Groundwater Storage Variations Research Articles

Spatiotemporal coupling analysis of surface water and groundwater in Tibet based on multi-source sensors

Abstract. Lakes and groundwater are two crucial components of the global terrestrial water cycle, collectively forming a vital network for Earth's water resources. However, in the Tibetan region, the spatiotemporal relationship between lakes and groundwater and their impact on the local hydrological cycle remain inadequately understood. Satellite remote sensing serves as an effective observational tool, enabling comprehensive investigation and analysis of surface lakes and groundwater in Tibet with high spatial resolution. Therefore, this study integrates Landsat and Cryosat-2 satellite data to examine the spatiotemporal patterns of surface lake extents and water levels in Tibet. Additionally, combining Gravity Recovery and Climate Experiment (GRACE) satellite observations with the Global Land Data Assimilation System (GLDAS) model data, we quantitatively analyze the spatiotemporal variations in groundwater storage and its correlation with lake water. The results indicate that: 1) Rivers and lakes in Tibet are mainly located in the central and northwest regions, displaying noticeable intra-annual variations; 2) Substantial lagged relationships exist between groundwater storage and lake water levels and areas, revealing that lakes contribute significantly to groundwater replenishment, especially in the Ngari prefecture and Lhokha prefecture. This study comprehensively utilizes multi-source remote sensing data to dynamically monitor surface and groundwater in Tibet, providing robust support for a better understanding of the interaction between groundwater and surface water.

Analyzing groundwater storage anomalies in data‐scarce areas of Ethiopia's Rift Valley Basin using artificial neural network

AbstractGroundwater storage anomalies (GWSA) study requires the use of hydro‐climatic models coupled with Gravity Recovery and Climate Experiment climate (GRACE) and GRACE Follow‐On (GRACE‐FO) Terrestrial Water Storage experiments. Understanding groundwater storage anomalies in the research area is difficult due to the restricted hydro‐meteorological data availability, especially, groundwater levels, changes in groundwater storage, and budgetary and technical constraints. No such investigation of GWS anomalies prior to this study in this Basin was conducted. The research focuses on GWSA investigations in the basin employing Global Land Data Assimilation Systems and Artificial Neural Networks‐Back Propagation Algorithm techniques are required. The ultimate objective of this study was to reduce the GRACE GWS from 1° to 0.25° and close the discontinuity between GRACE/GRACE‐FO observations. The results illustrated that GRACE/GRACE‐FO GWS throughout the basin were overall declining. The GWS anomaly significantly decreased between 2011 and 2013, with the highest monthly depletion in March 2011 (−158 mm). In contrast, from mid‐June to mid‐October, the maximum positive value varied from 20.80 mm in the southernmost basin to 39.49 mm in the central‐southeastern basin. The basin's eastern, central‐southeastern, northern, and southern areas displayed positive monthly GWS trends. The entire dry season has been influenced by negative anomalies. Hence, the identification of GWS variations and a comprehensive understanding of their effects provided valuable scientific insights. Identifying and analyzing anomalies in groundwater storage (GWS) can provide valuable information. This data can be efficiently used to develop appropriate regulatory frameworks, which may contribute to the long‐term viability of the availability of groundwater.

Estimation of groundwater storage variations in African river basins: Response to global climate change using GRACE and GRACE-FO among past two decades

Groundwater Storage (GWS) is an important component of the water cycle and a vital resource for supplying water to millions of people as well as sustaining domestic and economic activities, especially in arid and semi-arid regions such as Africa. This study aims to estimate and analyze the recent groundwater changes (ΔGW) for 11 major African basins in light of climate changes and global warming utilizing the data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) from January 2003 to December 2021. We proposed a new gap-filling technique to calculate the missing months between GRACE and GRACE-FO missions for the continuous estimation of groundwater changes. Then, we establish a new framework to analyze and investigated the climate parameters that could affect groundwater changes using Empirical Orthogonal Function (EOF) technique. Our analysis reveals that the new gap-filling technique is significantly consistent with the TWS time-series based on the trend line analysis. The lowest GPCC drought index value occurs in the lower Nile basin by approximately −0.93, while the highest occurs in the middle of Africa in Congo basin by approximately −0.02. The precipitation rate is mostly concentrated in mid-Africa while North and South Africa shows a weak rate. Meanwhile, according to the analysis of dependent climate parameters, climate change has had a negative impact on groundwater. However, the long-term effect on the groundwater does not clearly appear because most of Africa is located within semi-arid and arid regions. The effect of rain on groundwater was evident through EOF analysis, which shows GWS EOF Mode-2 (36.28%) and precipitation EOF Mode-1 (78.34%) were found to be in significant agreement in spatio-temporal domains.

