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At least 577 records · Page 32Linked to original sources

Control on groundwater flow in a semiarid folded and faulted intermountain basin

The major processes controlling groundwater flow in intermountain basins are poorly understood, particularly in basins underlain by folded and faulted bedrock and under regionally realistic hydrogeologic heterogeneity. To explore the role of hydrogeologic heterogeneity and poorly constrained mountain hydrologic conditions on regional groundwater flow in contracted intermountain basins, a series of 3-D numerical groundwater flow models were developed using the South Park basin, Colorado, USA as a proxy. The models were used to identify the relative importance of different recharge processes to major aquifers, to estimate typical groundwater circulation depths, and to explore hydrogeologic communication between mountain and valley hydrogeologic landscapes. Modeling results show that mountain landscapes develop topographically controlled and predominantly local-scale to intermediate-scale flow systems. Permeability heterogeneity of the fold and fault belt and decreased topographic roughness led to permeability controlled flow systems in the valley. The structural position of major aquifers in the valley fold and fault belt was found to control the relative importance of different recharge mechanisms. Alternative mountain recharge model scenarios showed that higher mountain recharge rates led to higher mountain water table elevations and increasingly prominent local flow systems, primarily resulting in increased seepage within the mountain landscape and nonlinear increases in mountain block recharge to the valley. Valley aquifers were found to be relatively insensitive to changing mountain water tables, particularly in structurally isolated aquifers inside the fold and fault belt.

Colorado↗

Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers

Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze-thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow-dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater-sourced thermal refugia may significantly increase under the most extreme climate scenarios.

Water Resources Research↗

Quantifying the predictive consequences of model error with linear subspace analysis

All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.

Water Resources Research↗

Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA

Understanding how nitrogen fluxes respond to changes in agriculture and climate is important for improving water quality. In the midwestern United States, expansion of corn cropping for ethanol production led to increasing N application rates in the 2000s during a period of extreme variability of annual precipitation. To examine the effects of these changes, surface water quality was analyzed in 10 major Iowa Rivers. Several decades of concentration and flow data were analyzed with a statistical method that provides internally consistent estimates of the concentration history and reveals flow-normalized trends that are independent of year-to-year streamflow variations. Flow-normalized concentrations of nitrate+nitrite-N decreased from 2000 to 2012 in all basins. To evaluate effects of annual discharge and N loading on these trends, multiple conceptual models were developed and calibrated to flow-weighted annual concentrations. The recent declining concentration trends can be attributed to both very high and very low discharge in the 2000s and to the long (e.g., 8 year) subsurface residence times in some basins. Dilution of N and depletion of stored N occurs in years with high discharge. Reduced N transport and increased N storage occurs in low-discharge years. Central Iowa basins showed the greatest reduction in flow-normalized concentrations, likely because of smaller storage volumes and shorter residence times. Effects of land-use changes on the water quality of major Iowa Rivers may not be noticeable for years or decades in peripheral basins of Iowa, and may be obscured in the central basins where extreme flows strongly affect annual concentration trends.

Iowa↗

Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach

Effective science-based management of water resources in large basins requires a qualitative understanding of hydrologic conditions and quantitative measures of the various components of the water budget, including difficult to measure components such as baseflow discharge to streams. Using widely available discharge and continuously collected specific conductance (SC) data, we adapted and applied a long established chemical hydrograph separation approach to quantify daily and representative annual baseflow discharge at fourteen streams and rivers at large spatial (> 1,000 km 2 watersheds) and temporal (up to 37 years) scales in the Upper Colorado River Basin. On average, annual baseflow was 21-58% of annual stream discharge, 13-45% of discharge during snowmelt, and 40-86% of discharge during low-flow conditions. Results suggest that reservoirs may act to store baseflow discharged to the stream during snowmelt and release that baseflow during low-flow conditions, and that irrigation return flows may contribute to increases in fall baseflow in heavily irrigated watersheds. The chemical hydrograph separation approach, and associated conceptual model defined here provide a basis for the identification of land use, management, and climate effects on baseflow.

Colorado, Utah↗

Robust, low-cost data loggers for stream temperature, flow intermittency, and relative conductivity monitoring

Water temperature and streamflow intermittency are critical parameters influencing aquatic ecosystem health. Low-cost temperature loggers have made continuous water temperature monitoring relatively simple but determining streamflow timing and intermittency using temperature data alone requires significant and subjective data interpretation. Electrical resistance (ER) sensors have recently been developed to overcome the major limitations of temperature-based methods for the assessment of streamflow intermittency. This technical note introduces the STIC (Stream Temperature, Intermittency, and Conductivity logger); a robust, low-cost, simple to build instrument that provides long-duration, high-resolution monitoring of both relative conductivity (RC) and temperature. Simultaneously collected temperature and RC data provide unambiguous water temperature and streamflow intermittency information that is crucial for monitoring aquatic ecosystem health and assessing regulatory compliance. With proper calibration, the STIC relative conductivity data can be used to monitor specific conductivity.

