Monitoring Groundwater Storage Changes Using the Gravity Recovery and Climate Experiment (GRACE) Satellite Mission: A Review

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.

Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute 0.5∘ standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003-2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections.

Long-term spatiotemporal dynamics of groundwater storage in the data-scarce region: Tana sub-basin, Ethiopia

Imprudent extraction of groundwater tends to undue stress and portends its sustainability. Spatiotemporal analysis of groundwater storage anomaly (GWSA) is imperative for the judicious use, management, and sustainable development of a region. This study aimed to examine the changes in groundwater storage over the past 20 years in the Tana sub-basin using Gravity Recovery and Climate Experiment (GRACE) assimilated into Global Land Data Assimilation Systems (GLDAS). Validation analysis was carried out to evaluate the accuracy of GWSA against anomalies of Lake Tana water level, precipitation, and in-situ groundwater level. Modified Mann-Kendal test and Sen's slope estimator were applied for trend analysis of the GWSA. The results exhibited that GWSA strongly correlated (Pearson's correlation coefficient, R ranges from 0.75 to 0.96) with the three validation above variables, which elucidated in general, credible GWSA estimation. The net annual GWSA curve showed a non-significant (p > 0.05) decreasing trend from 2003 to 2012. However, years including 2005, 2006, and 2009 were drought periods, which caused 0.49 billion cubic meters (BCM) groundwater loss. In the entire study period (2003-2022), on the other hand, the net annual GWSA revealed a significant increasing trend (p < 0.05) with a rate of 0.333 cm/year. Generally, the Tana sub-basin was nurtured with a net 4.87 BCM groundwater gain in the study period. The most sensitive parts of the study area to large fluctuations of groundwater storage were mainly the nearby southern and eastern directions of Lake Tana.

Machine Learning as a Strategic Tool for Helping Cocoa Farmers in Côte D'Ivoire

Machine learning can be used for social good. The employment of artificial intelligence in smart agriculture has many benefits for the environment: it helps small farmers (at a local scale) and policymakers and cooperatives (at regional scale) to take valid and coordinated countermeasures to combat climate change. This article discusses how artificial intelligence in agriculture can help to reduce costs, especially in developing countries such as Côte d'Ivoire, employing only low-cost or open-source tools, from hardware to software and open data. We developed machine learning models for two tasks: the first is improving agricultural farming cultivation, and the second is water management. For the first task, we used deep neural networks (YOLOv5m) to detect healthy plants and pods of cocoa and damaged ones only using mobile phone images. The results confirm it is possible to distinguish well the healthy from damaged ones. For actions at a larger scale, the second task proposes the analysis of remote sensors, coming from the GRACE NASA Mission and ERA5, produced by the Copernicus climate change service. A new deep neural network architecture (CIWA-net) is proposed with a U-Net-like architecture, aiming to forecast the total water storage anomalies. The model quality is compared to a vanilla convolutional neural network.

Evaluating the Hydrological Components Contributions to Terrestrial Water Storage Changes in Inner Mongolia with Multiple Datasets

In this study, multiple remote sensing data were used to quantitatively evaluate the contributions of surface water, soil moisture and groundwater to terrestrial water storage (TWS) changes in five groundwater resources zones of Inner Mongolia (GW_I, GW_II, GW_III, GW_IV and GW_V), China. The results showed that TWS increased at the rate of 2.14 mm/a for GW_I, while it decreased at the rate of 4.62 mm/a, 5.89 mm/a, 2.79 mm/a and 2.62 mm/a for GW_II, GW_III, GW_IV and GW_V during 2003-2021. Inner Mongolia experienced a widespread soil moisture increase with the rate of 4.17 mm/a, 2.13 mm/a, 1.20 mm/a, 0.25 mm/a and 1.36 mm/a for the five regions, respectively. Significant decreases were detected for regional groundwater storage (GWS) with the rate of 2.21 mm/a, 6.76 mm/a, 6.87 mm/a, 3.01 mm/a, and 4.14 mm/a, respectively. Soil moisture was the major contributor to TWS changes in GW_I, which accounted 58% of the total TWS changes. Groundwater was the greatest contributor to TWS changes in other four regions, especially GWS changes, which accounted for 76% TWS changes in GW_IV. In addition, this study found that the role of surface water was notable for calculating regional GWS changes.

Remote sensing-based monitoring and evaluation of the basin-wise dynamics of terrestrial water and groundwater storage fluctuations

The recent dynamics of terrestrial water storage (TWS) and groundwater storage (GWS) fluctuations were investigated based on the Gravity Recovery And Climate Experiment (GRACE) observations over 25 basins of Türkiye. Coarse-resolution GRACE estimates were downscaled based on the Random Forest algorithm. The impacts of precipitation (P) and evapotranspiration (ET) on the variations of water storage were also assessed. The findings demonstrated good performance for the RF model in simulating finer resolution estimates of TWS. The results indicated a diminishing trend of TWS and its hydrologic components over all the basins from 2003 to 2020. The Doğu Akdeniz Basin with the annually decreasing TWS and GWS of [Formula: see text] and [Formula: see text] was the most critical basin of Türkiye. The least storage loss was observed in the Batı Karadeniz Basin with the annual TWS and GWS loss of [Formula: see text] and [Formula: see text], respectively. Based on the results, Türkiye has lost, on average, an estimated [Formula: see text] and [Formula: see text] of its TWS and GWS, respectively, which are equivalent to the total storage loss of [Formula: see text] and [Formula: see text] of TWS and GWS during the last 18 years. The results also indicated that P and ET interact differently with the variations of TWS and GWS. The net water flux was revealed to be partially correlated with the total water storage fluctuations, suggesting the governing role of other deriving forces particularly the anthropogenic factors in the spatiotemporal variations of Türkiye's water storage; therefore, a sector-specific analysis of the water storage variations is crucial for the country, particularly by concentrating more on the dynamics of GWS.

