian Rhys for his kind help in revising this paper. References Aarnoudse, E., Bluemling, B., Qu, W., Herzfeld, T., 2019. Groundwater regulation in case of overdraft: national groundwater policy implementation in north-west China. Int. J. Water Resour. Dev. 35, 264–282. https://doi.org/10.1080/07900627.2017.1417115. Abou, Z.N., Torabi, H.A., Rossi, P.M., Tourian, M.J., Klove, B., 2018. Monitoring groundwater storage depletion using gravity recovery and climate experiment (GRACE) data in the semi-arid catchments. Hydrol. Earth Syst. Sci. Discuss., 1–21 https://doi.org/10.3390/ w11071456. Akiyama, T., Kubota, J., Fujita, K., Tsujimura, M., Nakawo, M., Avtar, R., Kharrazi, A., 2018. Use of water balance and tracer-based approaches to monitor groundwater recharge in the hyper-arid gobi desert of Northwestern China. Environments 5, 55. https://doi. org/10.3390/environments5050055. Alfarrah, N., Walraevens, K., 2018. Groundwater overexploitation and seawater intrusion in coastal areas of arid and semi-arid regions. Water 10. https://doi.org/10.3390/ w10020143. Alley, W.M., Reilly, T.E., Franke, O.L., 1999. Sustainability of groundwater resources. U.s. geol.surv.circulation. 1186, 79. https://doi.org/10.1016/B978-0-12-382182-9.000621. Alley, W.M., Healy, R.W., LaBaugh, J.W., Reilly, T.E., 2002. Flow and storage in groundwater systems. Science 296, 1985–1990. https://doi.org/10.1126/science.1067123. Bao, C., Fang, C., 2007. Water resources constraint force on urbanization in water deficient regions: a case study of the Hexi Corridor, arid area of northwest China. Ecol. Econ. 62, 508–517. https://doi.org/10.1016/j.ecolecon.2006.07.013. Bhanja, S.N., Mukherjee, A., Saha, D., Velicogna, I., Famiglietti, J.S., 2016. Validation of GRACE based groundwater storage anomaly using in-situ groundwater level

measurements in India. J. Hydrol. 543, 729–738. https://doi.org/10.1016/j. jhydrol.2016.10.042. Buvaneshwari, S., Riotte, J., Sekhar, M., Mohan, K.M.S., Sharma, A.K., Duprey, J.L., Audry, S., Giriraja, P.R., Praveenkumarreddy, Y., Moger, H., Durand, P., Braun, J.J., Ruiz, L., 2017. Groundwater resource vulnerability and spatial variability of nitrate contamination: insights from high density tubewell monitoring in a hard rock aquifer. Sci. Total Environ. 579, 838–847. https://doi.org/10.1016/j.scitotenv.2016.11.017. Cao, Y., Nan, Z., Hu, X., 2012. Estimating groundwater storage changes in the Heihe river basin using GRACE. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International IEEE, pp. 22–27. https://doi.org/10.1109/IGARSS.2012.6351441. Chen, J., Wang, C., 2009. Rising springs along the silk road. Geology 37, 243–246. https:// doi.org/10.1130/G25472A.1. Chen, Y., Li, W., Shen, Y., 2014a. Water resource management. In: Chen, Y. (Ed.), Water Resources Research in Northwest China. Springer Netherlands, Dordrecht, pp. 405–440. https://doi.org/10.1002/9781119198765.ch11. Chen, J., Liu, X., Sun, X., Su, Z., Yong, B., 2014b. The origin of groundwater in Zhangye Basin, northwestern China, using isotopic signature. Hydrogeol. J. 22, 411–424. https://doi.org/10.1007/s10040-013-1051-7. Chen, J., Wu, H., Qian, H., Li, X., 2018. Challenges and prospects of sustainable groundwater management in an agricultural plain along the Silk Road Economic Belt, northwest China. Int. J. Water Resour. Dev. 34, 354–368. https://doi.org/10.1080/ 07900627.2016.1238348. Chen, H., Zhang, W., Nie, N., Guo, Y., 2019. Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations. Sci. Total Environ. 649, 372–387. https://doi.org/10.1016/j. scitotenv.2018.08.352. Devlin, J.F., Sophocleous, M., 2005. The persistence of the water budget myth and its relationship to sustainability. Hydrogeol. J. 13, 549–554. https://doi.org/10.1007/s10040004-0354-0550. Dou, X., 2016. A critical review of groundwater utilization and management in China’s inland water shortage areas. Water Policy 18, 1367–1383. https://doi.org/10.2166/ wp.2016.043. Famiglietti, J.S., 2014. The global groundwater crisis. Nat. Clim. Chang. 