Groundwater depletion during drought threatens future water security of the Colorado River Basin

A database of groundwater wells in the United States

Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, USGWD comprises over 14.2 million well records with attributes, such as well purpose, location, depth, and capacity, for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.

Indirect regulation of topsoil nutrient cycling by groundwater depth: impacts on sand-fixing vegetation and rhizosphere bacterial communities

Introduction

The impact of groundwater table depth (GTD) on bacterial communities and soil nutrition in revegetated areas remains unclear.

Methods

We investigated the impacts of plant growth and soil physicochemical factors on rhizosphere bacterial communities under different GTD.

Results

The four plant growth indices (Pielou, Margalef, Simpson, and Shannon-Wiener indices) and soil water content (SWC) at the Artem and Salix sites all showed a decreasing trend with increasing GTD. Salix had a higher nutrient content than Artem. The response of plant rhizosphere bacterial communities to GTD changes were as follows. Rhizosphere bacteria at the Artem and Salix sites exhibited higher relative abundance and alpha diversity in SW (GTD < 5 m) compared than in DW (GTD > 5 m). Functional microbial predictions indicated that the rhizosphere bacterial communities of Artem and Salix promoted carbon metabolism in the SW. In contrast, Artem facilitated nitrogen cycling, whereas Salix enhanced both nitrogen cycling and phototrophic metabolism in the DW.

Discussion

Mantel test analysis revealed that in the SW of Artem sites, SWC primarily governed the diversity of rhizosphere and functional bacteria involved in the nitrogen cycle by affecting plant growth. In DW, functional bacteria increase soil organic carbon (SOC) to meet nutrient demands. However, higher carbon and nitrogen availability in the rhizosphere soil was observed in the SW of the Salix sites, whereas in DW, carbon nutrient availability correlated with keystone bacteria, and changes in nitrogen content could be attributed to nitrogen mineralization. This indicates that fluctuations in the groundwater table play a role in regulating microbes and the distribution of soil carbon and nitrogen nutrients in arid environments.

Evaluation of the effect of scenarios in the 6th report of IPCC on the prediction groundwater level using the non-linear model of the input-output time series

Due to the increase in greenhouse gases, water and climate crises, increasing population, and decreasing water resources, accurately predicting the changes in the GWL is essential for the management of water resources. For this purpose, in this research, the MIROCES2L model was used to predict the climatic parameters of Birjand Plain under three scenarios of the sixth climate change report: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The minimum temperature, maximum temperature, and precipitation parameters from these three scenarios were measured using the CMhyd model. The results indicated that the minimum and maximum temperature would generally increase in the future under the influence of climate change, but precipitation has a sinusoidal behavior and has a decreasing trend in the summer and spring seasons and an increasing trend in the winter and autumn seasons. Then, three ANN, NIO, and MLR models were employed to simulate groundwater depletion. The results indicated that the evaluation of the performance criteria of the NIO model is superior to the other two models, and it was chosen as the model for predicting groundwater depletion in the future period under the influence of climate change based on all three mentioned scenarios. The final results of this research indicated that the GWL of Birjand Plain in the future period (2024-2041) under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios would respectively decrease to 5.58m, 5.13m, and 5.38. The results of this research indicate that the need for sustainable management to conserve groundwater resources is also very important in the study area.

Changing climate and reorganized species interactions modify community responses to climate variability

While an array of ecological mechanisms has been shown to stabilize natural community dynamics, how the effectiveness of these mechanisms-including both their direction (stabilizing vs. destabilizing) and strength-shifts under a changing climate remains unknown. Using a 35-y dataset (1985 to 2019) from a desert stream in central Arizona (USA), we found that as annual mean air temperature rose 1°C and annual mean precipitation reduced by 40% over the last two decades, macroinvertebrate communities experienced dramatic changes, from relatively stable states during the first 15 y of this study to wildly fluctuating states highly sensitive to climate variability in the last 10 y. Asynchronous species responses to climatic variability, the primary mechanism historically undergirding community stability, greatly weakened. The emerging climate regime-specifically, concurrent warming and prolonged multiyear drought-resulted in community-wide synchronous responses and reduced taxa richness. Diversity loss and new establishment of competitors reorganized species interactions. Unlike manipulative experiments that often suggest stabilizing roles of species interactions, we found that reorganized species interactions switched from stabilizing to destabilizing influences, further amplifying community fluctuations. Our study provides evidence of climate change-induced modifications of mechanisms underpinning long-term community stability, resulting in an overall destabilizing effect.

Global assessment of the sensitivity of water storage to hydroclimatic variations

Observing basin water storage response due to hydroclimatic fluxes and human water use provides valuable insight to the sensitivity of water storage to climate change. Quantifying basin water storage changes due to climate and human water use is critical for water management yet remains a challenge globally. Observations from the Gravity Recovery and Climate Experiment (GRACE) mission are used to extract monthly available water (AW), representing the combined storage changes from groundwater and surface water stores. AW is combined with hydroclimatic fluxes, including precipitation (P) and evapotranspiration (ET) to quantify the hydroclimatic elasticity of AW for global basins. Our results detect consequential global water sensitivity to changes in hydroclimatic fluxes, where 25 % of land areas exhibit hydroclimatic elasticity of AW >10, implying that a 1 % change in monthly P-ET would result in a 10 % change in AW. Corroboration using a Budyko-derived metric substantiates our findings, demonstrating that basin water storage resilience to short-term water deficits is linked to basin partitioning predictability, and uniform seasonality of hydroclimatic fluxes. Our study demonstrates how small shifts in hydroclimate flux may affect available water storage potentially impacting billions globally.

Divergent spatiotemporal variability of terrestrial water storage and eight hydroclimatic components over three different scales of the Yangtze River basin

Terrestrial water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on was first exacted by using the forward modeling (FM) method at three different scales over the Yangtze River basin (YRB): whole basin, three middle sub-basins, and eleven small sub-basins (total 15 basins). The spatiotemporal variability of eight hydroclimatic variables, snow water storage change (SnWS), canopy water storage change (CnWS), surface water storage anomaly (SWSA), soil moisture storage anomaly (SMSA), groundwater storage anomaly (GWSA), precipitation (P), evapotranspiration (ET), and runoff (R), and their contribution to TWSA were comprehensively investigated over the YRB. The results showed that the root mean square error of TWS change after FM improved by 17 %, as validated by in situ P, ET, and R data. The seasonal, inter-annual, and trend revealed that TWSA over the YRB increased during 2003-2018. The seasonal TWSA signal increased from the lower to the upper of YRB, but the trend, sub-seasonal, and inter-annual signals receded from the lower to the upper of YRB. The contribution of CnWS to TWSA was small over the YRB. The contribution of SnWS to TWSA occurs mainly in the upper of YRB. The main contributors to TWSA were SMSA (~36 %), SWSA (~33 %), and GWSA (~30 %). GWSA can be affected by TWSA, but other hydrological elements may have a slight impact on groundwater in the YRB. The primary driver of TWSA over the YRB was P (~46 %), followed by ET and R (both ~27 %). The contribution of SMSA, SWSA, and P to TWSA increased from the upper to the lower of YRB. R was the key driver of TWSA in the lower of YRB. The proposed approaches and results of this study can provide valuable new insights for water resource management in the YRB and can be applied globally.

