Groundwater Storage Assessment Using Effective Downscaling GRACE Data in Water-Stressed Regions of India

Dynamic change of groundwater storage is one of the most important topics in the sustainable management of groundwater resources. Groundwater storage variations are firstly isolated from the terrestrial water storage change using the Global Land Data Assimilation System (GLDAS). Two datasets are used: (1) annual groundwater resources and (2) groundwater storage changes estimated from point-based groundwater level data in observation wells. Results show that the match between the GRACE-derived groundwater storage variations and annual water resources variation is not good in six river basins of Northern China. However, it is relatively good between yearly GRACE-derived groundwater storage data and groundwater storage change dataset in Huang-Huai-Hai Plain and the Song-Liao Plain. The mean annual depletion rate of groundwater storage in the Northern China was approximately 1.70 billion m3 yr−1 from 2003 to 2012. In terms of provinces, the yearly depletion rate is higher in Jing-Jin-Ji (Beijing, Tianjin, and Hebei province) and lowest in Henan province from 2003 to 2012, with the rate of 0.70 and 0.21 cm yr−1 Equivalent Water Height (EWH), respectively. Different land surface models suggest that the patterns from different models almost remain the same, and soil moisture variations are generally bigger than snow water equivalent variations.

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Assessing Impacts of Climate Extremes and Human Water Use on GRACE Total Water Storage Trends in Major U.S. Aquifers

10.5194/gstm2020-61 ◽

2020 ◽

Author(s):

Bridget Scanlon ◽

Ashraf Rateb ◽

Alexander Sun ◽

Himanshu Save

Keyword(s):

Surface Water ◽

Water Use ◽

Groundwater Level ◽

Water Storage ◽

Climate Extremes ◽

High Plains ◽

Total Water ◽

Groundwater Storage ◽

Grace Data ◽

The U.S

There is considerable concern about water depletion caused by climate extremes (e.g., drought) and human water use in the U.S. and globally. Major U.S. aquifers provide an ideal laboratory to assess water storage changes from GRACE satellites because the aquifers are intensively monitored and modeled. The objective of this study was to assess the relative importance of climate extremes and human water use on GRACE Total Water Storage Anomalies in 14 major U.S. aquifers and to evaluate the reliability of the GRACE data by comparing with groundwater level monitoring (~-23,000 wells) and regional and global models. We quantified total water and groundwater storage anomalies over 2002 &#8211; 2017 from GRACE satellites and compared GRACE data with groundwater level monitoring and regional and global modeling results. &#160; The results show that water storage changes were controlled primarily by climate extremes and amplified or dampened by human water use, primarily irrigation. The results were somewhat surprising, with stable or rising long-term trends in the majority of aquifers with large scale depletion limited to agricultural areas in the semi-arid southwest and southcentral U.S. GRACE total water storage in the California Central Valley and Central/Southern High Plains aquifers was depleted by drought and amplified by groundwater irrigation, totaling ~70 km3 (2002&#8211;2017), about 2&#215; the capacity of Lake Mead, the largest surface reservoir in the U.S. In the Pacific Northwest and Northern High Plains aquifers, lower drought intensities were partially dampened by conjunctive use of surface water and groundwater for irrigation and managed aquifer recharge, increasing water storage by up to 22 km3 in the Northern High Plains over the 15 yr period. GRACE-derived total water storage changes in the remaining aquifers were stable or slightly rising throughout the rest of the U.S. GRACE data compared favorably with composite groundwater level hydrographs for most aquifers except for those with very low signals, indicating that GRACE tracks groundwater storage dynamics. Comparison with regional models was restricted to the limited overlap periods but showed good correspondence for modeled aquifers with the exception of the Mississippi Embayment, where the modeled trend is 4x the GRACE trend. The discrepancy is attributed to uncertainties in model storage parameters and groundwater/surface water interactions. Global hydrologic models (WGHM-2d and PCR-GLOBWB-5.0 overestimated trends in groundwater storage in heavily exploited aquifers in the southwestern and southcentral U.S. Land surface models (CLSM-F2.5 and NOAH-MP) seem to track GRACE TWSAs better than global hydrologic models but underestimated TWS trends in aquifers dominated by irrigation. Intercomparing GRACE, traditional hydrologic monitoring, and modeling data underscore the importance of considering all data sources to constrain water storage changes.&#160; GRACE satellite data have critical implications for many nationally important aquifers, highlighting the importance of conjunctively using surface-water and groundwater and managed aquifer recharge to enhance sustainable development.

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Reconstructing annual groundwater storage changes in a large-scale irrigation region using GRACE data and Budyko model

Journal of Hydrology ◽

10.1016/j.jhydrol.2017.06.021 ◽

2017 ◽

Vol 551 ◽

pp. 397-406 ◽

Cited By ~ 18

Author(s):

Yin Tang ◽

Milad Hooshyar ◽

Tingju Zhu ◽

Claudia Ringler ◽

Alexander Y. Sun ◽

...

Keyword(s):

Large Scale ◽

Groundwater Storage ◽

Grace Data

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Improving the Resolution of GRACE Data for Spatio-Temporal Groundwater Storage Assessment

Remote Sensing ◽

10.3390/rs13173513 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3513

Author(s):

Shoaib Ali ◽

Dong Liu ◽

Qiang Fu ◽

Muhammad Jehanzeb Masud Cheema ◽

Quoc Bao Pham ◽

...

Keyword(s):

Spatial Scale ◽

Regional Scale ◽

Water Storage ◽

Slope Aspect ◽

Small Scale ◽

Ann Model ◽

Groundwater Storage ◽

Large Spatial Scale ◽

Grace Data ◽

Hydrological Variables

Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about −9.54 ± 1.27 km3 at the rate of −0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.