4, 945–948. https:// www.nature.com/articles/nclimate2425. Frappart, F., Ramillien, G., 2018. Monitoring groundwater storage changes using the gravity recovery and climate experiment (GRACE) satellite mission: a review. Remote Sens. 10. https://doi.org/10.3390/rs10060829. Gun, J.V.D., Lipponen, A., 2010. Reconciling groundwater storage depletion due to pumping with sustainability. Sustainability. 2, 3418–3435. https://doi.org/10.3390/ su2113418. Guo, H., Bao, A., Liu, T., Jiapaer, G., Ndayisaba, F., Jiang, L., Kurban, A., De, M.P., 2018. Spatial and temporal characteristics of droughts in Central Asia during 1966-2015. Sci. Total Environ. 624, 1523–1538. https://doi.org/10.1016/j.scitotenv.2017.12.120. Hao, Y., Xie, Y., Ma, J., Zhang, W., 2017. The critical role of local policy effects in arid watershed groundwater resources sustainability: a case study in the Minqin oasis, China. Sci. Total Environ. 601–602, 1084–1096. https://doi.org/10.1016/j. scitotenv.2017.04.177. Hartmann, J., Moosdorf, N., 2012. The new global lithological map database GLiM: a representation of rock properties at the Earth surface. Geochem. Geophys. Geosyst. 13. https://doi.org/10.1029/2012GC004370. Hashimoto, T., Stedinger, J.R., Loucks, D.P., 1982. Reliability, resiliency，and vulnerability criteria for water-resource system preformance evaluation. Water Resour. Res. 18, 14–20. https://doi.org/10.1029/WR018i001p00014. Henry, C.M., Allen, D.M., Huang, J., 2011. Groundwater storage variability and annual recharge using well-hydrograph and GRACE satellite data. Hydrogeol. J. 19, 741–755. https://doi.org/10.1007/s10040-011-0724-3742. Hiroko, B., Rodell, M., Huang, J., 2016. GLDAS Noah Land Surface Model L4 Monthly 0.25 x 0.25 Degree V2.1. Goddard Earth Sciences Data and Information Services Center (GES DISC) https://doi.org/10.5067/SXAVCZFAQLNO. Hochmuth, H., Thevs, N., He, P., 2015. Water allocation and water consumption of irrigation agriculture and natural vegetation in the Heihe River watershed, NW China. Environ. Earth Sci. 73, 5269–5279. https://doi.org/10.1007/s12665-014-3773-9. Huang, S., Zhou, L., Feng, Q., Lu, Z., Xiao, J., 2017. Evaluation of eco-environment effects of management policy implementing in inland river basin of China: a case in the Minqin oasis. J. Desert Res. 3, 580–586. https://doi.org/10.7522/j.issn.1000-694X.2015.00286 (in Chinese). Iqbal, N., Hossain, F., Lee, H., Akhter, G., 2017. Integrated groundwater resource management in Indus Basin using satellite gravimetry and physical modeling tools. Environ. Monit. Assess. 189, 128. https://doi.org/10.1007/s10661-017-5846-1. Jacobs, K.L., Holway, J.M., 2004. Managing for sustainability in an arid climate: lessons learned from 20 years of groundwater management in Arizona, USA. Hydrogeol. J. 12, 52–65. https://doi.org/10.1007/s10040-003-0308-y. Ji, X., Kang, E., Chen, R., Zhao, W., Zhang, Z., Jin, B., 2006. The impact of the development of water resources on environment in arid inland river basins of Hexi region, northwestern China. Environ. Geol. 50, 793–801. https://doi.org/10.1007/s00254-0060251-z. Jolliffe, I.T., 2002. Pincipal component analysis. J. Mark. Res. 25, 513. https://doi.org/ 10.2307/3172953. Kalf, F.R.P., Woolley, D.R., 2005. Applicability and methodology of determining sustainable yield in groundwater systems. Hydrogeol. J. 13, 295–312. https://doi.org/10.1007/ s10040-004-0401-x296. Kapur, R., 2018. Research Methodology: Methods and Strategies. https://www. researchgate.net/publication/324588113. Katpatal, Y.B., Rishma, C., Singh, C.K., 2018. Sensitivity of the Gravity Recovery and Climate Experiment (GRACE) to the complexity of aquifer systems for monitoring of groundwater. Hydrogeol. J. 26, 933–943. https://doi.org/10.1007/s10040-017-1686-x.

