Snowfall Replenishes Groundwater Loss in the Great Basin of the Western United States, but Cannot Compensate for Increasing Aridification Dorothy K. Hall1,2 , Bryant D. Loomis3 , Nicolo E. DiGirolamo2,4, and Barton A. Forman5 1Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA, 2Cryospheric Sciences Laboratory, NASA/Goddard Space Flight Center, Greenbelt, MD, USA, 3Geodesy and Geophysics Laboratory, NASA/ Goddard Space Flight Center, Greenbelt, MD, USA, 4Science Systems Applications, Inc., Lanham, MD, USA, 5Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA Abstract There has been an acceleration of groundwater loss in the Great Basin (GB) of the western U.S. as determined from total water storage (TWS) measurements from the GRACE/FO satellite missions. From 2002 to 2023, there was a loss of TWS in the GB of ∼68.7 km3 which is more than six times the current volume of the Lake Mead Reservoir. In this arid/semi‐arid region, groundwater is the primary factor contributing to the decade‐scale decline in TWS. Stronger declining trends are found in the western versus the eastern GB. Snow loading is the major cause of seasonal fluctuations of TWS in the GB. Despite annual replenishment of groundwater by snow, the downward trend persists even in notable snow years. Likely causes include declining snow mass, upstream water diversions and increased evaporation/sublimation due to increasing temperatures. Dire consequences for humans and wildlife are associated with this large loss of groundwater. Plain Language Summary The 21st Century megadrought in the southwestern U.S. caused a dramatic acceleration of groundwater loss in the Great Basin (GB) of the western U.S. as determined from changes in the Earth's gravity measured by the GRACE satellites. Groundwater is a major component of total water storage (TWS) in the GB, but snowfall and snowmelt are the major causes of seasonal fluctuations of TWS. As a snowpack accumulates or melts, water is redistributed causing a rapid regional change in gravity that can be measured from space. From 2002 to 2023, there is a substantial loss of groundwater in the GB of ∼68.7 km3 which is more than six times the current volume of water in the Lake Mead Reservoir in Arizona/Nevada. Stronger declining trends of groundwater loss are found in the western part of the GB while weaker declining trends are found in the eastern part. Despite annual replenishment by snowfall, even in notable snow years like 2010–2011, 2016–2017, 2018–2019, and 2022– 2023, the downward trend of groundwater depletion persists. Likely causes for this decline include declining snow mass, upstream water diversions and increased evaporation/sublimation due to increasing air and surface temperatures. Groundwater depletion is associated with dire consequences for humans and wildlife. 1. Introduction Since 1999, the southwestern U.S. has faced prolonged drought (Williams et al., 2022) characterized by rising temperatures, and diminishing snowfall (until the 2022–2023 winter). Elevated temperatures have led to reduced snowfall, fewer days of snow cover, lower soil moisture, more wildfires, tree loss (Abatzoglou &Williams, 2016; Yi et al., 2022), general aridification (Overpeck & Udall, 2020), and reduced water levels in lakes and reservoirs (Yao et al., 2023; Zhao et al., 2022) necessitating greater use of groundwater for agricultural and other needs (Famiglietti et al., 2011). The drought has accelerated desiccation of terminal lakes in the Great Basin (GB), with “toxic dust” from expanding lakebeds contributing to air pollution during windstorms (Hall et al., 2021, 2023; Larson, 2024; Larson et al., 2016; Wurtsbaugh et al., 2017). The Great Basin is a closed basin located in the western United States (Figure S1 in Supporting Informa- tion S1). While the majority of the water enters via snowfall in the winter months, water (largely from snow) leaves almost exclusively via evaporation, sublimation and consumptive water use (Milly & Dunne, 2020; Zhao & Gao, 2019). Gravimetry data from the Gravity Recovery And Climate Experiment (GRACE) and GRACE‐ RESEARCH LETTER 10.1029/2023GL107913 Key Points: • Snow accumulation in the Great Basin (GB) triggers an increase in total water storage (TWS) while snow ablation triggers a drop in TWS • There is an 68.7 km3 loss of groundwater in the GB from 2002 to 2023 which is more than six times greater than the current volume of Lake Mead • The 2002–2023 TWS decline in the GB is more pronounced in the western GB than in the eastern GB Supporting Information: Supporting Information may be found in the online version of this article. Correspondence to: D. K. Hall, dkhall1@umd.edu Citation: Hall, D. K., Loomis, B. D., DiGirolamo, N. E., & Forman, B. A. (2024). Snowfall replenishes groundwater loss in the Great Basin of the western United States, but cannot compensate for increasing aridification. Geophysical Research Letters, 51, e2023GL107913. https://doi. org/10.1029/2023GL107913 Received 18 DEC 2023 Accepted 11 MAR 2024 Author Contributions: Conceptualization: Dorothy K. Hall, Bryant D. Loomis Data curation: Dorothy K. Hall Formal analysis: Dorothy K. Hall, Bryant D. Loomis Funding acquisition: Dorothy K. Hall Investigation: Dorothy K. Hall Methodology: Dorothy K. Hall, Bryant D. Loomis, Nicolo E. DiGirolamo Project administration: Dorothy K. Hall Resources: Dorothy K. Hall Software: Bryant D. Loomis, Nicolo E. DiGirolamo Supervision: Dorothy K. Hall Validation: Dorothy K. Hall, Nicolo E. DiGirolamo © 2024. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. HALL ET AL. 1 of 8 https://orcid.org/0000-0001-8921-0773 https://orcid.org/0000-0002-9370-9160 mailto:dkhall1@umd.edu https://doi.org/10.1029/2023GL107913 https://doi.org/10.1029/2023GL107913 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://crossmark.crossref.org/dialog/?doi=10.1029%2F2023GL107913&domain=pdf&date_stamp=2024-03-20 Follow‐on (GRACE‐FO) missions, hereafter, GRACE/FO, may be used to measure total water storage (TWS) changes in the GB. TWS consists of groundwater, surface water, snow and ice, soil moisture and atmospheric water vapor. Snow and groundwater are the primary components of the TWS in the arid/semi‐arid GB. GRACE/FO measures variations in the Earth's gravity field to reveal changes in water storage (Rodell & Famiglietti, 1999). There has been tremendous progress in detecting groundwater changes from space since the launch of GRACE in 2002 (e.g., Rodell & Li, 2023; Rodell et al., 2009; Solander et al., 2017). Research shows that most of the major aquifers in the dry areas of the world are being depleted (Famiglietti, 2014) thus threatening water security in densely populated regions worldwide. The rates of depletion of groundwater storage in India, and in the major reservoirs in the Colorado River Basin exceed the rate of replenishment (Castle et al., 2014; Rodell et al., 2009). Unsustainable depletion of groundwater in California's highly‐ productive Central Valley, just west of the Great Basin, has also been documented (Famiglietti et al., 2011; Liu et al., 2022; Xiao et al., 2017). Groundwater is the primary source of water for irrigation during drought conditions. Changes in snow mass have been less studied than mass changes resulting from melting ice (e.g., Loomis, Richey, et al., 2019; Loomis et al., 2021; Luthcke et al., 2013), though there has been notable snow‐related research using GRACE/FO. Notarnicola (2020) showed that seasonal variations of TWS are influenced by snow‐covered area as determined from MODIS daily snow‐cover map products. Yin et al. (2020) measured vertical displacement changes related to seasonal hydrologic loading in the GB and Upper Colorado water- sheds, noting downward movement in winter due to snow loading and upward motion in summer from snow melting. Other relevant studies employing GRACE/FO data to study snow loading include Niu et al. (2007), Wang et al. (2017), and Behrangi et al. (2018). Predating GRACE, Chao et al. (1987) and Chao and O'Con- nor (1988) investigated snow‐load effects on Earth's rotation and gravitational field, emphasizing dominant seasonal cycles caused by shifts in snow loading. With the advent of GRACE, regional studies on a monthly time scale became tractable. In this work, we use both the GSFC GRACE/FO standard monthly mass concentration (mascon) (Loomis, Luthcke, & Sabaka, 2019) and the GSFC high‐resolution trend mascon (Loomis et al., 2021) data sets for a study period extending from 2002 to 2023. We also use standard data products from the MODerate‐resolution Imaging Spectroradiometer (MODIS) on the Terra satellite, and surrogate indicators of snow mass to examine the rela- tionship between monthly and decade‐scale changes in snow mass and TWS in the GB during the 21st Century megadrought. 