Water Resources Research↗

Understanding the hydrologic sources and sinks in the Nile Basin using multisource climate and remote sensing data sets

In this study, we integrated satellite-drived precipitation and modeled evapotranspiration data (2000–2012) to describe spatial variability of hydrologic sources and sinks in the Nile Basin. Over 2000–2012 period, 4 out of 11 countries (Ethiopia, Tanzania, Kenya, and Uganda) in the Nile Basin showed a positive water balance while three downstream countries (South Sudan, Sudan, and Egypt) showed a negative balance. Gravity Recovery and Climate Experiment (GRACE) mass deviation in storage data analysis showed that at annual timescales, the Nile Basin storage change is substantial while over longer time periods, it is minimal (<1% of basin precipitation). We also used long-term gridded runoff and river discharge data (1869–1984) to understand the discrepancy in the observed and expected flow along the Nile River. The top three countries that contribute most to the flow are Ethiopia, Tanzania, and Kenya. The study revealed that ∼85% of the runoff generated in the equatorial region is lost in an interstation basin that includes the Sudd wetlands in South Sudan; this proportion is higher than the literature reported loss of 50% at the Sudd wetlands alone. The loss in runoff and flow volume at different sections of the river tend to be more than what can be explained by evaporation losses, suggesting a potential recharge to deeper aquifers that are not connected to the Nile channel systems. On the other hand, we also found that the expected average annual Nile flow at Aswan is greater (97 km 3 ) than the reported amount (84 km 3 ). Due to the large variations of the reported Nile flow at different locations and time periods, the study results indicate the need for increased hydrometeorological instrumentation of the basin. The study also helped improve our understanding of the spatial dynamics of water sources and sinks in the Nile Basin and identified emerging hydrologic questions that require further attention.

Water Resources Research↗

A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the “multisite loop EnKF,” tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

California↗

Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties

The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.

Water Resources Research↗

Lattice Boltzmann methods applied to large-scale three-dimensional virtual cores constructed from digital optical borehole images of the karst carbonate Biscayne aquifer in southeastern Florida

Digital optical borehole images at approximately 2 mm vertical resolution and borehole caliper data were used to create three-dimensional renderings of the distribution of (1) matrix porosity and (2) vuggy megaporosity for the karst carbonate Biscayne aquifer in southeastern Florida. The renderings based on the borehole data were used as input into Lattice Boltzmann methods to obtain intrinsic permeability estimates for this extremely transmissive aquifer, where traditional aquifer test methods may fail due to very small drawdowns and non-Darcian flow that can reduce apparent hydraulic conductivity. Variogram analysis of the borehole data suggests a nearly isotropic rock structure at lag lengths up to the nominal borehole diameter. A strong correlation between the diameter of the borehole and the presence of vuggy megaporosity in the data set led to a bias in the variogram where the computed horizontal spatial autocorrelation is strong at lag distances greater than the nominal borehole size. Lattice Boltzmann simulation of flow across a 0.4 &times; 0.4 &times; 17 m (2.72 m 3 volume) parallel-walled column of rendered matrix and vuggy megaporosity indicates a high hydraulic conductivity of 53 m s &minus;1 . This value is similar to previous Lattice Boltzmann calculations of hydraulic conductivity in smaller limestone samples of the Biscayne aquifer. The development of simulation methods that reproduce dual-porosity systems with higher resolution and fidelity and that consider flow through horizontally longer renderings could provide improved estimates of the hydraulic conductivity and help to address questions about the importance of scale.

Water Resources Research↗

Runoff sources and flowpaths in a partially burned, upland boreal catchment underlain by permafrost

Boreal soils in permafrost regions contain vast quantities of frozen organic material that is released to terrestrial and aquatic environments via subsurface flowpaths as permafrost thaws. Longer flowpaths may allow chemical reduction of solutes, nutrients, and contaminants, with implications for greenhouse gas emissions and aqueous export. Predicting boreal catchment runoff is complicated by soil heterogeneities related to variability in active layer thickness, soil type, fire history, and preferential flow potential. By coupling measurements of permeability, infiltration potential, and water chemistry with a stream chemistry end member mixing model, we tested the hypothesis that organic soils and burned slopes are the primary sources of runoff, and that runoff from burned soils is greater due to increased hydraulic connectivity. Organic soils were more permeable than mineral soils, and 25% of infiltration moved laterally upon reaching the organic-mineral soil boundary on unburned hillslopes. A large portion of the remaining water infiltrated into deeper, less permeable soils. In contrast, burned hillslopes displayed poorly defined soil horizons, allowing rapid, mineral-rich runoff through preferential pathways at various depths. On the catchment scale, mineral/organic runoff ratios averaged 1.6 and were as high as 5.2 for an individual storm. Our results suggest that burned soils are the dominant source of water and solutes reaching the stream in summer, whereas unburned soils may provide longer term storage and residence times necessary for production of anaerobic compounds. These results are relevant to predicting how boreal catchment drainage networks and stream export will evolve given continued warming and altered fire regimes.