Integrated Management and Environmental Impact Assessment of Sustainable Groundwater-Dependent Development in Toshka District, Egypt

Egypt has recently inaugurated a mega development project aiming to alleviate the overpopulation along the Nile River and to meet the looming food gap. Toshka is a promising area where groundwater-dependent activities are being expanded adjacent to Lake Nasser. Thus, it is of utmost importance to provide a sustainable development approach and to assess the resulting environmental implications. Accordingly, a coupled groundwater flow and transport model was invoked. The generated model was successfully calibrated for the observed water levels and salinity. The proposed exploitation regime of 102 wells each pumping 1000 m3/day was simulated for a 100-year test period. The maximum resulting drawdown was about 25 m, compatible with the advocated sustainable restriction limit. Climate change (CC) impacts of reducing the lake’s storage and increasing the crops’ water requirements were investigated. The lake’s water level fluctuations were a key factor in the aquifer hydraulics and flow direction. The drawdown breakthrough considering the CC catastrophic scenario (RCP8.5) has increased by about 20%. The developed solute transport model was utilized to simulate the salinity spatial distribution and the lateral movement of leaking pollutants from the underway activities. Cultivation activities were found feasible up to 80 km away from the lake border where salinity does not exceed 2000 ppm. Yet, a protection strip of not less than 4.8, 6.0, and 7.2 km according to the lake operating condition is inevitable to ensure that pollutants do not intrude into the lake. These findings will assist the decision-makers in scheming environmental impact assessment criteria for sustainable development.

Using GRACE to Detect Groundwater Variation in North China Plain after South-North Water Diversion

The gravity recovery and climate experiment (GRACE) and its Follow-On mission provide a versatile tool for monitoring groundwater depletion in North China Plain (NCP). However, intermittent data gaps and inherent coarse spatial resolution have restricted the continuous detection of regional groundwater storage anomaly (GWSA) after 2014, the period of interest during the implementation of the south-to-north water diversion middle route project (SNWDP). Here, we investigated the spatiotemporal changes of GWSA in the NCP during 2004 to 2020 based on continuous downscaled GRACE data. First, we derived the continuous terrestrial water storage anomaly from six GRACE and Follow-On solutions (i.e., spherical harmonics (SH) and mass concentration [mascon] solutions). Second, we employed a long short-term memory (LSTM) model and water balance equation to downscale GWSA (i.e., 0.25° × 0.25°). Lastly, we investigated its spatiotemporal characteristics before (2004 to 2014) and after (2015 to 2020) the SNWDP operation. We show the applicability of the continuous downscaled GWSA to capture the characteristics of in situ measurements. The GWSA detects groundwater depletion at a significant (p < 0.05) rate of -17.09 ± 1.80 (SH) and -17.87 ± 1.65 (mascon) mm/a during 2004 to 2014, but a recovering trend of 7.18 ± 3.98 (SH) and 8.23 ± 4.99 (mascon) during 2015 to 2018. The subsequent groundwater extraction and precipitation reduction from 2019 to 2020, resulted in the decreasing trend of GWSA from 2015 to 2020, which is -19.11 ± 8.75 (SH) and -19.72 ± 9.08 mm/a (mascon), respectively. Spatially, the overall depletion trends become nonsignificant along the canals of SNWDP compared to the period 2004 to 2014, and groundwater recovering with trends <6 mm/a near Beijing and Tianjin are detected by the mascon solution during 2015 to 2020.

Satellite-based estimates of groundwater storage depletion over Egypt

An arid climate accompanied by a freshwater shortage plagued Egypt. It has resorted to groundwater reserves to meet the increasing water demands. Fossil aquifers were lately adopted as the sole water source to provide the irrigation water requirements of the ongoing reclamation activities in barren areas. Yet, the scarcity of measurements regarding the changes in the aquifers' storage poses a great challenge to such sustainable resource management. In this context, the Gravity Recovery and Climate Experiment (GRACE) mission enables a novel consistent approach to deriving aquifers' storage changes. In this study, the GRACE monthly solutions during the period 2003-2021 were utilized to estimate alterations in terrestrial water storage (TWS) throughout Egypt. Changes in groundwater storage (GWS) were inferred by subtracting soil water content, derived from the GLDAS-NOAH hydrological model, from the retrieved TWS. The secular trends in TWS and GWS were obtained using the linear least square method, while the non-parametric technique (Mann-Kendall's tau) was applied to check the trend significance. The derived changes in GWS showed that all aquifers are undergoing a significant loss rate in their storage. The average depletion rate over the Sinai Peninsula was estimated at 0.64 ± 0.03 cm/year, while the depletion rate over the Nile delta aquifer was 0.32 ± 0.03 cm/year. During the investigated period (2003-2021), the extracted groundwater quantity from the Nubian aquifer in the Western Desert is estimated at nearly 7.25 km³. The storage loss from the Moghra aquifer has significantly increased from 32 Mm³/year (2003-2009) to 262 Mm³/year (2015-2021). This reflects the aquifer exposure for extensive water pumping to irrigate newly cultivated lands. The derived findings on the aquifers' storage losses provide a vital source of information for the decision-makers to be employed for short- and long-term groundwater management.

Machine learning based downscaling of GRACE-estimated groundwater in Central Valley, California

California's Central Valley, one of the most agriculturally productive regions, is also one of the most stressed aquifers in the world due to anthropogenic groundwater over-extraction primarily for irrigation. Groundwater depletion is further exacerbated by climate-driven droughts. Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry has demonstrated the feasibility of quantifying global groundwater storage changes at uniform monthly sampling, though at a coarse resolution and is thus impractical for effective water resources management. Here, we employ the Random Forest machine learning algorithm to establish empirical relationships between GRACE-derived groundwater storage and in situ groundwater level variations over the Central Valley during 2002-2016 and achieved spatial downscaling of GRACE-observed groundwater storage changes from a few hundred km to 5 km. Validations of our modeled groundwater level with in situ groundwater level indicate excellent Nash-Sutcliffe Efficiency coefficients ranging from 0.94 to 0.97. In addition, the secular components of modeled groundwater show good agreements with those of vertical displacements observed by GPS, and CryoSat-2 radar altimetry measurements and is perfectly consistent with findings from previous studies. Our estimated groundwater loss is about 30 km³ from 2002 to 2016, which also agrees well with previous studies in Central Valley. We find the maximum groundwater storage loss rates of -5.7 ± 1.2 km³ yr^-1 and -9.8 ± 1.7 km³ yr^-1 occurred during the extended drought periods of January 2007-December 2009, and October 2011-September 2015, respectively while Central Valley also experienced groundwater recharges during prolonged flood episodes. The 5-km resolution Central Valley-wide groundwater storage trends reveal that groundwater depletion occurs mostly in southern San Joaquin Valley collocated with severe land subsidence due to aquifer compaction from excessive groundwater over withdrawal.