Assessing Groundwater Sustainability in the Arabian Peninsula and Its Impact on Gravity Fields through Gravity Recovery and Climate Experiment Measurements

This study addresses the imperative to comprehend gravity shifts resulting from groundwater storage (GWS) variations in the Arabian Peninsula. Despite the critical importance of water resource sustainability and its relationship with gravity, limited research emphasizes the need for expanded exploration. The investigation explores the impact of GWS extraction on the gravity field, utilizing Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data in addition to validation using the WaterGAP Global Hydrology Model (WGHM). Spanning April 2002 to June 2023, this study predicts GWS trends over the next decade using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The comprehensive time-series analysis reveals a significant GRACE-derived groundwater storage (GWS) trend of approximately −4.90 ± 0.32 mm/year during the study period. This trend has a notable impact on the gravity anomaly (GA) values, as observed through the decomposition analysis. The projected GWS indicates a depletion rate of 14.51 km3/year over the next decade. The correlation between GWS and GA is substantial at 0.80, while the GA and rainfall correlation is negligible due to low precipitation rates. Employing multiple linear regression explains 80.61% of the variance in gravity anomaly due to GWS, precipitation, and evapotranspiration. This study investigates climate change factors—precipitation, temperature, and evapotranspiration—providing a holistic understanding of the forces shaping GWS variations. Precipitation and evapotranspiration exhibit nearly equal values, limiting GWS replenishment opportunities. This research holds significance in studying extensive GWS withdrawal in the Arabian Peninsula, particularly concerning crust mass stability.

Spatiotemporal Variations and Sustainability Characteristics of Groundwater Storage in North China from 2002 to 2022 Revealed by GRACE/GRACE Follow-On and Multiple Hydrologic Data

North China (NC) is experiencing significant groundwater depletion. We used GRACE and GRACE-FO RL06 Level-2 data with Mascon data from April 2002 to July 2022. We fused these two types of data through the generalized three-cornered hat method and further combined them with hydrological models, precipitation, in situ groundwater-level, and groundwater extraction (GWE) data to determine and verify temporal and spatial variations in groundwater storage (GWS) in NC. We quantitatively assessed groundwater sustainability by constructing a groundwater index in NC. We further explored the dynamic cyclic process of groundwater change and quantified the impact of the South-to-North Water Transfer Project (SNWTP) on GWS change in NC. The overall GWS shows a decreasing trend. The GRACE/GRACE-FO-derived GWS change results are consistent with those shown by the in situ groundwater-level data from the monitoring well. Groundwater in NC is in various states of unsustainability throughout the period 2002 to 2022. The SNWTP affected the water use structure to some extent in NC. This study elucidates the latest spatial–temporal variations in GWS, especially in the groundwater sustainability assessment and quantitative description of the effects of the SNWTP on changes in GWS in NC. The results may provide a reference for groundwater resource management.

Application of gravity and remote sensing data to groundwater storage variation in Wadi Al Dawasir, Saudi Arabia

