Groundwater Storage Changes in China from Satellite Gravity: An Overview

Comparison of groundwater storage changes over losing and gaining aquifers of China using GRACE satellites, modeling and in-situ observations

Groundwater depletion in intensively exploited aquifers of China has been widely recognized, whereas an overall examination of groundwater storage (GWS) changes over major aquifers remains challenging due to limited data and notable uncertainties. Here, we present a study to explore GWS changes over eighteen major aquifers covering an area of 1,680,000 km2 in China using data obtained from the Gravity Recovery and Climate Experiments (GRACE), global models, and in-situ groundwater level observations. The analysis aims to reveal the discrepancy in annual trends, amplitudes, and phases associated with GWS changes among different aquifers. It is found that GWS changes in the studied aquifers represent a spatial pattern of 'Wet-gets-more, Dry-gets-less'. An overall decreasing trend of -4.65 ± 0.34 km3/yr is observed by GRACE from 2005 to 2016, consisting of a significant (p < 0.05) increase of 47.28 ± 3.48 km3 in 7 aquifers and decrease of 103.56 ± 2.4 km3 (∼2.6 times the full storage capacity of the Three Gorges Reservoir) in 10 aquifers summed over the 12 years. The annual GWS normally reaches a peak in late July with an area-weighted average annual amplitude of 19 mm, showing notable discrepancy in phases and amplitudes between the losing aquifers (12 mm in middle August) in northern China and gaining aquifers (28 mm in early July) mostly in southern China. GRACE estimates are generally comparable, but can be notably different, with the results obtained from model simulations and in-situ observations at aquifer scale, with the area-weighted average correlation coefficients of 0.6 and 0.5, respectively. This study highlights different GWS changes of losing and gaining aquifers in response to coupled impacts of hydrogeology, climate and human interventions, and calls for divergent adaptions in regional groundwater management.

The analysis on groundwater storage variations from GRACE/GRACE-FO in recent 20 years driven by influencing factors and prediction in Shandong Province, China

Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as an example, the data from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) is used to invert GWS fluctuation from January 2003 to December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ groundwater volume and level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), and the impact factors, such as precipitation and human activities, which are also analyzed. To predict the short-time changes of GWS, the Support Vector Machines (SVM) is adopted together with three commonly used methods Long Short-Term Memory (LSTM), Singular Spectrum Analysis (SSA), Auto-Regressive Moving Average Model (ARMA), as the comparison. The results show that: (1) The loss intensity of western GWS is significantly greater than those in coastal areas. From 2003 to 2006, GWS increased sharply; during 2007 to 2014, there exists a loss rate - 5.80 ± 2.28 mm/a of GWS; the linear trend of GWS change is - 5.39 ± 3.65 mm/a from 2015 to 2022, may be mainly due to the effect of South-to-North Water Diversion Project. The correlation coefficient between GRACE and WGHM is 0.67, which is consistent with in-situ groundwater volume and level. (2) The GWS has higher positive correlation with monthly Global Precipitation Climatology Project (GPCP) considering time delay after moving average, which has the similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, the influencing facotrs on annual GWS fluctuation are analyzed, the correlation coefficient between GWS and in-situ data including the consumption of groundwater mining, farmland irrigation is 0.80, 0.71, respectively. (3) For the GWS prediction, SVM method is adopted to analyze, three training samples with 180, 204 and 228 months are established with the goodness-of-fit all higher than 0.97. The correlation coefficients are 0.56, 0.75, 0.68; RMSE is 5.26, 4.42, 5.65 mm; NSE is 0.28, 0.43, 0.36, respectively. The performance of SVM model is better than the other methods for the short-term prediction.

Cleaner tillage and irrigation options for food-water-energy-carbon synergism in wheat-maize cropping systems

The conventional wheat-maize systems in the North China Plain are energy and water intensive with high carbon emissions. It is imperative to find cleaner production technologies for sustainable food-water-energy-carbon synergism. Here, a three-year field experiment was performed to explore the effects of two tillage modes and four irrigation regimes during wheat season on crop yield, economic profile, water use efficiency, energy utilization, and carbon footprint in typical wheat-maize cropping systems in the North China Plain. Pre-sowing irrigation resulted in the lowest crop yield and benefit profile. Pre-sowing + anthesis irrigation decreased economic benefit and water use efficiency with higher carbon footprint. Pre-sowing + jointing + anthesis irrigation led to the greatest energy consumption and greenhouse gas emissions. However, pre-sowing + jointing irrigation increased yield by 2.3-8.7%, economic benefit by 4.0-11.1%, water use efficiency by 7.4-10.9%, and net energy by 6.5-12.0% but reduced carbon footprint by 9.8-14.3% compared to pre-sowing + anthesis irrigation and pre-sowing + jointing + anthesis irrigation. The corresponding metrics in rotary tillage improved by 9.6%, 13.9%, 7.0%, and 14.2%, respectively, relative to subsoiling, whereas carbon footprint decreased by 12.4-17.2%. Besides, rotary tillage coupled with additional jointing irrigation obtained the highest value based on a Z-score method, which was recommended as a cleaner management practice to improve benefit return and water use efficiency with lower energy consumption and carbon footprint. This work provides valuable insights into food-water-energy-carbon nexus for ensuring food security and achieving environmental sustainability in the wheat-maize cropping systems.

The GWR model-based regional downscaling of GRACE/GRACE-FO derived groundwater storage to investigate local-scale variations in the North China Plain

Groundwater storage and depletion fluctuations in response to groundwater availability for irrigation require understanding on a local scale to ensure a reliable groundwater supply. However, the coarser spatial resolution and intermittent data gaps to estimate the regional groundwater storage anomalies (GWSA) prevent the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GARCE-FO) mission from being applied at the local scale. To enhance the resolution of GWSA measurements using machine learning approaches, numerous recent efforts have been made. With a focus on the development of a new algorithm, this study enhanced the GWSA resolution estimates to 0.05° by extensively investigating the continuous spatiotemporal variations of GWSA based on the regional downscaling approach using a regression algorithm known as the geographically weighted regression model (GWR). First, the modified seasonal decomposition LOESS method (STL) was used to estimate the continuous terrestrial water storage anomaly (TWSA). Secondly, to separate GWSA from TWSA, a water balance equation was used. Third, the continuous GWSA was downscaled to 0.05° based on the GWR model. Finally, spatio-temporal properties of downscaled GWSA were investigated in the North China Plain (NCP), China's fastest-urbanizing area, from 2003 to 2022. The results of the downscaled GWSA were spatially compatible with GRACE-derived GWSA. The downscaled GWSA results are validated (R = 0.83) using in-situ groundwater level data. The total loss of GWSA in cities of the NCP fluctuated between 2003 and 2022, with the largest loss seen in Handan (-15.21 ± 7.25 mm/yr), Xingtai (-14.98 ± 7.25 mm/yr), and Shijiazhuang (-14.58 ± 7.25 mm/yr). The irrigated winter-wheat farming strategy is linked to greater groundwater depletion in several cities of NCP (e.g., Xingtai, Handan, Anyang, Hebi, Puyang, and Xinxiang). The study's high-resolution findings can help with understanding local groundwater depletion that takes agricultural water utilization and provide quantitative data for water management.