Monitoring groundwater storage in a fractured volcanic aquifer system

The use of groundwater resources is under increasing pressure to meet the demands of the society. Despite this, the understanding of its availability is still limited when compared to other water reserves. The aquifer studied was the volcanic Serra Geral Aquifer System (SASG) located in a humid subtropical region. This research aims to explore in a pioneering way the large-scale hydrogeological processes taking place at the SASG using a unique and complementary tool of intensive field monitoring, remote sensing data, and hydrological modeling. Results showed a fast response of groundwater levels to rainfall, with an average of 29 days of lag times. We also identified areas in the southern region of the basin with higher depletion rates, with GRACE results indicating a negative trend (- 57 mm year^-1) associated with a major recharge event that occurred in the region before the period monitored. Also, the interflow calculated using the MGB hydrological model showed that the flow within the limits between the soil and the volcanic rocks (different in hydraulic conductivity) varies spatially, influencing the baseflow of rivers as for slopes and soil capacity to store water.

Using Satellite-Based Terrestrial Water Storage Data: A Review

Land water storage plays a key role for the Earth's climate, natural ecosystems, and human activities. Since the launch of the first Gravity Recovery and Climate Experiment (GRACE) mission in 2002, spaceborne observations of changes in terrestrial water storage (TWS) have provided a unique, global perspective on natural and human-induced changes in freshwater resources. Even though they have become much used within the broader Earth system science community, space-based TWS datasets still incorporate important and case-specific limitations which may not always be clear to users not familiar with the underlying processing algorithms. Here, we provide an accessible and illustrated overview of the measurement concept, of the main available data products, and of some frequently encountered technical terms and concepts. We summarize concrete recommendations on how to use TWS data in combination with other hydrological or climatological datasets, and guidance on how to avoid possible pitfalls. Finally, we provide an overview of some of the main applications of GRACE TWS data in the fields of hydrology and climate science. This review is written with the intention of supporting future research and facilitating the use of satellite-based terrestrial water storage datasets in interdisciplinary contexts.

Evaluating aquifer stress and resilience with GRACE information at different spatial scales in Cambodia

Groundwater exploitation for different sectors in Cambodia is expanding. Groundwater levels have already begun to decline in some parts of the country. Monitoring and assessing groundwater storage (GWS) change, aquifer stress and aquifer resilience will support the proper planning and management of the country's groundwater resources; however, information regarding groundwater in Cambodia is currently scarce. Thus, GWS change in Cambodia over the 15 years from April 2002 to March 2017 was assessed using remote-sensing-based Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) datasets, with a comprehensive validation of the GRACE-derived groundwater storage anomaly (GWSA) with respect to in-situ field-based observations. The current study also investigated the impact of surface water storage (SWS) change in Tonle Sap Lake, South-East Asia's largest freshwater lake, on deriving the GWS change in Cambodia. The groundwater aquifer stresses (GAS), and aquifer resilience (AR) were also evaluated. The validation results were promising, with the correlation coefficient between satellite-based estimations and ground-based measurements ranging from 0.82 to 0.88 over four subbasins. The overall decreasing rate of GWS was found to be -0.63 mm/month, with two basins having the highest declining rate of more than 1.4 mm/month. Meanwhile, the aquifer experiencing stress during the dry season had a very low ability to quickly recover from these stresses. These findings emphasise that appropriate management is urgently needed to ensure the sustainability of the groundwater resource system in this country.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10040-022-02570-w.

Space-time monitoring of groundwater fluctuations with passive seismic interferometry

Historic levels of drought, globally, call for sustainable freshwater management. Under pressing demand is a refined understanding of the structures and dynamics of groundwater systems. Here we present an unconventional, cost-effective approach to aquifer monitoring using seismograph arrays. Employing advanced seismic interferometry techniques, we calculate the space-time evolution of relative changes in seismic velocity, as a measure of hydrological properties. During 2000–2020 in basins near Los Angeles, seismic velocity variations match groundwater tables measured in wells and surface deformations inferred from satellite sensing, but the seismological approach adds temporal and depth resolutions for deep structures and processes. Maps of long-term seismic velocity changes reveal distinct patterns (decline or recovery) of groundwater storage in basins that are adjacent but adjudicated to water districts conducting different pumping practices. This pilot application bridges the gap between seismology and hydrology, and shows the promise of leveraging seismometers worldwide to provide 4D characterizations of groundwater and other near-surface systems.

Characterization of groundwater systems is important for sustainable freshwater management. Here, the authors map the distribution of groundwater storage changes at several hundred meters below the metropolitan Los Angeles during 2000–2020, by developing a cost-effective method using ambient ground vibrations recorded by seismometers.

A Review of GNSS/GPS in Hydrogeodesy: Hydrologic Loading Applications and Their Implications for Water Resource Research

Hydrogeodesy, a relatively new field within the earth sciences, is the analysis of the distribution and movement of terrestrial water at Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy with a specific focus on Global Navigation Satellite System (GNSS)/Global Positioning System measurements of hydrologic loading. As water cycles through the hydrosphere, GNSS stations anchored to Earth's crust measure the associated movement of the land surface under the weight of changing hydrologic loads. Recent advances in GNSS-based hydrogeodesy have led to exciting applications of hydrologic loading and subsequent terrestrial water storage (TWS) estimates. We describe how GNSS position time series respond to climatic drivers, can be used to estimate TWS across temporal scales, and can improve drought characterization. We aim to facilitate hydrologists' use of GNSS-observed surface deformation as an emerging tool for investigating and quantifying water resources, propose methods to further strengthen collaborative research and exchange between geodesists and hydrologists, and offer ideas about pressing questions in hydrology that GNSS may help to answer.

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.

Managing Land Carrying Capacity: Key to Achieving Sustainable Production Systems for Food Security

Many previous studies have estimated the carrying capacity and feasible planetary boundaries for humankind. However, less attention has been given to how we will sustainably feed 9 billion people in 2050 and beyond. Here, we review the major natural resources that limit food production and discuss possible options, measures, and strategies to sustainably feed a human population of 9 billion in 2050 and beyond. Currently, food production greatly depends on external inputs, e.g., irrigation water and fertilizers, but these approaches are not sustainable. Due to the unbalanced distribution of global natural resources and large regional differences, urbanization expansion causes important areas to face more serious arable land resource shortages. Hence, sustainably feeding 9 billion people in 2050 and beyond remains an immense challenge for humankind, and this challenge requires novel planning and better decision-making tools. Importantly, the measures and strategies employed must be region-/country-specific because of the significant differences in the socioeconomic characteristics and natural environmental carrying capacity in different parts of the world. Considering the impact of unexpected extreme events (e.g., a global pandemic and war) in the future, the food trade and translocation of goods will also face challenges, and the strategies and decision-making processes employed must consider the possible influences at both regional and global scales.