In order to deal with the increase in human-caused impacts, Saudi Arabia is exploring new groundwater sources. Significant agricultural development in Wadi Al Dawasir has resulted in an overuse of groundwater resources. Constant monitoring of the wadi's groundwater is necessary in order to make informed decisions about the future of the wadi's groundwater resources and the local economy. The rate of groundwater depletion in the Wadi Al Dawasir drainage basin in northern Saudi Arabia was calculated by combining data from the advanced Gravity Recovery and Climate Experiment (GRACE) mission with outputs from a land surface model. The analysis covered the period from April 2002 to December 2021. The results are as follows: (1) the average terrestrial water storage fluctuation (ΔTWS) was calculated at −0.48 ± 0.02 cm yr−1; (2) the average soil moisture storage change (ΔSMS) was calculated at + 0.0008 ± 0.0002 cm yr−1; (3) the average groundwater depletion rate was computed at −0.48 ± 0.02 cm yr−1; (4) the average yearly rainfall data for the Wadi Al Dawasir was 90.1 mm; (5) The surface relief is creating eastward streams that carry surface water downstream; (6) Significant agricultural expansions over the past few decades can be observed through Landsat change detection; (7) Higher sediment accumulation varying from 400 to more than 3000 m is observed in the east, near the Wadi's downstream, where the Wajid aquifer can be found. The integrated approach is a cost-effective and efficient tool for accurately evaluating the variability of groundwater resources over large regions.

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.

Providing Enhanced Insights into Groundwater Exchange Patterns through Downscaled GRACE Data

The measurement of groundwater exchange between neighboring regions is a critical topic in water resource management and can usually be achieved through a combination of field investigations and the use of groundwater flow models. In this study, we employed the water balance and Darcy’s law methods, utilizing downscaled Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) data to assess groundwater exchange patterns in the Beijing-Tianjin-Hebei (BTH) region of China. Additionally, we determined the contributions of human activities and climate factors to the observed variations via residual analysis. The results revealed a consistent decrease in groundwater storage in the study area since 2008, especially in the spring and summer months. The groundwater exchange rates calculated by 1° and 0.05° groundwater storage anomalies (GWSAs) were basically consistent, and the downscaled GWSAs could better reflect the small-scale groundwater exchange characteristics. The groundwater exchange rate showed a decreasing trend from the Piedmont plain to the coastal areas. A notable trend of declining groundwater exchange between the Taihang Mountains and Piedmont plains was observed, and the downward trend gradually intensified from north to south between 2003 and 2007. After 2008, there was an increasing trend, and coastal areas exhibited the smallest amount of groundwater exchange. Human activities emerged as the predominant factor accounting for more than 90.9% of the overall reduction in groundwater storage, while climate change imposed a minimal influence on groundwater storage variations. The insights obtained in this study hold significant implications for groundwater resource planning and management in the region.

Evaluating groundwater resources trends through multiple conceptual models and GRACE satellite data.

In this research, three numerical groundwater flow models, developed and calibrated from three equally plausible conceptual models over the Nasia Basin, have been used to assess groundwater resources variations over a transient period. The use of multiple numerical models reduces the effect of uncertainties in conceptual model formulation. All the three calibrated numerical models indicate an increasing trend of groundwater recharge and storage over the period of the groundwater level monitoring. This suggests that the prevailing erratic climatic conditions in the area are conducive for increasing groundwater recharge and storage in the terrain. The high-intensity, short duration rainfall patterns, attending climate change in the basin, enhance high levels of infiltration and percolation, leading to steadily increasing groundwater recharge. Groundwater recharge estimates from each of the models over the transient period appear to reflect the pattern of seasonal variations in rainfall in the region. Data from the models indicates a significant role of baseflow in sustaining perennial streamflow in the area. This presents a significant development in terms of groundwater-based adaptation projects, especially in agriculture. The trend of groundwater recharge in the Nasia Basin is in sync with regional groundwater storage variations estimated from the Gravity Recovery and Climate Experiment (GRACE) satellite data collected and processed over the Volta Basin. At the Volta Basin level, groundwater storage variations indicate a strong positive trend of increasing groundwater recharge from 2002 (beginning of the GRACE mission) to 2022 (end point of the data used for this research). Analysis of the GRACE data suggests that there is a cumulative increase in groundwater storage by 30cm, representing approximately 120 km3 of groundwater over the period in the basin. This translates into approximately 15mm/year of groundwater storage increase. Thus, at both the regional and local levels, groundwater appears to be responding positively to the impacts of erratic rainfall patterns observed in the area recently. The high-intensity, short duration rainfall patterns appear to favor significant groundwater recharge, resulting in a strong positive groundwater storage signal. The high positive groundwater storage signal suggests increasing groundwater resources potential in the area, indicating promising opportunities for groundwater-based climate change adaptation interventions.

