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Groundwater is the most ubiquitous source of liquid freshwater globally, yet its role in supporting diverse ecosystems is rarely acknowledged1,2. However, the location and extent of groundwater-dependent ecosystems (GDEs) are unknown in many geographies, and protection measures are lacking1,3. Here, we map GDEs at high-resolution (roughly 30 m) and find them present on more than one-third of global drylands analysed, including important global biodiversity hotspots4. GDEs are more extensive and contiguous in landscapes dominated by pastoralism with lower rates of groundwater depletion, suggesting that many GDEs are likely to have already been lost due to water and land use practices. Nevertheless, 53% of GDEs exist within regions showing declining groundwater trends, which highlights the urgent need to protect GDEs from the threat of groundwater depletion. However, we found that only 21% of GDEs exist on protected lands or in jurisdictions with sustainable groundwater management policies, invoking a call to action to protect these vital ecosystems. Furthermore, we examine the linkage of GDEs with cultural and socio-economic factors in the Greater Sahel region, where GDEs play an essential role in supporting biodiversity and rural livelihoods, to explore other means for protection of GDEs in politically unstable regions. Our GDE map provides critical information for prioritizing and developing policies and protection mechanisms across various local, regional or international scales to safeguard these important ecosystems and the societies dependent on them.

Continental-to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth system above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths, and limitations, so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities, and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when, or where large-scale models achieve their purpose or where opportunities for improvements exist so that such models better achieve their purpose. We suggest that reproducing the spatiotemporal details of regional-scale models and matching local data are not relevant goals. Instead, it is important to decide on reasonable model expectations regarding when a large-scale model is performing "well enough"in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria are quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental-to global-scale models. We describe current modeling strategies and evaluation practices, and we subsequently discuss the value of three evaluation strategies: (1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation), (2) comparing several models with each other with or without reference to actual observations (model-based evaluation), and (3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning, and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models, thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

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.

The dwindling groundwater resource of India, supporting almost one fifth of the global population and also the largest groundwater user, has been of great concern in recent years. However, in contrary to the well documented Indian groundwater depletion due to rapid and unmanaged groundwater withdrawal, here for the first time, we report regional-scale groundwater storage (GWS) replenishment through long-term (1996-2014, using more than 19000 observation locations) in situ and decadal (2003-2014) satellite-based groundwater storage measurements in western and southern parts of India. In parts of western and southern India, in situ GWS (GWSobs) has been decreasing at the rate of -5.81 ± 0.38 km3/year (in 1996-2001) and -0.92 ± 0.12 km3/year (in 1996-2002), and reversed to replenish at the rate of 2.04 ± 0.20 km3/year (in 2002-2014) and 0.76 ± 0.08 km3/year (in 2003-2014), respectively. Here, using statistical analyses and simulation results of groundwater management policy change effect on groundwater storage in western and southern India, we show that paradigm shift in Indian groundwater withdrawal and management policies for sustainable water utilization appear to have started replenishing the aquifers in western and southern parts of India.

The dwindling groundwater resource of India, supporting almost one fifth of the global population and also the largest groundwater user, has been of great concern in recent years. However, in contrary to the well documented Indian groundwater depletion due to rapid and unmanaged groundwater withdrawal, here for the first time, we report regional-scale groundwater storage (GWS) replenishment through long-term (1996-2014, using more than 19000 observation locations) in situ and decadal (2003-2014) satellite-based groundwater storage measurements in western and southern parts of India. In parts of western and southern India, in situ GWS (GWSobs) has been decreasing at the rate of -5.81 ± 0.38 km3/year (in 1996-2001) and -0.92 ± 0.12 km3/year (in 1996-2002), and reversed to replenish at the rate of 2.04 ± 0.20 km3/year (in 2002-2014) and 0.76 ± 0.08 km3/year (in 2003-2014), respectively. Here, using statistical analyses and simulation results of groundwater management policy change effect on groundwater storage in western and southern India, we show that paradigm shift in Indian groundwater withdrawal and management policies for sustainable water utilization appear to have started replenishing the aquifers in western and southern parts of India.

