The arid region of Northwest China (ANC) has a distinct and fragile inland water cycle. This study examined the hydrological variations in ANC and its three subregions from August 2002 to December 2013 by integrating terrestrial water storage (TWS) anomaly data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite, soil moisture data modeled by the Global Land Data Assimilation System, and passive microwave snow water equivalent data. The results show that the TWS in ANC increased at a rate of 1.7 mm/a over the past decade, which consisted of an increasing trend of precipitation (0.12 mm/a). Spatially, in the northern ANC, TWS exhibited a significant decreasing trend of −3.64 mm/a (
Climate change together with human activities (e.g., land reclamation and agricultural irrigation) can result in large variations in hydrological regimes and increase the severity of hydrological and water resources issues, particularly in areas such as the arid region of Northwest China (ANC) [
The ANC in this study is one of the largest arid regions in the world and is extremely vulnerable to water scarcity [
During the past decades, climate conditions have been rapidly changed in ANC [
Recently, some studies have examined TWSA in subregions of ANC. Yang and Chen [
The main objective of this study is to examine hydrological variabilities of TWS and its major components in the entire ANC and three subregions with distinct climate characteristics on multiple time scales. Special aims include (i) quantifying the change rate of TWSA in the entire ANC and the three subregions during the past decade, (ii) examining the variabilities in TWS components on multiple time scales, and (iii) investigating potential factors affecting hydrological variabilities. These findings will be beneficial to sustainable water resource management and ecological protection in arid regions in the context of climate change.
The ANC is located at the center of the Eurasian continent far from oceans (Figure
Location map showing the arid region of Northwest China (ANC) and its three subregions.
The ANC has a vast territory of complex topography that includes mountains, plateaus, deserts, and basins [
GRACE data are available from three different processing centers: Center for Space Research (CSR) at the University of Texas, Austin, GeoForschungsZentrum (GFZ) Potsdam, and Jet Propulsion Laboratory (JPL). The latest Level 2 Release 05 (RL05) gravity field products provided by CSR [
We compared the produced TWSA time series with three standard monthly gridded GRACE TWSA products from CSR, GFZ, and JPL, all based on RL05 spherical harmonics (Figure
Comparison between TWSA time series produced in this study (Our_TWSA) and from three standard GRACE products (CSR, GFZ, and JPL).
The gridded soil moisture data in ANC were obtained from GLDAS models outputs [
The snow water equivalent (SWE) data were computed from snow depth data [
The climate data, including monthly (2002–2013) and annual (1961–2013) precipitation and temperature data, were collected from 76 meteorological stations located within the ANC. The gridded precipitation
The gridded temperature
The climate and topography in ANC are highly heterogeneous. The Xinjiang region is composed of Northern Xinjiang and Southern Xinjiang with the Tianshan Mountains between them as a natural geographical dividing line (Figure
Figure
Precipitation and air temperature variations in the entire ANC and its subregions in 1961–2013.
Entire study region
Hexi-Alashan region
Northern Xinjiang
Southern Xinjiang
Potential ET is generally high in Southern Xinjiang (2000–3000 mm) and low in Northern Xinjiang (1300–2300 mm) [
The derived hydrological signals generally consist of secular, periodic variations and the residuals. We used (
Following this model, the anomaly signals in GRACE TWSA and precipitation could be obtained by removing the annual and semiannual cycles and tide alias information.
The uncertainty in GRACE TWSA can be categorized into
The amplitude of GRACE-derived TWS may be damped because of filtering and coefficient truncation. We applied a scaling factor (
The total TWS is a vertical integration of groundwater, soil moisture, snow, ice, surface water, and wet biomass. In a specific region, TWSA equates to the sum of the contributions of the different constituents, as expressed in (
Among these components, surface and ground water anomalies are difficult to measure. Soil moisture content can be estimated by models, and SWE can be determined via remote sensing methods. Therefore, in this study, we focused on investigating the relationships between TWSA and soil moisture and SWE anomalies.
Climate change due to global warming will significantly affect the water cycle in the arid region of northwest China [
With the produced TWSA data, both temporal and spatial variabilities of hydrological variability in the entire ANC were examined. The variabilities in subregions were specially analyzed on different temporal scales (monthly, seasonal, and annual). The factors contributing to variations in TWSA and its components in the study period were specially investigated, particularly under the changing climate. Standard deviation and
Figure
Regional averages of TWSA, soil moisture anomaly (SMA), snow water equivalent anomaly (SWEA), precipitation, and temperature in the entire ANC.
Figure
The correlation between climate factors and TWSA can be better represented after removal of annual and semiannual cycles and tide alias information using (
Best-fitted TWSA and precipitation anomaly in the entire ANC.
The measurement error was estimated to be approximately 10.0 mm in RMS, as indicated by error bars in Figure
The spatial variability of the TWSA trend (in mm/a) from August 2002 to December 2013 is shown in Figure
Spatial variability of GRACE TWSA trend in the entire ANC region and its three subregions: (I) Hexi-Alashan, (II) Northern Xinjiang, and (III) Southern Xinjiang.
Figure
Interannual variability of TWSA in the ANC subregions.
The intra-annual hydrological variations in TWS, soil moisture, SWE, and precipitation averaged over the study period in the three subregions are presented in Figure
Multiple-year averaged monthly variations of TWSA and its components (SMA, SWEA, and inverse GSWA) as well as precipitation in the three subregions.