Characterization of Aquifer System and Groundwater Storage Change Due to South-to-North Water Diversion Project at Huairou Groundwater Reserve Site, Beijing, China, Using Geodetic and Hydrological Data

Groundwater overexploitation is a critical issue in the North China Plain (NCP), resulting in groundwater level decline and surface subsidence for the last half-century. This problem, however, has been greatly alleviated by the South-to-North Water Diversion (SNWD) Project since 2015. Monitoring of this process has been steadily improved in recent years using water level and geodetic observations. Here, we characterize the water storage change at the Huairou groundwater reserve site (HGRS) in Beijing due to the SNWD by combining Interferometric Synthetic Aperture Radar (InSAR) data of the Sentinel-1 satellites, continuous Global Positioning System (GPS) data, and well water level data observed during the same time. InSAR observations revealed subsidence up to ~400 mm in the Beijing plain but uplift at ~40 mm in the HGRS during 2015–2019, and more than 70% of the uplift occurred from October 2018 to January 2019. By integrating the most significant uplift deformation during October 2018 to January 2019 with water level observations at the same time, we estimated the storativity of the confined aquifer system at HGRS as 1.68–7.82×10−3, weighing in the correction for effective stress and surface deformation for various situations. Based on the estimated aquifer storativity and the observed water level change in the unconfined and confined aquifer, the recharged water storage for the confined and unconfined aquifers was estimated as 1.20–1.39×107 m3 and ~2.86×108 m3 from 6 October 2018 to 22 January 2019, respectively, which is about 4% and 91% of the surface water recharge through river channels in the same period due to the SNWD Project. Our study demonstrates that integration of geodetic and hydrological data can provide crucial information for the assessment of groundwater circulation and assistance of groundwater management.

Quantifying Water Consumption through the Satellite Estimation of Land Use/Land Cover and Groundwater Storage Changes in a Hyper-Arid Region of Egypt

One of the areas that show the most visible effects of human-induced land alterations is also the world’s most essential resource: water. Decision-makers in arid regions face considerable difficulties in providing and maintaining sustainable water resource management. However, developing appropriate and straightforward approaches for quantifying water use in arid/hyper-arid regions is still a formidable challenge. Meanwhile, a better knowledge of the effects of land use land cover (LULC) changes on natural resources and environmental systems is required. The purpose of this study was to quantify the water consumption in a hyper-arid region (New Valley, Egypt) using two different approaches—LULC based on optical remote sensing data and groundwater storage changes based on Gravity Recovery Climate Experiment (GRACE) satellite data—and to compare and contrast the quantitative results of the two approaches. The LULC of the study area was constructed from 1986 to 2021 to identify the land cover changes and investigate the primary water consumption patterns. The analysis of groundwater storage changes utilized two GRACE mascon solutions from 2002 to 2021 in New Valley. The results showed an increase in agricultural areas in New Valley’s oases. They also showed an increased in irrigation water usage and a continuous decrease in the groundwater storage of New Valley. The overall water usage in New Valley for domestic and irrigation was calculated as 18.62 km3 (0.93 km3/yr) based on the LULC estimates. Moreover, the groundwater storage changes of New Valley were extracted using GRACE and calculated to be 19.36 ± 7.96 km3 (0.97 ± 0.39 km3/yr). The results indicated that the water use calculated from LULC was consistent with the depletion in groundwater storage calculated by applying GRACE. This study provides an essential reference for regional sustainability and water resource management in arid/hyper-arid regions.

Whether Increasing Maize Planting Density Increases the Total Water Use Depends on Soil Water in the 0–60 cm Soil Layer in the North China Plain

Increasing planting density generally increases total water use by maize (Zea mays L.), but there are contrasting conclusions as well. To determine whether increasing planting density would increase total water use by maize, a 3-year field experiment was conducted in the North China Plain. In 2018, maize was planted at the four densities of 57,100, 66,700, 80,000, and 100,000 plants ha−1. In 2019 and 2020, another four planting densities of 27,800, 41,700, 66,700, and 111,100 plants ha−1 were selected. The results showed that increasing planting density increased leaf area index but decreased leaf stomatal conductance; maize grain yield reached the maximum at about 80,000 plants ha−1. At the VE-V6 and R3-R6 stage, soil water use occurred mainly in the 0–60 cm soil layer, and planting density showed no effect on total soil water use by maize. At the V6-R3 stage, when soil water in the 0–60 cm soil layer was sufficient to meet the evapotranspiration demand, soil water use occurred mainly in the 0–60 cm soil layer; increasing planting density did not increase total soil water use. When soil water in the 0–60 cm soil layer was insufficient and could not meet the demand of evapotranspiration, soil water use in the 60–100 cm soil layer increased greatly and kept rising with increased planting density, resulting in elevated total soil water use. Therefore, we conclude that the effect of planting density on water use by maize varies with soil water content in the 0–60 cm soil layer in the North China Plain.

Data Quality Assessment of Time-Variable Surface Microgravity Surveys in the Southeastern Tibetan Plateau

Ground-based time-variable gravimetry with high accuracy is an important approach in monitoring geodynamic processes. The uncertainty of instruments including scale factor (SF) and drift rate are the primary factors affect the quality of observation data. Differing from the conventional gravity adjustment procedure, this study adopted the modified Bayesian gravity adjustment (MBGA) method, which accounts for the nonlinear drift rate, and where the SF is considered as one of the hyperparameters estimated using Akaike’s Bayesian information criterion. Based on the terrestrial time-variable gravity datasets (2018–2020) from the southeastern Tibetan Plateau, errors caused by nonlinear drift rate and SF were processed quantitatively through analysis of the gravity difference (GD) residuals and the mutual difference of the GD. Additionally, cross validation from absolute gravity (AG) values was also applied. Results suggest that: (1) the drift rate of relavive instruments show nonlinear characteristics, and owing to their different spring features, the drift rate of CG-5 is much larger than that of LCR-G gravimeters; (2) the average bias between the original and optimized SF of the CG-5 gravimeters is approximately 169 ppm, while that of the LCR-G is no more than 63 ppm; (3) comparison of the differences in gravity values (GV) suggests that the uncertainty caused by the nonlinear drift rate is smaller than that attributable to SF. Overall, the novel approach adopted in this study was found effective in removing errors, and shown to be adaptive and robust for large-scale hybrid surface gravity campaign which providing high accuracy gravity data for the geoscience research.

Determination of Weak Terrestrial Water Storage Changes from GRACE in the Interior of the Tibetan Plateau

Time series of the Gravity Recovery and Climate Experiment (GRACE) satellite mission have been successfully used to reveal changes in terrestrial water storage (TWS) in many parts of the world. This has been hindered in the interior of the Tibetan Plateau since the derived TWS changes there are very sensitive to the selections of different available GRACE solutions, and filters to remove north-south-oriented (N-S) stripe features in the observations. This has resulted in controversial distributions of the TWS changes in previous studies. In this paper, we produce aggregated hydrology signals (AHS) of TWS changes from 2003 to 2009 in the Tibetan Plateau and test a large set of GRACE solution-filter combinations and mascon models to identify the best combination or mascon model whose filtered results match our AHS. We find that the application of a destriping filter is indispensable to remove correlated errors shown as N-S stripes. Three best-performing destriping filters are identified and, combined with two best-performing solutions, they represent the most reliable solution-filter combinations for determination of weak terrestrial water storage changes in the interior of the Tibetan Plateau from GRACE. In turn, more than 100 other tested solution-filter combinations and mascon solutions lead to very different distributions of the TWS changes inside and outside the plateau that partly disagree largely with the AHS. This is mainly attributed to less effective suppression of N-S stripe noises. Our results also show that the most effective destriping is performed within a maximum degree and order of 60 for GRACE spherical harmonic solutions. The results inside the plateau show one single anomaly in the TWS trend when additional smoothing with a 340-km-radius Gaussian filter is applied. We suggest using our identified best solution-filter combinations for the determination of TWS changes in the Tibetan Plateau and adjacent areas during the whole GRACE operation time span from 2002 to 2017 as well as the succeeding GRACE-FO mission.