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Comparing Groundwater Storage Changes in Two Main Grain Producing Areas in China: Implications for Sustainable Agricultural Water Resources Management

Remote Sensing ◽

10.3390/rs12132151 ◽

2020 ◽

Vol 12 (13) ◽

pp. 2151 ◽

Cited By ~ 3

Author(s):

Longqun Zheng ◽

Yun Pan ◽

Huili Gong ◽

Zhiyong Huang ◽

Chong Zhang

Keyword(s):

Food Production ◽

Groundwater Abstraction ◽

Groundwater Storage ◽

The North ◽

Grace Data ◽

Groundwater Supply ◽

Agricultural Water Resources ◽

Gravity Recovery ◽

Sown Area ◽

Additional Area

Balancing groundwater supply and food production is challenging, especially in large regions where there is often insufficient information on the groundwater budget, such as in the North China Plain (NCP) and the Northeast China Plain (NECP), which are major food producing areas in China. This study aimed to understand this process in a simple but efficient way by using Gravity Recovery and Climate Experiment (GRACE) data, and it focused on historical and projected groundwater storage (GWS) changes in response to changes in grain-sown areas. The results showed that during 2003–2016, the GWS was depleted in the NCP at a rate of −17.2 ± 0.8 mm/yr despite a decrease in groundwater abstraction along with an increase in food production and a stable sown area, while in the NECP, the GWS increased by 2.3 ± 0.7 mm/yr and the groundwater abstraction, food production and the sown area also increased. The scenario simulation using GRACE-derived GWS anomalies during 2003–2016 as the baseline showed that the GWS changes in the NCP can be balanced (i.e., no decreasing trend in storage) by reducing the area of winter wheat and maize by 1.31 × 106 ha and 3.21 × 106 ha, respectively, or by reducing both by 0.93 × 106 ha. In the NECP, the groundwater can sustain an additional area of 0.62 × 106 ha of maize without a decrease in storage. The results also revealed that the current groundwater management policies cannot facilitate the recovery of the GWS in the NCP unless the sown ratio of drought-resistance wheat is increased from 90% to 95%. This study highlights the effectiveness of using GRACE to understanding the nexus between groundwater supply and food production at large scales.

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Understanding the effects of climate warming on streamflow and active groundwater storage in an alpine catchment: the upper Lhasa River

Hydrology and Earth System Sciences ◽

10.5194/hess-24-1145-2020 ◽

2020 ◽

Vol 24 (3) ◽

pp. 1145-1157

Author(s):

Lu Lin ◽

Man Gao ◽

Jintao Liu ◽

Jiarong Wang ◽

Shuhong Wang ◽

...

Keyword(s):

River Basin ◽

Air Temperature ◽

Climate Warming ◽

Gray Relational Analysis ◽

Permafrost Degradation ◽

Groundwater Storage ◽

Alpine Regions ◽

Grace Data ◽

Lhasa River Basin ◽

Lhasa River

Abstract. Climate warming is changing streamflow regimes and groundwater storage in cold alpine regions. In this study, the Yangbajain headwater catchment in the Lhasa River basin is adopted as the study area to assess streamflow changes and active groundwater storage in response to climate warming. The results show that both annual streamflow and the mean air temperature increase significantly at respective rates of about 12.30 mm per decade and 0.28 ∘C per decade from 1979 to 2013 in the study area. The results of gray relational analysis indicate that the air temperature acts as a primary factor for the increased streamflow. Due to climate warming, the total glacier volume has retreated by over 25 % during the past 50 years, and the areal extent of permafrost has degraded by 15.3 % over the last 20 years. Parallel comparisons with other subbasins in the Lhasa River basin indirectly reveal that the increased streamflow at the Yangbajain Station is mainly fed by the accelerated glacier retreat. Using baseflow recession analysis, we also find that the estimated groundwater storage that is comparable with the GRACE data increases significantly at rates of about 19.32 mm per decade during the abovementioned period. That is to say, as permafrost thaws, more spaces have been made available to accommodate the increasing meltwater. Finally, a large water imbalance (of more than 5.79×107 m3 a−1) between the melt-derived runoff and the actual increase in runoff as well as the groundwater storage is also observed. The results from this study suggest that the impacts of glacial retreat and permafrost degradation show compound behaviors on the storage–discharge mechanism due to climate warming, and that this fundamentally affects the water supply and the mechanisms of streamflow generation and change.

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The appraisal of groundwater storage dwindling effect, by applying high resolution downscaling GRACE data in and around Mehsana district, Gujarat, India

Groundwater for Sustainable Development ◽

10.1016/j.gsd.2021.100559 ◽

2021 ◽

Vol 13 ◽

pp. 100559

Author(s):

Anuradha Karunakalage ◽

Tandrila Sarkar ◽

Suresh Kannaujiya ◽

Prakash Chauhan ◽

Pranshu Pranjal ◽

...

Keyword(s):

High Resolution ◽

Groundwater Storage ◽

Grace Data

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

Remote Sensing ◽

10.3390/rs14010202 ◽

2022 ◽

Vol 14 (1) ◽

pp. 202

Author(s):

Kai Su ◽

Wei Zheng ◽

Wenjie Yin ◽

Litang Hu ◽

Yifan Shen

Keyword(s):

Human Factors ◽

River Basin ◽

Groundwater Level ◽

Efficiency Coefficient ◽

Fusion Model ◽

Groundwater Storage ◽

Effective Measure ◽

Weighted Fusion ◽

Grace Data

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.

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