Alaska↗

Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection

Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO 3 −) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.

California↗

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

Amhara region↗

Comparison of fluvial suspended-sediment concentrations and particle-size distributions measured with in-stream laser diffraction and in physical samples

Laser-diffraction technology, recently adapted for in-stream measurement of fluvial suspended-sediment concentrations (SSCs) and particle-size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In-Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8-415 &micro;m in 32 log-spaced size classes. Measured SSCs and PSDs from the LISST-SL were compared to a suite of 22 datasets (262 samples in all) of concurrent suspended-sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010-12 at 16 U.S. Geological Survey streamflow-gaging stations in Illinois and Washington (basin areas: 38 &ndash; 69,264 km 2 ). An unrealistically low computed effective density (mass SSC / volumetric SSC) of 1.24 g/ml (95% confidence interval: 1.05-1.45 g/ml) provided the best-fit value (R 2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over 2 orders of magnitude of SSC (12-2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST-SL) despite being substantially lower than the sediment particle density of 2.67 g/ml (range: 2.56-2.87 g/ml, 23 samples). The PSDs measured by the LISST-SL were in good agreement with those derived from physical samples over the LISST-SL's measureable size range. Technical and operational limitations of the LISST-SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST-SL is briefly described to motivate its potential for advancing our understanding of suspended-sediment transport by rivers.

Water Resources Research↗

Dual-domain mass-transfer parameters from electrical hysteresis: Theory and analytical approach applied to laboratory, synthetic streambed, and groundwater experiments

Models of dual‐domain mass transfer (DDMT) are used to explain anomalous aquifer transport behavior such as the slow release of contamination and solute tracer tailing. Traditional tracer experiments to characterize DDMT are performed at the flow path scale (meters), which inherently incorporates heterogeneous exchange processes; hence, estimated “effective” parameters are sensitive to experimental design (i.e., duration and injection velocity). Recently, electrical geophysical methods have been used to aid in the inference of DDMT parameters because, unlike traditional fluid sampling, electrical methods can directly sense less‐mobile solute dynamics and can target specific points along subsurface flow paths. Here we propose an analytical framework for graphical parameter inference based on a simple petrophysical model explaining the hysteretic relation between measurements of bulk and fluid conductivity arising in the presence of DDMT at the local scale. Analysis is graphical and involves visual inspection of hysteresis patterns to (1) determine the size of paired mobile and less‐mobile porosities and (2) identify the exchange rate coefficient through simple curve fitting. We demonstrate the approach using laboratory column experimental data, synthetic streambed experimental data, and field tracer‐test data. Results from the analytical approach compare favorably with results from calibration of numerical models and also independent measurements of mobile and less‐mobile porosity. We show that localized electrical hysteresis patterns resulting from diffusive exchange are independent of injection velocity, indicating that repeatable parameters can be extracted under varied experimental designs, and these parameters represent the true intrinsic properties of specific volumes of porous media of aquifers and hyporheic zones.

Water Resources Research↗

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly-gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index-flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage-area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern US resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted-variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low-flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities.

Water Resources Research↗

Multimodel analysis of anisotropic diffusive tracer-gas transport in a deep arid unsaturated zone

Gas transport in the unsaturated zone affects contaminant flux and remediation, interpretation of groundwater travel times from atmospheric tracers, and mass budgets of environmentally important gases. Although unsaturated zone transport of gases is commonly treated as dominated by diffusion, the characteristics of transport in deep layered sediments remain uncertain. In this study, we use a multimodel approach to analyze results of a gas-tracer (SF 6 ) test to clarify characteristics of gas transport in deep unsaturated alluvium. Thirty-five separate models with distinct diffusivity structures were calibrated to the tracer-test data and were compared on the basis of Akaike Information Criteria estimates of posterior model probability. Models included analytical and numerical solutions. Analytical models provided estimates of bulk-scale apparent diffusivities at the scale of tens of meters. Numerical models provided information on local-scale diffusivities and feasible lithological features producing the observed tracer breakthrough curves. The combined approaches indicate significant anisotropy of bulk-scale diffusivity, likely associated with high-diffusivity layers. Both approaches indicated that diffusivities in some intervals were greater than expected from standard models relating porosity to diffusivity. High apparent diffusivities and anisotropic diffusivity structures were consistent with previous observations at the study site of rapid lateral transport and limited vertical spreading of gas-phase contaminants. Additional processes such as advective oscillations may be involved. These results indicate that gases in deep, layered unsaturated zone sediments can spread laterally more quickly, and produce higher peak concentrations, than predicted by homogeneous, isotropic diffusion models.

California, Nevada↗

Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know

Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. Geological Survey and U.S. Environmental Protection Agency data sets to increase understanding of the spatial distribution of unconventional oil and gas development in the U.S. and broadly assess surface water quality trends in these areas. Based on sample size limitations, we were able to estimate trends in specific conductance (SC) and chloride (Cl − ) from 1970 to 2010 in 16% ( n = 155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface water quality for SC and Cl − in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality.

Water Resources Research↗