Overview of terrestrial water storage changes over the Indus River Basin based on GRACE/GRACE-FO solutions

Water resources are under severe stress in the highly populated Indus River Basin due to the increased consumption of water across different sectors and climate change. Coping with these challenges, requires a clear understanding on hydrological processes and anthropogenic activities, and how these are influencing recharging and spatiotemporal availability of groundwater in the basin. The present study aims to investigate the natural and anthropogenic impact on Terrestrial Water Storage (TWS) over the Indus River Basin by using a series of statistical methods and the observation data from the Gravity Recovery and Climate Experiment (GRACE) and Follow-On (GRACE-FO). Our results show that (i) TWS Anomaly (TWSA) experienced a significant decrease from 2002 to 2020, particularly in the MUIP; (ii) the UIB showed a weak decreasing trend in TWSA as a result of the accelerated glacier melting; (iii) there was significant loss of groundwater (1.57 mm/month) caused by ineffective water management and over-exploitation; and (iv) assisted by favorable meteorological conditions, the precipitation presented a positive trend against the weakness of the Westerlies, which exerted the positive influence on TWSA.

The Different Spatial and Temporal Variability of Terrestrial Water Storage in Major Grain-Producing Regions of China

Irrigation is an important factor affecting the change of terrestrial water storage (TWS), especially in grain-producing areas. The Northeast China Plain (NECP), the Huang-Huai-Hai Plain (HHH) and the middle and lower reaches of the Yangtze River Basin Plain (YRB) are major grain-producing regions of China, with particular climate conditions, crops and irrigation schemes. However, there are few papers focusing on the different variation pattern of water storage between NECP, HHH and YRB. In this paper, the characteristics of terrestrial water storage anomaly (TWSA) and groundwater storage in the three regions mentioned above from 2003 to 2014 were analyzed, and the main reasons for water storage variations in the three regions were also discussed. The result shows that although effective irrigated areas increased in all three regions, TWSA only decreased in HHH and TWSA in the other two regions have shown an increasing trend. Spatially, the water storage deficit was more serious in middle and south NECP and HHH. In the three regions, water storage variations were impacted by meteorological condition and anthropogenic stress (e.g., irrigation). However, irrigation water consumption has a greater impact on water storage deficit in HHH than the other two regions, and water storage variation in YRB was mainly impacted by meteorological conditions. In this case, we suggest that the structure of agricultural planting in HHH should be adjusted to reduce the water consumption for irrigation.

Validation of GRACE and GRACE-FO Mascon Data for the Study of Polar Motion Excitation

In this study, we calculate the hydrological plus cryospheric excitation of polar motion (hydrological plus cryospheric angular momentum, HAM/CAM) using mascon solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We compare and evaluate HAM/CAM computed from GRACE and GRACE-FO mascon data provided by the Jet Propulsion Laboratory (JPL), the Center for Space Research (CSR), and the Goddard Space Flight Center (GSFC). A comparison with HAM obtained from the Land Surface Discharge Model is also provided. An analysis of HAM/CAM and HAM is performed for overall variability, trends, and seasonal and non-seasonal variations. The HAM/CAM and HAM estimates are validated using the geodetic residual time series (GAO), which is an estimation of the hydrological plus cryospheric signal in geodetically observed polar motion excitation. In general, all mascon datasets are found to be equally suitable for the determination of overall, seasonal, and non-seasonal HAM/CAM oscillations, but some differences in trends remain. The use of an ellipsoidal correction, implemented in the newest solution from CSR, does not noticeably affect the consistency between HAM/CAM and GAO. Analysis of the data from the first two years of the GRACE-FO mission indicates that the current accuracy of HAM/CAM from GRACE-FO mascon data meets expectations, and the root mean square deviation of HAM/CAM components are between 5 and 6 milliarcseconds. The findings from this study can be helpful in assessing the role of satellite gravimetry in polar motion studies and may contribute towards future improvements to GRACE-FO data processing.

Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.

Using GRACE Data to Study the Impact of Snow and Rainfall on Terrestrial Water Storage in Northeast China

Water resources are important for agricultural, industrial, and urban development. In this paper, we analyzed the influence of rainfall and snowfall on variations in terrestrial water storage (TWS) in Northeast China from Gravity Recovery and Climate Experiment (GRACE) gravity satellite data, GlobSnow snow water equivalent product, and ERA5-land monthly total precipitation, snowfall, and snow depth data. This study revealed the main composition and variation characteristics of TWS in Northeast China. We found that GRACE provided an effective method for monitoring large areas of stable seasonal snow cover and variations in TWS in Northeast China at both seasonal and interannual scales. On the seasonal scale, although summer rainfall was 10 times greater than winter snowfall, the terrestrial water storage in Northeast China peaked in winter, and summer rainfall brought about only a sub-peak, 1 month later than the maximum rainfall. On the interannual scale, TWS in Northeast China was controlled by rainfall. The correlation analysis results revealed that the annual fluctuations of TWS and rainfall in Northeast China appear to be influenced by ENSO (EI Niño–Southern Oscillation) events with a lag of 2–3 years. In addition, this study proposed a reconstruction model for the interannual variation in TWS in Northeast China from 2003 to 2016 on the basis of the contemporary terrestrial water storage and rainfall data.

Divergent Trends of Water Storage Observed via Gravity Satellite across Distinct Areas in China

Knowledge of the spatiotemporal variations of terrestrial water storage (TWS) is critical for the sustainable management of water resources in China. However, this knowledge has not been quantified and compared for the different climate types and underlying surface characteristics. Here, we present observational evidence for the spatiotemporal dynamics of water storage based on the products from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS) in China over 2003–2016. Our results were the following: (1) gravity satellite dataset showed divergent trends of TWS across distinct areas due to human factors and climate factors. The overall changing trend of water storage is that the north experiences a loss of water and the south gains in water, which aggravates the uneven spatial distribution of water resources in China. (2) In the eastern monsoon area, the depletion of water storage in North China (NC) was found to be mostly due to anthropogenic disturbance through groundwater pumping in plain areas. However, precipitation was shown to be a key driver for the increase of water storage in South China (SC). Increasing precipitation in SC was linked to atmospheric circulation enhancement and Pacific Ocean warming, meaning an unrecognized teleconnection between circulation anomalies and water storage. (3) At high altitudes in the west, the change of water storage was affected by the melting of ice and snow due to the rising temperatures, yet the topography determines the trend of water storage. We found that the mountainous terrain led to the loss of water storage in Tianshan Mountain (TSM), while the closed basin topography gathered the melted water in the interior of the Tibetan Plateau (ITP). This study highlights the impacts of the local climate and topography on terrestrial water storage, and has reference value for the government and the public to address the crisis of water resources in China.