Abstract The widespread influence of reservoirs on global rivers makes representations of reservoir outflow and storage essential components of large-scale hydrology and climate simulations across the land surface and atmosphere. Yet, reservoirs have yet to be commonly integrated into earth system models. This deficiency influences model processes such as evaporation and runoff, which are critical for accurate simulations of the coupled climate system. This study describes the development of a generalized reservoir model capable of reproducing realistic reservoir behavior for future integration in a global land surface model (LSM). Equations of increasing complexity relating reservoir inflow, outflow, and storage were tested for 14 California reservoirs that span a range of spatial and climate regimes. Temperature was employed in model equations to modulate seasonal changes in reservoir management behavior and to allow for the evolution of management seasonality as future climate varies. Optimized parameter values for the best-performing model were generalized based on the ratio of winter inflow to storage capacity so a future LSM user can generate reservoirs in any grid location by specifying the given storage capacity. Model performance statistics show good agreement between observed and simulated reservoir storage and outflow for both calibration (mean normalized RMSE = 0.48; mean coefficient of determination = 0.53) and validation reservoirs (mean normalized RMSE = 0.15; mean coefficient of determination = 0.67). The low complexity of model equations that include climate-adaptive operation features combined with robust model performance show promise for simulations of reservoir impacts on hydrology and climate within an LSM.

Abstract The widespread influence of reservoirs on global rivers makes representations of reservoir outflow and storage essential components of large-scale hydrology and climate simulations across the land surface and atmosphere. Yet, reservoirs have yet to be commonly integrated into earth system models. This deficiency influences model processes such as evaporation and runoff, which are critical for accurate simulations of the coupled climate system. This study describes the development of a generalized reservoir model capable of reproducing realistic reservoir behavior for future integration in a global land surface model (LSM). Equations of increasing complexity relating reservoir inflow, outflow, and storage were tested for 14 California reservoirs that span a range of spatial and climate regimes. Temperature was employed in model equations to modulate seasonal changes in reservoir management behavior and to allow for the evolution of management seasonality as future climate varies. Optimized parameter values for the best-performing model were generalized based on the ratio of winter inflow to storage capacity so a future LSM user can generate reservoirs in any grid location by specifying the given storage capacity. Model performance statistics show good agreement between observed and simulated reservoir storage and outflow for both calibration (mean normalized RMSE = 0.48; mean coefficient of determination = 0.53) and validation reservoirs (mean normalized RMSE = 0.15; mean coefficient of determination = 0.67). The low complexity of model equations that include climate-adaptive operation features combined with robust model performance show promise for simulations of reservoir impacts on hydrology and climate within an LSM.

© 2015. American Geophysical Union. All Rights Reserved. The impacts of droughts on the Amazon ecosystem have been broadly discussed in recent years, but a comprehensive understanding of the consequences is still missing. In this study, we show evidence of a fragile hydrological equilibrium in the western Amazon. While drainage systems located near the equator and the western Amazon do not show water deficit in years with average climate conditions, this equilibrium can be broken during drought events. More importantly, we show that this effect is persistent, taking years until the normal hydrological patterns are reestablished. We show clear links between persistent changes in forest canopy structure and changes in hydrological patterns, revealing physical evidence of hydrological mechanisms that may lead to permanent changes in parts of the Amazon ecosystem. If prospects of increasing drought frequency are confirmed, a change in the current hydroecological patterns in the western Amazon could take place in less than a decade.

Sustainable groundwater management requires approaches to assess the influence of climate and management actions on the evolution of groundwater systems. Traditional approaches that apply continuity to assess groundwater sustainability fail to capture the spatial variability of aquifer responses. To address this gap, our study evaluates groundwater elevation data from the Coachella Valley, California, within a groundwater sustainability framework given the adoption of integrative management strategies in the valley. Our study details an innovative approach employing traditional statistical methods to improve understanding of aquifer responses. In this analysis, we evaluate trends at individual groundwater observation wells and regional groundwater behaviors using field significance. Regional elevation trends identified no significant trends during periods of intense groundwater replenishment, active since 1973, despite spatial variability in individual well trends. Our results illustrate the spatially limited effects of groundwater replenishment occur against a setting of long-term groundwater depletion, raising concerns over the definition of sustainable groundwater management in aquifer systems employing integrative management strategies.