Is groundwater running out in the Western Cape, South Africa? Evaluating GRACE data to assess groundwater storage during droughts

Study regionThe Western Cape (WC), South Africa. Study focusThe WC has become increasingly dependent on groundwater in recent years due to repeated droughts. A framework to monitor the regional groundwater levels is urgently required to sustainably manage the WC’s water resources, since the region has inconsistent or unavailable monitoring data. Therefore, this study aims to understand how Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data can be used to monitor groundwater storage variations (ΔGWS) in the WC. In-situ ΔGWS time-series from twelve aquifers in the WC were compared to GRACE and GLDAS data. New hydrological insights for the regionGRACE terrestrial water storage anomalies (ΔTWS) showed moderate positive correlation (r = 0.69) with in-situ ΔGWS from the Adelaide Subgroup Aquifer (ASA), an unconfined aquifer with large areal extent and large ΔGWS. The Table Mountain Group Upper Aquifer Unit (TMG UAU) and Cape Flats Aquifer (CFA) also showed significant positive correlations with GLDAS ΔGWS of 0.83 and 0.73, respectively. Our results suggest that ΔGWS in the ASA can be monitored using GRACE ΔTWS, while GLDAS ΔGWS data can be used to monitor ΔGWS in the unconfined TMG UAU and CFA. GRACE and GLDAS data may be suitable to monitor groundwater availability in other water- and data-scarce regions of Africa.

Downscaled GRACE/GRACE-FO observations for spatial and temporal monitoring of groundwater storage variations at the local scale using machine learning

Groundwater utilization for several purposes such as irrigation in agriculture, industry, and domestic use substantially impacts water storage. Groundwater Storage Anomaly (GWSA) estimates have improved owing to the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) advancements. However, the characterization of GWSA fluctuation hotspots has been hindered by the coarse resolution of GRACE data. To better measure groundwater storage and depletion variations throughout an area and identify GWSA variation hotspots, a fine spatial resolution of GWSA estimations is required. Therefore, due to the coarse resolution of GRACE measurements, the eXtreme Gradient Boosting (XGBoost) model was developed to simulate fine resolution 0.1° GWSA combining climatic variables (soil moisture storage, evapotranspiration, temperature, surface runoff, and rainfall) from improved spatial high resolution FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) model derived data and geospatial variables (elevation, slope, and aspect) extracted from Digital Elevation Model (DEM). A correlation of 0.98 demonstrated that the XGBoost model successfully simulated groundwater storage at a finer scale over the Upper Indus Plain Aquifer (UIPA). The findings suggested that the UIPA's groundwater storage has been depleted at an annual rate of 0.44 km3/yr which was 7.94 km3 in total between 2003 and 2020. According to the results, there seems to be consistency between the downscaled and original GWSA regarding temporal and spatial variability. The results were verified to show an improved correlation of 0.77 between the downscaled and the in-situ GWSA, compared to 0.75 between the GRACE-derived and the in-situ GWSA.

Multi-sensor observations for monitoring groundwater depletion and land subsidence

Study regionThe Kabudarahang Plain and the Razan-Qahavand Plain. Study focusImproper use of water resources has reduced groundwater levels and created land subsidence (LS) in many plains of Iran. The aim and innovation of this research are to study multi-sensor observations for LS and groundwater depletion and explore the relationships of the involved variables with high confidence. The gravity recovery and climate experiment (GRACE) observations can be used to evaluate water storage changes at the Earth’s surface. GRACE has stripe errors, leakage and various noises that multilevel 3D wavelet decomposition (M3WD) has been suggested to mitigate noises and downscale for small scale. This study has investigated the interferometric synthetic-aperture radar (InSAR) of Sentinel-1 images from October 2014 to September 2019, the GRACE data from March 2002 to July 2016, and groundwater hydrograph (GH) from 2014 to 2020. New hydrological insight for the regionThe maximum LS rate, obtained from small baseline subset-differential of InSAR is 20 mm/year at the Kabudarahang Plain (KP) and 30 mm/year at Razan-Qahavand Plain (RQP). The groundwater storage variations (ΔGW) have a decreasing trend of 78.45 ± 0.2 million cubic meters/year. The GH for the KP and RQP shows a downward trend of 3.25 and 1.81 m/year, respectively. Based on the outcomes, the M3WD can increase the correlation of ΔGW with other sensors by 15 %. Also, validation between sensors with normalized cross-correlation has remarkable compatibility. The multi-sensor study of ΔGW and LS revealed various dimensions with high reliability and can facilitate the water resource management.