Analysis on impacts of hydro-climatic changes and human activities on available water changes in Central Asia

Water resources in Central Asia are very scarce due to natural and anthropogenic impacts. Water shortages have been a major factor hampering the socio-economic development of Central Asia. Exploring internal interactions among climate change, human activities and terrestrial hydrological cycles will help to improve the management of water resources in Central Asia. In this paper, hydro-climatic and anthropogenic data for the period 2003-2016 from the Gravity Recovery and Climate Experiment (GRACE), the Global Land Data Assimilation System (GLDAS), the Climatic Research Unit (CRU) and the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to analyze the influence of natural factors and human activities on changes of available water (AWC). The terrestrial water storage derived from GRACE and GLDAS remarkably declined in 2008, due to a serious drought, but increased thereafter. The AWC positively responded to the vegetation index, evapotranspiration, potential evapotranspiration and air temperature at a lag of 0-1 month, but to precipitation at a lag of 2-3 months. Results of correlation analysis with a spatial square moving window indicated that forests, grasses, croplands and water areas presented significantly positive correlations with AWC, while barren areas and urban areas were negatively correlated with AWC. According to the Boruta algorithm and the Random Forest model, natural factors, namely precipitation, evapotranspiration and potential evapotranspiration, were major factors for AWC in the whole Central Asia. Human activities had direct and indirect impacts on AWC. With the development of society and economy, croplands and urban areas gradually increased, resulting in a rising demand for water withdrawals for agriculture irrigation and industry. The unreasonable utilization and exploitation of water resources led to vegetation degradation and ecosystem deterioration, which would worsen the shortage of water resources in arid regions of Central Asia.

Divergent Sensitivities of Spaceborne Solar-Induced Chlorophyll Fluorescence to Drought among Different Seasons and Regions

As a newly emerging satellite form of data, solar-induced chlorophyll fluorescence (SIF) provides a direct measurement of photosynthetic activity. The potential of SIF for drought assessment in different grassland ecosystems is not yet clear. In this study, the correlations between spaceborne SIF and nine drought indices were evaluated. Standardized precipitation evapotranspiration index (SPEI) at a 1, 3, 6, 9, 12 month scale, Palmer drought severity index (PDSI), soil moisture, temperature condition index (TCI), and vapor pressure deficit (VPD) were evaluated. The relationships between different grassland types and different seasons were compared, and the driving forces affecting the sensitivity of SIF to drought were explored. We found that the correlations between SIF and drought indices were different for temperate grasslands and alpine grasslands. The correlation coefficients between SIF and soil moisture were the highest (the mean value was 0.72 for temperate grasslands and 0.69 for alpine grasslands), followed by SPEI and PDSI at a three month scale, and the correlation coefficient between SIF and TCI was the lowest (the mean value was 0.38 for both temperate and alpine grasslands). Spaceborne SIF is more effective for drought monitoring during the peak period of the growing season (July and August). Temperature and radiation are important factors affecting the sensitivity of SIF to drought. The results from this study demonstrated the importance of SIF in drought monitoring especially for temperate grasslands in the peak growing season.

Groundwater Storage Change in the Jinsha River Basin from GRACE, Hydrologic Models, and In Situ Data

Groundwater plays a major role in the hydrological processes driven by climate change and human activities, particularly in upper mountainous basins. The Jinsha River Basin (JRB) is the uppermost region of the Yangtze River and the largest hydropower production region in China. With the construction of artificial cascade reservoirs increasing in this region, the annual and seasonal flows are changing and affecting the water cycles. Here, we first infer the groundwater storage changes (GWSC), accounting for sediment transport in JRB, by combining the Gravity Recovery and Climate Experiment mission, hydrologic models and in situ data. The results indicate: (1) the average estimation of the GWSC trend, accounting for sediment transport in JRB, is 0.76 ± 0.10 cm/year during the period 2003 to 2015, and the contribution of sediment transport accounts for 15%; (2) precipitation (P), evapotranspiration (ET), soil moisture change, GWSC, and land water storage changes (LWSC) show clear seasonal cycles; the interannual trends of LWSC and GWSC increase, but P, runoff (R), surface water storage change and SMC decrease, and ET remains basically unchanged; (3) the main contributor to the increase in LWSC in JRB is GWSC, and the increased GWSC may be dominated by human activities, such as cascade damming and climate variations (such as snow and glacier melt due to increased temperatures). This study can provide valuable information regarding JRB in China for understanding GWSC patterns and exploring their implications for regional water management.

Lessons to Be Learned: Groundwater Depletion in Chile’s Ligua and Petorca Watersheds through an Interdisciplinary Approach

Groundwater (GW) is the primary source of unfrozen freshwater on the planet and in many semi-arid areas, it is the only source of water available during low-water periods. In north-central Chile, there has been GW depletion as a result of semi-arid conditions and high water demand, which has unleashed major social conflicts, some due to drought and others due to agribusiness practices against the backdrop of a private water management model. The Ligua and Petorca watersheds in the Valparaíso Region were studied in order to analyze the influence of climatic and anthropogenic factors on aquifer depletion using an interdisciplinary approach that integrates hydroclimatic variables, remote sensing data techniques, and GW rights data to promote sustainable GW management. The Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) were calculated and the 2002–2017 land-use change was analyzed. It was shown that GW decreased significantly (in 75% of the wells) and that the hydrological drought was moderate and prolonged (longest drought in the last 36 years). The avocado-growing area in Ligua increased significantly—by 2623 ha—with respect to other agricultural areas (higher GW decrease), while in Petorca, it decreased by 128 ha. In addition, GW-rainfall correlations were low and GW rights were granted continuously despite the drought. The results confirmed that aquifer depletion was mostly influenced by human factors due to overexploitation by agriculture and a lack of water management.

A Climatic Perspective on the Impacts of Global Warming on Water Cycle of Cold Mountainous Catchments in the Tibetan Plateau: A Case Study in Yarlung Zangbo River Basin

Global warming has a profound influence on global and regional water cycles, especially in the cold mountainous area. However, detecting and quantifying such changes are still difficult because noise and variability in observed streamflow are relatively larger than the long-term trends. In this study, the impacts of global warming on the catchment water cycles in the Yarlung Zangbo River Basin (YZRB), one of most important catchments in south of the Tibetan Plateau, are quantified using a climatic approach based on the relationship between basin-scale groundwater storage and low flow at the annual time scale. By using a quantile regression method and flow recession analysis, changes in low flow regimes and basin-scale groundwater storage at the Nuxia hydrological station are quantified at the annual time scale during 1961–2000. Results show annual low flows (10th and 25th annual flows) of the YZRB have decreased significantly, while long-term annual precipitation, total streamflow, and high flows are statistically unchanged. Annual lowest seven-day flow shows a significantly downward trend (2.2 m3/s/a, p < 0.05) and its timing has advanced about 12 days (2.8 day/10a, p < 0.1) during the study period. Estimated annual basin-scale groundwater storage also shows a significant decreasing trend at a rate of 0.079 mm/a (p < 0.05) over the study period. Further analysis suggests that evaporation increase, decreased snow-fraction, and increased annual precipitation intensity induced by the rising temperature possibly are the drivers causing a significant decline in catchment low flow regimes and groundwater storage in the study area. This highlights that an increase in temperature has likely already caused significant changes in regional flow regimes in the high and cold mountainous regions, which has alarming consequences in regional ecological protection and sustainable water resources management.