2. Data and Methods GRACE was a joint space mission between NASA and the German Aerospace Center; the mission operated from March 2002 to October 2017 (Tapley et al., 2004). It consisted of two identical satellites orbiting in tandem around the Earth with an approximate separation distance of 220 km. Precise measurements of the satellite range changes were used to compute changes in the Earth's gravity. Utilizing the same mission concept, GRACE Follow‐On was launched in May 2018 as a partnership between NASA and the German Research Centre for Geosciences. Though the record is not continuous, the GRACE/FO record spans more than 21 years. We use both the GSFC standard monthly mascon data with a spatial resolution of ∼300–500 km (Loomis, Luthcke, & Sabaka, 2019) and the new GSFC higher‐resolution trend mascon yearly data with a resolution of ∼110 km (Loomis et al., 2021). Utilizing the high‐resolution trend mascon data enhances the capability to locate the source of the signal, and provides more precise measurements of mass rates or totals, but provides a lower temporal resolution (yearly) as compared to the standard (monthly) data products. All data products were gridded to a 500‐m resolution grid. MODIS standard data products have provided global maps of the Earth at 250‐m, 500‐m or 1‐km resolution and have been used extensively to map geophysical changes since early 2000 (Román et al., 2024). The NASA standard data products used in this work are daily snow‐cover extent and land surface temperature (LST) from the MODIS sensor on the Terra satellite. These data products are well characterized and validated over a global set of sites (MODIS Land, 2023). Visualization: Dorothy K. Hall Writing – original draft:Dorothy K. Hall Writing – review & editing: Dorothy K. Hall, Bryant D. Loomis Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 2 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 2.1. GRACE/FO Mascon Data Sets Trend data from the RL6v02 GSFC GRACE/FO 1‐arc degree standard monthly mascons (Loomis, Luthcke, & Sabaka, 2019) and mascons from the GSFC high‐resolution trend mascon product (Loomis et al., 2021) were used to measure change, and trends in centimeters of water equivalent (CMWE) from April 2002–September 2023. TWS was calculated from the CMWE data (Equation S1 in Supporting Information S1). The GSFC high‐ resolution trend mascon data may be found in a Zenodo data repository (Hall & DiGirolamo, 2024). Additionally, Jet Propulsion Laboratory (JPL) RL06/1v03 (JPL, 2024), and Center for Space Research (CSR), RL06.2 (CSR, 2024) monthly mascon trend data were also plotted. 2.2. Snow Mass Because we cannot measure snow mass directly over the entire GB, we used three surrogate indicators: (a) mean‐monthly snow‐water equivalent (SWE) from the SNOw Data Assimilation System (SNODAS); (b) number of days of snow cover per month from the daily MOD10A1F snow‐cover map products; and (c) mean‐monthly snow depth from meteorological and SNOw TELemetry (SNOTEL) stations (NOHRSC, 2004). Snow depth measure- ments, assumed accurate at individual station locations, may not provide a representative average in the GB due to wide separation or clustering of stations (Figure 1). Additionally, stations may be preferentially located in valleys, rather than on mountain peaks, thus there is a negative bias in snow depth measurements. In spite of some uncertainties, the surrogate indicators generally agree in terms of timing of peak snow and relative amounts of snow. We investigated the agreement of monthly values of each of the surrogate indicators (see Figure S2 and Table S1 in Supporting Information S1). 2.2.1. SWE SWE data were obtained from NOAA's National Weather Service (NWS) National Operational Hydrologic Remote Sensing Center (NOHRSC) SNODAS model (SNODAS, 2004), which has provided an estimate of daily SWE for the western U.S. and elsewhere since September 2003 (Carroll et al., 2001; NOHRSC, 2004). Absolute errors in SWE have been estimated at 11%–20% (Castle et al., 2014; Rutter et al., 2008). From the daily SWE data, we developed monthly averages for the GB. 2.2.2. Number of Days of Snow Cover The daily, cloud‐gap‐filled MODIS Collection 6.1 (C6.1) snow‐cover prod- uct, MOD10A1F (Hall & Riggs, 2020; Riggs et al., 2019), was used to map snow cover in the GB. Number of days (#days) of snow cover per month was calculated during each snow season (from day 1–182 of each water year (WY) from 2003 to 2023). 