How does DEM resolution affect microtopographic characteristics,hydrologic connectivity,and modelling of hydrologic processes?

The resolution of a digital elevation model (DEM) is a crucial factor in watershed hydrologic and environmental modelling. DEM resolution can cause significant variability in the representation of surface topography, which further affects quantification of hydrologic connectivity and simulation of hydrologic processes. The objective of this study is to examine the effects of DEM resolution on (1) surface microtopographic characteristics, (2) hydrologic connectivity, and (3) the spatial and temporal variations of hydrologic processes. A puddle‐to‐puddle modelling system was utilized for surface delineation and modelling of the puddle‐to‐puddle overland flow dynamics, surface runoff, infiltration, and unsaturated flow for nine DEM resolution scenarios of a field plot surface. Comparisons of the nine modelling scenarios demonstrated that coarser DEM resolutions tended to eliminate topographic features, reduce surface depression storage, and strengthen hydrologic connectivity and surface runoff. We found that reduction in maximum depression storage and maximum ponding area was as high as 97.56% and 76.36%, respectively, as the DEM grid size increased from 2 to 80 cm. The paired t‐test and fractal analysis demonstrated the existence of a threshold DEM resolution (10 cm for the field plot), within which the DEM‐based hydrologic modelling was effective and acceptable. The effects of DEM resolution were further evaluated for a larger surface in the Prairie Pothole Region subjected to observed rainfall events. It was found that simulations based on coarser resolution DEMs (>10 m) tended to overestimate ponded areas and underestimate runoff discharge peaks. The simulated peak discharge from the Prairie Pothole Region surface reduced by approximately 50% as the DEM resolution changed from 2 to 90 m. Fractal analysis results elucidated scale dependency of hydrologic and topographic processes. In particular, scale analysis highlighted a unique constant–threshold–power relationship between DEM scale and topographic and hydrologic parameters/variables. Not only does this finding allow one to identify threshold DEM but also further develop functional relationships for scaling to achieve valid topographic characterization as well as effective and efficient hydrologic modelling. Copyright © 2016 John Wiley & Sons, Ltd.     

A groundwater-based, objective-heuristic parameter optimisation method for a precipitation-runoff model and its application to a semi-arid basin

A hydrologic model calibration methodology that is based on groundwater data is developed and implemented using the US Geological Survey's precipitation-runoff modelling system (PRMS) and the modular modelling system (MMS), which performs automatic calibration of parameters. The developed methodology was tested in the Akrotiri basin, Cyprus. The necessity for the groundwater-based model calibration, rather than a typical runoff-based one, arose from the very intermittent character of the runoff in the Akrotiri basin, a case often met in semi-arid regions. Introducing a datum and converting groundwater storage to head made the observable groundwater level the calibration indicator. The modelling of the Akrotiri basin leads us to conclude that groundwater level is a useful indicator for hydrological model calibration that can be potentially used in other similar situations in the absence of river flow measurements. However, the option of an automatic calibration of the complex hydrologic model PRMS by MMS did not ensure a good outcome. On the other hand, automatic optimisation, combined with heuristic expert intervention, enabled achievement of good calibration and constitutes a valuable means for saving effort and improving modelling performance. To this end, results must be scrutinised, melding the viewpoint of physical sense with mathematical efficiency criteria. Thus optimised, PRMS achieved a low simulation error, good reproduction of the historic trend of the aquifer water level evolution and reasonable physical behaviour (good hydrologic balance, Reasonable match of aquifer level evolution, good estimation of mean natural recharge rate).     

Isotopic variation in groundwater across the conterminous United States – Insight into hydrologic processes