© 2015. American Geophysical Union. This study presents a new algorithm for parallel computation of river flow that builds on recent work demonstrating the relative independence of distant river reaches in the update step of the Muskingum method. The algorithm is designed to achieve enhanced fixed-size parallel speedup and uses a mathematical approximation applied at the boundaries of large subbasins. In order to use such an algorithm, a balanced domain decomposition method that differs from the traditional classifications of river reaches and subbasins and based on network topology is developed. An application of the algorithm and domain decomposition method to the Mississippi River Basin results in an eightfold decrease in computing time with 16 computing cores which is unprecedented for Muskingum-type algorithms applied in classic parallel-computing paradigms having a one-to-one relationship between cores and subbasins. An estimated 300 km between upstream and downstream reaches of subbasins guarantees the applicability of the algorithm in our study and motivates further investigation of domain decomposition methods.

Renewable groundwater stress is quantified in the world's largest aquifersCharacteristic stress regimes are defined to determine the severity of stressOverstressed aquifers are mainly in rangeland biomes with some croplands.

Groundwater resilience is defined and quantified with remote sensing from GRACETimescales of aquifer depletion are assessed as a Total Groundwater Stress ratioThe volume of usable global groundwater storage is found to be largely unknown.

Renewable groundwater stress is quantified in the world's largest aquifersCharacteristic stress regimes are defined to determine the severity of stressOverstressed aquifers are mainly in rangeland biomes with some croplands.

Groundwater resilience is defined and quantified with remote sensing from GRACETimescales of aquifer depletion are assessed as a Total Groundwater Stress ratioThe volume of usable global groundwater storage is found to be largely unknown.

Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.

Soil water storage is a fundamental signal in the land hydrological cycle and changes in soil moisture can affect regional climate. In this study, we used simulations from Coupled Model Intercomparison Project Phase 5 archives to investigate changes in the annual range of soil water storage under global warming at northern middle and high latitudes. Results show that future warming could lead to significant declines in snowfall, and a corresponding lack of snowmelt water recharge to the soil, which makes soil water less available during spring and summer. Conversely, more precipitation as rainfall results in higher recharge to soil water during its accumulating season. Thus, the wettest month of soil water gets wetter, and the driest month gets drier, resulting in an increase of the annual range and suggesting that stronger heterogeneity in global water distribution (changing extremes) could occur under global warming; this has implications for water management and water security under a changing climate.

Porous shallow-water models (porosity models) simulate urban flood flows orders of magnitude faster than classical shallow-water models due to a relatively coarse grid and large time step, enabling flood hazard mapping over far greater spatial extents than is possible with classical shallow-water models. Here the errors of both isotropic and anisotropic porosity models are examined in the presence of anisotropic porosity, i.e., unevenly spaced obstacles in the cross-flow and along-flow directions, which is common in practical applications. We show that porosity models are affected by three types of errors: (a) structural model error associated with limitations of the shallow-water equations, (b) scale errors associated with use of a relatively coarse grid, and (c) porosity model errors associated with the formulation of the porosity equations to account for sub-grid scale obstructions. Results from a unique laboratory test case with strong anisotropy indicate that porosity model errors are smaller than structural model errors, and that porosity model errors in both depth and velocity are substantially smaller for anisotropic versus isotropic porosity models. Test case results also show that the anisotropic porosity model is equally accurate as classical shallow-water models when compared directly to gage measurements, while the isotropic model is less accurate. Further, results show the anisotropic porosity model resolves flow variability at smaller spatial scales than the isotropic model because the latter is restricted by the assumption of a Representative Elemental Volume (REV) which is considerably larger than the size of obstructions. These results point to anisotropic porosity models as being well-suited to whole-city urban flood prediction, but also reveal that point-scale flow attributes relevant to flood risk such as localized wakes and wave reflections from flow obstructions may not be resolved.