Joint Inversion of GNSS and GRACE for Terrestrial Water Storage Change in California

Global Navigation Satellite System (GNSS) vertical displacements measuring the elastic response of Earth's crust to changes in hydrologic mass have been used to produce terrestrial water storage change (∆TWS) estimates for studying both annual ∆TWS as well as multi-year trends. However, these estimates require a high observation station density and minimal contamination by nonhydrologic deformation sources. The Gravity Recovery and Climate Experiment (GRACE) is another satellite-based measurement system that can be used to measure regional TWS fluctuations. The satellites provide highly accurate ∆TWS estimates with global coverage but have a low spatial resolution of ∼400 km. Here, we put forward the mathematical framework for a joint inversion of GNSS vertical displacement time series with GRACE ∆TWS to produce more accurate spatiotemporal maps of ∆TWS, accounting for the observation errors, data gaps, and nonhydrologic signals. We aim to utilize the regional sensitivity to ∆TWS provided by GRACE mascon solutions with higher spatial resolution provided by GNSS observations. Our approach utilizes a continuous wavelet transform to decompose signals into their building blocks and separately invert for long-term and short-term mass variations. This allows us to preserve trends, annual, interannual, and multi-year changes in TWS that were previously challenging to capture by satellite-based measurement systems or hydrological models, alone. We focus our study in California, USA, which has a dense GNSS network and where recurrent, intense droughts put pressure on freshwater supplies. We highlight the advantages of our joint inversion results for a tectonically active study region by comparing them against inversion results that use only GNSS vertical deformation as well as with maps of ∆TWS from hydrological models and other GRACE solutions. We find that our joint inversion framework results in a solution that is regionally consistent with the GRACE ∆TWS solutions at different temporal scales but has an increased spatial resolution that allows us to differentiate between regions of high and low mass change better than using GRACE alone.

An Overview of Groundwater Monitoring through Point-to Satellite-Based Techniques

Groundwater supplies approximately half of the total global domestic water demand. It also complements the seasonal and annual variabilities of surface water. Monitoring of groundwater fluctuations is mandatory to envisage the composition of terrestrial water storage. This research provides an overview of traditional techniques and detailed discussion on the modern tools and methods to monitor groundwater fluctuations along with advanced applications. The groundwater monitoring can broadly be classified into three groups. The first one is characterized by the point measurement to measure the groundwater levels using classical instruments and electronic and physical investigation techniques. The second category involves the extensive use of satellite data to ensure robust and cost-effective real-time monitoring to assess the groundwater storage variations. Many satellite data are in use to find groundwater indirectly. However, GRACE satellite data supported with other satellite products, computational tools, GIS techniques, and hydro-climate models have proven the most effective for groundwater resources management. The third category is groundwater numerical modeling, which is a very useful tool to evaluate and project groundwater resources in future. Groundwater numerical modeling also depends upon the point-based groundwater monitoring, so more research to improve point-based detection methods using latest technologies is required, as these still play the baseline role. GRACE and numerical groundwater modeling are suggested to be used conjunctively to assess the groundwater resources more efficiently.

Evaluation of Groundwater Storage Depletion Using GRACE/GRACE Follow-On Data with Land Surface Models and Its Driving Factors in Haihe River Basin, China

Groundwater storage (GWS) in the Haihe River Basin (HRB), which is one of the most densely populated and largest agricultural areas in China, is of great importance for the ecosystem environment and socio-economic development. In recent years, large-scale overexploitation of groundwater in HRB has made it one of the global hotspots of GWS depletion. In this study, monthly GWS variations in HRB from 2003 to 2020 were estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data in combination with three land surface models (LSMs) from the Global Land Data Assimilation System (GLDAS). The results show the following: (1) HRB suffered extensive GWS depletion from 2003 to 2020, which has been aggravated since 2014, with a mean rate of 1.88 cm·yr−1, which is equivalent to a volume of 6 billion m3·yr−1. The GWS depletion is more serious in the plain zone (−2.36 cm·yr−1) than in the mountainous zone (−1.63 cm·yr−1). (2) Climate changes are excluded from the reasons for GWS depletion due to annual precipitation and evaporation being close to normal throughout the period. In addition, GWS changes show a low correlation with meteorological factors. (3) The consumption of groundwater for irrigation and land use/cover changes have been confirmed to be the dominant factors for GWS depletion in HRB. (4) The effects of inter-basin water transfer projects cannot be obviously observed using the GRACE and GRACE-FO; more inter-basin water transfers are needed for recovering the GWS in HRB. Therefore, it is imperative to control groundwater exploitation and develop a more economical agricultural irrigation structure for the sustainability of groundwater resources in HRB.

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

It is an effective measure to estimate groundwater storage anomalies (GWSA) by combining Gravity Recovery and Climate Experiment (GRACE) data and hydrological models. However, GWSA results based on a single hydrological model and GRACE data may have greater uncertainties, and it is difficult to verify in some regions where in situ groundwater-level measurements are limited. First, to solve this problem, a groundwater weighted fusion model (GWFM) is presented, based on the extended triple collocation (ETC) method. Second, the Shiyang River Basin (SYRB) is taken as an example, and in situ groundwater-level measurements are used to evaluate the performance of the GWFM. The comparison indicates that the correlation coefficient (CC) and Nash-Sutcliffe efficiency coefficient (NSE) are increased by 9–40% and 23–657%, respectively, relative to the original results. Moreover, the root mean squared error (RMSE) is reduced by 9–28%, which verifies the superiority of the GWFM. Third, the spatiotemporal distribution and influencing factors of GWSA in the Hexi Corridor (HC) are comprehensively analyzed during the period between 2003 and 2016. The results show that GWSA decline, with a trend of −2.37 ± 0.38 mm/yr from 2003 to 2010, and the downward trend after 2011 (−0.46 ± 1.35 mm/yr) slow down significantly compared to 2003–2010. The spatial distribution obtained by the GWFM is more reliable compared to the arithmetic average results, and GWFM-based GWSA fully retain the advantages of different models, especially in the southeastern part of the SYRB. Additionally, a simple index is used to evaluate the contributions of climatic factors and human factors to groundwater storage (GWS) in the HC and its different subregions. The index indicates that climate factors occupy a dominant position in the SLRB and SYRB, while human factors have a significant impact on GWS in the Heihe River Basin (HRB). This study can provide suggestions for the management and assessments of groundwater resources in some arid regions.