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.

Groundwater depletion in California's Central Valley accelerates during megadrought

Groundwater provides nearly half of irrigation water supply, and it enables resilience during drought, but in many regions of the world, it remains poorly, if at all managed. In heavily agricultural regions like California's Central Valley, where groundwater management is being slowly implemented over a 27-year period that began in 2015, groundwater provides two-thirds or more of irrigation water during drought, which has led to falling water tables, drying wells, subsiding land, and its long-term disappearance. Here we use nearly two decades of observations from NASA's GRACE satellite missions and show that the rate of groundwater depletion in the Central Valley has been accelerating since 2003 (1.86 km³/yr, 1961-2021; 2.41 km³/yr, 2003-2021; 8.58 km³/yr, 2019-2021), a period of megadrought in southwestern North America. Results suggest the need for expedited implementation of groundwater management in the Central Valley to ensure its availability during the increasingly intense droughts of the future.

Smart Sharing Plan: The Key to the Water Crisis

Over the years, the Colorado River has become inadequate for development due to natural factors and human activities. The hydroelectric facilities in Lake Mead and Lake Powell are also not fully utilized. Downstream, Mexico is also involved in the competition for water. The resulting allocation of water and electricity resources and sustainable development are hanging over our heads and waiting to be solved. In this work, a simplified Penstock Dam model and a Distance Decay model are designed based on publicly available data, and a Multi-attribute Decision model for hydropower based on the Novel Technique for Order Preference by Similarity to an Ideal Solution method is proposed. In addition, an Improved Particle Swarm Optimization model is proposed by adding oscillation parameters. The Mexican equity problem is also explored. The theoretical results show that the average error of the Penstock Dam model is 3.2%. The minimum water elevation requirements for Lake Mead and Lake Powell are 950 ft and 3460 ft, respectively; they will not meet demand in 2026 and 2027 without action, and they will require the introduction of 3.69×1010 m3 and 2.08×109 m3 water in 2027 and 2028, respectively. The solution shows that the net profit for the United States is greatest when 38.6% of the additional water is used for general purposes, 47.5% is used for power generation, and the rest flows to Mexico. A final outlook on the sustainability of the Colorado River is provided.

Local-Scale Groundwater Sustainability Assessment Based on the Response to Groundwater Mining (MGSI): A Case Study of Da’an City, Jilin Province, China

Sustainable groundwater utilization is important for social and economic development. There is a need for groundwater sustainability assessment in small-scale areas lacking detailed mining data. Here, exploiting water level data series, we propose an indicator of groundwater sustainability based on the response to mining (MGSI) for better evaluation; it integrates groundwater data and spatio-temporal variability at a local scale. A decomposition coefficient was applied to decompose the pressure exerted by groundwater mining on the groundwater system for each monitoring well. It correlated with the groundwater response state. In Da’an City, Jilin Province, China, the appraised results revealed that the aquifer type exhibiting the greatest risk to groundwater sustainability changed from phreatic to confined during 2008–2017. The spatio-temporal distribution of different sustainability levels between and within the aquifers indicated that adjustment of the groundwater mining layout should be the focus of groundwater management in Da’an City. Additionally, the Mann–Kendall trend test and Sen’s slope trend analysis effectively explained the sustainable evolution of groundwater in Da’an City and confirmed the reliability of the MGSI method. The proposed method highlights the effects of groundwater mining on sustainability and helps us better understand the interaction between anthropogenic activities and groundwater resources.

Buffering the impacts of extreme climate variability in the highly engineered Tigris Euphrates river system

More extreme and prolonged floods and droughts, commonly attributed to global warming, are affecting the livelihood of major sectors of the world’s population in many basins worldwide. While these events could introduce devastating socioeconomic impacts, highly engineered systems are better prepared for modulating these extreme climatic variabilities. Herein, we provide methodologies to assess the effectiveness of reservoirs in managing extreme floods and droughts and modulating their impacts in data-scarce river basins. Our analysis of multiple satellite missions and global land surface models over the Tigris-Euphrates Watershed (TEW; 30 dams; storage capacity: 250 km³), showed a prolonged (2007–2018) and intense drought (Average Annual Precipitation [AAP]: < 400 km³) with no parallels in the past 100 years (AAP during 1920–2020: 538 km³) followed by 1-in-100-year extensive precipitation event (726 km³) and an impressive recovery (113 ± 11 km³) in 2019 amounting to 50% of losses endured during drought years. Dam reservoirs captured water equivalent to 40% of those losses in that year. Additional studies are required to investigate whether similar highly engineered watersheds with multi-year, high storage capacity can potentially modulate the impact of projected global warming-related increases in the frequency and intensity of extreme rainfall and drought events in the twenty-first century.

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.

Groundwater Drought Analysis under Data Scarcity: The Case of the Salento Aquifer (Italy)

Salento is a regional coastal karst aquifer located in Southern Italy with a highly complex geological, geomorphological, and hydrogeological structure. High and unruly exploitation of groundwater from licensed and unlicensed wells for irrigation and drinking purposes affects groundwater, with consequent degradation of its qualitative and quantitative status. The increased frequency of meteorological droughts and rising temperatures may only worsen the already compromised situation. The absence of complete and enduring monitoring of groundwater levels prevents the application of some methodologies, which require long time series. The analysis of climate indexes to describe the groundwater level variation is a possible approach under data scarcity. However, this approach may not be obvious for complex aquifers (in terms of scale, intrinsic properties, and boundary conditions) where the response of the groundwater to precipitation is not necessarily linear. Thus, the proposed research deals with the assessment of the response of the Salento aquifer to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration Index (SPEI) and groundwater levels for nine monitoring wells from July 2007 to December 2011. The study aims at evaluating the ability of the above indicators to explain the behavior of groundwater on complex aquifers. Moreover, it has the general aim to verify their more general reliable application. Results of three different correlation factors outline direct and statistically significant correlations between the time series. They describe the Salento aquifer as a slow filter, with a notable inertial behavior in response to meteorological events. The SPI 18-months demonstrates to be a viable candidate to predict the groundwater response to precipitation variability for the Salento aquifer.