Identifying potential hotspots of groundwater-climate interaction in the Great Artesian Basin, Australia

Groundwater aquifers around the world are experiencing stress due to the composite influence of climate change and excessive groundwater withdrawal. Despite this influence, there is still insufficient knowledge on climate-groundwater interaction dynamics in complex aquifers like Australia's Great Artesian Basin. This understanding can inform improved management, which can in turn, increase resilience of groundwater system to on-going groundwater withdrawal and climate change. The main aim of this research was to assess the impacts of climatic change on groundwater storage (GWS) changes over the Great Artesian Basin (GAB) using a range of multi-scale indicators, including Gravity Recovery and Climate Experiment (GRACE)-derived groundwater observations and standardized precipitation evapotranspiration indices (SPEI). Rotated principal component analysis (rPCA) was used to identify climatic hotspots (where GWS variation is particularly sensitive or vulnerable to the impacts of climate change), and correlation analyses were used to assess the relationship between these hotspots and changes in groundwater over space and time. The localized spatial pattern via rPCA was uncovered in the GAB's southeastern region, where annual variations in GWS exhibited conspicuous peaks in 2002, 2014, and 2015. Another finding was that the southeast region of the GAB experienced higher GWS variations as compared to other sub-basins during 2007–2008, which resulted in low groundwater recharge. These findings underscore the variations in GWS within the GAB, emphasizing its responsiveness to climatic variations (e.g., rainfall contributes to recharge of groundwater system and drought intensifies water extraction and restricts discharge). Moreover, this study found a substantial negative correlation (r = −0.7), between SPEI at 12-month scale and GWS variation in the southern GAB region. This relationship highlights the vulnerability of groundwater storage in the southern GAB region to prolonged drought conditions. Furthermore, this study identified positive correlations (r = 0.4 to 0.8), between key climate indices such as the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) with GWS anomalies in the southeast and northern GAB regions. These correlations underscore the pivotal roles played by ENSO and PDO in shaping GWS variations in these areas, highlighting the need to incorporate an understanding of these climatic processes into water resource management strategies. This consideration is crucial for ensuring sustainable water management practices that can adapt to the influence of these climate phenomena. These findings provide essential insights into the dynamics of groundwater in the face of changing environmental conditions, with implications for sustainable water management.

Spatial and temporal downscaling schemes to reconstruct high-resolution GRACE data: A case study in the Tarim River Basin, Northwest China

Climate change and excessive exploitation of water resources exert pressure on groundwater supply and the ecosystem in drylands. Although The Gravity Recovery and Climate Experiment (GRACE) satellites has demonstrated the feasibility of quantifying global groundwater storage variations, monitoring regional-scale groundwater has been challenging due to the coarse resolution of GRACE. Previous GRACE downscaling studies focused on develop new algorithms based on the perspective of pixel spatial correlation to improve resolution, which cannot better capture the temporal evolution of GRACE data effectively. In this study, we employ the semi-supervised variational autoencoder (SSVAER) algorithm and the multi-scale geographically weighted regression (MGWR) model to establish two different downscaling schemes: pixel temporal continuity downscaling and pixel spatial correlation downscaling. These schemes achieve spatial resolution downscaling of GRACE-derived groundwater storage anomalies (GWSA) from 0.5° to 0.1°. Additionally, the applicability of the PCR-GLOBWB model in drylands is verified. Furtherly, the spatiotemporal distribution patterns of GWSA are analyzed. The results show that (1) Both the temporal and spatial downscaling methods produced consistent results, with data correlations ranged from 0.94 to 0.98 observed in over 80 % of the range before and after downscaling; (2) The groundwater storage change rate in the northern Tarim River Basin (TRB) is 25 times greater than the model results, while in other regions, the average deviation is 2.6 times; (3) The two schemes enhance the correlation (0.27) between GWSA and groundwater level anomaly (GWLA) to 0.59 and 0.52, respectively, with a three-month lag in GWSA relative to GWLA. The temporal downscaling approach exhibited higher CC and lower RMSE, outperforming the spatial downscaling approach. The high-resolution results in this study can well complement groundwater level prediction efforts in arid regions and provide quantitative information for local water resource management.