2.2.3. Snow Depth and Snowfall Snow depths were obtained from NOAA and SNOTEL stations in the GB (NCEI, 2023; SNOTEL, 2023). We selected 89 stations in the GB based on the following criteria: a station must have reported snow depth for at least 22 years of the 23‐year study period, with 75% of the days reporting a snow depth measurement (Figure 1). We calculated a mean‐monthly snow depth from the daily data. Snowfall data were available for most, but not all of the 89 stations; for the stations for which both were available, the snow depth and snowfall trends were highly correlated (R= 0.675); we chose to use snow depth as it is more stable as an indicator of snow mass change. Figure 1. Map showing the Great Basin (∼500 km2) with locations of the 89 stations (shown as blue dots) that were used to determine snow depth and snowfall. Note the clusters of stations in the East Sierra subregion and the Great Salt Lake Basin and the sparsity of stations in the rest of the GB. Figure 2. GSFC standard monthly mascon CMWE trend map, April 2002– September 2023. Colors represent departure from the 2002 baseline values of CMWE. The Great Basin, East Sierra subregion and the Great Salt Lake Basin are outlined in black. Individual mascons are shown as blocks outlined in light gray. Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 3 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 2.3. Land Surface Temperature (LST) MODIS LST daily C6.1 data products, MOD21A1D (daytime) and MOD21A1N (nighttime) (Hulley and Hook, 2021a, 2021b; Hulley et al., 2017), were used to calculate trends in LST in the GB, WY 2003–2023. Daytime and nighttime MODIS‐derived LST values for each day were averaged to develop a mean‐daily LST for each grid cell. Mean‐monthly LST and trends in LST were calculated. To fill in the gaps caused by clouds and short instrument outage periods when no MODIS data were obtained, a third‐order cubic polynomial (e.g., Wolfram, 2023) of the LST data was used to develop basin trend plots. 3. Results and Discussion 3.1. Trends in TWS in the Great Basin TWS has been declining in the GB as depicted by the red colors in the CMWE trend map from the GSFC standard monthly mascon data (Figure 2). There is a “hotspot” of decline over the Central Valley in southwestern Cali- fornia which is even more evident in the GSFC high‐resolution trend mascon maps (Figure 3), in which a sharply declining trend in the East Sierra subregion of the Sierra Nevada Mountains may also be seen. The rate of TWS loss is greatest in the southwestern and least in the northeastern parts of the GB, and it increases after ∼2012 (Figures 3b and 3c) and Figure 4. There is a loss of 89.3 km3 (4.2 km3/yr) of TWS in the GB as a whole, from April 2002–September 2023 as determined from the GSFC standard monthly mascon trend data (Figure 2). Over the same time period, using the GSFC high‐resolution trend mascons, a loss of 68.7 km3 (3.2 km3/yr) is found (Figure 3a). The high‐resolution data captures mass rates/totals more accurately by reducing the leakage of the very large mass loss signals in the Central Valley. The increasing rate of decline in TWS in the second half of the study period is especially notable in the East Sierra subregion (Figures 2–4). When the influence of seasonal snow loading is removed, the declining trend of groundwater in the GB may be seen as the trend lines in Figure 4. Monthly trends from the JPL and CSR mascon solutions were also plotted and reveal similar patterns though different trend numbers (Figure S5 in Supporting Information S1). Figure 3. (a, b, and c) Trend maps derived from GSFC high‐resolution trend mascon data, April 2002–September 2023. Colors represent departure from the 2002 baseline values of CMWE: (a) 2002–2023; (b) 2002–2011; (c) 2012–2023. The Great Basin, East Sierra subregion and the Great Salt Lake Basin are outlined in black. Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 4 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense The TWS decline derived from the high‐resolution trend mascon data, 68.7 km3, is more than six times the current (December 2023) volume of water in the Lake Mead Reservoir in Arizona/Nevada (Figure 5). Lake Mead is the largest reservoir in the U.S., providing water to nearly 20 million people. 3.2. TWS and Snow Mass The GSFC standard monthly mascon trend data are highly suited for com- parisons with monthly snow data (Figure 6). Despite “big” snow years (e.g., WY 2011, 2017, 2019, and 2023) mitigating TWS decline, the overall decline in TWS persists (Figure 4a). In Figure 6, mean‐monthly snow depth plotted with detrended monthly CMWE data demonstrates this relationship with a Pearson correlation coefficient of R = 0.76. There is a lag of ∼20 days be- tween the peak of snow depth and the approximate peak of CMWE in Figure 6 (though the CMWE measurement does not necessarily coincide with the actual peak CMWE). Though there is high intra‐ and interannual variability in the snow cover within the GB (also see Petersky and Harpold (2018)), two of the three sur- rogate measures of snow mass showed a decline during the study period prior to the record‐breaking winter of 2022 to 2023 (WY 2023). Mean‐monthly snow depth decreased by ∼81 mm from 2002 to 2022, but when WY 2023 is included, the decrease was ∼10 mm, 2002 to 2023. MODIS #days snow cover maps (Figure S3 in Supporting Information S1) show predominantly decreasing snow cover (Hall et al., 2023) in the GB prior to the inclusion of WY 2023. The snowpack in the 2022 to 2023 winter was one of the largest on record in California, with many areas in the southern Sierra Nevada Moun- tains experiencing snow accumulations more than 200% of normal (DWR, 2023). The Wasatch Mountains in Utah, in the eastern GB, also experienced copious amounts of snowfall in WY 2023. 3.3. Land Surface Temperature (LST) Air and surface temperatures in the U.S. West have been increasing over the last few decades (Vose et al., 2017) contributing to earlier snowmelt, and aridification including the desiccation of terminal lakes in the GB. The mean‐ daily LST in the GB increased 1.64°C from WY 2003–2023 (Figure S6 in Supporting Information S1). 4. Summary and Conclusions In the Great Basin, seasonal changes in gravity measured by GRACE/FO are largely caused by the deposition, and ablation (sublimation and melt) of snow. Longer‐term changes are primarily due to a decline in groundwater because the other components of TWS—surface water, soil moisture and atmospheric water vapor—are not major constituents of TWS in this arid/semi‐arid region. During the 21st Century megadrought there were years with notably larger amounts of snow that helped to mitigate the effects of the drought temporarily, but did not change the overall decline in TWS. Our results show steady loss of TWS in the GB as a whole, with greater loss in the western part (Figures 2–4). The 2002–2023 decline of groundwater of 68.7 km3 is more than six times greater than the current total volume of water in the Lake Mead Reservoir in Arizona/Nevada (Figure 5). Likely causes for the declining trend in TWS and groundwater include declining snow mass (prior to WY 2023), upstream water diversions, and increased evaporation/sublimation in some parts of the GB due to increasing air and surface temperatures. Loss of groundwater has a detrimental effect on human activities and health, wildlife and the economies of the western U.S. states. Figure 4. Trends in CMWE derived from the GSFC standard mascon product showing departure from the 2002 baseline values of CMWE, April 2002– September 2023: (a) Great Basin, (b) East Sierra subregion, (c) Great Salt Lake Basin. The total uncertainty (shaded areas) was derived using the leakage trend, as described in Loomis, Luthcke, and Sabaka (2019). Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 5 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense Figure 5. Comparison of the volume of TWS change from 2002 to 2023, derived from the GSFC high‐resolution trend mascon data from GRACE/FO, with the maximum and current volumes of the Lake Mead Reservoir since 1937. Lake Mead volume information was obtained from SNOFLO (2024). Figure 6. Monthly CMWE mascon data (detrended) and mean‐monthly snow depths for the Great Basin, WY 2003–2023. Snow depth in mm was divided by 10 so that the CMWE and snow depth units would match. The declining trend of CMWE (Figure 4a) was removed to enhance visualization of this relationship. Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 6 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense Conflict of Interest The authors declare no conflicts of interest relevant to this study. Data Availability Statement All the data used to undertake this research are freely available in a Zenodo data repository (Hall & DiGirolamo, 2024). References Abatzoglou, J. T., & Williams, A. P. (2016). Impact of anthropogenic climate change on wildfire across western US forests. Proceedings of the National Academy of Sciences of the United States of America, 113(42), 11770–11775. https://doi.org/10.1073/pnas.1607171113 Behrangi, A., Gardner, A., Reager, J. T., Fisher, J. B., Yang, D., Huffman, G. J., & Adler, R. F. (2018). Using GRACE to estimate snowfall accumulation and assess gauge undercatch corrections in high latitudes. 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NSIDC: National Snow and Ice Data Center. https://doi.org/10.7265/N5TB14TC Acknowledgments This work was supported by NASA's Terrestrial Hydrology Program and Earth Observing Systems programs: 80NSSC22K0554 and 80NSSC21K1927 and NASA's GRACE‐FO Science Team, NN‐H19ZDA001N‐GRACEFO. We thank Drs. Ron Larson/Oregon Lakes Association and Kevin Perry/University of Utah, for discussions about upstream diversions in the GB. Drs. Justin Pflug/ University of Maryland and Sujay Kumar/ NASA Goddard Space Flight Center, provided helpful insights about LSMs. We also thank the editor and reviewers for their insightful and useful comments. Geophysical Research Letters 10.1029/2023GL107913 HALL ET AL. 7 of 8 19448007, 2024, 6, D ow nloaded from https://agupubs.onlinelibrary.w iley.com /doi/10.1029/2023G L 107913 by U niversity O f M aryland, W iley O nline L ibrary on [09/07/2024]. 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See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense https://doi.org/10.3390/rs12233913 https://doi.org/10.1073/pnas.2006323117 https://doi.org/10.5194/hess-22-4891-2018 https://modis-snow-ice.gsfc.nasa.gov/?c=userguides https://modis-snow-ice.gsfc.nasa.gov/?c=userguides https://doi.org/10.1029/1999wr900141 https://doi.org/10.1038/s44221-023-00040-5 https://doi.org/10.1038/nature08238 https://doi.org/10.1016/j.rse.2023.113963 https://doi.org/10.1175/2008JHM861.1 https://snoflo.org/reservoir/nevada/lake-mead https://www.nrcs.usda.gov/programs-initiatives/sswsf-snow-survey-and-water-supply-forecasting-program/national-water-and https://www.nrcs.usda.gov/programs-initiatives/sswsf-snow-survey-and-water-supply-forecasting-program/national-water-and https://doi.org/10.1016/j.ejrh.2017.05.004 https://doi.org/10.1029/2004gl019920 https://science2017.globalchange.gov/chapter/6/ https://science2017.globalchange.gov/chapter/6/ https://doi.org/10.3390/rs9030256 https://doi.org/10.1038/s41558-022-01290-z https://mathworld.wolfram.com/CubicPolynomial.html https://doi.org/10.1038/ngeo3052 https://doi.org/10.1002/2017gl073333 https://doi.org/10.1126/science.abo2812 https://doi.org/10.1088/1748-9326/ac507b https://doi.org/10.1029/2020JB019432 https://doi.org/10.1016/j.rse.2019.03.015 https://doi.org/10.1038/s41467-022-31125-6 https://doi.org/10.1038/s41467-022-31125-6 https://gis.data.ca.gov/datasets/837b5a3dd2914788b9839f30b17336b5_0/explore https://www.usgs.gov/national-hydrography/watershed-boundary-dataset https://www.usgs.gov/national-hydrography/watershed-boundary-dataset https://worldview.earthdata.nasa.gov/ description Snowfall Replenishes Groundwater Loss in the Great Basin of the Western United States, but Cannot Compensate for Increasing ... 1. Introduction 2. Data and Methods 2.1. GRACE/FO Mascon Data Sets 2.2. Snow Mass 2.2.1. SWE 2.2.2. Number of Days of Snow Cover 2.2.3. Snow Depth and Snowfall 2.3. Land Surface Temperature (LST) 3. Results and Discussion 3.1. Trends in TWS in the Great Basin 3.2. TWS and Snow Mass 3.3. Land Surface Temperature (LST) 4. Summary and Conclusions Conflict of Interest Data Availability Statement