The legacy of large dams in the United States

The sustainability of large dams has been questioned on several grounds. One aspect that has been less explored is that the development of dams and reservoirs often enables agricultural expansion and urban growth, which in turn increase water consumption. As such, dam development influences, while being influenced by, the spatial and temporal distribution of both supply and demand of water resources. In this paper, we explore the interplay between large dams, patterns of population growth and agricultural expansion in the United States over the past two centuries. Based on a large-scale analysis of spatial and temporal trends, we identify three distinct phases, in which different processes dominated the interplay. Then, we focus on agricultural water use in the Southwest region (Arizona, California and Nevada) and explore chicken-and-egg dynamics where water supply partly meets and partly fuels water demand. Lastly, we show that the legacy of dams in the United States consists of a lock-in condition characterized by high levels of water consumption, especially in the Southwest, which leads to severe water crises and groundwater overexploitation when droughts occur.

Using machine learning classification to detect simulated increases of de facto reuse and urban stormwater surges in surface water

Water quality events such as increases in stormwater or wastewater effluent in drinking water sources pose hazards to drinking water consumers. Stormwater and wastewater effluent enter Lake Mead-an important drinking water source in the southwest USA-via the Las Vegas Wash. Previous studies have applied machine learning and online instruments to detect contamination in water distribution systems. However, alert systems at drinking water intakes would provide more time for corrective action. An array of online instruments measuring pH, conductivity, redox potential, turbidity, temperature, tryptophan-like fluorescence, UV absorbance (UVA₂₅₄), TOC, and chlorophyll-a was fed raw water directly from Lake Mead. Wastewater effluent, dry weather Las Vegas Wash, and storm-impacted Las Vegas Wash samples were blended into the instrument inlets at known ratios to simulate three types of adverse water quality events. Data preprocessing was conducted to correct for diurnal patterns or instrument drift. Supervised machine learning was conducted using previously published models in R. Ninety-nine models were screened on the raw data. Eight high-performing models were evaluated in-depth and optimized. Weighted k-Nearest Neighbors, Single C5.0 Ruleset, Mixture Discriminant Analysis, and an ensemble of these three models had accuracy over 97% when assigning test set data among three classes (Normal, Event, or Maintenance). The ensemble detected all event types at the earliest timepoint and had one false positive that was not a lag error (i.e., consecutively following a true positive). Omitting Maintenance, the Adaboost model had over 99% test set accuracy and zero false positives that were not lag errors. Data preprocessing was beneficial, but the optimal methods were model-specific. All nine water quality variables were useful for most models, but UVA₂₅₄ and turbidity were most important.

Bayesian machine learning ensemble approach to quantify model uncertainty in predicting groundwater storage change

Agricultural water demand, groundwater extraction, surface water delivery and climate have complex nonlinear relationships with groundwater storage in agricultural regions. As an alternative to elaborate computationally intensive physical models, machine learning methods are often adopted as surrogate to capture such complex relationships due to their high computational efficiency. Inevitably, using only one machine learning model is prone to underestimate prediction uncertainty and subjected to poor accuracy. This study presents a novel machine learning-based groundwater ensemble modeling framework in conjunction with a Bayesian model averaging approach to predict groundwater storage change and improve overall model predicting reliability. Three different machine learning models have been developed namely artificial neural network, support vector machine and response surface regression. To explicitly quantify uncertainty from machine learning model parameter and structure, Bayesian model averaging is employed to produce a forecast distribution associated with each machine learning prediction. Model weights and variances are obtained based on model performance to construct ensemble models. Then, the developed individual and Bayesian model averaging machine learning ensemble models are applied, evaluated and validated at different spatial scales including subregional and regional scales in an overdrafted agricultural region-the San Joaquin River Basin, through independent training and testing dataset. Results shows the machine learning models have remarkable predicting capability without sacrificing accuracy but with higher computational efficiency. Compared to a single-model approach, the ensemble model is able to produce consistently reliable predictions across the basin, yet it does not always outperform the best model in the ensemble. Additionally, model results suggest that groundwater pumping for agricultural irrigation is the primary driving force of groundwater storage change across the region. The modeling framework can serve as an alternative approach to simulating groundwater response, especially in those agricultural regions where lack of subsurface data hinders physically-based modeling.

Monthly and Seasonal Drought Characterization Using GRACE-Based Groundwater Drought Index and Its Link to Teleconnections across South Indian River Basins

Traditional drought monitoring is based on observed data from both meteorological and hydrological stations. Due to the scarcity of station observation data, it is difficult to obtain accurate drought distribution characteristics, and also tedious to replicate the large-scale information of drought. Thus, Gravity Recovery and Climate Experiment (GRACE) data are utilized in monitoring and characterizing regional droughts where ground station data is limited. In this study, we analyzed and assessed the drought characteristics utilizing the GRACE Groundwater Drought Index (GGDI) over four major river basins in India during the period of 2003–2016. The spatial distribution, temporal evolution of drought, and trend characteristics were analyzed using GGDI. Then, the relationship between GGDI and climate factors were evaluated by the method of wavelet coherence. The results indicate the following points: GRACE’s quantitative results were consistent and robust for drought assessment; out of the four basins, severe drought was noticed in the Cauvery river basin between 2012 and 2015, with severity of −27 and duration of 42 months; other than Godavari river basin, the remaining three basins displayed significant negative trends at monthly and seasonal scales; the wavelet coherence method revealed that climate factors had a substantial effect on GGDI, and the impact of Southern Oscillation Index (SOI) on drought was significantly high, followed by Sea Surface Temperature (SST) Index (namely, NINO3.4) and Multivariate El Niño–Southern Oscillation Index (MEI) in all the basins. This study provides reliable and robust quantitative result of GRACE water storage variations that shares new insights for further drought investigation.

Future global socioeconomic risk to droughts based on estimates of hazard, exposure, and vulnerability in a changing climate

A consistent and equitable global drought risk assessment for multiple regions, populations, and economic sectors at the gridded scale under future diverse climate change scenarios has been the subject of scarce research. Climate change is projected to increase the future hazard of drought and cause consequential damages to socioeconomic systems. The risk assessment of drought caused by climate change can be a bridge between impacts and adaptation. To assess the socioeconomic risk to droughts in a base period and two future periods (2016 to 2035 and 2046 to 2065), the projections of five general circulation models and population and gross domestic product (GDP), land cover, and water resources data were used to analyze the socioeconomic risk under three scenarios combining representative concentration pathways (RCPs) and shared socioeconomic pathways (SSPs). The socioeconomic risk was calculated as the product of three determinants: hazard, exposure, and vulnerability. The risk of the global population to drought was projected to be highest in 2046 to 2065 under scenario RCP8.5-SSP3, with up to 1.45 × 10⁹ persons affected, a 63% increase compared with the base period. The highest risk to GDP (4.29 × 10¹³ purchasing power parity $) was possibly in 2046 to 2065 under scenario RCP2.6-SSP1, with the risk increasing 5.64 times compared to the base period. Regions with high socioeconomic risk were primarily concentrated in the East and South Asia, Midwestern Europe, eastern US, and the coastal areas of South America. With climate change, the inequality in future socioeconomic risk to drought among countries is predicted to increase. The ten countries with the highest risks to population and GDP accounted for nearly 70% of the global risk.

