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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.

To compensate for the coarse resolution of groundwater storage (GWS) estimation by the Gravity Recovery and Climate Experiment (GRACE) satellites and make better use of available observed groundwater‐level (GWL) data in some aquifers, a ground‐based scaling factor (SF) method is proposed here to derive high‐resolution GRACE GWS estimates. Improvement is achieved by using the gridded SF derived from assimilating ground‐based GWL observations. The proposed SF method is tested on the North China Plain (NCP, ∼140,000 km2), where a dense network of observation wells and a consistently estimated specific yield (SY) data set are available, to demonstrate its effectiveness and practical applications. The sensitivities of SF‐estimated GWS accuracy to the specification of SY and the assimilation of GWL observation data are explored through four designed numerical experiments. Results show that this novel ground‐based method can reduce the impact of SY uncertainty on GWS estimates, particularly in regions with more pronounced regional GWS trends. The accuracy of SF‐estimated GWS is primarily determined by whether the assimilated wells can reflect the regionally averaged GWS trend. GWS accuracy is less dependent on the number of available wells assimilated. The estimated GWS trend (2004–2015) in NCP is −32.6 ± 1.3 mm/yr (−4.6 ± 0.2 km3/yr), with contrasting GWS trends found in the west Piedmont Plain (∼54,000 km2, with a loss of −66.8 mm/yr) and the coastal Eastern Plain (∼20,000 km2, and a gain of +7.2 mm/yr). Despite the limitations of regional and time scale dependence inherent in SF method, this study highlights the benefits of assimilating in situ observed GWL data instead of using model simulations in estimating SF to downscale GRACE GWS to the higher‐resolution that is desired by local water resources management. Key Points: A new downscaling method based on groundwater‐based scaling factor correction is proposed to improve gravity recovery and climate experiment (GRACE) groundwater storage estimatesThe proposed method can reduce the impact of specific yield uncertainty on groundwater storage (GWS) estimation due to the GWS information provided by the assimilated wells of groundwater levelThe accuracy of GWS change based on the proposed method is primarily determined by whether the assimilated wells can reflect the regional‐averaged GWS trend, less dependent on the number of available wells assimilated [ABSTRACT FROM AUTHOR]

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.

Groundwater is a dynamic component of the global water cycle with important social, economic, ecological, and Earth system functions. We present a new global classification and mapping of groundwater systems, which we call groundwaterscapes, that represent predominant configurations of large‐scale groundwater system functions. We identify and map 15 groundwaterscapes which offer a new lens to conceptualize, study, model, and manage groundwater. Groundwaterscapes are derived using a novel application of sequenced self‐organizing maps that capture patterns in groundwater system functions at the grid cell level (∼10 km), including groundwater‐dependent ecosystem type and density, storage capacity, irrigation, safe drinking water access, and national governance. All large aquifer systems of the world are characterized by multiple groundwaterscapes, highlighting the pitfalls of treating these groundwater bodies as lumped systems in global assessments. We evaluate the distribution of Global Groundwater Monitoring Network wells across groundwaterscapes and find that industrial agricultural regions are disproportionately monitored, while several groundwaterscapes have next to no monitoring wells. This disparity undermines the ability to understand system dynamics across the full range of settings that characterize groundwater systems globally. We argue that groundwaterscapes offer a conceptual and spatial tool to guide model development, hypothesis testing, and future data collection initiatives to better understand groundwater's embeddedness within social‐ecological systems at the global scale. Key Points: Groundwaterscapes are presented as landscape units representing configurations of groundwater's social‐ecological and Earth system functionsA two‐stage self‐organizing map clustering method is implemented to derive 15 groundwaterscapes at the global scaleAll large aquifer systems of the world contain multiple groundwaterscapes [ABSTRACT FROM AUTHOR]

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.

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.

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 underestimation of precipitation (UoP) in the hilly and mountainous parts of South Asia is estimated by some studies to be as large as the observed precipitation (P). However, UoP has been analyzed to only a limited extent across India. To help bridge this gap, watershed-scale UoP was analyzed using various P datasets within a water imbalance analysis. Among these P datasets, the often-used Indian Meteorological Department (IMD) dataset is of primary interest. The gross UoP was identified by analyzing the extent of the imbalance in the annual water budget of watersheds corresponding to 242 river gauging stations for which quality-controlled data on catchment boundaries and streamflow are available. The water year (WY)-based volume of observed annual P was compared against the observed annual streamflow (R) and the satellite-based actual evapotranspiration (ET). Across many watersheds of both Northern and Peninsular India, spurious water imbalance scenarios (P≤R or P≪R+ET) were realized. It is shown that the management of water, such as groundwater extraction, reservoir storage and water diversion, is generally minimal compared to the annual P in such watersheds. It is also shown that annual changes in terrestrial water storage are minimal compared to the annual P in such watersheds. Assuming that data on R (and, to a lesser extent, ET) are reliable, it is concluded that UoP is very likely the cause of this imbalance. Inter-watershed groundwater flow (IGF) is assumed to be negligible. While the effect of IGF on R is unknown, examples are provided which show that IGF is unlikely to be the cause of the observed imbalance in certain watersheds. All 12 of the P datasets analyzed here suffer from UoP, but the extent of the UoP varies by dataset and region. The reanalysis-based datasets ERA5-Land and IMDAA are less affected by UoP than the IMD dataset. Based on the 30-year period of WY 1985–2014, P for the whole of India could be as much as 19 % (ERA5-Land) to 37 % (IMDAA) higher than that from the IMD, with substantial variability within years and river basins. The actual magnitude of UoP is speculated to be even greater. Moreover, trends seen in the IMD's P are not always present in ERA5-Land and IMDAA. Studies using IMD should exercise caution since UoP could lead to the misrepresentation of water budgets and long-term trends. Limitations of this study are discussed. [ABSTRACT FROM AUTHOR]

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.