Accurate quantification of evapotranspiration (ET) at the watershed-scale remains an important research challenge. ET products from model simulations and remote sensing, even after incorporating in situ ET observations from flux towers in calibration or assimilation procedures, often produce different watershed areal-averaged ET estimates. These differences in ET estimates are magnified when they are integrated over time as part of water balance calculations. To address this challenge, we present a methodology for comparing watershed-average ET within a water balance framework that makes use of Gravity Recovery and Climate Experiment (GRACE)-observed terrestrial water storage change (TWSC). The methodology is demonstrated for South Carolina for a five-year period (2003-2007) using four different ET products: ET generated using a locally calibrated VIC model, a MODIS-derived ET product, and ET generated from two models (NOAH and VIC) as part of the North American Land Data Assimilation Systems 2 (NLDAS-2) project. The results of the example application suggest that the NLDAS-NOAH ET product is most consistent with GRACE-observed TWSC for the overall study region and time period. However, for periods of decreasing TWS, when ET becomes a more significant term in the water balance, the locally calibrated VIC model showed the most agreement with GRACE-observed TWSC. Application of the methodology for other regions and time periods can provide insight into different ET products when used for watershed-scale water resources management.

We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

The fate of irrigation in urban ecosystems is highly uncertain, due to uncertainties in urban ecohydrology. We compared irrigation rates, soil moisture, evapotranspiration (ET), stomatal conductance, and water budgets of landscape ecosystems managed with different turfgrass species and irrigation technologies. The "Typical" landscape had a cool-season fescue and was irrigated by an automatic timer. The "Alternative1" landscape had a warm-season paspalum and a "smart" soil moisture sensor-based irrigation system. The "Alternative2" landscape had a cool-season native sedge and a "smart" weather station-based drip irrigation system. ET was measured with a portable closed chamber and modeled using a Penman-Monteith approach, and the two methods agreed well. The water applied to the Alternative1 was 54 % less than the water applied to the Typical landscape, and the water applied to the Alternative2 was 24 % less. Soil moisture was similar in the Typical and Alternative2, while Alternative1 was drier in spring. The stomatal conductance of sedge was lower than the other two species, but its ET was not lower due to higher leaf area. Irrigation efficiencies (ET/applied irrigation) were 57 - 58 %, 86 - 97 %, and 78 - 80 % for the Typical, Alternative1, and Alternative2 landscapes, respectively. Runoff was less than 2 % in each landscape, and excess irrigation primarily drained below the root zone. Differences in irrigation efficiency between landscapes were due mainly to irrigation application, which varied more than species water use. Smart irrigation systems provided substantial water savings relative to a timer-based system, and prevented significant drainage losses. The utilization of smart sensors was more important than the choice of turfgrass species for irrigation efficiency. © 2014 Springer Science+Business Media New York.

Streamflow of the Colorado River Basin is the most overallocated in the world. Recent assessment indicates that demand for this renewable resource will soon outstrip supply, suggesting that limited groundwater reserves will play an increasingly important role in meeting future water needs. Here we analyze 9 years (December 2004 to November 2013) of observations from the NASA Gravity Recovery and Climate Experiment mission and find that during this period of sustained drought, groundwater accounted for 50.1 km3 of the total 64.8 km3 of freshwater loss. The rapid rate of depletion of groundwater storage (-5.6 ± 0.4 km3 yr-1) far exceeded the rate of depletion of Lake Powell and Lake Mead. Results indicate that groundwater may comprise a far greater fraction of Basin water use than previously recognized, in particular during drought, and that its disappearance may threaten the long-term ability to meet future allocations to the seven Basin states.

Streamflow of the Colorado River Basin is the most overallocated in the world. Recent assessment indicates that demand for this renewable resource will soon outstrip supply, suggesting that limited groundwater reserves will play an increasingly important role in meeting future water needs. Here we analyze 9 years (December 2004 to November 2013) of observations from the NASA Gravity Recovery and Climate Experiment mission and find that during this period of sustained drought, groundwater accounted for 50.1 km3 of the total 64.8 km3 of freshwater loss. The rapid rate of depletion of groundwater storage (-5.6 ± 0.4 km3 yr-1) far exceeded the rate of depletion of Lake Powell and Lake Mead. Results indicate that groundwater may comprise a far greater fraction of Basin water use than previously recognized, in particular during drought, and that its disappearance may threaten the long-term ability to meet future allocations to the seven Basin states.