Recognition of district-wise groundwater stress zones using the GLDAS-2 catchment land surface model during lean season in the Indian state of West Bengal

Water is essential for irrigation, drinking and industrial purposes from global to the regional scale. The groundwater considered a significant water resource specifically in regions where the surface water is not sufficient. Therefore, the research problem is focused on district-wise sustainable groundwater management due to urbanization. The number of impervious surface areas like roofing on built-up areas, concrete and asphalt road surface were increased due to the level of urban development. Thus, these surface areas can inhibit infiltration and surface retention by the impact of urbanization because vegetation/forest areas are decreased. The present research examines the district-wise spatiotemporal groundwater storage (GWS) changes under terrestrial water storage using the global land data assimilation system-2 (GLDAS-2) catchment land surface model (CLSM) from 2000 to 2014 in West Bengal, India. The objective of the research is mainly focused on the delineation of groundwater stress zones (GWSZs) based on ten biophysical and hydrological factors according to the deficiency of groundwater storage using the analytic hierarchy process by the GIS platform. Additionally, the spatiotemporal soil moisture (surface soil moisture, root zone soil moisture, and profile soil moisture) changes for the identification of water stress areas using CLSM were studied. Finally, generated results were validated by the observed groundwater level and groundwater recharge data. The sensitivity analysis has been performed for GWSZs mapping due to the deficit of groundwater storage. Three correlation coefficient methods (Kendall, Pearson and Spearman) are applied for the interrelationship between the most significant parameters for the generation of GWSZ from sensitivity analysis. The results show that the northeastern (max: 1097.35 mm) and the southern (max: 993.22 mm) parts have high groundwater storage due to higher amount of soil moisture and forest cover compared to other parts of the state. The results also show that the maximum and minimum total annual groundwater recharge shown in Paschim Medinipore [(361,148.51 hectare-meter (ham)] and Howrah (31,510.46 ham) from 2012 to 2013. The generated outcome can create the best sustainable groundwater management practices based upon the human attitude toward risk.

Significant Baseflow Reduction in the Sao Francisco River Basin

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of the surface-groundwater interaction, have not yet been investigated. Here, we assess long-term trends in the streamflow and baseflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through a trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that, on average, over 86% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend along the SFR, with a spatial agreement between the decreased baseflow, increased ET, and irrigated agricultural land in the Middle SFB. We also noted a decreasing trend in TWS across the SFB exceeding –20 mm year−1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are providing the observed reduction in the total SFR flow. A lack of significant P trends and the strong TWS depletion indicate that a P variability only has likely not caused the observed baseflow reduction, in mainly the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may likely be a driver of baseflow reduction in some regions of the SFB.

Resilience Viewed through the Lens of Climate Change and Water Management

Resilience is not a new idea but there has been an upsurge in efforts to operationalize the concept within water management. This review begins with a synopsis of related themes around persistent and emerging pressures on freshwaters; environmental thresholds (or tipping points); ‘safe’ operating conditions; multiple stable states; regime shifts. A case is made for viewing and managing the resilience of water systems at nested scales. Indicators are needed to track evolving climate risks as well as to measure socio-ecological responses. Catchment properties can identify those river systems that are more or less likely to return to a pre-disturbance state; resilience further depends on institutional and social landscapes. Ideally, allied notions of resistance and reliability are applied alongside resilience to broaden the portfolio of adaptation measures. Water managers would also benefit from more consistent use of resilience terminology; incentives to build back better after catastrophes; strategic monitoring of incipient threats and tipping points; availability of long-term adaptation indicators; coordinated efforts to reduce non-climatic pressures on freshwaters (especially in headwaters); evidence-based, practical guidance on adaptation measures that build resilience.

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.

Springs and Springs-Dependent Taxa of the Colorado River Basin, Southwestern North America: Geography, Ecology and Human Impacts

The Colorado River basin (CRB), the primary water source for southwestern North America, is divided into the 283,384 km2, water-exporting Upper CRB (UCRB) in the Colorado Plateau geologic province, and the 344,440 km2, water-receiving Lower CRB (LCRB) in the Basin and Range geologic province. Long-regarded as a snowmelt-fed river system, approximately half of the river’s baseflow is derived from groundwater, much of it through springs. CRB springs are important for biota, culture, and the economy, but are highly threatened by a wide array of anthropogenic factors. We used existing literature, available databases, and field data to synthesize information on the distribution, ecohydrology, biodiversity, status, and potential socio-economic impacts of 20,872 reported CRB springs in relation to permanent stream distribution, human population growth, and climate change. CRB springs are patchily distributed, with highest density in montane and cliff-dominated landscapes. Mapping data quality is highly variable and many springs remain undocumented. Most CRB springs-influenced habitats are small, with a highly variable mean area of 2200 m2, generating an estimated total springs habitat area of 45.4 km2 (0.007% of the total CRB land area). Median discharge also is generally low and variable (0.10 L/s, N = 1687, 95% CI = 0.04 L/s), but ranges up to 1800 L/s. Water pH and conductivity is negatively related to elevation, with a stronger negative relationship in the UCRB compared to the LCRB. Natural springs water temperature and geochemistry throughout the CRB varies greatly among springs, but relatively little within springs, and depends on aquifer hydrogeology, elevation, and residence time. As the only state nearly entirely included within the CRB, Arizona is about equally divided between the two geologic provinces. Arizona springs produce approximately 0.6 km3/year of water. Data on >330 CRB springs-dependent taxa (SDT) revealed at least 62 plant species; 216 aquatic and riparian Mollusca, Hemiptera, Coleoptera, and other invertebrate taxa; several herpetofanual species; and two-thirds of 35 CRB fish taxa. Springs vegetation structure, composition, and diversity vary strongly by springs type, and plant species density within springs is high in comparison with upland habitats. Plant species richness and density is negatively related to elevation below 2500 m. Human population in and adjacent to the CRB are growing rapidly, and ecological impairment of springs exceeds 70% in many landscapes, particularly in urbanized and rangeland areas. Anthropogenic stressors are primarily related to groundwater depletion and pollution, livestock management, flow abstraction, non-native species introduction, and recreation. Ensuring the ecological integrity and sustainability of CRB groundwater supplies and springs will require more thorough basic inventory, assessment, research, information management, and local ecosystem rehabilitation, as well as improved groundwater and springs conservation policy.