Hexi-Alashan
Northern Xinjiang
Southern Xinjiang
Meltwater from glacier and snow/ice are an important extra source, particularly in pre-rainy season months. Almost half of the total glaciated areas in China are located in Northwest China [
TWSA was the highest in June and July in Hexi-Alashan on the east and in Southern Xinjiang on the south (~12.2 and 26.4 mm, resp.) and the lowest in October (~−8.8 and −24.2 mm, resp.). In both regions, TWSA reached the maximum at approximately the same time as precipitation (Figures
On a seasonal scale, the three subregions exhibited much similar variability, with increases in spring and summer and decreases in autumn and winter. TWSA increased more in summer than in spring in Hexi-Alashan and Southern Xinjiang and was opposite in Northern Xinjiang. TWSA was the least in autumn and winter in Hexi-Alashan. The seasonality of TWS was most prominent in Southern Xinjiang and least prominent in Hexi-Alashan.
SMA displayed similar monthly variability to TWSA but with overall smaller amplitude. SMA in Southern Xinjiang did not fluctuate much and had a relatively small amplitude because of the extreme aridity in Southern Xinjiang. The largest desert in China, the Taklimakan Desert, is located there. The desert soils have a low capability for water storage. The soil moisture in Hexi-Alashan and Southern Xinjiang surpassed the average in spring and summer and dropped below the average in autumn and winter. Unlike TWSA, the seasonal change patterns of SMA differed by subregion. Maximum soil moisture anomaly (~5.2 mm) in Northern Xinjiang occurred in spring when soil moisture was primarily fed by glacier ablation and snow/ice thawing, whereas maximum TWSA occurred in summer when soil moisture began to decrease.
SWEA generally surpassed the average in winter and spring and dropped in summer and fall but its characteristics varied by subregion. The seasonal oscillation was the smallest in Hexi-Alashan and accounted for a small portion of TWSA. By contrast, it was large in Northern Xinjiang. SWEA in February was approximately 15 mm in Northern Xinjiang, five times higher than that in Southern Xinjiang in the same month. This indicates that SWEA constituted an important portion of TWSA in Northern Xinjiang, especially in winter.
Groundwater and surface water anomalies (GSWA) were inversely determined by (
Over the past 50 years, both precipitation and temperature presented an increasing trend in ANC and its three subregions (Figure
Variabilities and trends of GRACE TWSA and changing climatic conditions in the three subregions: (a) Hexi-Alashan, (b) Northern Xinjiang, and (c) Southern Xinjiang.
The Qilian Mountains supply water resources to the Hexi-Alashan region. The glaciers in this region are about 811.2 km3 in volume [
The time series of TWSA in Northern Xinjiang can be divided into three stages (Figure
Three stages detected by TWSA in Northern Xinjiang.
Period | TWSA (mm) | Precipitation (mm) | Temperature (°C) |
---|---|---|---|
2002–2007 | 13.43 | 16.7 | 6.8 |
2008-2009 | | 14.0 | 7.3 |
2010–2013 | | 16.7 | 6.6 |
Precipitation in Northern Xinjiang was declining at an average rate of −1.0 mm/a from January 2002 to December 2013. Apart from the changes in precipitation, glacier meltwater loss was an extra important factor leading to the overall decreased TWSA in Northern Xinjiang. The amount of glacier melt is highly related to rising temperature. Previous studies in the Tianshan Mountains and the adjacent areas reported a decrease rate of −0.48 mm/month in TWSA from January 2003 to December 2010 [
The Southern Xinjiang-averaged TWSA exhibited strong seasonality (Figure
This study investigated the spatiotemporal characteristics of hydrological variability in the arid region of Northwest China from August 2002 to December 2013 using GRACE-derived TWSA, GLDAS soil moisture output, and remote sensed snow water data.
In the study region, TWSA has increased at a rate of 1.7 mm/a over the past decade, which mimicked the increasing trend of precipitation (0.12 mm/a). TWSA in Northern Xinjiang, Southern Xinjiang, and Hexi-Alashan varied at a rate of −
TWSA and soil moisture anomaly exhibited strong seasonality across the ANC. TWS and soil moisture were recharged in rainy months (May–September) and depleted in dry months (October–April). Regionally, the soil moisture, groundwater, and surface water accounted for the major proportion of TWSA in Southern Xinjiang and Hexi-Alashan, while all the components contributed to the same extent to TWSA in Northern Xinjiang. The largest TWSA and smallest soil moisture anomaly were observed in Southern Xinjiang and the smallest TWSA was observed in Hexi-Alashan. In the case of identifying drought in 2008-2009 in the study area, TWSA is found to be superior over precipitation in detecting wet and dry states and drought conditions.
The method proposed takes advantage of remote sensing data and model outputs. It is able to depict a complete picture of spatiotemporal characteristics of hydrological variability in arid regions without the need for field observations and can be applied to other large arid areas around the world.
The authors declare no conflicts of interest regarding the publication of this paper.
This study was financially supported by the National Key R&D Program of China (no. 2017YFA0603603), the National Natural Science Foundation of China (nos. 41701503 and 41471059), Scientific Research Start-Up Funding of the Program Supporting Special Talent Zone (Henan University), and Scientific Promotion Funding of the Prioritized Academic Discipline (Geography, Henan University). The authors would like to thank the Center for Space Research of the University of Texas at Austin for providing GRACE data. They are also grateful to Professor Matthew Rodell from NASA for the helpful and constructive comments that greatly contributed to improving the quality of the paper.