The effect of mesh type on the accuracy and computational demands of a two-dimensional Godunov-type flood inundation model is critically examined. Cartesian grids, constrained and unconstrained triangular grids, constrained quadrilateral grids, and mixed meshes are considered, with and without local time stepping (LTS), to determine the approach that maximizes computational efficiency defined as accuracy relative to computational effort. A mixed-mesh numerical scheme is introduced so all grids are processed by the same solver. Analysis focuses on a wide range of dam-break type test cases, where Godunov-type flood models have proven very successful. Results show that different mesh types excel under different circumstances. Cartesian grids are 2-3 times more efficient with relatively simple terrain features such as rectilinear channels that call for a uniform grid resolution, while unstructured grids are about twice as efficient in complex domains with irregular terrain features that call for localized refinements. The superior efficiency of locally refined, unstructured grids in complex terrain is attributable to LTS; the locally refined unstructured grid becomes less efficient using global time stepping. These results point to mesh-type tradeoffs that should be considered in flood modeling applications. A mixed mesh model formulation with LTS is recommended as a general purpose solver because the mesh type can be adapted to maximize computational efficiency. © 2014 Elsevier Ltd.

We present a quantitative approach for measuring hydrological drought occurrence and severity based on terrestrial water storage observations from NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission. GRACE measurements are applied by calculating the magnitude of the deviation of regional, monthly terrestrial water storage anomalies from the time series' monthly climatology, where negative deviations represent storage deficits. Monthly deficits explicitly quantify the volume of water required to return to normal water storage conditions. We combine storage deficits with event duration to calculate drought severity. Drought databases are referenced to identify meteorological drought events in the Amazon and Zambezi River basins and the southeastern United States and Texas regions. This storage deficit method clearly identifies hydrological drought onset, end, and duration; quantifies instantaneous severity and peak drought magnitude; and compares well with the meteorological drought databases. It also reveals information about the hydrological effects of meteorological drought on regional water storage. Key Point GRACE-based drought severity using water storage rather than just precipitation explicitly quantifies the volume of water needed to return to normal conditions and identifies hydrological drought onset, peak magnitude, duration, and severity ©2014. American Geophysical Union. All Rights Reserved.

A thorough assessment of evapotranspiration (ET) pervades several important issues of the 21st century including climate change, food-security, land-management, flood and drought prediction, and water resources assessment and management. Such a proper assessment is of particular importance in the Ganga river basin (GRB) with its backdrop of a rapidly increasing population pressure and unregulated use of water resources. Spatially averaged ET over the GRB is computed as the residual of atmospheric and terrestrial water budget computations using a combination of model simulations and satellite and ground-based observations. The best estimate of monthly ET is obtained as the monthly mean of atmospheric and terrestrial water balance computations for the period 1980-2007. The mean monthly average of ET from these various estimates is 72.3±18.8 mm month-1. Monthly variations of ET peak between July and August and reach a minimum in February. For the entire study period, the rate of change of ET across the GRB is -11 mm yr -2 (i.e., mm/yr/yr). Alongside a notable influence of the 1997-1998 El Niño, results allude to the existence of interim periods during which ET trends varied significantly. More specifically, during the period of 1998-2002, the rate of decline increased to -55.8 mm yr -2, which is almost 5 times the overall trend. Based on the correlation between ET and independent estimates of near-surface temperature and soil moisture, we can infer that the ET over the GRB is primarily limited by moisture availability. The analysis has important potential for use in large-scale water budget assessments and intercomparison studies. The analysis also emphasizes the importance of synergistic use of mutliplatform hydrologic information. © 2014. American Geophysical Union. All Rights Reserved.

The Seogu (western) portion of Daegu, Korea experiences chronic urban flooding and there is a need to increase flood detention and storage to reduce flood impacts. Since the site is densely developed, use of an underground car park as a cistern has been proposed. The stormwater management model (SWMM) is applied to study alternative hydraulic designs and overall performance, and it is shown that by linking SWMM to a two-dimensional flood inundation model, SWMM parameters can be calibrated from observations of flood extent. Calibration would otherwise not be possible because storm sewer flows are not internally monitored. This study reveals a significant sensitivity in SWMM relative to surcharge prediction, demonstrates a creative repurposing of urban infrastructure to manage extreme flood events and shows the importance of flood documentation relative to drainage infrastructure analysis and design.