Groundwater supplies a significant proportion of water use in the United States and is critical to the maintenance of healthy ecosystems and environmental processes, thus characterizing aquifer hydrology is important to managing and preserving these resources. While groundwater isotopes provide insight into hydrologic and ecologic processes, their application is limited to where measurements exist. To help overcome this limitation, we used the random forest algorithm to develop a predictive model for shallow groundwater isotopes in the conterminous United States. Our model uses environmental variables (e.g. temperature, elevation, precipitation isotopes) as predictors. We used our model to develop the first shallow groundwater isoscape of δ²H and δ¹⁸O for the conterminous United States. We describe the patterns in groundwater isotopes using both observations and our modelled isoscape. We find that throughout much of the Eastern United States, groundwater isotopes are close to annual amount weighted precipitation, while groundwater isotopes are significantly depleted relative precipitation across much of the High Plains and Western United States. Furthermore, we compare the observations compiled for this study to isotopes of precipitation, which allows us to determine the relative recharge efficiency (i.e. ratio of groundwater recharge to precipitation) between seasons and the proportion of annual recharge that occurs in a given season. Our findings suggest that winter recharge is generally more efficient than summer recharge; however, the dominant recharge season is more varied as it is the product of both seasonal recharge efficiency and the seasonal timing of precipitation. Parts of the central United States have summer dominant recharge, which is likely the result of heavy summer precipitation/nocturnal summer precipitation. Interestingly, parts of coastal California appear to have summer dominant recharge, which we suggest could be due to recharge from fog-drip. Our results summarize spatial patterns in groundwater isotopes across the conterminous United States, provide insight into the hydrologic processes affecting shallow groundwater, and are valuable information for future ecologic and hydrologic studies.     

New mapping techniques to estimate the preferential loss of small wetlands on prairie landscapes

Reliable estimates of wetland loss require improved wetland inventories and effective monitoring programmes. The Prairie Pothole Region of North America is experiencing rapid urban, agricultural and economic development, which places wetlands at risk, especially small geographically isolated wetlands. This loss is concomitant with a loss of ecosystem services. To improve upon current wetland inventories, a method for mapping wetlands using an automated object‐based approach was developed for a regional watershed in Alberta. The method improves upon existing wetland mapping methods by effectively mapping small wetlands and better capturing the convolution of wetland edges. This approach uses digital terrain objects derived from light detection and ranging data, from which 130 157 wetlands were identified. Wetland loss estimates (% number and % area) were obtained by applying a wetland area versus frequency power‐law function to the wetland inventory. We estimated a 16.2% historic loss of wetland number and a 2.6% loss of wetland area, with the size of these lost wetlands <0.04 ha. The improved techniques for mapping wetland loss and estimating wetland loss provide a more accurate representation of the magnitude of wetland loss in the Prairie Pothole Region. Copyright © 2015 John Wiley & Sons, Ltd.     

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three-dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R-squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically-informed estimates. The results of this work are used to inform a follow-on study that tests additional data-driven approaches in multiple basins within the contiguous United States.     

Development of a continuous soil moisture accounting procedure for curve number methodology and its behaviour with different evapotranspiration methods

The curve number (CN) method is widely used for rainfall–runoff modelling in continuous hydrologic simulation models. A sound continuous soil moisture accounting procedure is necessary for models using the CN method. For shallow soils and soils with low storage, the existing methods have limitations in their ability to reproduce the observed runoff. Therefore, a simple one‐parameter model based on the Soil Conservation Society CN procedure is developed for use in continuous hydrologic simulation. The sensitivity of the model parameter to runoff predictions was also analysed. In addition, the behaviour of the procedure developed and the existing continuous soil moisture accounting procedure used in hydrologic models, in combination with Penman–Monteith and Hargreaves evapotranspiration (ET) methods was also analysed. The new CN methodology, its behaviour and the sensitivity of the depletion coefficient (model parameter) were tested in four United States Geological Survey defined eight‐digit watersheds in different water resources regions of the USA using the SWAT model. In addition to easy parameterization for calibration, the one‐parameter model developed performed adequately in predicting runoff. When tested for shallow soils, the parameter is found to be very sensitive to surface runoff and subsurface flow and less sensitive to ET. Copyright © 2007 John Wiley & Sons, Ltd.     

Application of isotope tracers in continental scale hydrological modeling

Isotope tracers are widely used to study hydrological processes in small catchments, but their use in continental-scale hydrological modeling has been limited. This paper describes the development of an isotope-enabled global water balance and transport model (iWBM/WTM) capable of simulating key hydrological processes and associated isotopic responses at the large scale. Simulations and comparisons of isotopic signals in precipitation and river discharge from available datasets, particularly the IAEA GNIP global precipitation climatology and the USGS river isotope dataset spanning the contiguous United States, as well as selected predictions of isotopic response in yet unmonitored areas illustrate the potential for isotopes to be applied as a diagnostic tool in water cycle model development. Various realistic and synthetic forcings of the global hydrologic and isotopic signals are discussed. The test runs demonstrate that the primary control on isotope composition of river discharge is the isotope composition of precipitation, with land surface characteristics and precipitation-amount having less impact. Despite limited availability of river isotope data at present, the application of realistic climatic and isotopic inputs in the model also provides a better understanding of the global distribution of isotopic variations in evapotranspiration and runoff, and reveals a plausible approach for constraining the partitioning of surface and subsurface runoff and the size and variability of the effective groundwater pool at the macro-scale.     