Water Storage Monitoring in the Aral Sea and its Endorheic Basin from Multisatellite Data and a Hydrological Model

Inland water storage change is a fundamental part of the hydrologic cycle, which reflects the impact of climate change and anthropogenic activities on water resources. In this study, we used multisatellite data (from satellite altimetry, remote sensing, and the Gravity Recovery and Climate Experiment (GRACE)) to investigate water storage changes in the Aral Sea and its endorheic basin. The water storage depletion rate in the Aral Sea from calibrated hypsometric curves (CHCs) created by satellite altimetry and image data agrees with the GRACE-derived result using the Slepian space domain inverse method (SSDIM). Compared with the combined filtering method (CFM) and mascon solutions, the SSDIM was shown to be an effective method of reducing the GRACE leakage error and restoring the signal attenuation in the Aral Sea. Moreover, we used the WaterGAP global hydrology model (WGHM) to qualitatively analyze the variations in the water storage components. The results show that the groundwater in the Aral Sea affects the change in the interannual water storage, especially during the extreme dry and humid periods. However, from the long-term water storage trend, the decrease in the surface storage dominates the shrinking of the Aral Sea. In addition, more details of the water storage change pattern in the endorheic basin were revealed by the enhanced GRACE solution. Our findings accentuate the severe water storage states of the Aral Sea endorheic basin under the impact of climate change and human interventions.

Satellite Monitoring of Mass Changes and Ground Subsidence in Sudan’s Oil Fields Using GRACE and Sentinel-1 Data

Monitoring environmental hazards, owing to natural and anthropogenic causes, is an important issue, which requires proper data, models, and cross-validation of the results. The geodetic satellite missions, for example, the Gravity Recovery and Climate Experiment (GRACE) and Sentinel-1, are very useful in this respect. GRACE missions are dedicated to modeling the temporal variations of the Earth’s gravity field and mass transportation in the Earth’s surface, whereas Sentinel-1 collects synthetic aperture radar (SAR) data, which enables us to measure the ground movements accurately. Extraction of large volumes of water and oil decreases the reservoir pressure and form compaction and, consequently, land subsidence occurs, which can be analyzed by both GRACE and Sentinel-1 data. In this paper, large-scale groundwater storage (GWS) changes are studied using the GRACE monthly gravity field models together with different hydrological models over the major oil reservoirs in Sudan, that is, Heglig, Bamboo, Neem, Diffra, and Unity-area oil fields. Then, we correlate the results with the available oil wells production data for the period of 2003–2012. In addition, using the only freely available Sentinel-1 data, collected between November 2015 and April 2019, the ground surface deformation associated with this oil and water depletion is studied. Owing to the lack of terrestrial geodetic monitoring data in Sudan, the use of GRACE and Sentinel-1 satellite data is very valuable to monitor water and oil storage changes and their associated land subsidence over our region of interest. Our results show that there is a significant correlation between the GRACE-based GWS anomalies (ΔGWS) and extracted oil and water volumes. The trend of ΔGWS changes due to water and oil depletion ranged from –18.5 ± 6.3 to –6.2 ± 1.3 mm/year using the CSR GRACE monthly solutions and the best tested hydrological model in this study. Moreover, our Sentinel-1 SAR data analysis using the persistent scatterer interferometry (PSI) method shows a high rate of subsidence, that is, –24.5 ± 0.85, –23.8 ± 0.96, –14.2 ± 0.85, and –6 ± 0.88 mm/year over Heglig, Neem, Diffra, and Unity-area oil fields, respectively. The results of this study can help us to control the integrity and safety of operations and infrastructure in that region, as well as to study the groundwater/oil storage behavior.

Characterization of the hydro-geological regime of Yangtze River basin using remotely-sensed and modeled products

The hydrology of the Third Pole, Asia's freshwater tower, has shown considerable sensitivity to the impacts of climate change and human interventions, which affect the headwaters of many rivers that originate therein. For example, the Yangtze River has its basin (YRB) experiencing wetness of terrestrial water storage (TWS), whose rainfall seems to be the primary source as inferred from the previous studies. Consequently, it is crucial to understand the contributions of each TWS's sub-domain - i.e., groundwater (GWS); total water content (TWC) stored as soil moisture, ice/snow, and canopy; and the surface water (SWS) storages - on YRB's wetness. Hence, SWS, from altimetry and imagery satellites, and TWC, from Global Land Data Assimilation System, are inverted considering the same basis function as for TWS from the Gravity Recovery and Climate Experiment, which account for the differences in the resolutions inherent in each product. Furthermore, a "tie-in" signal approach is used to fit the temporal patterns of GWS, TWC, and SWS to TWS (i.e., the observations). Results show improvements in the reconstructed GWS series concerning standard deviation, correlation coefficient, and Nash-Sutcliffe efficiency of 22%, 27%, and 120%, respectively, regarding the use of the TWS-budget equation. The reconstructed time series of GWS, TWC, and SWS present an increase of 1.76, 2.69, and 0.14 mm per year (mm/yr) and that YRB loses water stored at its aquifers 55% of the time (regarding 2003-2016 period) based on the quantile function of storage (QFS). The QFS's slope shows that TWS has a fast and small storage potential w.r.t. GWS since inland waters and soil moisture reflect the dryness impacting TWS first. Despite the evidence of an increase of 19.05 mm/yr in annual precipitation, which seems to explain the bulk in TWS, further investigation to characterize controls on TWS memory within YRB is still necessary.

Mitigation of greenhouse gas emissions through optimized irrigation and nitrogen fertilization in intensively managed wheat-maize production

In the wheat-maize rotation cultivation system in northern China, excessive irrigation and over-fertilization have depleted groundwater and increased nitrogen (N) losses. These problems can be addressed by optimized N fertilization and water-saving irrigation. We evaluated the effects of these practices on greenhouse gas emissions (GHG), net profit, and soil carbon (C) sequestration. We conducted a field experiment with flood irrigation (FN0, 0 kg N ha^-1 yr^-1, FN600, 600 kg N ha^-1 yr^-1) and drip fertigation treatments (DN0, 0 kg N ha^-1 yr^-1; DN420, 420 kg N ha^-1 yr^-1; DN600, 600 kg N ha^-1 yr^-1) in 2015-2017. Compared with FN600, DN600 decreased direct GHGs (N₂O + CH₄) emissions by 21%, and increased the net GHG balance, GHG intensity, irrigation water-use efficiency (IWUE), and soil organic C content (ΔSOC) by 13%, 12%, 88%, and 89.8%, respectively. Higher costs in DN600 (for electricity, labour, polyethylene) led to a 33.8% lower net profit than in FN600. Compared with FN600, DN420 reduced N and irrigation water by 30% and 46%, respectively, which increased partial factor productivity and IWUE (by 49% and 94%, respectively), but DN420 did not affect GHG mitigation or net profit. Because lower profit is the key factor limiting the technical extension of fertigation, financial subsidies should be made available for farmers to install fertigation technology.