Glacier mass variations have a direct impact on some of the key components of the global water cycle, including sea level rise and freshwater availability. Apart from being one of the largest Himalayan glaciers, Gangotri is one of the sources of water for the Ganges river, which has a considerable influence on the socioeconomic structure of a largely over-populated catchment area accounting for ~26% of India's landmass. In this study, we present the most recent assessment of the Gangotri glacier dynamics, combining the use of interferometric techniques on synthetic aperture radar data and sub-pixel offset tracking on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. Results show that on average, the Gangotri glacier snout has receded at a rate of 21.3 ± 3 m year-1 over a period of 6 years (2004-2010). While glacier surface velocity near the snout is estimated to be between 24.8 ± 2.3 and 28.9 ± 2.3 m year-1, interior portions of the glacier recorded velocities in the range of 13.9 ± 2.3 to 70.2 ± 2.3 m year-1. Further, the average glacier surface velocity in the northern (lower) portions (28.1 ± 2.3 m year-1) is observed to be significantly lower than in the southern (higher) portions (48.1 ± 2.3 m year-1) of the Gangotri glacier. These values are calculated with an uncertainty of less than 5 m year-1. Results also highlight a consistent retreat and non-uniform dynamics of the Gangotri glacier. © 2013 © Taylor & Francis.

The base flow recession constant, Kb , is used to characterize the interaction of groundwater and surface water systems. Estimation ofKb  is critical in many studies including rainfall-runoff modeling, estimation of low flow statistics at ungaged locations, and base flow separation methods. The performance of several estimators of Kb  are compared, including several new approaches which account for the impact of human withdrawals. A traditional semilog estimation approach adapted to incorporate the influence of human withdrawals was preferred over other derivative-based estimators. Human withdrawals are shown to have a significant impact on the estimation of base flow recessions, even when withdrawals are relatively small. Regional regression models are developed to relate seasonal estimates ofKb  to physical, climatic, and anthropogenic characteristics of stream-aquifer systems. Among the factors considered for explaining the behavior of Kb , both drainage density and human withdrawals have significant and similar explanatory power. We document the importance of incorporating human withdrawals into models of the base flow recession response of a watershed and the systemic downward bias associated with estimates of Kb  obtained without consideration of human withdrawals.

We analyze 10 years of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) over tropical South America along with seven climate indices linked to equatorial Pacific and tropical Atlantic oceans sea surface temperatures (SSTs) using a multichannel singular spectrum analysis and lagged cross correlations. We focus on the interannual, nonlinear modes of covariability between TWSAs and SSTs. By comparing the relative distributions of the leading modes, we identify teleconnections between TWSAs, Pacific and Atlantic SSTs at different time periods. Thus, the northern and northeastern regions of tropical South America are mainly influenced by Pacific SSTs, while the central and western Amazon regions are more influenced by Atlantic SSTs. The former regions are more sensitive to central Pacific SSTs than to eastern Pacific SSTs. A quasi-biennial mode explains the largest part (27%) of the residual, interannual cross covariance and is found both in the El Niño–Southern Oscillation and in the Atlantic meridional mode. A trend-like mode explains the second largest part (24%) of the residual cross covariance and may be caused by the following: (1) the decadal variability in the North Pacific climate, as expressed by the negative trend in the Pacific decadal oscillation and by increased water storage in northern and northeastern South America, (2) the melting of Andean glaciers in Peru and Bolivia due to man-induced increase in land surface temperatures, and (3) the land use/cover changes after deforestation leading to increased runoff and groundwater recharge, expressed by increased water storage in southern Amazon regions.