Quantifying the Contributions of Climate Change and Human Activities to Water Volume in Lake Qinghai, China

Lake Qinghai has shrunk and then expanded over the past few decades. Quantifying the contributions of climate change and human activities to lake variation is important for water resource management and adaptation to climate change. In this study, we calculated the water volume change of Lake Qinghai, analyzed the climate and land use changes in Lake Qinghai catchment, and distinguished the contributions of climate change and local human activities to water volume change. The results showed that lake water volume decreased by 9.48 km3 from 1975 to 2004 and increased by 15.18 km3 from 2005 to 2020. The climate in Lake Qinghai catchment is becoming warmer and more pluvial, and the changes in land use have been minimal. Based on the Soil and Water Assessment Tool (SWAT), land use change, climate change and interaction effect of them contributed to 7.46%, 93.13% and −0.59%, respectively, on the variation in surface runoff into the lake. From the perspective of the water balance, we calculated the proportion of each component flowing into and out of the lake and found that the contribution of climate change to lake water volume change was 97.55%, while the local human activities contribution was only 2.45%. Thus, climate change had the dominant impact on water volume change in Lake Qinghai.

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.

Surface Water Storage in Rivers and Wetlands Derived from Satellite Observations: A Review of Current Advances and Future Opportunities for Hydrological Sciences

Surface water storage (SWS), the amount of freshwater stored in rivers/wetlands/floodplains/lakes, and its variations are key components of the water cycle and land surface hydrology, with strong feedback and linkages with climate variability. They are also very important for water resources management. However, it is still very challenging to measure and to obtain accurate estimates of SWS variations for large river basins at adequate time/space sampling. Satellite observations offer great opportunities to measure SWS changes, and several methods have been developed combining multisource observations for different environments worldwide. With the upcoming launch in 2022 of the Surface Water and Ocean Topography (SWOT) satellite mission, which will provide, for the first time, direct estimates of SWS variations with an unprecedented spatial resolution (~100 m), it is timely to summarize the recent advances in the estimates of SWS from satellite observations and how they contribute to a better understanding of large-scale hydrological processes. Here, we review the scientific literature and present major results regarding the dynamic of surface freshwater in large rivers, floodplains, and wetlands. We show how recent efforts have helped to characterize the variations in SWS change across large river basins, including during extreme climatic events, leading to an overall better understanding of the continental water cycle. In the context of SWOT and forthcoming SWS estimates at the global scale, we further discuss new opportunities for hydrological and multidisciplinary sciences. We recommend that, in the near future, SWS should be considered as an essential water variable to ensure its long-term monitoring.

Improving the Accuracy of Water Storage Anomaly Trends Based on a New Statistical Correction Hydrological Model Weighting Method

The Gravity Recovery and Climate Experiment (GRACE) satellite solutions have been considerably applied to assess the reliability of hydrological models on a global scale. However, no single hydrological model can be suitable for all regions. Here, a New Statistical Correction Hydrological Model Weighting (NSCHMW) method is developed based on the root mean square error and correlation coefficient between hydrological models and GRACE mass concentration (mascon) data. The NSCHMW method can highlight the advantages of good models compared with the previous average method. Additionally, to verify the effect of the NSCHMW method, taking the Haihe River Basin (HRB) as an example, the spatiotemporal patterns of Terrestrial Water Storage Anomalies (TWSA) in HRB are analyzed through a comprehensive comparison of decadal trends (2003–2014) from GRACE and different hydrological models (Noah from GLDAS-2.1, VIC from GLDAS-2.1, CLSM from GLDAS-2.1, CLSM from GLDAS-2.0, WGHM, PCR-GLOBWB, and CLM-4.5). Besides, the NSCHMW method is applied to estimate TWSA trends in the HRB. Results demonstrate that (1) the NSCHMW method can improve the accuracy of TWSA estimation by hydrological models; (2) the TWSA trends continue to decrease through the study period at a rate of 15.7 mm/year; (3) the WGHM and PCR-GLOBWB have positive reliability with respect to GRACE with r > 0.9, while all the other models underestimate TWSA trends; (4) the NSCHMW method can effectively improve RMSE, NES, and r with 3–96%, 35–282%, 1–255%, respectively, by weighting the WGHM and PCR-GLOBWB. Indeed, groundwater depletion in HRB also proves the necessity of the South-North Water Diversion Project, which has already contributed to groundwater recovery.

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.

Downscaling GRACE total water storage change using partial least squares regression

The Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surface of the Earth. GRACE provided a first global observational record of water mass redistribution at spatial scales greater than 63000 km². This limits their usability in regional hydrological applications. In this study, we implement a statistical downscaling approach that assimilates 0.5° × 0.5° water storage fields from the WaterGAP hydrology model (WGHM), precipitation fields from 3 models, evapotranspiration and runoff from 2 models, with GRACE data to obtain TWSC at a 0.5° × 0.5° grid. The downscaled product exploits dominant common statistical modes between all the hydrological datasets to improve the spatial resolution of GRACE. We also provide open access to scripts that researchers can use to produce downscaled TWSC fields with input observations and models of their own choice.

Measurement(s)	Gravity
Technology Type(s)	gravity field theory • computational modeling technique
Factor Type(s)	geographic location • temporal interval
Sample Characteristic - Environment	water body
Sample Characteristic - Location	global

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13503114

Drought Events over the Amazon River Basin (1993–2019) as Detected by the Climate-Driven Total Water Storage Change

The Gravity Recovery and Climate Experiment (GRACE) mission has measured total water storage change (TWSC) and interpreted drought patterns in an unparalleled way since 2002. Nevertheless, there are few sources that can be used to understand drought patterns prior to the GRACE era. In this study, we extended the gridded GRACE TWSC to 1993 by combining principal component analysis (PCA), least square (LS) fitting, and multiple linear regression (MLR) methods using climate variables as input drivers. We used the extended (climate-driven) TWSC to interpret drought patterns (1993–2019) over the Amazon basin. Results showed that, in the Amazon area with the resolution of 0.5°, GRACE, GRACE follow on, and Swarm had correlation coefficients of 0.95, 0.92, and 0.77 compared with climate-driven TWSCS, respectively. The drought patterns assessed by the climate-driven TWSC were consistent with those interpreted by the Palmer Drought Severity Index and GRACE TWSC. We also found that the 1998 and 2016 drought events in the Amazon, both induced by strong El Niño events, showed similar drought patterns. This study provides a new perspective for interpreting long-term drought patterns prior to the GRACE period.