Integrated Hydrologic Modeling to Untangle the Impacts of Water Management During Drought

Over the past century, groundwater levels in California's San Joaquin Valley have dropped by more than 30 m in some areas mostly due to excessive groundwater extraction used to irrigate agricultural lands and sustain a growing population. Between 2012 and 2015, California experienced the worst drought in its recorded history, depleting surface water supplies and further exacerbating groundwater depletion in the region. Due to a lack of groundwater regulation, exact quantities of extracted groundwater in California are unknown and hard to quantify. Recent adoption of the Sustainable Groundwater Management Act has intensified efforts to identify sustainable groundwater use. However, understanding sustainable use in a highly productive agricultural system with an extremely complex surface water allocation system, variable groundwater use, and spatially extensive and diverse irrigation practices is no easy task. Using an integrated hydrologic model coupled with a land surface model, we evaluated how water management activities, specifically a suite of irrigation and groundwater pumping scenarios, impact surface water-groundwater fluxes and storage components and how those activities and the relationships between them change during drought. Results showed that groundwater pumping volume had the most significant impact on long-term water storage changes. A comparison with total water storage anomaly (TWSA) estimates from NASA's Gravity Recover and Climate Experiment (GRACE) provided some insight regarding which combinations of pumping and irrigation matched the GRACE TWSA estimates, lending credibility to these scenarios. In addition, the majority of long-term water storage changes during the recent drought occurred in groundwater storage in the deeper subsurface.

A Comprehensive Process for Stakeholder Identification and Engagement in Addressing Wicked Water Resources Problems

Various sectors of stakeholders (urban, agricultural, policymakers, etc.) are frequently engaged in participatory research projects aimed at improving water resources’ sustainability. However, a process for comprehensive and integrative identification, classification, and engagement of all types of water stakeholders for a region or river basin, especially in a transboundary context, is missing for water resources research projects. Our objective was to develop a systematic approach to identifying and classifying water stakeholders, and engage them in a discussion of water futures, as a foundation for a participatory modeling research project to address the wicked water resource problems of the Middle Rio Grande basin on the U.S./Mexico border. This part of the Rio Grande basin can be characterized as having limited and dwindling supplies of water, increasing demands for water from multiple sectors, and a segmented governance system spanning two U.S. states and two countries. These challenges are being exacerbated by climate change; a transitioning agriculture to more water demanding, high value crops; urbanization; and growing demand for environmental services. Moving forward, a core question for this region is how can water be managed so that the three competing sectors—agricultural, urban, and environmental—can realize a sustainable future in this challenged water system? We identified the major water-using sectors who represent competing demands as including agricultural, municipal, self-supplied industrial users, environmental, and a sector we labeled “social justice”, comprised of individuals who lack access to potable water, or who represent groups who advocate for access to water. We included stakeholders from both the U.S. and Mexico, which is seldom done, who share transboundary water resources in the region. We hosted a series of stakeholder dialogues and obtained results that identified and described their vision for the future of water; challenges to be overcome; and important research questions that could be addressed using participatory modeling approaches. Four broad themes common to multiple sectors emerged: (1) quantity, drought, and scarcity; (2) quality/salinization; (3) urbanization; and (4) conservation and sustainability. Each sector expressed distinctive views regarding the future of water. Agricultural stakeholders, in particular, had strong feelings of ownership of water rights as part of land ownership and a concomitant sense of threat to those water rights emanating from dwindling supplies and competing demands. The contribution of this work is a methodology for identifying, classifying, and engaging all types of stakeholders in the context of a research project, enabling us to compare and contrast views of different types of stakeholders. Heretofore, this has been accomplished in “bits and pieces”, but never comprehensively and holistically.

The Response of Groundwater Level to Climate Change and Human Activities in Baotou City, China

The response mechanism of groundwater to climate change and human activities in cities within arid and semi-arid regions, such as the Urban Planning Area of Baotou City (UPABC), northern China, is a complicated problem to understand. We analyzed the climate change relationships, including precipitation and temperature, and analyzed changes in human activities, such as groundwater consumption, and then statistically analyzed the main factors affecting groundwater depth. Furthermore, cross-wavelet and wavelet coherence methods were used to analyze the response relationship and hysteresis of groundwater depth to precipitation to better understand the groundwater depth response law. The results showed that the annual precipitation in the UPABC reduction rate was 3.3 mm/10 yr, and the annual average temperature increase rate was 0.43 °C/10 yr, from 1981 to 2017. The unconfined water decrease rate was 0.50 m/yr, and the confined water decrease rate was 0.7 m/yr. The unconfined and confined water depths were affected by precipitation and groundwater exploitation, respectively, with correlation coefficients of 0.58 and 0.57, respectively. The hysteresis of groundwater depth to precipitation was about 9–14 months. However, changes in groundwater depth, especially confined water depth, were greatly affected by groundwater exploitation. This reflected the imbalance in consumption and recharges in the UPABC, highlighting the long-term risk in areas relying on access to this resource. Therefore, arid inland zones of northern China, such as the UPABC, should pay more attention to the rational development of groundwater and strengthen the management and protection of groundwater resources.

Using GRACE to quantify the depletion of terrestrial water storage in Northeastern Brazil: The Urucuia Aquifer System

Covering a plateau area of approximately 125,000 km², the Urucuia Aquifer System (UAS) represents a national strategic water resource in the drought-stricken Northeastern part of Brazil. Variations in terrestrial water storage (TWS) extracted using a three-model-ensemble from the Gravity Recovery and Climate Experiment (GRACE) mission showed a negative balance equal to water stress. Monthly GRACE-derived water storage changes from 2002 to 2014 were compared with those derived from an independent hydrologic water balance of the region using in situ measurements and estimated evapotranspiration rates. Trend analyses revealed a TWS depletion rate of 6.5 ± 2.6 mm yr^-1, but no significant decline in precipitation as observed from available data records. Water storage depletion was found to be driven by anthropogenic impacts rather than by natural climatic variability. The obtained results demonstrate that GRACE is able to adequately capture water storage changes at the subregional scale, particularly during dry seasons.

Statistical Applications to Downscale GRACE-Derived Terrestrial Water Storage Data and to Fill Temporal Gaps

The Gravity Recovery and Climate Experiment (GRACE) has been successfully used to monitor variations in terrestrial water storage (GRACETWS) and groundwater storage (GRACEGWS) across the globe, yet such applications are hindered on local scales by the limited spatial resolution of GRACE data. Using the Lower Peninsula of Michigan as a test site, we developed optimum procedures to downscale GRACE Release-06 monthly mascon solutions. A four-fold exercise was conducted. Cluster analysis was performed to identify the optimum number and distribution of clusters (areas) of contiguous pixels of similar geophysical signals (GRACETWS time series); three clusters were identified (cluster 1: 13,700 km2; cluster 2: 59,200 km2; cluster 3: 33,100 km2; Step I). Variables (total precipitation, normalized difference vegetation index (NDVI), snow cover, streamflow, Lake Michigan level, Lake Huron level, land surface temperature, soil moisture, air temperature, and evapotranspiration (ET)), which could potentially contribute to, or correlate with, GRACETWS over the test site were identified, and the dataset was randomly partitioned into training (80%) and testing (20%) datasets (Step II). Multivariate regression, artificial neural network, and extreme gradient boosting techniques were applied on the training dataset for each of the identified clusters to extract relationships between the identified hydro-climatic variables and GRACETWS solutions on a coarser scale (13,700–33,100 km2), and were used to estimate GRACETWS at a spatial resolution matching that of the fine-scale (0.125° × 0.125° or 120 km2) inputs. The statistical models were evaluated by comparing the observed and modeled GRACETWS values using the R-squared, the Nash–Sutcliffe model efficiency coefficient (NSE), and the normalized root-mean-square error (NRMSE; Step III). Lastly, temporal variations in GRACEGWS were extracted using outputs of land surface models and those of the optimum downscaling methodology (downscaled GRACETWS) (Step IV). Findings demonstrate that (1) consideration should be given to the cluster-based extreme gradient boosting technique in downscaling GRACETWS for local applications given their apparent enhanced performance (average value: R-squared: 0.86; NRMSE 0.37; NSE 0.86) over the multivariate regression (R-squared: 0.74; NRMSE 0.56; NSE 0.64) and artificial neural network (R-squared: 0.76; NRMSE 0.5; NSE 0.37) methods; and (2) identifying local hydrologic variables and the optimum downscaling approach for individual clusters is critical to implementing this method. The adopted method could potentially be used for groundwater management purposes on local scales in the study area and in similar settings elsewhere.