Stratocumulus clouds (SC) often exist over the eastern subtropical oceans during the summer and have significant impacts on the surface radiation budget. Both atmospheric subsidence and lower troposphere stability (LTS) have been found to play important roles in maintaining SC. Using global climate model simulations, we find that irrigation in California's Central Valley results in a decrease of land surface temperature, leading to a smaller land-sea heat contrast, and a corresponding reduction in sea breeze, subsidence, and LTS over the near-coastal region. The decrease in LTS directly drives a reduction in modeled SC coverage, and it would arguably do so in reality because of the well-known link between LTS and SC coverage. Consequently, simulated absorbed surface solar radiation over this region increases by 8 W/m2 (3.7%) due to the reduction in SC cover, resulting in the warming at the Earth's surface. This study has important implications for how SC can change with regard to future climate. In contrast to the general effects of climate change on the formation of SC, our results suggest that irrigation practices in the Central Valley may drive a decrease in nearby SC coverage.

Satellite data may enable improved management of regional groundwater reserves.

Fire risk in the Amazon can be predicted several months before the onset of the dry season using sea surface temperatures in the tropical north Atlantic and tropical Pacific. The lead times between ocean state and the period of maximum burning (4–11 months) may enable the development of forecasts with benefits for forest conservation, yet the underlying physical and biological mechanisms responsible for these temporal offsets are not well known. Here, we examined the hypothesis that year-to-year variations in soil water recharge during the wet season modify atmospheric water vapor and fire behavior during the following dry season. We tested this hypothesis by analyzing terrestrial water storage observations from the Gravity Recovery and Climate Experiment (GRACE), active fires from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several other satellite and atmospheric reanalysis datasets during 2002–2011. We found that terrestrial water storage deficits preceded severe fire seasons across the southern Amazon. The most significant relationships between monthly terrestrial water storage and the sum of active fires during the dry season occurred during April–August (p

A long-standing challenge for hydrologists has been a lack of observational data on global-scale basin hydrological behavior. With observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission, hydrologists are now able to study terrestrial water storage for large river basins (>200,000 km2), with monthly time resolution. Here we provide results of a time series model of basin-averaged GRACE terrestrial water storage anomaly and Global Precipitation Climatology Project precipitation for the world's largest basins. We address the short (10 year) length of the GRACE record by adopting a parametric spectral method to calculate frequency-domain transfer functions of storage response to precipitation forcing and then generalize these transfer functions based on large-scale basin characteristics, such as percent forest cover and basin temperature. Among the parameters tested, results show that temperature, soil water-holding capacity, and percent forest cover are important controls on relative storage variability, while basin area and mean terrain slope are less important. The derived empirical relationships were accurate (0.54 ≤ Ef  ≤ 0.84) in modeling global-scale water storage anomaly time series for the study basins using only precipitation, average basin temperature, and two land-surface variables, offering the potential for synthesis of basin storage time series beyond the GRACE observational period. Such an approach could be applied toward gap filling between current and future GRACE missions and for predicting basin storage given predictions of future precipitation.

Fire risk in the Amazon can be predicted several months before the onset of the dry season using sea surface temperatures in the tropical north Atlantic and tropical Pacific. The lead times between ocean state and the period of maximum burning (4–11 months) may enable the development of forecasts with benefits for forest conservation, yet the underlying physical and biological mechanisms responsible for these temporal offsets are not well known. Here, we examined the hypothesis that year-to-year variations in soil water recharge during the wet season modify atmospheric water vapor and fire behavior during the following dry season. We tested this hypothesis by analyzing terrestrial water storage observations from the Gravity Recovery and Climate Experiment (GRACE), active fires from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several other satellite and atmospheric reanalysis datasets during 2002–2011. We found that terrestrial water storage deficits preceded severe fire seasons across the southern Amazon. The most significant relationships between monthly terrestrial water storage and the sum of active fires during the dry season occurred during April–August (p

Satellite data may enable improved management of regional groundwater reserves.

Accurate estimation of the characteristics of the winter snowpack is crucial for prediction of available water supply, flooding, and climate feedbacks. Remote sensing of snow has been most successful for quantifying the spatial extent of the snowpack, although satellite estimation of snow water equivalent (SWE), fractional snow covered area, and snow depth is improving. Here we show that GPS observations of vertical land surface loading reveal seasonal responses of the land surface to the total weight of snow, providing information about the stored SWE. We demonstrate that the seasonal signal in Scripps Orbit and Permanent Array Center (SOPAC) GPS vertical land surface position time series at six locations in the western United States is driven by elastic loading of the crust by the snowpack. GPS observations of land surface deformation are then used to predict the water load as a function of time at each location of interest and compared for validation to nearby Snowpack Telemetry observations of SWE. Estimates of soil moisture are included in the analysis and result in considerable improvement in the prediction of SWE.