Characterization of Basin-Scale Dynamic Storage–Discharge Relationship Using Daily GRACE Based Storage Anomaly Data

Despite the fact that streamflow occurs mainly due to depletion of storage, our knowledge on how a drainage basin stores and releases water is very limited due to measurement limitations. A window of opportunity, however, is provided to us by GRACE (Gravity Recovery and Climate Experiment) satellite mission that provides storage anomaly (San) data. Many studies have explored a range of potential applications of San data such as flood forecasting. Here we argue that the capability of GRACE satellite mission has not been fully explored as most of the studies in the past have performed analysis using monthly San data for large river basins. In this study, we use daily San data for several mid-sized catchments to perform storage–discharge analysis. Our results support the earlier notion that storage–discharge relationship is highly dynamic. Furthermore, we demonstrate that San data can be exploited for prediction of k of the Brutsaet–Nieber equation −dQ/dt=kQα (Q is discharge at time t). For comparison we also use storage information provided by Catchment Land Surface Model (CLSM) as well as past discharge information to predict k. Our results suggest that GRACE based storage information can be used to predict k reasonably well in gauged as well as ungauged basins.

Terrestrial Water Storage Change Retrieved by GRACE and Its Implication in the Tibetan Plateau: Estimating Areal Precipitation in Ungauged Region

The Tibetan Plateau (TP) is referred to as the water tower of Asia, where water storage and precipitation have huge impacts on most major Asian rivers. Based on gravity recovery and climate experiment data, this study analyzed the terrestrial water storage (TWS) changes and estimated areal precipitation based on the water balance equation in four different basins, namely, the upper Yellow River (UYE), the upper Yangtze River (UYA), the Yarlung Zangbo River (YZ), and the Qiangtang Plateau (QT). The results show that the TWS change exhibits different patterns in the four basins and varies from −13 to 2 mm/year from 2003 to 2017. The estimated mean annual precipitation was 260 ± 19 mm/year (QT), 697 ± 26 mm/year (UYA), 541 ± 36 mm/year (UYE), and 1160 ± 39 mm/year (YZ) which performed better than other precipitation products in the TP. It indicates a potential method for estimating basin-scale precipitation through integrating basin average precipitation from the water balance equation in the poorly gauged and ungauged regions.

Groundwater Storage Changes in the Major North African Transboundary Aquifer Systems during the GRACE Era (2003–2016)

Groundwater is an essential component of the terrestrial water cycle and a key resource for supplying water to billions of people and for sustaining domestic and economic (agricultural and industrial) activities, especially in arid and semi-arid areas. The goal of this study is to analyze the recent groundwater changes which occurred in the major North African transboundary aquifers in the beginning of the 21st century. Groundwater storage anomalies were obtained by removing soil moisture in the root zone (and surface water in the case of the Nubian Sandstone Aquifer System) from the terrestrial water storage anomalies estimated using the Gravity Recovery and Climate Experiment (GRACE) over the 2003–2016 time period. Spatio-temporal changes in groundwater storage contrast significantly among the different transboundary aquifers. Low changes (lower than 10 km3) were observed in the Tindouf Aquifer System but they were found to be highly correlated (R = 0.74) to atmospheric fluxes (precipitation minus evapotranspiration, P − ET) at annual scale. The GRACE data revealed huge water loss in the North Western Sahara and the Nubian Sandstone Aquifer Systems, above 30 km3 and around 50 km3, respectively. In the former case, the aquifer depletion can be attributed to both climate (R = 0.67 against P − ET) and water abstraction, and only to water abstraction in the latter case. The increase in water abstraction results from an increase in irrigated areas and population growth. For these two aquifers, a deceleration in the water loss observed after 2013 is likely to be attributed either to an increase in rainfall favoring rain-fed agriculture or to measures taken to reduce the over-exploitation of the groundwater resources.

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.

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.

State of the Art and Recent Advancements in the Modelling of Land Subsidence Induced by Groundwater Withdrawal

Land subsidence is probably one of the most evident environmental effects of groundwater pumping. Globally, freshwater demand is the leading cause of this phenomenon. Land subsidence induced by aquifer system drainage can reach total values of up to 14.5 m. The spatial extension of this phenomenon is usually extensive and is often difficult to define clearly. Aquifer compaction contributes to many socio-economic effects and high infrastructure-related damage costs. Currently, many methods are used to analyze aquifer compaction. These include the fundamental relationship between groundwater head and groundwater flow direction, water pressure and aquifer matrix compressibility. Such solutions enable satisfactory modelling results. However, further research is needed to allow more efficient modelling of aquifer compaction. Recently, satellite radar interferometry (InSAR) has contributed to significant progress in monitoring and determining the spatio-temporal land subsidence distributions worldwide. Therefore, implementation of this approach can pave the way to the development of more efficient aquifer compaction models. This paper presents (1) a comprehensive review of models used to predict land surface displacements caused by aquifer drainage, as well as (2) recent advances, and (3) a summary of InSAR implementation in recent years to support the aquifer compaction modelling process.

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales. Whilst these data effectively characterize water cycle variability at regional to global scales, they are less suitable for sustainable management of local water resources, which needs detailed information to represent the spatial heterogeneity of soil and vegetation. The following questions are critical to effectively exploit information from remotely sensed and in situ Earth observations (EOs): How to downscale the global water cycle products to the local scale using multiple sources and scales of EO data? How to explore and apply the downscaled information at the management level for a better understanding of soil-water-vegetation-energy processes? How can such fine-scale information be used to improve the management of soil and water resources? An integrative information flow (i.e., iAqueduct theoretical framework) is developed to close the gaps between satellite water cycle products and local information necessary for sustainable management of water resources. The integrated iAqueduct framework aims to address the abovementioned scientific questions by combining medium-resolution (10 m–1 km) Copernicus satellite data with high-resolution (cm) unmanned aerial system (UAS) data, in situ observations, analytical- and physical-based models, as well as big-data analytics with machine learning algorithms. This paper provides a general overview of the iAqueduct theoretical framework and introduces some preliminary results.

Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery

In this study, a new approach for estimating volume variations of lakes and reservoirs using water levels from satellite altimetry and surface areas from optical imagery is presented. Both input data sets, namely water level time series and surface area time series, are provided by the Database of Hydrological Time Series of Inland Waters (DAHITI), developed and maintained by the Deutsches Geodätisches Forschungsinsitut der Technischen Universität München (DGFI-TUM). The approach is divided into three parts. In the first part, a hypsometry model based on the new modified Strahler approach is computed by combining water levels and surface areas. The hypsometry model describes the dependency between water levels and surface areas of lakes and reservoirs. In the second part, a bathymetry between minimum and maximum surface area is computed. For this purpose, DAHITI land-water masks are stacked using water levels derived from the hypsometry model. Finally, water levels and surface areas are intersected with the bathymetry to estimate a time series of volume variations in relation to the minimum observed surface area. The results are validated with volume time series derived from in-situ water levels in combination with bathymetric surveys. In this study, 28 lakes and reservoirs located in Texas are investigated. The absolute volumes of the investigated lakes and reservoirs vary between 0.062 km 3 and 6.041 km 3 . The correlation coefficients of the resulting volume variation time series with validation data vary between 0.80 and 0.99. Overall, the relative errors with respect to volume variations vary between 2.8% and 14.9% with an average of 8.3% for all 28 investigated lakes and reservoirs. When comparing the resulting RMSE with absolute volumes, the absolute errors vary between 1.5% and 6.4% with an average of 3.1%. This study shows that volume variations can be calculated with a high accuracy which depends essentially on the quality of the used water levels and surface areas. In addition, this study provides a hypsometry model, high-resolution bathymetry and water level time series derived from surface areas based on the hypsometry model. All data sets are publicly available on the Database of Hydrological Time Series of Inland Waters.

The Lake Chad hydrology under current climate change

Lake Chad, in the Sahelian zone of west-central Africa, provides food and water to ~50 million people and supports unique ecosystems and biodiversity. In the past decades, it became a symbol of current climate change, held up by its dramatic shrinkage in the 1980s. Despites a partial recovery in response to increased Sahelian precipitation in the 1990s, Lake Chad is still facing major threats and its contemporary variability under climate change remains highly uncertain. Here, using a new multi-satellite approach, we show that Lake Chad extent has remained stable during the last two decades, despite a slight decrease of its northern pool. Moreover, since the 2000s, groundwater, which contributes to ~70% of Lake Chad’s annual water storage change, is increasing due to water supply provided by its two main tributaries. Our results indicate that in tandem with groundwater and tropical origin of water supply, over the last two decades, Lake Chad is not shrinking and recovers seasonally its surface water extent and volume. This study provides a robust regional understanding of current hydrology and changes in the Lake Chad region, giving a basis for developing future climate adaptation strategies.

Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses

Changes in terrestrial water storage as observed by the satellite gravity mission GRACE (Gravity Recovery and Climate Experiment) represent a new and completely independent way to constrain the net flux imbalance in atmospheric reanalyses. In this study daily GRACE gravity field changes are used for the first time to investigate high-frequency hydro-meteorological fluxes over the continents. Band-pass filtered water fluxes are derived from GRACE water storage time series by first applying a numerical differentiation filter and subsequent high-pass filtering to isolate fluxes at periods between 5 and 30 days corresponding to typical time-scales of weather system persistence at moderate latitudes. By comparison with the latest atmospheric reanalysis ERA5 of the European Centre for Medium-Range Weather Forecasts (ECWMF) we show that daily GRACE gravity field models contain realistic high-frequency water flux information. Furthermore, GRACE-derived water fluxes can clearly identify improvements realized within ERA5 over its direct predecessor ERA-Interim particularly in equatorial and temperate climate zones. The documented improvements are in good agreement with rain gauge validation, but GRACE also identifies three distinct regions (Sahel Zone, Okavango Catchment, Kimberley Plateau) with a slight degradation of net-fluxes in ERA5 with respect to ERA-Interim, thereby highlighting the potentially added value of non-standard daily GRACE gravity series for hydro-meteorological monitoring purposes.

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

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 (∆GWS) 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 (SI_GWS), 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 ∆GWS = 16.79 cm/year and SI_GWS = 0.46 (1985-1990) to ∆GWS = -28.96 cm/year and SI_GWS = 0.008 (2007-2016); (2) the lowest value of groundwater sustainability in the HC appeared in the central and eastern regions (SI_GWS = 0); (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.

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.

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.

Water Storage Trends in High Mountain Asia

Changes in terrestrial water storage (TWS) in High Mountain Asia (HMA) could have major societal impacts, as the region's large reservoirs of glaciers, snow, and groundwater provide a freshwater source to more than one billion people. We seek to quantify and close the budget of secular changes in TWS over the span of the GRACE satellite mission (2003-2016). To assess the TWS trend budget we consider a new high-resolution mass trend product determined directly from GRACE L1B data, glacier mass balance derived from Digital Elevation Models (DEMs), groundwater variability determined from confined and unconfined well observations, and terrestrial water budget estimates from a suite of land surface model simulations with the NASA Land Information System (LIS). This effort is successful at closing the aggregated TWS trend budget over the entire HMA region, the glaciated portion of HMA, and the Indus and Ganges basins, where the full-region trends are primarily due to the glacier mass balance and groundwater signals. Additionally, we investigate the closure of TWS trends at individual 1-arc-degree mascons (area ≈12,000 km2); a significant improvement in spatial resolution over previous analyses of GRACE-derived trends. This mascon-level analysis reveals locations where the TWS trends are well-explained by the independent datasets, as well as regions where they are not; identifying specific geographic areas where additional data and model improvements are needed. The accurate characterization of total TWS trends and its components presented here is critical to understanding the complex dynamics of the region, and is a necessary step toward projecting future water mass changes in HMA.

Monitoring and Analysis of Drought Using Gravity Recovery and Climate Experiment (GRACE)

Drought monitoring needs comprehensive and integrated meteorological and hydrologic data. However, such data are generally not available in extensive catchments. The present study aimed to analyze drought in the central plateau catchment of Iran using the terrestrial water storage deficit index (TSDI). In this arid catchment, the meteorological and hydrologic observed data are scarce. First, the time series of terrestrial water storage changes (TWSC) obtained from the gravity recovery and climate experiment (GRACE) was calculated and validated by the water budget output. Then, the studied area was divided into semi-arid, arid, and hyper-arid zones and the common drought indices of SPI and RDIe within a timescale of 3, 6, and 12 months were calculated to compare the results obtained from the TSDI by using the meteorological data of 105 synoptic stations. Based on the results, the study area experienced a drought with extreme severity and expansion during 2007–2008. The drought spatial distribution map obtained from three indices indicated good conformity. Based on the maps, the severity, duration, and frequency of drought in the semi-arid zone were greater than that in other zones, while no significant drought occurred in the hyper-arid zone. Furthermore, the temporal distribution of drought in all three zones indicated that the TSDI could detect all short- and long-term droughts. The study results showed that the TSDI is a reliable, integrated, and comprehensive index. Using this index in arid areas with little field data led to some valuable results for planning and water resource management.