Evaluating the sensitivity of wetlands to climate change with remote sensing techniques

Wetlands are valuable ecosystems that provide many valuable services, yet many of these important ecosystems are at risk because of current trends in climate change. The Prairie Pothole Region (PPR) in the upper‐midwest of the United States and south‐central Canada, characterized by glacially sculpted landscapes and abundant wetlands, is one such vulnerable region. According to regional/global climate model predictions, drought occurrence will increase in the PPR region through the 21st century and thus will probably cause the amount of water in wetlands to decline. Water surface area (WSA) of Kidder County, ND, from 1984–2011 was measured by classifying TM/ETM+(Landsat Thematic Mapper / Enhanced Thematic Mapper Plus) images through the modified normalized difference water index. We then developed a linear model based on the WSA of these wetlands and historical climate data and used this to determine the wetland sensitivity to climate change and predict future wetlands WSA in the PPR. Our model based on Palmer drought severity index (PDSI) of the current year (PDSI_{t ? 0}) and of the previous two years (PDSI_{t ? 2}) can explain 79% of the annual wetland WSA variance, suggesting a high sensitivity of wetlands to drought/climate change. We also predicted the PPR wetlands WSA in the 21st century under A1B scenario (a mid‐carbon emission scenario) using simulated PDSI based on Intergovernmental Panel on Climate Change AR4 22‐model ensemble climate. According to our prediction, the WSA of the PPR wetlands will decrease to less than half of the baseline WSA (defined as the mean wetlands WSA of the 2000s) by the mid of the 21st century, and to less than one‐third by the 2080s, and will then slightly increase in the 2090s. This considerable future wetland loss caused only by climate change provides important implication to future wetland management and climate adaptation policy. Copyright © 2012 John Wiley & Sons, Ltd.     

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

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

Intercomparison of the total storage deficit index (TSDI) over two Canadian Prairie catchments

Retrieval of the terrestrial moisture storage dataset from the Gravity Recovery and Climate Experiment (GRACE) satellite remote sensing system is possible when the catchment of interest is of large spatial scale. These dataset are of paramount importance for the estimation of the total storage deficit index (TSDI), which enables the characterization of a particular drought event from the perspective of the terrestrial moisture storage over that catchment. Incidentally, the GRACE gravity signal over the 13,000 km² Upper Assiniboine River Basin on the drought-prone Canadian Prairie is so poor therefore making the computation of the total storage deficit index for this basin infeasible. Consequently, the estimation of the terrestrial moisture storage from other reliable sources becomes imperative in order to enable the computation of the TSDI over this basin.This study explores the utilization of the Variable Infiltration Capacity (VIC) model, a physically based, spatially distributed hydrologic model to simulate the total moisture storage over the Upper Assiniboine River Basin which was then employed in the estimation of the TSDI over this basin for subsequent characterization of the recent Prairie-wide drought. Interestingly, the temporal patterns in the computed TSDI from the VIC model reveal a strong resemblance with the same drought characterization undertaken over the larger adjacent Saskatchewan River Basin, which was accomplished utilizing terrestrial moisture storage from the GRACE-based approach. Additionally, these independent techniques employed in the characterization of the last Prairie drought over the two adjacently situated basins resulted in similar drought severity classification from the standpoint of the total moisture storage deficits over these basins. This study has therefore shown that in the computation of the total storage deficit index over small-scale catchments during anomalous climatic conditions that propagate extreme dryness through the terrestrial hydrologic systems, simulations of the total water storage from a structurally sound model such as the VIC model could be resourceful for the computation of the monthly total storage deficit index if no constraint is placed on the availability of accurate meteorological forcing.     