The mathematical formulation of the Muskingum method, like that of many numerical schemes used for river routing, requires that all upstream river reaches be updated prior to updating the flow rate of any given reach. Due to this topological constraint, such numerical schemes have traditionally been solved in an upstream-to-downstream manner which imposes inherent limitations on the speedup that can be achieved in a parallel computing environment because each computing core has to wait for completion of all cores addressing upstream subbasins prior to starting its own subbasin. The research presented in this paper quantifies the exact influence among river reaches during the update step of the Muskingum method and shows that the influence decreases with increasing distance between two reaches until it becomes too small to be accounted for by floating-point arithmetic. A formal definition of the minimal distance from which the relative influence becomes numerically inexistent—the radius of influence—is presented. Based on this distance, expressed as a number of river reaches, a new estimate of the maximum theoretical speedup that can be achieved by the Muskingum method or by similar numerical schemes is presented and implies large potential gains in computing time when domains are much larger than the radius of influence. An application to the approximately 180,000 river reaches of the Upper Mississippi River Basin at a 15 min time step over 2004 shows a radius of influence on the order of 150 river reaches. The speedup obtained for this application is much higher than previously thought possible but also much lower than could be attained, suggesting that further investigations are necessary.

In this study, we use observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to evaluate freshwater storage trends in the north-central Middle East, including portions of the Tigris and Euphrates River Basins and western Iran, from January 2003 to December 2009. GRACE data show an alarming rate of decrease in total water storage of approximately −27.2±0.6 mm yr−1equivalent water height, equal to a volume of 143.6 km3 during the course of the study period. Additional remote-sensing information and output from land surface models were used to identify that groundwater losses are the major source of this trend. The approach used in this study provides an example of “best current capabilities” in regions like the Middle East, where data access can be severely limited. Results indicate that the region lost 17.3±2.1 mm yr−1 equivalent water height of groundwater during the study period, or 91.3±10.9 km3 in volume. Furthermore, results raise important issues regarding water use in transboundary river basins and aquifers, including the necessity of international water use treaties and resolving discrepancies in international water law, while amplifying the need for increased monitoring for core components of the water budget.

Characterizing climatological and hydrological responses to agricultural irrigation continues to be an important challenge to understanding the full impact of water management on the Earth's environment and hydrological cycle. In this study, we use a global climate model, combined with realistic estimates of regional agricultural water use, to simulate the local and remote impacts of irrigation in California's Central Valley. We demonstrate a clear mechanism that the resulting increase in evapotranspiration and water vapor export significantly impacts the atmospheric circulation in the southwestern United States, including strengthening the regional hydrological cycle. We also identify that irrigation in the Central Valley initiates a previously unknown, anthropogenic loop in the regional hydrological cycle, in which summer precipitation is increased by 15%, causing a corresponding increase in Colorado River streamflow of ~30%. Ultimately, some of this additional streamflow is returned to California via managed diversions through the Colorado River aqueduct and the All-American Canal.

Estimates of consumptive use of surface water by agriculture are vital for assessing food security, managing water rights, and evaluating anthropogenic impacts on regional hydrology. However, reliable, current, and public data on consumptive use can be difficult to obtain, particularly in international and less developed basins. We combine remotely-sensed precipitation and satellite observations of evapotranspiration and groundwater depletion to estimate surface water consumption by irrigated agriculture in California's Central Valley for the 2004–09 water years. We validated our technique against measured consumption data determined from streamflow observations and water export data in the Central Valley. Mean satellite-derived surface water consumption was 291.0 ± 32.4 mm/year while measured surface water consumption was 308.1 ± 6.5 mm/year. The results show the potential for remotely-sensed hydrologic data to independently observe irrigated agriculture's surface water consumption in contested or unmonitored basins. Improvements in the precision and spatial resolution of satellite precipitation, evapotranspiration and gravimetric groundwater observations are needed to reduce the uncertainty in this method and to allow its use on smaller basins and at shorter time scales.