Seasonal and Interannual Variations in China’s Groundwater Based on GRACE Data and Multisource Hydrological Models

In this study, we used in situ measurements for the first time to analyze the applicability and effectiveness of evaluating groundwater storage (GWS) changes across China using Gravity Recovery and Climate Experiment (GRACE) satellite products and hydrological data derived from the WaterGap Global Hydrological Model (WGHM), Global Land Data Assimilation System (GLDAS) and eartH2Observe (E2O). The results show that the GWS derived from GRACE JPL Mascons products combined with GLDAS Noah V2.1 data most accurately reflect the overall distribution of GWS changes in China and the correlation coefficient between the in situ measurements reaches 0.538. The empirical orthogonal function decomposition for GWS indicates clear interannual variation and seasonal variation in China. The trends of China’s GWS changes showed a clear regional characteristic from 2003 to 2016. The GWS in the northeast, central-south, and western junction of Xinjiang-Qinghai-Tibet had increased significantly, and the North China Plain (NCP) had a severe decline. The correlation coefficient between the annual trends of precipitation and GWS was 0.57, and it reached 0.73 when four provinces (Beijing, Tianjin, Shanxi, Hebei) that are wholly or partially located in the NCP were excluded. The seasonal variability of GWS in China was obvious and the volatilities in Jiangxi, Hunan and Fujian provinces were the highest, reaching 6.39 cm, 6.33 cm and 5.20 cm, respectively. The empirical orthogonal function decomposition for GWS and precipitation over China indicated seasonal consistency with a correlation coefficient of 0.76. The awareness of areas with significant depletion and large seasonal fluctuation of GWS help adaptations to manage local GWS situation.

Swine farming elevated the proliferation of Acinetobacter with the prevalence of antibiotic resistance genes in the groundwater

Swine farming generates a large amount of wastes containing various contaminants, resulting in environmental contamination and human health problems. Here we investigated the contamination profiles of antibiotics and antibiotic resistance genes (ARGs) as well as microbial community in groundwater of the two villages with or without swine farms, and then assessed the human exposure risks of antibiotics, ARGs and indicator bacteria through drinking groundwater. The results showed that swine farming could lead to enhanced concentration levels of various veterinary antibiotics and ARGs in the groundwater in comparison to the reference village without swine farming. The microbial diversity of groundwater was significantly decreased with predominance of conditional pathogens Acinetobacter (up to 90%) in some wells of the swine farming village. Meanwhile, the abundance of Acinetobacter was significantly correlated to bacterial abundance, ARGs and integrons. The local residents could ingest various antibiotic residues and ARGs as well as pathogens, with daily intake of Acinetobacter up to approximately 10 billion CFU/resident through drinking groundwater contaminated by swine farming. The findings from this study suggest potential health risks of changing gut microbial community and resistome by drinking contaminated groundwater.

Spatio-Temporal Variations in Groundwater Revealed by GRACE and Its Driving Factors in the Huang-Huai-Hai Plain, China

The Huang-Huai-Hai (3H) Plain is the major crop-producing region in China. Due to the long-term overexploitation of groundwater for irrigation, the groundwater funnel is constantly expanding and the scarcity of water resources is prominent in this region. In this study, Gravity Recovery and Climate Experiment (GRACE) and hydrological models were used to estimate the spatial-temporal changes of groundwater storage (GWS) and the driving factors of GWS variations were discussed in the 3H Plain. The results showed that GRACE-based GWS was depleted at a rate of -1.14 ± 0.89 cm/y in the 3H Plain during 2003 to 2015. The maximum negative anomaly occurred in spring due to agricultural irrigation activities. Spatially, the loss of GWS in the Haihe River Basin is more serious than that in the Huaihe River Basin, presenting a decreasing trend from south to north. Conversely, the blue water footprint (WF_blue) of wheat exhibited an increasing trend from south to north. During the drought years of 2006, 2013, and 2014, more groundwater was extracted to offset the surface water shortage, leading to an accelerated decline in GWS. This study demonstrated that GWS depletion in the 3H Plain is well explained by reduced precipitation and groundwater abstraction due to anthropogenic irrigation activities.

Evaluation of Evapotranspiration for Exorheic Catchments of China during the GRACE Era: From a Water Balance Perspective

Evapotranspiration (ET) is usually difficult to estimate at the regional scale due to scarce direct measurements. This study uses the water balance equation to calculate the regional ET with observations of precipitation, runoff, and terrestrial water storage changes (TWSC) in nine exorheic catchments of China. We compared the regional ET estimates from a water balance perspective with and without considering TWSC (ETWB: ET estimates with considering TWSC, and ETPQ: ET estimates from precipitation minus runoff without considering TWSC). Results show that the regional annual ET ranges from 417.7 mm/yr to 831.5 mm/yr in the nine exorheic catchments based on the water balance equation. The impact of ignoring TWSC on calculating ET is notable, as the root mean square errors (RMSEs) of annual ET between ETWB and ETPQ range from 12.0–105.8 mm/yr (2.6–12.7% in corresponding annual ET) among the exorheic catchments. We also compared the estimated regional ET with other ET products. Different precipitation products are assessed to explain the inconsistency between different ET products and regional ET from a water balance perspective. The RMSEs between ET estimates from Gravity Recovery and Climate Experiment (GRACE) and ET from land surface models can be reduced if the deviation of precipitation forcing data is considered. ET estimates from Global Land Evaporation Amsterdam Model (GLEAM) can be improved by reducing the uncertainty of precipitation forcing data in three semiarid catchments. This study emphasizes the importance of considering TWSC when calculating the regional ET using a water balance equation and provides more accurate ET estimates to help improve modeled ET results.

Greening Trends of Southern China Confirmed by GRACE

As reported by the National Aeronautics and Space Administration (NASA), the world has been greening over the last two decades, with the highest greening occurring in China and India. The increasing vegetation will increase plant tissue accumulation and water storage capacity, and all of these variations will cause mass change. In this study, we found that the mass change related to greening in Southern China could be confirmed by Gravity Recovery and Climate Experiment (GRACE) observations. The mean mass change rate detected by GRACE is 6.7 ± 0.8 mm/yr in equivalent water height during 2003–2016 in our study region. This is consistent with the sum of vegetation tissue, soil water and groundwater change calculated using multi-source data. The vegetation accumulation is approximately 3.8 ± 1.3 mm/yr, which is the major contribution to region mass change. We also found that the change of water storage capacity related to vegetation can be detected by GRACE.

Human-Induced and Climate-Driven Contributions to Water Storage Variations in the Haihe River Basin, China

Terrestrial water storage (TWS) can be influenced by both climate change and anthropogenic activities. While the Gravity Recovery and Climate Experiment (GRACE) satellites have provided a global view on long-term trends in TWS, our ability to disentangle human impacts from natural climate variability remains limited. Here we present a quantitative method to isolate these two contributions with reconstructed climate-driven TWS anomalies (TWSA) based on long-term precipitation data. Using the Haihe River Basin (HRB) as a case study, we find a higher human-induced water depletion rate (−12.87 ± 1.07 mm/yr) compared to the original negative trend observed by GRACE alone for the period of 2003–2013, accounting for a positive climate-driven TWSA trend (+4.31 ± 0.72 mm/yr). We show that previous approaches (e.g., relying on land surface models) provide lower estimates of the climate-driven trend, and thus likely underestimated the human-induced trend. The isolation method presented in this study will help to interpret observed long-term TWS changes and assess regional anthropogenic impacts on water resources.