Short-term trends in Africa's freshwater resources: Rates and drivers

The freshwater resources in Africa are vulnerable to natural variabilities as well as anthropogenic interventions. In this study, temporal (April 2002-June 2017) Gravity Recovery and Climate Experiment (GRACE) data are integrated, in a geographic information system environment, with rainfall, temperature, evapotranspiration, and altimetry remote sensing datasets to monitor the short-term trends in terrestrial water storage (TWS) over the African hydrogeologic systems and to explore their origins. Results show that short-term trends over the African continent are largely driven by natural variability such as changes in rainfall, evapotranspiration, and associated variations in lake levels. Exceptions to this observation include central Africa, where deforestation is found to additionally drive changes in TWS, as well as northern Africa, where TWS changes are dominated by anthropogenic groundwater extraction from fossil aquifers. Findings highlight the need for integrative responses at local, national, regional, and international levels by the African nations to overcome current and future challenges related to freshwater availability in Africa.

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

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

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.

Forecasting GRACE Data over the African Watersheds Using Artificial Neural Networks

The GRACE-derived terrestrial water storage (TWSGRACE) provides measurements of the mass exchange and transport between continents, oceans, and ice sheets. In this study, a statistical approach was used to forecast TWSGRACE data using 10 major African watersheds as test sites. The forecasted TWSGRACE was then used to predict drought events in the examined African watersheds. Using a nonlinear autoregressive with exogenous input (NARX) model, relationships were derived between TWSGRACE data and the controlling and/or related variables (rainfall, temperature, evapotranspiration, and Normalized Difference Vegetation Index). The performance of the model was found to be “very good” (Nash–Sutcliffe (NSE) > 0.75; scaled root mean square error (R*) < 0.5) for 60% of the investigated watersheds, “good” (NSE > 0.65; R* < 0.6) for 10%, and “satisfactory” (NSE > 0.50; R* < 0.7) for the remaining 30% of the watersheds. During the forecasted period, no drought events were predicted over the Niger basin, the termination of the latest (March–October 2015) drought event was observed over the Zambezi basin, and the onset of a drought event (January-March 2016) over the Lake Chad basin was correctly predicted. Adopted methodologies generate continuous and uninterrupted TWSGRACE records, provide predictive tools to address environmental and hydrological problems, and help bridge the current gap between GRACE missions.

New light in the dark - a proposed multidisciplinary framework for studying functional ecology of groundwater fauna

Groundwaters provide the vast majority of unfrozen freshwater resources on the planet, but our knowledge of subsurface ecosystems is surprisingly limited. Stygofauna, or stygobionts -subterranean obligate aquatic animals - provide ecosystem services such as grazing biofilms and maintaining water quality, but we know little about how their ecosystems function. The cryptic nature of groundwaters, together with the high degree of local endemism and stygofaunal site-specific adaptations, represent major obstacles for the field. To overcome these challenges, and integrate biodiversity and ecosystem function, requires a holistic design drawing on classical ecology, taxonomy, molecular ecology and geochemistry. This study presents an approach based on the integration of existing concepts in groundwater ecology with three more novel scientific techniques: compound specific stable isotope analysis (CSIA) of amino acids, radiocarbon analysis (¹⁴C) and DNA analyses of environmental samples, stygofauna and gut contents. The combination of these techniques allows elucidation of aspects of ecosystem function that are often obscured in small invertebrates and cryptic systems. Carbon (δ¹³C) and nitrogen (δ¹⁵N) CSIA provides a linkage between biogeochemical patterns and ecological dynamics. It allows the identification of stygofaunal food web structures and energy flows based on the metabolic pathway of specific amino groups. Concurrently, ¹⁴C provides complementary data on the carbon recycling and incorporation within the stygobiotic trophic webs. Changes in groundwater environmental conditions (e.g. aquifer recharge), and subsequent community adaptations, can be pinpointed via the measurementof the radiocarbon fingerprint of water, sediment and specimens. DNA analyses are a rapidly expanding approach in ecology. eDNA is mainly employed as a biomonitoring tool, while metabarcoding of individuals and/or gut contents provides insight into diet regimes. In all cases, the application of the approaches in combination provides more powerful data than any one alone. By combining quantitative (CSIA and ¹⁴C) and qualitative (eDNA and DNA metabarcoding) approaches via Bayesian Mixing Models (BMM), linkages can be made between community composition, energy and nutrient sources in the system, and trophic function. This suggested multidisciplinary design will contribute to a more thorough comprehension of the biogeochemical and ecological patterns within these undervalued but essential ecosystems.

Contributions of GRACE to understanding climate change

Time-resolved satellite gravimetry has revolutionized understanding of mass transport in the Earth system. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) has enabled monitoring of the terrestrial water cycle, ice sheet and glacier mass balance, sea level change and ocean bottom pressure variations and understanding responses to changes in the global climate system. Initially a pioneering experiment of geodesy, the time-variable observations have matured into reliable mass transport products, allowing assessment and forecast of a number of important climate trends and improve service applications such as the U.S. Drought Monitor. With the successful launch of the GRACE Follow-On mission, a multi decadal record of mass variability in the Earth system is within reach.