Groundwater Storage Variations in the Main Karoo Aquifer Estimated Using GRACE and GPS

The Gravity Recovery and Climate Experiment (GRACE) provided valuable insights into variations in Groundwater Storage (GWS). However, the sensitivity of utilizing Global Positioning System (GPS) time series displacement data for detecting changes in GWS remains a subject of ongoing discussion. In order to estimate the spatiotemporal GWS, we selected a vertical displacement from 65 GPS stations located in the Main Karoo Aquifer (MKA). We performed total water storage (TWS) inversion on GPS vertical displacement components; after that, we deducted surface water components based on the Global Land Data Assimilation System (GLDAS) from January 2013 to December 2021. Additionally, for validation, we compared our GWS estimates with the GRACE-derived GWS and observed GWS values derived from the WaterGAP Global Hydrology Model (WGHM) compartments. We discovered that the TWS and GWS trends derived from GPS and GRACE exhibited similar behaviors with trend values overestimated by GRACE and WGHM. Our findings demonstrate relatively typical behavior between GPS and GRACE in the first and second principal component behaviors (PCs) and empirical orthogonal function (EOF) loadings (or spatial patterns). With a contribution of 71.83% to GPS-derived GWS variability and 68.92% to GRACE-derived GWS variability, EOF-1 is a relatively potent factor. For Principal Components PC1 and PC2, the GRACE and GPS PCs have correlation coefficients of 0.75 and 0.84, respectively. Finally, with higher temporal resolution, GPS can perform the same task as GRACE in hydrological applications. In addition, GPS can add important and valuable information to assess regional GWS change.

Contributions of Climate Variability and Anthropogenic Activities to Confined Groundwater Storage in Hengshui, North China Plain

Groundwater storage (GWS) in confined aquifer systems is often influenced by climate variability and anthropogenic activities, and it is vital to quantify their contributions for the purpose of groundwater management and surface water allocation plans. In this study, we characterize the spatiotemporal evolution of the GWS in confined aquifer systems across Hengshui, North China Plain, and investigate its relationships with changing climate conditions and human activities through the integration of InSAR-derived surface displacements with hydraulic head observations and precipitation data, during 2004–2010 and 2016–2020. Our results indicate that the GWS in confined aquifer systems decreased markedly by 4.59 ± 0.35 km3 with an accelerating trend during the study period. The GWS variations show a strong correlation with precipitation during irrigation periods (March to July), and hence, the climate and anthropogenic-driven GWS variations can be separated from each other with a linear model. We find that the GWS depletion caused by climate variability and anthropogenic activities were −0.31 ± 0.10 km3 and −4.28 ± 0.40 km3, respectively, during the study period. The mean contribution of anthropogenic activities to the GWS variations was −71.9%, implying that the GWS variations in confined aquifer systems were primarily anthropogenic driven. It is also found that the well observations alone poorly characterize the spatiotemporal evolution of the GWS due to their limited spatial density, and the integrated InSAR/well approach appears to be promising for overcoming this challenge.

Evaluation of shallow groundwater dynamics after water supplement in North China Plain based on attention-GRU model

The continuous ecological river supplement has enhanced the recharge of groundwater in the North China Plain, and alleviated the depletion of groundwater resources. In the study of ecological river supplement, efficient quantitative prediction of groundwater level (GWL) and groundwater storage (GWS) is a crucial issue. To predict GWL and estimate the variation of GWS in the North China Plain, this paper uses the attention-gated recurrent unit (Attention-GRU) model as a primary method and coefficient of determination (R2) and root mean square error (RMSE) as the indices to evaluate model performance. Compared to traditional recursive neural network (RNN) and long short-term memory (LSTM) model, Attention-GRU model demonstrated an outstanding performance, as the RMSE is respectively 0.5 m and 2.28 m in the training and testing periods, and the R2 is 0.87 and 0.68. With the usage of the convolution neural network (CNN) model, the specific yield field was continuously updated from 2018 to 2021. The average annual variation of GWS estimated by this method is respectively −15.19 × 104 m3, −13.29 × 104 m3, 2.55×104 m3 and 100.05×104 m3 from 2018 to 2021 in the North China Plain. Besides, the semiannual GWS variation, calculated using the updated specific yield, is −59.56 × 104 m3 in 2022. Furthermore, the influence of the reference time length and the driving factors were evaluated. Results show that the precipitation, evaporation and human activities are the most important temporal features influencing the changes in GWS, and the changes in different areas have varying local characteristics. In the piedmont plain, river ecological recharge played a crucial role for groundwater storage recovery. When it moved to the coastal plain, the contribution rate of recharge decreased from 23% to 11%. In addition, the optimal reference time length used in Attention-GRU model varies in different hydrogeology divisions, and the specific yield variation would result in substantial differences for the GWS estimation under different climate conditions and human activities. The systematic framework proposed in this paper is effective for evaluating and predicting GWL and GWS, and thereby able to support the management and development of groundwater, and provide a guidance for ecological river supplement.

Terrestrial and groundwater storage characteristics and their quantification in the Chitral (Pakistan) and Kabul (Afghanistan) river basins using GRACE/GRACE-FO satellite data

In Pakistan and Afghanistan, intensive groundwater abstraction has accelerated socioeconomic development, but it also endangers the long-term sustainability of groundwater resources. Sustainable water resource management throughout river basins requires a spatiotemporal analysis of groundwater storage changes, but continuous groundwater monitoring is critical while there are few observation wells in the Chitral Kabul River Basin (CKRB). Therefore, this study uses total water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-on (GRACE-FO) and the Global Land Data Assimilation System (GLDAS) model water storage components, such as surface runoff (Qs), soil moisture content (SMS), and snow water equivalent (SWE) to determine the characteristics of groundwater storage (GWS) variations from 2003 to 2021. The seasonal decomposition LOESS method (STL) was used to assess the long-term trend, seasonal trend, and associated uncertainty of TWS and GWS time-series, while Mann-Kendall and Sen's slope estimator was used to detect and quantify the increasing and decreasing trend values of TWS and GWS time-series. The results showed that TWS indicated a general decreasing trend of − 3.67 ± 0.98 mm/month while GWS indicated a harsh declining trend of − 7.83 ± 0.52 mm/month from 2003 to 2021 in CKRB. The validation of GRACE-derived GWS results showed a correlation of R2 = 0.47 in comparison to in situ GWS. Spatially and temporally, according to sub-basins of CKRB, the more severe decline of TWS in Chitral-Kunar (− 2.66 mm/year) and GWS in Swat (− 4.34 mm/year) was observed. This research would be insightful to estimate the agroeconomic impact of the intensive groundwater in CKRB and its sub-basins.

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 18years. 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.

Spatial-temporal variations of groundwater storage in China: A multiscale analysis based on GRACE data

Groundwater storage (GWS) plays a key role in the freshwater supply in China. Revealing the changes in GWS in China is critical for realizing sustainable utilization of groundwater resources. We used Gravity Recovery and Climate Experiment (GRACE) satellite data as well as HydroSHEDS datasets to quantify the variation of GWS in China from 2003 to 2020 at multiple scales. We found that GWS was decreasing at a rate of -2.09 mm/a in China. Three hot-spot areas with dramatic GWS decrease, located in Northwest, Southwest and North China, accounted for 55.52% of the total GWS decrease in China, and the reduction in GWS in these areas was driven primarily by human activities. Additionally, more than half of the urban agglomerations in China potentially impacted by the declining GWS. Therefore, it is suggested that targeted measures should be taken according to local conditions to strengthen the scientific management of groundwater.