Please cite this article as: S. Wang, H. Liu, Y. Yu, et al., Evaluation of groundwater sustainability in the arid Hexi Corridor of Northwestern China, using GRAC..., Science of the Total Environment, https://doi.org/10.1016/j.scitotenv.2019.135829

S. Wang et al. / Science of the Total Environment xxx (xxxx) xxx Khan, H.F., Yang, Y.C.E., Ringler, C., Wi, S., Cheema, M.J.M., Basharat, M., 2017. Guiding groundwater policy in the indus basin of Pakistan using a physically based groundwater model. J. Water Resour. Plan. Manag. 143, 05016014. https://doi.org/10.1061/ (ASCE)WR.1943-5452.0000733. Konikow, L.F., 2015. Long-term groundwater depletion in the United States. Ground Water 53, 2–9. https://doi.org/10.1111/gwat.12306. Lee, C.H., 1915. The determination of safe yield of underground reservoirs of the Closed Basin type. Trans. Am. Soc. Civ. Eng. 78, 148–251. https://core.ac.uk/display/ 59822441. Li, Y., Yang, J., 1998. Tectonic geomorphology in the Hexi Corridor, north-west China. Basin Res. 10, 345–352. https://doi.org/10.1046/j.1365-2117.1998.00070.x. Liang, L., Li, L., Liu, Q., 2010. Temporal variation of reference evapotranspiration during 1961–2005 in the Taoer river basin of northeast China. Agric. For. Meteorol. 150, 298–306. https://doi.org/10.1016/j.agrformet.2009.11.014. Liesch, T., Ohmer, M., 2016. Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan. Hydrogeol. J. 24, 1547–1563. https:// doi.org/10.1007/s10040-016-1416-9. Long, D., Pan, Y., Zhou, J., Chen, Y., Hou, X., Yang, H., Scanlon, B.R., Longuevergne, L., 2017. Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models. Remote Sens. Environ. 192, 198–216. https://doi.org/10.1016/j.rse.2017.02.011. Loucks, D.P., 1997. Quantifying trends in system sustainability. Hydrol. Sci. J. 42, 513–530. https://doi.org/10.1080/02626669709492051. Mays, L.W., 2013. Groundwater resources sustainability: past, present, and future. Water Resour. Manag. 27, 4409–4424. https://doi.org/10.1007/s11269-013-0436-7. Mehta, V.K., Young, C., Esney, S.R.B., Spivak, D.S., Winter, J.M., 2018. How can we support the development of robust groundwater sustainability plans? Calif. Agric. 72, 54–64. https://doi.org/10.3733/ca.2018a0005. Merritt, D.M., Bateman, H.L., 2012. Linking stream flow and groundwater to avian habitat in a desert riparian system. Ecol. Appl. 22, 1973–1988. https://doi.org/10.2307/ 41723108. Mi, L., Xiao, H., Zhang, J., Yin, Z., Shen, Y., 2016. Evolution of the groundwater system under the impacts of human activities in middle reaches of Heihe River Basin (Northwest China) from 1985 to 2013. Hydrogeol. J. 24, 971–986. https://doi.org/10.1007/ s10040-015-1346-y. Nanekely, M., Scholz, M., Aziz, S.Q., 2017. Towards sustainable management of groundwater: a case study of semi-arid area, Iraqi Kurdistan Region. World Congress of Ewra on Water Resources and Environment. European Water Resources Association, Athens http://www.ewra.net/ew/pdf/EW_2017_57_64.pdf. Pingale, S.M., Khare, D., Jat, M.K., Adamowski, J., 2014. Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centers of the arid and semi-arid state of Rajasthan. Atmos. Res. 138, 73–90. https://doi.org/10.1016/j. atmosres.2013.10.024. Qi, J., 2017. The Research on Oasis Ecological Evolution of Shule River Basin. Lanzhou University. Rakhmatullaev, S., Huneau, F., Kazbekov, J., Le, C.P., Jumanov, J., El, O.B., Motelica, H.M., Hrkal, Z., 2010. Groundwater resources use and management in the Amu Darya River Basin (Central Asia). Environ. Earth Sci. 59, 1183–1193. https://doi.org/ 10.1007/s12665-009-0107-4. Rodell, M., Houser, P.R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., 2003. The Global Land Data Assimilation System. https://doi.org/10.1175/BAMS-85-3-381. Ross, A., 2012. Easy to say, hard to do: integrated surface water and groundwater management in the Murray-Darling Basin. Water Policy 14, 709–724. https://doi.org/ 10.2166/wp.2012.129. Sandoval, S.S., McKinney, D.C., Loucks, D.P., 2011. Sustainability index for water resources planning and management. J. Water Resour. Plan. Manag. 137, 381–390. https://doi. org/10.1061/(ASCE)WR.1943-5452.0000134. Save, H., Bettadpur, S., Tapley, B.D., 2016. High resolution CSR GRACE RL05 mascons. J. Geophys. Res. Solid Earth 121, 7547–7569. https://doi.org/10.1002/2016JB013007. Scanlon, B.R., Longuevergne, L., Long, D., 2012. Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USA. Water Resour. Res. 48. https://doi.org/10.1029/2011WR011312. Seward, P., Xu, Y., Turton, A., 2015. Investigating a spatial approach to groundwater quantity management using radius of influence with a case study of South Africa. Water SA 41, 71. https://doi.org/10.4314/wsa.v41i1.10. Sophocleous, M., 2005. Groundwater recharge and sustainability in the high plains aquifer in Kansas, USA. Hydrogeol. J. 13, 351–365. https://doi.org/10.1007/s10040-0040385-6352. Sophocleous, M., 2010. Review: groundwater management practices, challenges, and innovations in the High Plains aquifer, USA-lessons and recommended actions. Hydrogeol. J. 18, 559–575. https://doi.org/10.1007/s10040-009-0540-1560.

13

Strassberg, G., Scanlon, B.R., Chambers, D., 2009. Evaluation of groundwater storage monitoring with the GRACE satellite: case study of the High Plains aquifer, Central United States. Water Resour. Res. 45. https://doi.org/10.1029/2008WR006892. Sultan, M., Sturchio, N.C., Alsefry, S., Emil, M.K., Ahmed, M., Abdelmohsen, K., AbuAbdullah, M.M., Yan, E., Save, H., Alharbi, T., Othman, A., Chouinard, K., 2019. Assessment of age, origin, and sustainability of fossil aquifers: a geochemical and remote sensing-based approach. J. Hydrol. 576, 325–341. https://doi.org/10.1016/j. jhydrol.2019.06.017. Tangdamrongsub, N., Han, S.C., Tian, S., Müller, S.H., Sutanudjaja, E.H., Ran, J., Wei, F., 2018. Evaluation of groundwater storage variations estimated from GRACE data assimilation and state-of-the-Art Land Surface Models in Australia and the North China Plain. Remote Sens. 10, 483. https://doi.org/10.3390/rs10030483. Thomas, B.F., Famiglietti, J.S., Landerer, F.W., Wiese, D.N., Molotch, N.P., Argus, D.F., 2017. GRACE Groundwater Drought Index: evaluation of California Central Valley groundwater drought. Remote Sens. Environ. 198, 384–392. https://doi.org/10.1016/j. rse.2017.06.026. Toure, M.Y.A., Goita, K., Magagi, R., Toure, A.M., 2016. Comparison of in situ and GRACE estimated groundwater in the Canadian prairies. 