Spatio-temporal dynamics of groundwater storage changes in the Yellow River Basin

Groundwater is an important source of water supply and ecosystem resilience. However, limited information on spatio-temporal dynamics makes a complete assessment of available groundwater resources difficult, impairing sustainable water management. The Gravity Recovery and Climate Experiment mission (GRACE) has recently made this possible. In this study, we used the Yellow River Basin (YRB) as a model system to explore the use of spatio-temporal dynamics information about groundwater change derived from the GRACE datasets for regional groundwater management. While there was an overall decreasing trend (R² = 0.57) during the last 14 year, the groundwater storage over the whole basin decreased significantly (p < 0.0001, slope changed from -0.0137 cm/month to -0.0684 cm/month) since 2010 (2010-2016) and showed stronger fluctuations than the time before (2003-2009). The range and the standard deviation of groundwater storage change also increased in recent years especially after 2010. At the basin scale, locations which exhibited higher variabilities (large standard deviation) over time generally showed radical decrease of groundwater storage. The results indicated that groundwater depletion may reduce the aquifers' function for ecosystem resilience, thus posing risks to the ecosystem of the YRB and threatening its people to climate change and extreme events. Despite the overall trend, the changes were heterogeneous if looking at finer scales: spatially, there was a gradual decline of storage from west to east (e.g. the change in December 2016 was -3.6, -9.1 and -25.8 cm for the upper, middle and lower reach, respectively); and temporally, the timeseries among the reaches were significantly different (p = 0.023). Our hotspot analysis also indicated the heterogeneity in groundwater decline across the basin and through the time. Additionally, it showed that human factors (e.g. groundwater consumption) become dominant in determining the groundwater change pattern over climatic variations. We therefore call for more attention to groundwater in developing sustainable water management strategies and suggest a closer cooperation of neighboring provinces in the YRB to have a reciprocal strategic plan for water regulation, protection, and management.

Identifying Climate-Induced Groundwater Depletion in GRACE Observations

Depletion of groundwater resources has been identified in numerous global aquifers, suggesting that extractions have exceeded natural recharge rates in critically important global freshwater supplies. Groundwater depletion has been ascribed to groundwater pumping, often ignoring influences of direct and indirect consequences of climate variability. Here, we explore relations between natural and human drivers and spatiotemporal changes in groundwater storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites using regression procedures and dominance analysis. Changes in groundwater storage are found to be influenced by direct climate variability, whereby groundwater recharge and precipitation exhibited greater influence as compared to groundwater pumping. Weak influence of groundwater pumping may be explained, in part, by quasi-equilibrium aquifer conditions that occur after “long-time” pumping, while precipitation and groundwater recharge records capture groundwater responses linked to climate-induced groundwater depletion. Evaluating groundwater response to climate variability is critical given the reliance of groundwater resources to satisfy water demands and impending changes in climate variability that may threaten future water availability.

Statistical and Numerical Assessments of Groundwater Resource Subject to Excessive Pumping: Case Study in Southwest Taiwan

Groundwater, a salient water resource in Taiwan, has been subject to incessant and excessive pumping, inducing serious regional land subsidence and seawater intrusion. This study aims at assessing how excessive pumping impacts groundwater variations over the Pingtung Alluvial Plain (PAP) in Southwest Taiwan using both statistical and numerical techniques. We apply nonparametric methods to analyze the changing point and annual trend in various hydro-meteorological time series (e.g., rainfall, temperature, and groundwater levels (GLs)). Afterwards, we employ an integrated surface-subsurface model referred to as WASH123D to simulate GLs under the pumping-free scenario; any discrepancies identified between simulated and observed GLs could be an indicator of unregulated/illegal pumping. We find that annual GLs exhibit a significant increasing (decreasing) trend in the western (eastern) PAP. Our numerical experiment reveals diverging trends in simulated and observed GLs, mostly at the downstream of all the major tributaries, suggesting the consequence of unregulated/illegal pumping. Furthermore, upstream pumping may reduce lateral flow towards the downstream coastal area, triggering land subsidence in remote locations.

Modeling of GRACE-Derived Groundwater Information in the Colorado River Basin

Groundwater depletion has been one of the major challenges in recent years. Analysis of groundwater levels can be beneficial for groundwater management. The National Aeronautics and Space Administration’s twin satellite, Gravity Recovery and Climate Experiment (GRACE), serves in monitoring terrestrial water storage. Increasing freshwater demand amidst recent drought (2000–2014) posed a significant groundwater level decline within the Colorado River Basin (CRB). In the current study, a non-parametric technique was utilized to analyze historical groundwater variability. Additionally, a stochastic Autoregressive Integrated Moving Average (ARIMA) model was developed and tested to forecast the GRACE-derived groundwater anomalies within the CRB. The ARIMA model was trained with the GRACE data from January 2003 to December of 2013 and validated with GRACE data from January 2014 to December of 2016. Groundwater anomaly from January 2017 to December of 2019 was forecasted with the tested model. Autocorrelation and partial autocorrelation plots were drawn to identify and construct the seasonal ARIMA models. ARIMA order for each grid was evaluated based on Akaike’s and Bayesian information criterion. The error analysis showed the reasonable numerical accuracy of selected seasonal ARIMA models. The proposed models can be used to forecast groundwater variability for sustainable groundwater planning and management.

Species delimitation in endangered groundwater salamanders: Implications for aquifer management and biodiversity conservation

Groundwater-dependent species are among the least-known components of global biodiversity, as well as some of the most vulnerable because of rapid groundwater depletion at regional and global scales. The karstic Edwards-Trinity aquifer system of west-central Texas is one of the most species-rich groundwater systems in the world, represented by dozens of endemic groundwater-obligate species with narrow, naturally fragmented distributions. Here, we examine how geomorphological and hydrogeological processes have driven population divergence and speciation in a radiation of salamanders (Eurycea) endemic to the Edwards-Trinity system using phylogenetic and population genetic analysis of genome-wide DNA sequence data. Results revealed complex patterns of isolation and reconnection driven by surface and subsurface hydrology, resulting in both adaptive and nonadaptive population divergence and speciation. Our results uncover cryptic species diversity and refine the borders of several threatened and endangered species. The US Endangered Species Act has been used to bring state regulation to unrestricted groundwater withdrawals in the Edwards (Balcones Fault Zone) Aquifer, where listed species are found. However, the Trinity and Edwards-Trinity (Plateau) aquifers harbor additional species with similarly small ranges that currently receive no protection from regulatory programs designed to prevent groundwater depletion. Based on regional climate models that predict increased air temperature, together with hydrologic models that project decreased springflow, we conclude that Edwards-Trinity salamanders and other codistributed groundwater-dependent organisms are highly vulnerable to extinction within the next century.

SWB Modeling of Groundwater Recharge on Catalina Island, California, during a Period of Severe Drought

This study applied a soil water balance (SWB) model to simulate groundwater recharge on Catalina Island, California, for the years 2008–2014, a period that coincided with a severe drought. Island-wide average recharge ranged from 0.05 mm/year in 2013 to 82.3 mm/year in 2008, with a 7-year mean of 23.0 mm/year. High recharge is primarily associated with east-facing mountain fronts and the land cover types “developed, open space” and “herbaceous”. This spatial trend is also reflected in recharge estimates for groundwater well locations produced by the Cl mass balance method. Only in 2008 did all areas of the island experience recharge, while the recharge was very low during the drought years 2009 and 2012–2014. Sensitivity analyses indicate an unresolved discrepancy in land cover classification (i.e., herbaceous grass dominated vs. chaparral and coastal sage dominated) to be a significant factor. In a scenario where herbaceous grass dominates, as field studies from the early 1980s imply, recharge estimates nearly double. Nevertheless, the overall low recharge rates presented herein and the fact that drought conditions in Southern California have worsened since 2014 suggest that large parts of the island may not have received any recharge in nearly a decade.