Seismicity and neotectonic uplift in the Augrabies Falls National Park,Namaqualand,Northern Cape,South Africa

Gneissic rocks in the Augrabies Falls National Park are part of the Proterozoic Namaqua-Natal mobile belt. Finding neotectonic evidence in old terranes is always not an easy task. In South Africa, the mid-Miocene is believed to be the beginning of neotectonics. This study investigated the occurrence and recurrence of earthquake activity, occurrence of faulting, jointing, uplift, and potholes in the gneisses cropping out around the Augrabies Falls area that may account for neotectonics. A historic seismic event obtained from the United States Geological Survey(USGS), and seismic epicenters downloaded in October 2015 from IRIS earthquake browser and overlaid on a satellite image with digitised faults and lineaments,indicates that the area is seismically active and is a zone of seismic risk. Potholes occurring today on a dry surface at approximately 613 m above sea level are a direct consequence of the Griqualand-Transvaal neotectonic uplift,which generated a major fault along which water flows continuously. It is concluded that the Augrabies Falls National Park area is a zone of neotectonics. This zone should not be considered for the storage of nuclear wastes.     

Choosing an arbitrary calibration period for hydrologic models: How much does it influence water balance simulations?

The selection of calibration and validation time periods in hydrologic modelling is often done arbitrarily. Nonstationarity can lead to an optimal parameter set for one period which may not accurately simulate another. However, there is still much to be learned about the responses of hydrologic models to nonstationary conditions. We investigated how the selection of calibration and validation periods can influence water balance simulations. We calibrated Soil and Water Assessment Tool hydrologic models with observed streamflow for three United States watersheds (St. Joseph River of Indiana/Michigan, Escambia River of Florida/Alabama, and Cottonwood Creek of California), using time period splits for calibration/validation. We found that the choice of calibration period (with different patterns of observed streamflow, precipitation, and air temperature) influenced the parameter sets, leading to dissimilar simulations of water balance components. In the Cottonwood Creek watershed, simulations of 50-year mean January streamflow varied by 32%, because of lower winter precipitation and air temperature in earlier calibration periods on calibrated parameters, which impaired the ability for models calibrated to earlier periods to simulate later periods. Peaks of actual evapotranspiration for this watershed also shifted from April to May due to different parameter values depending on the calibration period's winter air temperatures. In the St. Joseph and Escambia River watersheds, adjustments of the runoff curve number parameter could vary by 10.7% and 20.8%, respectively, while 50-year mean monthly surface runoff simulations could vary by 23%–37% and 169%–209%, depending on the observed streamflow and precipitation of the chosen calibration period. It is imperative that calibration and validation time periods are chosen selectively instead of arbitrarily, for instance using change point detection methods, and that the calibration periods are appropriate for the goals of the study, considering possible broad effects of nonstationary time series on water balance simulations. It is also crucial that the hydrologic modelling community improves existing calibration and validation practices to better include nonstationary processes.     

Regional patterns of postwildfire streamflow response in the Western United States: The importance of scale‐specific connectivity

Wildfires can impact streamflow by modifying net precipitation, infiltration, evapotranspiration, snowmelt, and hillslope run‐off pathways. Regional differences in fire trends and postwildfire streamflow responses across the conterminous United States have spurred concerns about the impact on streamflow in forests that serve as water resource areas. This is notably the case for the Western United States, where fire activity and burn severity have increased in conjunction with climate change and increased forest density due to human fire suppression. In this review, we discuss the effects of wildfire on hydrological processes with a special focus on regional differences in postwildfire streamflow responses in forests. Postwildfire peak flows and annual water yields are generally higher in regions with a Mediterranean or semi‐arid climate (Southern California and the Southwest) compared to the highlands (Rocky Mountains and the Pacific Northwest), where fire‐induced changes in hydraulic connectivity along the hillslope results in the delivery of more water, more rapidly to streams. No clear streamflow response patterns have been identified in the humid subtropical Southeastern United States, where most fires are prescribed fires with a low burn severity, and more research is needed in that region. Improved assessment of postwildfire streamflow relies on quantitative spatial knowledge of landscape variables such as prestorm soil moisture, burn severity and correlations with soil surface sealing, water repellency, and ash deposition. The latest studies furthermore emphasize that understanding the effects of hydrological processes on postwildfire dynamic hydraulic connectivity, notably at the hillslope and watershed scales, and the relationship between overlapping disturbances including those other than wildfire is necessary for the development of risk assessment tools.     