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.

Detecting Water Diversion Fingerprints in the Danjiangkou Reservoir from Satellite Gravimetry and Altimetry Data

The Danjiangkou Reservoir (DJKR) is the freshwater source for the Middle Route of the South-to-North Water Diversion Project in China, and its water level and storage changes are important for water resource management. To maximize the potential capacity of the Gravity Recovery and Climate Experiment (GRACE) mission, an improved Lagrange multiplier method (ILMM) is first proposed to detect terrestrial water storage anomalies (TWSA) in the small-scale basin (DJKR). Moreover, for the first time, water diversion fingerprints are proposed to analyze the spatiotemporal pattern of the TWSA in the DJKR. The results indicate that the increased water level and storage signals due to the DJKR impoundment in 2014 can be effectively detected by using the ILMM, and they agree well with the results from altimetry and in situ data. Additionally, the water diversion fingerprints due to the DJKR impoundment are inferred, and describe the progression of spatiotemporal variability in water storage. The results show that water storage decreased in the upper Hanjiang River and increased in the DJKR as well as to the east of it during the period 2013–2015. Our research provides a scientific decision-making basis for monitoring the water resources of the DJKR and managing the South-to-North Water Diversion Project.

Assessment of Physical Water Scarcity in Africa Using GRACE and TRMM Satellite Data

The critical role of water in enabling or constraining human well-being and socioeconomic activities has led to an interest in quantitatively establishing the status of water (in)sufficiency over space and time. Falkenmark introduced the first widely accepted measure of water status, the Water Scarcity Index (WSI), which expressed the status of the availability of water resources in terms of vulnerability, stress, and scarcity. Since then, numerous indicators have been introduced, but nearly all adopt the same basic formulation; water status is a function of “available water” resource—by the demand or use. However, the accurate assessment of “available water” is difficult, especially in data-scarce regions, such as Africa. In this paper, therefore, we introduce a satellite-based Potential Available Water Storage indicator, PAWS. The method integrates GRACE (Gravity Recovery and Climate Experiment) satellite Total Water Storage (TWS) measurements with the Tropical Rainfall Measuring Mission (TRMM) precipitation estimates between 2002 and 2016. First, we derived the countries’ Internal Water Storage (IWS) using GRACE and TRMM precipitation data. Then, the IWS was divided by the population density to derive the PAWS per capita. Following the Falkenmark thresholds, 54% of countries are classified in the same water vulnerability status as the AQUASTAT Internal Renewable Water Resources (IRWR) method. Of the remaining countries, PAWS index leads to one or two categories shift (left or right) of water status. The PAWS index shows that 14% (~160 million people) of Africa’s population currently live under water scarcity status. With respect to future projections, PAWS index suggests that a 10% decrease in future water resources would affect ~37% of Africa’s 2025 population (~600 million people), and 57% for 2050 projections (~1.4-billion people). The proposed approach largely overcomes the constraints related to the data needed to rapidly and robustly estimate available water resources by incorporating all stocks of water within the country, as well as underscores the recent water storage dynamics. However, the estimates obtained concern potential available water resources, which may not be utilizable for practical, economic, and technological issues.

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.

Understanding the global hydrological droughts of 2003-2016 and their relationships with teleconnections

Droughts often evolve gradually and cover large areas, and therefore, affect many people and activities. This motivates developing techniques to integrate different satellite observations, to cover large areas, and understand spatial and temporal variability of droughts. In this study, we apply probabilistic techniques to generate satellite derived meteorological, hydrological, and hydro-meteorological drought indices for the world's 156 major river basins covering 2003-2016. The data includes Terrestrial Water Storage (TWS) estimates from the Gravity Recovery And Climate Experiment (GRACE) mission, along with soil moisture, precipitation, and evapotranspiration reanalysis. Different drought characteristics of trends, occurrences, areal-extent, and frequencies corresponding to 3-, 6-, 12-, and 24-month timescales are extracted from these indices. Drought evolution within selected basins of Africa, America, and Asia is interpreted. Canonical Correlation Analysis (CCA) is then applied to find the relationship between global hydro-meteorological droughts and satellite derived Sea Surface Temperature (SST) changes. This relationship is then used to extract regions, where droughts and teleconnections are strongly interrelated. Our numerical results indicate that the 3- to 6-month hydrological droughts occur more frequently than the other timescales. Longer memory of water storage changes (than water fluxes) has found to be the reason of detecting extended hydrological droughts in regions such as the Middle East and Northern Africa. Through CCA, we show that the El Niño Southern Oscillation (ENSO) has major impact on the magnitude and evolution of hydrological droughts in regions such as the northern parts of Asia and most parts of the Australian continent between 2006 and 2011, as well as droughts in the Amazon basin, South Asia, and North Africa between 2010 and 2012. The Indian ocean Dipole (IOD) and North Atlantic Oscillation (NAO) are found to have regional influence on the evolution of hydrological droughts.

Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations

Influences of climatic change and anthropogenic activities on the terrestrial water storage (TWS) change are significant in the mid- and high-latitude areas. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided quantitative measurements of TWS changes with unprecedented accuracy at global, regional and basin scales. In this study, the noise level of various GRACE-derived TWS anomalies (TWSA) data were evaluated by using a generalized three-cornered hat (GTCH) method. A time-dependent weights approach was adopted to obtain a combined TWSA series over the Songhua River Basin (SRB) from 2003 to 2013. Monthly TWSA data during the past decades (1982-2002) were reconstructed by using an artificial neural network (ANN) approach with the good performance evaluated by the correlation coefficient of 0.89 and the Nash-Sutcliff efficiency of 0.79 over the study region. In-situ groundwater level measurements were used for validation of the groundwater storage (GWS) changes (estimated by using GRACE-derived TWS changes in association with the other simulated components of water storage changes from land surface models (LSMs)). The primary driving factors of spatiotemporal variations of GWS, as well as their inter-/intra-annually varying characteristics, were explored. The present study revealed that the variations of GWS featured a "downward fluctuations" (1982-1994), "stable upward" (1998-2008) and "decreasing dramatically" (2009-2013) period, respectively, over the SRB. In general, GWS had varied in a steady decline trend at a decreasing rate of 1.04 ± 0.59 mm year^-1 from 1982 to 1994. With the enhanced climatic and anthropogenic influences over the region since 2000, several severe fluctuations characterized the GWS variations with occurrences of spring droughts and flooding over the region, which suggested significant effects of global changes posed on GWS variations of the region.