Monitoring of Land Use/Land-Cover Changes in the Arid Transboundary Middle Rio Grande Basin Using Remote Sensing

Expanding urbanization in highly fragile desert environments requires a thorough understanding of the current state and trends of land uses to achieve an optimal balance between development and the integrity of vital ecosystems. The objectives of this study are to quantify land use change over the 25-year period 1990–2015 and analyze temporal and spatial urbanization trends in the Middle Rio Grande Basin. We conclude by indicating how the results can inform on-going water resource research and public policy discussion in an arid region. Results show that the predominant upland mixed vegetation land cover category has been steadily declining, giving up land to urban and agricultural development. Urban development across the region of interest increased from just under three percent in 1990 to more than 11 percent in 2015, mainly around the major urban areas of El Paso, Ciudad Juárez, and Las Cruces. Public policy aspects related to results from this study include transfer of water rights from agriculture to land developers in cities, higher risk of flooding, loss of natural ecosystems, and increased water pollution from point and non-point sources. Various stakeholders can find the study useful for a better understanding of historical spatial and temporal aspects of urban development and environmental change in arid regions. Such insights can help municipal authorities, farmers, and other stakeholders to strike a balance between development needs and protecting vital ecosystems that support the much needed development, especially in regions that are endowed with transboundary natural resources that often are incompletely represented in single nation data.

Joint Operation of Surface Water and Groundwater Reservoirs to Address Water Conflicts in Arid Regions: An Integrated Modeling Study

At the basin scale, the operation of surface water reservoirs rarely takes groundwater aquifers into consideration, which can also be regarded as reservoirs underground. This study investigates the impact of reservoir operation on the water cycle and evaluates the effect of the joint operation of surface water and groundwater reservoirs on the water conflict in arid regions through an integrated modeling approach. The Heihe River Basin (HRB) in northwestern China is selected as the study area. Our results show that the ecological operational strategies of a reservoir under construction in the upper HRB have a direct impact on the agricultural water uses and consequently affect other hydrological processes. The ecological operation strategy with a smaller water release and a longer duration is beneficial to securing the environmental flow towards the downstream area and to replenishing aquifers. With the joint operation of surface water and groundwater reservoirs, a balance among the agriculture water need, the groundwater sustainability in the Middle HRB and the ecological water need in the Lower HRB can be flexibly achieved. However, the joint operation can hardly improve the three aspects simultaneously. To resolve the water conflict in HRB, additional engineering and/or policy measures are desired.

Groundwater Development Stress: Global-Scale Indices Compared to Regional Modeling

The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.

Long-term Water Table Monitoring of Rio Grande Riparian Ecosystems for Restoration Potential Amid Hydroclimatic Challenges

Hydrological processes drive the ecological functioning and sustainability of cottonwood-dominated riparian ecosystems in the arid southwestern USA. Snowmelt runoff elevates groundwater levels and inundates floodplains, which promotes cottonwood germination. Once established, these phreatophytes rely on accessible water tables (WTs). In New Mexico's Middle Rio Grande corridor diminished flooding and deepening WTs threaten native riparian communities. We monitored surface flows and riparian WTs for up to 14 years, which revealed that WTs and surface flows, including peak snowmelt discharge, respond to basin climate conditions and resource management. WT hydrographs influence the composition of riparian communities and can be used to assess if potential restoration sites meet native vegetation tolerances for WT depths, rates of recession, and variability throughout their life stages. WTs were highly variable in some sites, which can preclude native vegetation less adapted to deep drawdowns during extended droughts. Rates of WT recession varied between sites and should be assessed in regard to recruitment potential. Locations with relatively shallow WTs and limited variability are likely to be more viable for successful restoration. Suitable sites have diminished greatly as the once meandering Rio Grande has been constrained and depleted. Increasing demands on water and the presence of invasive vegetation better adapted to the altered hydrologic regime further impact native riparian communities. Long-term monitoring over a range of sites and hydroclimatic extremes reveals attributes that can be evaluated for restoration potential.

How might recharge change under projected climate change in western US?

Although groundwater is a major resource of water in the western US, little research has been done on the impacts of climate change on groundwater storage and recharge in the West. Here we assess the impact of projected changes in climate on groundwater recharge in the near (2021-2050) and far (2071-2100) future across the western US. Recharge is expected to decrease slightly (highly certain) in the West (-1.6%) and Southwest (-2.9%) regions in the near future and decrease considerably (highly certain) in the South region (-10.6%) in the far future. The Northern Rockies region is expected to get more recharge (highly certain) in both the near (+5.0%) and far (+9.0%) future. In general, southern portions of the western US are expected to get less recharge in the future and northern portions will get more. This study also shows that climate change interacts with land surface properties to affect the amount of recharge that occurs in the future.

GRACE satellite observations reveal the severity of recent water over-consumption in the United States

Changes in the climate and population growth will critically impact the future supply and demand of water, leading to large uncertainties for sustainable resource management. In the absence of on-the-ground measurements to provide spatially continuous, high-resolution information on water supplies, satellite observations can provide essential insight. Here, we develop a technique using observations from the Gravity Recovery and Climate Experiment (GRACE) satellite to evaluate the sustainability of surface water and groundwater use over the continental United States. We determine the annual total water availability for 2003–2015 using the annual variability in GRACE-derived total water storage for 18 major watersheds. The long-term sustainable water quantity available to humans is calculated by subtracting an annual estimate of the water needed to maintain local ecosystems, and the resulting water volumes are compared to reported consumptive water use to determine a sustainability fraction. We find over-consumption is highest in the southwest US, where increasing stress trends were observed in all five basins and annual consumptive use exceeded 100% availability twice in the Lower Colorado basin during 2003–2015. By providing a coarse-scale evaluation of sustainable water use from satellite and ground observations, the established framework serves as a blueprint for future large-scale water resource monitoring.

Partitioning Evapotranspiration into Green and Blue Water Sources in the Conterminous United States

In this study, we combined two 1 km actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface water/groundwater) sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001–2015. Our results indicate that average green and blue water for all land cover types in CONUS accounts for nearly 70% and 30% of the total ET, respectively. The ET in the eastern US arises mostly from GWET, and in the western US, it is mostly BWET. Analysis of the BWET in the 16 irrigated areas in CONUS revealed interesting results. While the magnitude of the BWET gradually showed a decline from west to east, the increase in coefficient of variation from west to east confirmed greater use of supplemental irrigation in the central and eastern US. We also established relationships between different hydro-climatology zones and their blue water requirements. This study provides insights on the relative contributions and the spatiotemporal dynamics of GWET and BWET, which could lead to improved water resources management.