Analysis of Groundwater and Total Water Storage Changes in Poland Using GRACE Observations, In-situ Data, and Various Assimilation and Climate Models

The Gravity Recovery and Climate Experiment (GRACE) observations have provided global observations of total water storage (TWS) changes at monthly intervals for over 15 years, which can be useful for estimating changes in GWS after extracting other water storage components. In this study, we analyzed the TWS and groundwater storage (GWS) variations of the main Polish basins, the Vistula and the Odra, using GRACE observations, in-situ data, GLDAS (Global Land Data Assimilation System) hydrological models, and CMIP5 (the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 5) climate data. The research was conducted for the period between September 2006 and October 2015. The TWS data were taken directly from GRACE measurements and also computed from four GLDAS (VIC, CLM, MOSAIC, and NOAH) and six CMIP5 (FGOALS-g2, GFDL-ESM2G, GISS-E2-H, inmcm4, MIROC5, and MPI-ESM-LR) models. The GWS data were obtained by subtracting the model TWS from the GRACE TWS. The resulting GWS values were compared with in-situ well measurements calibrated using porosity coefficients. For each time series, the trends, spectra, amplitudes, and seasonal components were computed and analyzed. The results suggest that in Poland there has been generally no major TWS or GWS depletion. Our results indicate that when comparing TWS values, better compliance with GRACE data was obtained for GLDAS than for CMIP5 models. However, the GWS analysis showed better consistency of climate models with the well results. The results can contribute toward selection of an appropriate model that, in combination with global GRACE observations, would provide information on groundwater changes in regions with limited or inaccurate ground measurements.

Insight into the preparation of the 2016 MS6.4 Menyuan earthquake from terrestrial gravimetry-derived crustal density changes

Geophysical processes of the pre-earthquake activities are difficult to be determined since less pre-seismic signal is observed directly. Crustal density changes derived from the periodical terrestrial gravimetry may provide meaningful deep information for the pre-earthquake cue. In this study, the crustal density changes following the 2016 M_S6.4 Menyuan earthquake are estimated using ground-based gravity-change data from 2011 to 2015 in the northeastern Tibetan Plateau. The results show that negative density changes dominate the region between the South Longshou Mountain fault and the Daban Mountain fault except the southeast of this region (the seismic region) during 2011–2012. Positive density changes appeared in the middle crust near the epicenter during 2012–2013 and in the upper and middle crust east of the epicenter approximately 1.5 years before the earthquake (2013–2014), and then negative density changes appeared under and northeast of the epicenter approximately four months before the earthquake (2014–2015). The state of the crustal materials near the seismic region changed from convergence to expansion, in turn, indicating that the characteristics of the deep seismogenic process was corresponding to Amos Nur’s 1974 dilatancy-fluid diffusion model.

Sustainable and resilient management scenarios for groundwater resources of the Red Sea coastal aquifers

Gravity Recovery and Climate Experiment (GRACE) data, along with readily available remote sensing datasets and the outputs of land-surface and climate models, are used to monitor spatiotemporal variabilities in the groundwater resources of the Red Sea Coastal Aquifer (RSCA) system in Saudi Arabia; to investigate their responses to climate projections; and to provide sustainable and resilient management scenarios for these resources. Our results indicate that, during the investigated period (April 2002-June 2017), the RSCA received an average annual recharge of 3.16 ± 0.52 km³. Recharge events (~16% of rainfall) are related to the observed increase in rainfall rates. Analysis of climate models' outputs over the RSCA indicates an increase in the median annual rainfall (17-31%) and recharge rates (2.7-4.9%) by the end of the 21st century. To ensure sustainable management and utilization of RSCA's water resources, groundwater extraction should be located in the southern and central parts of the aquifer, and groundwater extraction rates should be kept lower than 2.0 km³/yr. Findings highlight the importance of GRACE data as a unique, cost-effective, and decisive tool in monitoring the health of coastal and inland aquifer systems across the globe.

Detecting Winter Wheat Irrigation Signals Using SMAP Gridded Soil Moisture Data

The southern part of the Hebei Province is one of China’s major crop-producing regions. Due to the continuous decline in groundwater level, agricultural water use is facing significant challenges. Precision agricultural irrigation management is undoubtedly an effective way to solve this problem. Based on multisource data (time series soil moisture active passive (SMAP) data, Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and evapotranspiration (ET), and meteorological station precipitation), the irrigation signal (frequency, timing and area) is detected in the southern part of the Hebei Province. The SMAP data was processed by the 5-point moving average method to reduce the error caused by the uncertainty of the microwave data derived SM. Irrigation signals can be detected by removing the precipitation effect and setting the SM change threshold. Based on the validation results, the overall accuracy of the irrigation signal detection is 77.08%. Simultaneously, considering the spatial resolution limitation of SMAP pixels, the SMAP irrigation area was downscaled using the winter wheat area extracted from MODIS NDVI. The analytical results of 55 winter wheat samples (5 samples in a group) showed that winter wheat covered by one SMAP pixel had an 82.72% growth consistency in surface water irrigation period, which can indicate a downscaling effectiveness. According to the above statistical analysis, this paper considers that although the spatial resolution of SMAP data is insufficient, it can reflect the change of SM more sensitively. In areas where the crop pattern is relatively uniform, the introduction of high-resolution crop pattern distribution can be used not only to detect irrigation signals but also to validate the effectiveness of irrigation signal detection by analyzing crop growth consistency. Therefore, the downscaling results can indicate the true winter wheat irrigation timing, area and frequency in the study area.

Groundwater Depletion Estimated from GRACE: A Challenge of Sustainable Development in an Arid Region of Central Asia

Under climate change and increasing water demands, groundwater depletion has become regional and global threats for water security, which is an indispensable target to achieving sustainable developments of human society and ecosystems, especially in arid and semiarid regions where groundwater is a major water source. In this study, groundwater depletion of 2003–2016 over Xinjiang in China, a typical arid region of Central Asia, is assessed using the gravity recovery and climate experiment (GRACE) satellite and the global land data assimilation system (GLDAS) datasets. In the transition of a warm-dry to a warm-wet climate in Xinjiang, increases in precipitation, soil moisture and snow water equivalent are detected, while GRACE-based groundwater storage anomalies (GWSA) exhibit significant decreasing trends with rates between-3.61 ± 0.85 mm/a of CSR-GWSA and −3.10 ± 0.91 mm/a of JPL-GWSA. Groundwater depletion is more severe in autumn and winter. The decreases in GRACE-based GWSA are in a good agreement with the groundwater statistics collected from local authorities. However, at the same time, groundwater abstraction in Xinjiang doubled, and the water supplies get more dependent on groundwater. The magnitude of groundwater depletion is about that of annual groundwater abstraction, suggesting that scientific exploitation of groundwater is the key to ensure the sustainability of freshwater withdrawals and supplies. Furthermore, GWSA changes can be well estimated by the partial least square regression (PLSR) method based on inputs of climate data. Therefore, GRACE observations provide a feasible approach for local policy makers to monitor and forecast groundwater changes to control groundwater depletion.