2016 IEEE International Geoscience and Remote Sensing Symposium, pp. 7639–7642. https://doi.org/10.1109/ IGARSS.2016.7730992. Velis, M., Conti, K.I., Biermann, F., 2017. Groundwater and human development: synergies and trade-offs within the context of the sustainable development goals. Sustain. Sci. 2, 1–11. https://doi.org/10.1007/s11625-017-0490-9. Vest, K.R., Elmore, A.J., Kaste, J.M., Okin, G.S., Li, J., 2013. Estimating total horizontal aeolian flux within shrub-invaded groundwater-dependent meadows using empirical and mechanistic models. J. Geophys. Res. Earth Surf. 118, 1132–1146. https://doi.org/ 10.1002/jgrf.20048. Von, R.C., Kreuzer, A., Chen, Z., Kipfer, R., Aeschbach, H.W., 2010. Characterizing the recharge regime of the strongly exploited aquifers of the North China Plain by environmental tracers. Water Resour. Res. 46. https://doi.org/10.1029/2008wr007660. Voss, K.A., Famiglietti, J.S., Lo, M., de Linage, C., Rodell, M., Swenson, S.C., 2013. Groundwater depletion in the Middle East from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region. Water Resour. Res. 49, 904–914. https://doi.org/10.1002/wrcr.20078. Wang, Y., Chen, J., Chen, L., 2009. Tracing groundwater with strontium isotopic compositions in the Hexi Corridor Basin, Northwestern China. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 184–187. https://doi.org/10.1007/978-3-540-89465-0_34. Werth, S., White, D., Bliss, D.W., 2017. GRACE detected rise of groundwater in the Sahelian Niger River Basin. J. Geophys. Res. Solid Earth 122, 10,459–410,477. https://doi.org/ 10.1002/2017jb014845. Woldeyohannes, Y., Waqar, M., 2017. The move from safe yield to sustainability and manage yield. Glob. J. Hum.-Soc. Sci. 17, 1–6. https://globaljournals.org/GJHSS_Volume17/ 4-The-Move-from-Safe-Yield.pdf. Xie, X., Xu, C., Wen, Y., Li, W., 2018a. Monitoring groundwater storage changes in the Loess Plateau using GRACE satellite gravity data, hydrological models and coal mining data. Remote Sens. 10. https://doi.org/10.3390/rs10040605. Xie, Y., Bie, Q., Lu, H., He, L., 2018b. Spatio-temporal changes of oases in the Hexi Corridor over the past 30 years. Sustainability 10. https://doi.org/10.3390/su10124489. Yin, Y., Xu, Z., Long, A., 2008. Evaluation of adaptation options for the Heihe River Basin of China. Climate Change and Adaptation. Earthscan, London, pp. 211–228. https://doi. org/10.4324/9781315067179. Yin, W., Hu, L., Wang, J., 2015. Changes of groundwater storage variation based on GRACE data at the Beishan area, Gansu Province. Hydrogeol. Eng. Geol. 42, 30–35. https://doi. org/10.16030/j.cnki.issn.1000-3665.2015.04.06 (in Chinese). Yu, L., Ding, Y., Chen, F., Hou, J., Liu, G.J., Tang, S., Ling, M., Liu, Y., Yan, Y., An, N., 2018. Groundwater resources protection and management in China. Water Policy 20, 447–460. https://doi.org/10.2166/wp.2017.035. Zhang, X., Zhang, L., He, C., Li, J., Jiang, Y., Ma, L., 2014. Quantifying the impacts of land use/ land cover change on groundwater depletion in Northwestern China - a case study of the Dunhuang oasis. Agric. Water Manag. 146, 270–279. https://doi.org/10.1016/j. agwat.2014.08.017. Zhang, F., Zhang, M., Wang, S., Qiang, F., Che, Y., Wang, J., 2017. Evaluation of the tourism climate in the Hexi Corridor of northwest China’s Gansu Province during 1980-2012. Theor. Appl. Climatol. 129, 901–912. https://doi.org/10.1007/s00704-016-1814-x. Zhao, W., Chang, X., 2014. The effect of hydrologic process changes on NDVI in the desertoasis ecotone of the Hexi Corridor. Sci. China Earth Sci. 57, 3107–3117. https://doi. org/10.1007/s11430-014-4927-z. Zhou, D., Wang, X., Shi, M., 2017. Human driving forces of oasis expansion in northwestern China during the last decade - a case study of the Heihe River Basin. Land Degrad. Dev. 28, 412–420. https://doi.org/10.1002/ldr.2563.

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