Differing controls on river‐ and lake‐water hydrogen and oxygen isotopic values in the western United States

Surface water oxygen and hydrogen isotopic values are commonly used as proxies of precipitation isotopic values to track modern hydrologic processes while proxies of water isotopic values preserved in lake and river sediments are used for paleoclimate and paleoaltimetry studies. Previous work has been able to explain variability in USA river‐water and meteoric‐precipitation oxygen isotope variability with geographic variables. These studies show that in the western United States, river‐water isotopic values are depleted relative to precipitation values. In comparison, the controls on lake‐water isotopic values are not well constrained. It has been documented that western United States lake‐water input values, unlike river water, reflect the monthly weighted mean isotopic value of precipitation. To understand the differing controls on lake‐ and river‐water isotopic values in the western United States, we examine the seasonal distribution of precipitation, evaporation and snowmelt across a range of seasonality regimes. We generate new predictive equations based on easily measured factors for western United States lake‐water, which are able to explain 69–63% of the variability in lake‐water hydrogen and oxygen isotopic values. In addition to the geographic factors that can explain river and precipitation values, lake‐water isotopic values need factors related to local hydrologic and climatic characteristics to explain variability. Study results suggest that the spring snowmelt runs off the landscape via rivers and streams, depleting river and stream‐water isotopic values. By contrast, lakes receive seasonal contributions of precipitation in proportion to the seasonal fraction of total annual precipitation within their watershed. Climate change may alter the ratio of snow to rain fall, affecting water resource partitioning between rivers and lakes and by implication of groundwater. Paleolimnological studies must account for the multiple drivers of water isotopic values; likewise, studies based on the isotopic composition of fossil material need to distinguish between species that are associated with rivers versus lakes. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of dynamically downscaled reanalysis precipitation data for hydrological application

Skilful and reliable precipitation data are essential for seasonal hydrologic forecasting and generation of hydrological data. Although output from dynamic downscaling methods is used for hydrological application, the existence of systematic errors in dynamically downscaled data adversely affects the skill of hydrologic forecasting. This study evaluates the precipitation data derived by dynamically downscaling the global atmospheric reanalysis data by propagating them through three hydrological models. Hydrological models are calibrated for 28 watersheds located across the southeastern United States that is minimally affected by human intervention. Calibrated hydrological models are forced with five different types of datasets: global atmospheric reanalysis (National Centers for Environmental Prediction/Department of Energy Global Reanalysis and European Centre for Medium‐Range Weather Forecasts 40‐year Reanalysis) at their native resolution; dynamically downscaled global atmospheric reanalysis at 10‐km grid resolution; stochastically generated data from weather generator; bias‐corrected dynamically downscaled; and bias‐corrected global reanalysis. The reanalysis products are considered as surrogates for large‐scale observations. Our study indicates that over the 28 watersheds in the southeastern United States, the simulated hydrological response to the bias‐corrected dynamically downscaled data is superior to the other four meteorological datasets. In comparison with synthetically generated meteorological forcing (from weather generator), the dynamically downscaled data from global atmospheric reanalysis result in more realistic hydrological simulations. Therefore, we conclude that dynamical downscaling of global reanalysis, which offers data for sufficient number of years (in this case 22 years), although resource intensive, is relatively more useful than other sources of meteorological data with comparable period in simulating realistic hydrological response at watershed scales. Copyright © 2013 John Wiley & Sons, Ltd.     

Thresholds for run‐off generation in a drained closed depression

Hydrological threshold behaviour has been observed across hillslopes and catchments with varying characteristics. Few studies, however, have evaluated rainfall–run‐off response in areas dominated by agricultural land use and artificial subsurface drainage. Hydrograph analysis was used to identify distinct hydrological events over a 9‐year period and examine rainfall characteristics, dynamic water storage, and surface and subsurface run‐off generation in a drained and farmed closed depression in north‐eastern Indiana, USA. Results showed that both surface flow and subsurface tile flow displayed a threshold relationship with the sum of rainfall amount and soil moisture deficit (SMD). Neither surface flow nor subsurface tile flow was observed unless rainfall amount exceeded the SMD. Timing of subsurface tile flow relative to soil moisture response on the shoulder slope of the depression indicated that the formation and drainage of perched water tables on depression hillslopes were likely the main mechanism that produced subsurface connectivity. Surface flow generation was delayed compared with subsurface tile flow during rainfall events due to differences in soil water storage along depression hillslopes and run‐off generation mechanisms. These findings highlight the substantial impact of subsurface tile drainage on the hydrology of closed depressions; the bottom of the depression, the wettest area prior to drainage installation, becomes the driest part of the depression after installation of subsurface drainage. Rapid connectivity of localized subsurface saturation zones during rainfall events is also greatly enhanced because of subsurface drainage. Thus, less fill is required to generate substantial spill. Understanding hydrologic processes in drained and farmed closed depressions is a critical first step in developing improved water and nutrient management strategies in this landscape.     

Quantifying watershed surface depression storage: determination and application in a hydrologic model

Hydrologic models often require correct estimates of surface macro‐depressional storage to accurately simulate rainfall–runoff processes. Traditionally, depression storage is determined through model calibration or lumped with soil storage components or on an ad hoc basis. This paper investigates a holistic approach for estimating surface depressional storage capacity (DSC) in watersheds using digital elevation models (DEMs). The methodology includes implementing a lumped DSC model to extract geometric properties of storage elements from DEMs of varying grid resolutions and employing a consistency zone criterion to quantify the representative DSC of an isolated watershed. DSC obtained using the consistency zone approach is compared to DSC estimated by “brute force” (BF) optimization method. The BF procedure estimates optimal DSC by calibrating DRAINMOD, a quasi‐process based hydrologic model, with observed streamflow under different climatic conditions. Both methods are applied to determine the DSC for relatively low‐gradient coastal plain watersheds on forested landscape with slopes less than 3%. Results show robustness of the consistency zone approach for estimating depression storage. To test the adequacy of the calculated DSC values obtained, both methods are applied in DRAINMOD to predict the daily watershed flow rates. Comparison between observed and simulated streamflow reveals a marginal difference in performance between BF optimization and consistency zone estimated DSCs during wet periods, but the latter performed relatively better in dry periods. DSC is found to be dependent on seasonal antecedent moisture conditions on surface topography. The new methodology is beneficial in situations where data on depressional storage is unavailable for calibrating models requiring this input parameter. Copyright © 2012 John Wiley & Sons, Ltd.     

Incorporating landscape depression heterogeneity into the Soil and Water Assessment Tool (SWAT) using a probability distribution

Modelling the hydrology of North American Prairie watersheds is complicated because of the existence of numerous landscape depressions that vary in storage capacity. The Soil and Water Assessment Tool (SWAT) is a widely applied model for long‐term hydrological simulations in watersheds dominated by agricultural land uses. However, several studies show that the SWAT model has had limited success in handling prairie watersheds. In past works using SWAT, landscape depression storage heterogeneity has largely been neglected or lumped. In this study, a probability distributed model of depression storage is introduced into the SWAT model to better handle landscape storage heterogeneity. The work utilizes a probability density function to describe the spatial heterogeneity of the landscape depression storages that was developed from topographic characteristics. The integrated SWAT–PDLD model is tested using datasets for two prairie depression dominated watersheds in Canada: the Moose Jaw River watershed, Saskatchewan; and the Assiniboine River watershed, Saskatchewan. Simulation results were compared to observed streamflow using graphical and multiple statistical criterions. Representation of landscape depressions within SWAT using a probability distribution (SWAT–PDLD) provides improved estimations of streamflow for large prairie watersheds in comparison to results using a lumped, single storage approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Groundwater Governance in the United States: Common Priorities and Challenges

Groundwater is a critical component of the water supply for agriculture, urban areas, industry, and ecosystems, but managing it is a challenge because groundwater is difficult to map, quantify, and evaluate. Until recently, study and assessment of governance of this water resource has been largely neglected. A survey was developed to query state agency officials about the extent and scope of groundwater use, groundwater laws and regulations, and groundwater tools and strategies. Survey responses revealed key findings: states' legal frameworks for groundwater differ widely in recognizing the hydrologic connection between surface water and groundwater, the needs of groundwater‐dependent ecosystems, and the protection of groundwater quality; states reported a range in capacity to enforce groundwater responsibilities; and states have also experienced substantial changes in groundwater governance in the past few decades. Overall, groundwater governance across the United States is fragmented. States nevertheless identified three common priorities for groundwater governance: water quality and contamination, conflicts between users, and declining groundwater levels. This survey represents an initial step in a broader, continuing effort to characterize groundwater governance practices in the United States.