Comparisons of WUE in twelve genotypes of winter wheat and the relationship between δ 13C and WUE

Twelve winter wheat (Triticum aestivum) genotypes were examined for differences in grain yield, water use efficiency (WUE), and stable carbon isotope composition (δ13C) in flag leaves. The plants were subjected to rain-fed treatment and supplemental irrigation at the jointing and anthesis stages, during the 2015–2016 and 2016–2017 winter wheat growing seasons. The relationships between δ13C with grain yield and WUE were analyzed under two different water environments. The results indicated that there were significant differences in δ13C, grain yield, and WUE among wheat genotypes both under rain-fed and supplemental irrigation conditions. The δ13C values increased with grain-filling proceeding, the δ13C being lower under supplemental irrigation treatment than that under rain-fed treatment. The relationships between the average of δ13C with grain yield and WUE were significantly positive during three measurement periods (R2 = 0.5785 − 0.8258), whether under rain-fed or irrigation environments. This suggests that δ13C might be associated with the grain yield and WUE in winter wheat under rain-fed and supplemental irrigation conditions in the climate region of the northwest Huang-Huai-Hai Plain of China.

Analysis of the Spatiotemporal Changes of Ice Sheet Mass and Driving Factors in Greenland

With the warming of the global climate, the mass loss of the Greenland ice sheet is intensifying, having a profound impact on the rising of the global sea level. Here, we used Gravity Recovery and Climate Experiment (GRACE) RL06 data to retrieve the time series variations of ice sheet mass in Greenland from January 2003 to December 2015. Meanwhile, the spatial changes of ice sheet mass and its relationship with land surface temperature are studied by means of Theil–Sen median trend analysis, the Mann–Kendall (MK) test, empirical orthogonal function (EOF) analysis, and wavelet transform analysis. The results showed: (1) in terms of time, we found that the total mass of ice sheet decreases steadily at a speed of −195 ± 21 Gt/yr and an acceleration of −11 ± 2 Gt/yr2 from 2003 to 2015. This mass loss was relatively stable in the two years after 2012, and then continued a decreasing trend; (2) in terms of space, the mass loss areas of the Greenland ice sheet mainly concentrates in the southeastern, southwestern, and northwestern regions, and the southeastern region mass losses have a maximum rate of more than 27 cm/yr (equivalent water height), while the northeastern region show a minimum rate of less than 3 cm/yr, showing significant changes as a whole. In addition, using spatial distribution and the time coefficients of the first two models obtained by EOF decomposition, ice sheet quality in the southeastern and northwestern regions of Greenland show different significant changes in different periods from 2003 to 2015, while the other regions showed relatively stable changes; (3) in terms of driving factors temperature, there is an anti-phase relationship between ice sheet mass change and land surface temperature by the mean XWT-based semblance value of −0.34 in a significant oscillation period variation of 12 months. Meanwhile, XWT-based semblance values have the largest relative change in 2005 and 2012, and the smallest relative change in 2009 and 2010, indicating that the influence of land surface temperature on ice sheet mass significantly varies in different years.

Hydro-climatic changes and their impacts on vegetation in Xinjiang, Central Asia

Central Asia is one of the most arid regions in the world. Xinjiang is the core area of the arid region in Central Asia. Climate warming and hydrological changes might affect the vegetation dynamics in the region; however there has been no systematic evaluation of the hydro-climatic changes and their impacts on vegetation in Xinjiang. In this study, the vegetation growth and its response to hydro-climatic changes from 2003 to 2013 were analyzed based on multiple satellite observations. It was found that precipitation increased, with fluctuations, at a rate of 12.07 mm/decade, and evapotranspiration decreased, also with fluctuations, at a rate of -14.79 mm/decade. The change in total water storage, derived from the Gravity Recovery and Climate Experiment satellite, displayed an increasing trend, with a rate of increase of 112.91 mm/decade. The changes in the Global Land Data Assimilation System-derived soil moisture and groundwater estimated by the water budget presented a slight increasing trend from 2003 to 2013. The total water storage, soil moisture, and groundwater all significantly increased after 2008, and the increases in soil moisture and groundwater had positive effects on the increasing total water storage in Xinjiang. There were more obvious time lags in the response of changes in total water storage to precipitation than for the changes in soil moisture. The changes in the normalized difference vegetation index from 2003 to 2013 indicated a slight greening, and the accumulated normalized difference vegetation index anomalies also increased sharply after 2008. There were significant increases in the Tianshan Mountains, Altay Mountains, and around the Tarim Basin, especially along the Tarim River. The results suggested that the changes in total water storage and soil moisture were regarded as better indicators of the vegetation dynamics than other hydro-climatic variables in Xinjiang. Climate warming has led to accelerated glacier shrinkage and snow melt, and the increased runoff is likely to lead to more infiltration of surface water into the soil and ground, resulting in increased total water storage.

Correlation Analysis Between Groundwater Decline Trend and Human-Induced Factors in Bashang Region

In Northern China, many regions and cities are located in semi-arid regions, and groundwater is even the only source of water to support human survival and social development. Affected by human activities, the Bashang (BS) region (including Zhangjiakou City and part of Xilin Gol League) have showed a significant decline in groundwater levels in recent years. However, in the BS region, the causes for the decline in groundwater level were not clear. In this study, we used time series of multi-source data Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) to analyze vegetation and groundwater changes based on linear regression models. The variation trends of NDVI (Normalized Difference Vegetation Index, derived from MODIS) and GWSA (groundwater storage anomaly, derived from GRACE and GLDAS) indicated the increasingly better vegetation in the agriculture planting areas, partially degraded vegetation in the grassland, and the declining groundwater level in the whole study region. In order to assess the impact of human-induced factors on vegetation and groundwater, the R U E s e a s o n a l calculation model was proposed based on RUE (rain use efficiency) in this study. The R U E s e a s o n a l calculation results showed that human-induced factors promoted the growth of vegetation in agricultural areas and accelerated the consumption of groundwater. In addition, we also obtained temporal and spatial distributions of human activities-affected regions. The area affected by human-induced factors in the south-central study area increased, which accelerated the decline in groundwater levels. From bulletin data, we found that the increasing tourists and vegetable production are respectively the most important factors for the increased consumption of urban water and agricultural water. Based on multi-source data, the influences of various human-induced factors on the ecological environment were explored and the area affected by human-induced factors was estimated. The results provide the valuable guidance for water resource management departments. In the BS region, it is necessary to regulate agricultural water use and strengthen residential water management.

Combination Analysis of Future Polar-Type Gravity Mission and GRACE Follow-On

Thanks to the unprecedented success of Gravity Recovery and Climate Experiment (GRACE), its successive mission GRACE Follow-On (GFO) has been in orbit since May 2018 to continue measuring the Earth’s mass transport. In order to possibly enhance GFO in terms of mass transport estimates, four orbit configurations of future polar-type gravity mission (FPG) (with the same payload accuracy and orbit parameters as GRACE, but differing in orbit inclination) are investigated by full-scale simulations in both standalone and jointly with GFO. The results demonstrate that the retrograde orbit modes used in FPG are generally superior to prograde in terms of gravity field estimation in the case of a joint GFO configuration. Considering the FPG’s independent capability, the orbit configurations with 89- and 91-degree inclinations (namely FPG-89 and FPG-91) are further analyzed by joint GFO monthly gravity field models over the period of one-year. Our analyses show that the FPG-91 basically outperforms the FPG-89 in mass change estimates, especially at the medium- and low-latitude regions. Compared to GFO & FPG-89, about 22% noise reduction over the ocean area and 17% over land areas are achieved by the GFO & FPG-91 combined model. Therefore, the FPG-91 is worthy to be recommended for the further orbit design of FPGs.

Drought and Flood Monitoring of the Liao River Basin in Northeast China Using Extended GRACE Data

In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably.