Showing papers in "Water Resources Research in 2008"

Treatment of input uncertainty in hydrologic modeling: doing hydrology backward with Markov chain Monte Carlo simulation.

Abstract: [1] There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

Agricultural green and blue water consumption and its influence on the global water system

Abstract: [1] This study quantifies, spatially explicitly and in a consistent modeling framework (Lund-Potsdam-Jena managed Land), the global consumption of both “blue” water (withdrawn for irrigation from rivers, lakes and aquifers) and “green” water (precipitation) by rainfed and irrigated agriculture and by nonagricultural terrestrial ecosystems. In addition, the individual effects of human-induced land cover change and irrigation were quantified to assess the overall hydrological impact of global agriculture in the past century. The contributions to irrigation of nonrenewable (fossil groundwater) and nonlocal blue water (e.g., from diverted rivers) were derived from the difference between a simulation in which these resources were implicitly considered (IPOT) and a simulation in which they were neglected (ILIM). We found that global cropland consumed >7200 km3 year−1 of green water in 1971–2000, representing 92% (ILIM) and 85% (IPOT), respectively, of total crop water consumption. Even on irrigated cropland, 35% (ILIM) and 20% (IPOT) of water consumption consisted of green water. An additional 8155 km3 year−1 of green water was consumed on grazing land; a further ∼44,700 km3 year−1 sustained the ecosystems. Blue water consumption predominated only in intensively irrigated regions and was estimated at 636 km3 year−1 (ILIM) and 1364 km3 year−1 (IPOT) globally, suggesting that presently almost half of the irrigation water stemmed from nonrenewable and nonlocal sources. Land cover conversion reduced global evapotranspiration by 2.8% and increased discharge by 5.0% (1764 km3 year−1), whereas irrigation increased evapotranspiration by up to 1.9% and decreased discharge by 0.5% at least (IPOT, 1971–2000). The diverse water fluxes displayed considerable interannual and interdecadal variability due to climatic variations and the progressive increase of the global area under cultivation and irrigation.

On the value of soil moisture measurements in vadose zone hydrology: a review

Abstract: [1] We explore and review the value of soil moisture measurements in vadose zone hydrology with a focus on the field and catchment scales This review is motivated by the increasing ability to measure soil moisture with unprecedented spatial and temporal resolution across scales We highlight and review the state of the art in using soil moisture measurements for (1) estimation of soil hydraulic properties, (2) quantification of water and energy fluxes, and (3) retrieval of spatial and temporal dynamics of soil moisture profiles We argue for the urgent need to have access to field monitoring sites and databases that include detailed information about variability of hydrological fluxes and parameters, including their upscaled values In addition, improved data assimilation methods are needed that fully exploit the information contained in soil moisture data The development of novel upscaling methods for predicting effective moisture fluxes and disaggregation schemes toward integrating large-scale soil moisture measurements in hydrological models will increase the value of soil moisture measurements Finally, we recognize a need to develop strategies that combine hydrogeophysical measurement techniques with remote sensing methods

Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

Abstract: [1] The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding research challenges for the discipline of hydrology. Progress on these problems requires understanding of the nature of differences between models. This paper presents a methodology to diagnose differences in hydrological model structures: the Framework for Understanding Structural Errors (FUSE). FUSE was used to construct 79 unique model structures by combining components of 4 existing hydrological models. These new models were used to simulate streamflow in two of the basins used in the Model Parameter Estimation Experiment (MOPEX): the Guadalupe River (Texas) and the French Broad River (North Carolina). Results show that the new models produced simulations of streamflow that were at least as good as the simulations produced by the models that participated in the MOPEX experiment. Our initial application of the FUSE method for the Guadalupe River exposed relationships between model structure and model performance, suggesting that the choice of model structure is just as important as the choice of model parameters. However, further work is needed to evaluate model simulations using multiple criteria to diagnose the relative importance of model structural differences in various climate regimes and to assess the amount of independent information in each of the models. This work will be crucial to both identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure. To facilitate research on these problems, the FORTRAN-90 source code for FUSE is available upon request from the lead author.

Field observations of soil moisture variability across scales

Abstract: In this study, over 36,000 ground-based soil moisture measurements collected during the SGP97, SGP99, SMEX02, and SMEX03 field campaigns were analyzed to characterize the behavior of soil moisture variability across scales. The field campaigns were conducted in Oklahoma and Iowa in the central USA. The Oklahoma study region is sub-humid with moderately rolling topography, while the Iowa study region is humid with low-relief topography. The relationship of soil moisture standard deviation, skewness and the coefficient of variation versus mean moisture content was explored at six distinct extent scales, ranging from 2.5 m to 50 km. Results showed that variability generally increases with extent scale. The standard deviation increased from 0.036 cm3/cm3 at the 2.5-m scale to 0.071 cm3/cm3 at the 50-km scale. The log standard deviation of soil moisture increased linearly with the log extent scale, from 16 m to 1.6 km, indicative of fractal scaling. The soil moisture standard deviation versus mean moisture content exhibited a convex upward relationship at the 800-m and 50-km scales, with maximum values at mean moisture contents of roughly 0.17 cm3/cm3 and 0.19 cm3/cm3, respectively. An empirical model derived from the observed behavior of soil moisture variability was used to estimate uncertainty in the mean moisture content for a fixed number of samples at the 800-m and 50-km scales, as well as the number of ground-truth samples needed to achieve 0.05 cm3/cm3 and 0.03 cm3/cm3 accuracies. The empirical relationships can also be used to parameterize surface soil moisture variations in land surface and hydrological models across a range of scales. To our knowledge, this is the first study to document the behavior of soil moisture variability over this range of extent scales using ground-based measurements. Our results will contribute not only to efficient and reliable satellite validation, but also to better utilization of remotely sensed soil moisture products for enhanced modeling and prediction.

New analytical derivation of the mean annual water-energy balance equation

Abstract: [1] The coupled water-energy balance on long-term time and catchment scales can be expressed as a set of partial differential equations, and these are proven to have a general solution as E/P = F(E0/P, c), where c is a parameter. The state-space of (P, E0, E) is a set of curved faces in P − E0 − E three-dimensional space, whose projection into E/P − E0/P two-dimensional space is a Budyko-type curve. The analytical solution to the partial differential equations has been obtained as E = E0P/(Pn + E0n)1/n (parameter n representing catchment characteristics) using dimensional analysis and mathematic reasoning, which is different from that found in a previous study. This analytical solution is a useful theoretical tool to evaluate the effect of climate and land use changes on the hydrologic cycle. Mathematical comparisons between the two analytical equations showed that they were approximately equivalent, and their parameters had a perfectly significant linear correlation relationship, while the small difference may be a result of the assumption about derivatives in the previous study.

Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS

Abstract: Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Heat as a tracer to determine streambed water exchanges

Abstract: [1] This work reviews the use of heat as a tracer of shallow groundwater movement and describes current temperature-based approaches for estimating streambed water exchanges. Four common hydrologic conditions in stream channels are graphically depicted with the expected underlying streambed thermal responses, and techniques are discussed for installing and monitoring temperature and stage equipment for a range of hydrological environments. These techniques are divided into direct-measurement techniques in streams and streambeds, groundwater techniques relying on traditional observation wells, and remote sensing and other large-scale advanced temperature-acquisition techniques. A review of relevant literature suggests researchers often graphically visualize temperature data to enhance conceptual models of heat and water flow in the near-stream environment and to determine site-specific approaches of data analysis. Common visualizations of stream and streambed temperature patterns include thermographs, temperature envelopes, and one-, two-, and three-dimensional temperature contour plots. Heat and water transport governing equations are presented for the case of transport in streambeds, followed by methods of streambed data analysis, including simple heat-pulse arrival time and heat-loss procedures, analytical and time series solutions, and heat and water transport simulation models. A series of applications of these methods are presented for a variety of stream settings ranging from arid to continental climates. Progressive successes to quantify both streambed fluxes and the spatial extent of streambeds indicate heat-tracing tools help define the streambed as a spatially distinct field (analogous to soil science), rather than simply the lower boundary in stream research or an amorphous zone beneath the stream channel.

A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model

Abstract: Received 29 November 2007; revised 12 May 2008; accepted 23 May 2008; published 11 September 2008. [1] Distributed hydrological models have the potential to provide improved streamflow forecasts along the entire channel network, while also simulating the spatial dynamics of evapotranspiration, soil moisture content, water quality, soil erosion, and land use change impacts. However, they are perceived as being difficult to parameterize and evaluate, thus translating into significant predictive uncertainty in the model results. Although a priori parameter estimates derived from observable watershed characteristics can help to minimize obstacles to model implementation, there exists a need for powerful automated parameter estimation strategies that incorporate diagnostic information regarding the causes of poor model performance. This paper investigates a diagnostic approach to model evaluation that exploits hydrological context and theory to aid in the detection and resolution of watershed model inadequacies, through consideration of three of the four major behavioral functions of any watershed system; overall water balance, vertical redistribution, and temporal redistribution (spatial redistribution was not addressed). Instead of using classical statistical measures (such as mean squared error), we use multiple hydrologically relevant ‘‘signature measures’’ to quantify the performance of the model at the watershed outlet in ways that correspond to the functions mentioned above and therefore help to guide model improvements in a meaningful way. We apply the approach to the Hydrology Laboratory Distributed Hydrologic Model (HL-DHM) of the National Weather Service and show that diagnostic evaluation has the potential to provide a powerful and intuitive basis for deriving consistent estimates of the parameters of watershed models. Citation: Yilmaz, K. K., H. V. Gupta, and T. Wagener (2008), A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model, Water Resour. Res., 44, W09417, doi:10.1029/2007WR006716.

Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model

Abstract: [1] The influence of groundwater dynamics on the energy balance at the land surface is studied using an integrated, distributed watershed modeling platform. This model includes the mass and energy balance at the land surface; three-dimensional variably saturated subsurface flow; explicit representation of the water table; and overland flow. The model is applied to the Little Washita watershed in Central Oklahoma, USA and compared to runoff, soil moisture and energy flux observations. The connection between groundwater dynamics and the land surface energy balance is studied using a variety of conventional and spatial statistical measures. For a number of energy variables a strong interconnection is demonstrated with water table depth. This connection varies seasonally and spatially depending on the spatial composition of water table depth. A theoretical critical water table depth range is presented where a strong sensitivity between groundwater and land-surface processes may be observed. For this particular watershed, a critical depth range is established between 1 and 5 m in which the land surface energy budget is most sensitive to groundwater storage. Finally, concrete recommendations are put forth to characterize this interconnection in the field.

Modeling blue and green water availability in Africa

Abstract: [1] Despite the general awareness that in Africa many people and large areas are suffering from insufficient water supply, spatially and temporally detailed information on freshwater availability and water scarcity is so far rather limited. By applying a semidistributed hydrological model SWAT (Soil and Water Assessment Tool), the freshwater components blue water flow (i.e., water yield plus deep aquifer recharge), green water flow (i.e., actual evapotranspiration), and green water storage (i.e., soil water) were estimated at a subbasin level with monthly resolution for the whole of Africa. Using the program SUFI-2 (Sequential Uncertainty Fitting Algorithm), the model was calibrated and validated at 207 discharge stations, and prediction uncertainties were quantified. The presented model and its results could be used in various advanced studies on climate change, water and food security, and virtual water trade, among others. The model results are generally good albeit with large prediction uncertainties in some cases. These uncertainties, however, disclose the actual knowledge about the modeled processes. The effect of considering these model-based uncertainties in advanced studies is shown for the computation of water scarcity indicators.

Spatial proximity, physical similarity, regression and ungaged catchments: A comparison of regionalization approaches based on 913 French catchments

Abstract: [1] Given the contradictory results from recent studies, this paper compares classical regionalization schemes of catchment model parameters over the wide range of hydroclimates found in France To ensure the generality of the conclusions, we used two lumped rainfall-runoff models applied to daily data over a large set of 913 French catchments Three types of approaches were considered: regionalization using regression, regionalization based on spatial proximity and regionalization based on physical similarity This comparison shows that in France, where a dense network of gauging stations is available, spatial proximity provides the best regionalization solution The regression approach is the least satisfactory, with results very close to those obtained using one median parameter set for the whole country The physical similarity approach is intermediary However, the results obtained with these three methods lag far behind those obtained by full model calibration Our results also show that some improvement could be made by combining spatial proximity and physical similarity, and that there is still considerable room for progress in the field of ungaged catchment modeling

Responses of streamflow to changes in climate and land use/cover in the Loess Plateau, China

Abstract: [1] To control the severe soil erosion in the Loess Plateau, China, a great number of soil conservation measures including terracing, afforestation, and construction of sediment-trapping dams have been implemented since the 1950s. These measures have resulted in large-scale land use and land cover change. It is important to evaluate the impacts of these soil conservation measures on streamflow as streamflow is an important determinant on catchment sediment yield and obviously is related to water security in the region. In this study, data from 11 catchments in the Loess Plateau were analyzed to investigate the responses of streamflow to the land use/cover changes. The nonparametric Mann-Kendall test and the Pettitt test were used to identify trends and change points in the streamflow records. All 11 catchments had significant negative trend in annual streamflow of −0.13 to −1.58 mm a−1. Change points in streamflow occurred between 1971 and 1985. A method was employed to evaluate the impacts of climate variability and land use/cover changes on mean annual streamflow on the basis of precipitation and potential evaporation. It was estimated that the land use/cover changes accounted for over 50% of the reduction in mean annual streamflow in 8 out of the 11 catchments. However, climate (i.e., precipitation and potential evaporation) played a more important role in reducing the streamflow in the three remaining catchments. Among the soil conservation measures, construction of sediment-trapping dams and reservoirs, with associated irrigation water extractions from the latter, appeared to be the main cause of the reduced streamflow.

A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman‐Monteith equation

Abstract: [1] We introduce a simple biophysical model for surface conductance, Gs, for use with remotely sensed leaf area index (Lai) data and the Penman-Monteith (PM) equation to calculate daily average evaporation, E, at kilometer spatial resolution. The model for Gs has six parameters that represent canopy physiological processes and soil evaporation: gsx, maximum stomatal conductance; Q50 and D50, the values of solar radiation and atmospheric humidity deficit when the stomatal conductance is half its maximum; kQ and kA, extinction coefficients for visible radiation and available energy; and f, the ratio of soil evaporation to the equilibrium rate corresponding to the energy absorbed at the soil surface. Model parameters were estimated using 2–3 years of data from 15 flux station sites covering a wide range of climate and vegetation types globally. The PM estimates of E are best when all six parameters in the Gs model are optimized at each site, but there is no significant reduction in model performance when Q50, D50, kQ, and kA are held constant across sites and gsx and f are optimized (linear regression of modeled mean daily evaporation versus measurements: slope = 0.83, intercept = 0.22 mm/d, R2 = 0.80, and N = 10623). The average systematic root-mean-square error in daytime mean evaporation was 0.27 mm/d (range 0.09–0.50 mm/d) for the 15 sites. The average unsystematic component was 0.48 mm/d (range 0.28–0.71 mm/d). The new model for Gs with two parameters yields better estimates of E than an earlier, simple model Gs = cLLai, where cL is an optimized parameter. Our study confirms that the PM equation provides reliable estimates of evaporation rates from land surfaces at daily time scales and kilometer space scales when remotely sensed leaf area indices are incorporated into a simple biophysical model for surface conductance. Developing remote sensing techniques to measure the temporal and spatial variation in f is expected to enhance the utility of the model proposed in this paper.

Appraisal of the generalized likelihood uncertainty estimation (GLUE) method

Abstract: [1] Recent research documents that the widely accepted generalized likelihood uncertainty estimation (GLUE) method for describing forecasting precision and the impact of parameter uncertainty in rainfall/runoff watershed models fails to achieve the intended purpose when used with an informal likelihood measure. In particular, GLUE generally fails to produce intervals that capture the precision of estimated parameters, and the difference between predictions and future observations. This paper illustrates these problems with GLUE using a simple linear rainfall/runoff model so that model calibration is a linear regression problem for which exact expressions for prediction precision and parameter uncertainty are well known and understood. The simple regression example enables us to clearly and simply illustrate GLUE deficiencies. Beven and others have suggested that the choice of the likelihood measure used in a GLUE computation is subjective and may be selected to reflect the goals of the modeler. If an arbitrary likelihood is adopted that does not reasonably reflect the sampling distribution of the model errors, then GLUE generates arbitrary results without statistical validity that should not be used in scientific work. The traditional subjective likelihood measures that have been used with GLUE also fail to reflect the nonnormality, heteroscedasticity, and serial correlation among the residual errors generally found in real problems, and hence are poor metrics for even simple sensitivity analyses and model calibration. Most previous applications of GLUE only produce uncertainty intervals for the average model prediction, which by construction should not be expected to include future observations with the prescribed probability. We show how the GLUE methodology when properly implemented with a statistically valid likelihood function can provide prediction intervals for future observations which will agree with widely accepted and statistically valid analyses.

Infinite slope stability under steady unsaturated seepage conditions

Abstract: [1] We present a generalized framework for the stability of infinite slopes under steady unsaturated seepage conditions. The analytical framework allows the water table to be located at any depth below the ground surface and variation of soil suction and moisture content above the water table under steady infiltration conditions. The framework also explicitly considers the effect of weathering and porosity increase near the ground surface on changes in the friction angle of the soil. The factor of safety is conceptualized as a function of the depth within the vadose zone and can be reduced to the classical analytical solution for subaerial infinite slopes in the saturated zone. Slope stability analyses with hypothetical sandy and silty soils are conducted to illustrate the effectiveness of the framework. These analyses indicate that for hillslopes of both sandy and silty soils, failure can occur above the water table under steady infiltration conditions, which is consistent with some field observations that cannot be predicted by the classical infinite slope theory. A case study of shallow slope failures of sandy colluvium on steep coastal hillslopes near Seattle, Washington, is presented to examine the predictive utility of the proposed framework.

Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions

Abstract: [1] Over the last century, land use and land cover (LULC) in the United States Corn Belt region shifted from mixed perennial and annual cropping systems to primarily annual crops. Historical LULC change impacted the annual water balance in many Midwestern basins by decreasing annual evapotranspiration (ET) and increasing streamflow and base flow. Recent expansion of the biofuel industry may lead to future LULC changes from increasing corn acreage and potential conversion of the industry to cellulosic bioenergy crops of warm or cool season grasses. In this paper, the Soil and Water Assessment Tool (SWAT) model was used to evaluate potential impacts from future LULC change on the annual and seasonal water balance of the Raccoon River watershed in west-central Iowa. Three primary scenarios for LULC change and three scenario variants were evaluated, including an expansion of corn acreage in the watershed and two scenarios involving expansion of land using warm season and cool season grasses for ethanol biofuel. Modeling results were consistent with historical observations. Increased corn production will decrease annual ET and increase water yield and losses of nitrate, phosphorus, and sediment, whereas increasing perennialization will increase ET and decrease water yield and loss of nonpoint source pollutants. However, widespread tile drainage that exists today may limit the extent to which a mixed perennial-annual land cover would ever resemble pre-1940s hydrologic conditions. Study results indicate that future LULC change will affect the water balance of the watershed, with consequences largely dependent on the future LULC trajectory.

Large‐scale particle image velocimetry for measurements in riverine environments

Abstract: [1] Large-scale particle image velocimetry (LSPIV) is a nonintrusive approach to measure velocities at the free surface of a water body. The raw LSPIV results are instantaneous water surface velocity fields, spanning flow areas up to hundreds of square meters. Measurements conducted in typical conditions in conjunction with appropriate selections of parameters for image processing resulted in mean velocity errors of less than 3.5%. The current article reviews the background of LSPIV and the work of three research teams spanning over a decade. Implementation examples using various LSPIV configurations are then described to illustrate the capability of the technique to characterize spatially distributed two- and three-dimensional flow kinematic features that can be related to important morphologic and hydrodynamic aspects of natural rivers. Finally, results and a critique of research methods are discussed to encourage LSPIV use and to improve its capabilities to collect field data needed to better understand complex geomorphic, hydrologic, and ecologic river processes and interactions under normal and extreme conditions.

Inhomogeneous precipitation distribution and snow transport in steep terrain

Abstract: [1] The inhomogeneous snow distribution found in alpine terrain is the result of wind and precipitation interacting with the (snow) surface over topography We introduce and explain preferential deposition of precipitation as the deposition process without erosion of previously deposited snow and thus in absence of saltation A numerical model is developed, describing the relevant processes of saltation, suspension, and preferential deposition The model uses high-resolution wind fields calculated with a meteorological model, ARPS The model is used to simulate a 120 h snow storm period over a steep alpine ridge, for which snow distribution measurements are available The comparison to measurements shows that the model captures the larger-scale snow distribution patterns and predicts the total additional lee slope loading well However, the spatial resolution of 25 m is still insufficient to capture the smaller-scale deposition features observed The model suggests that the snow distribution on the ridge scale is primarily caused by preferential deposition and that this result is not sensitive to model parameters such as turbulent diffusivity, drift threshold, or concentration in the saltation layer

Numerical simulation of hydrodynamics and bank erosion in a river bend

Abstract: We present an integrated analysis of bank erosion in a high-curvature bend of the gravel bed Cecina River (central Italy). Our analysis combines a model of fluvial bank erosion with groundwater flow and bank stability analyses to account for the influence of hydraulic erosion on mass failure processes, the key novel aspect being that the fluvial erosion model is parameterized using outputs from detailed hydrodynamic simulations. The results identify two mechanisms that explain how most bank retreat usually occurs after, rather than during, flood peaks. First, in the high curvature bend investigated here the maximum flow velocity core migrates away from the outer bank as flow discharge increases, reducing sidewall boundary shear stress and fluvial erosion at peak flow stages. Second, bank failure episodes are triggered by combinations of pore water and hydrostatic confining pressures induced in the period between the drawdown and rising phases of multipeaked flow events.

Real-time groundwater flow modeling with the Ensemble Kalman Filter: Joint estimation of states and parameters and the filter inbreeding problem

Abstract: [1] Real-time groundwater flow modeling with filter methods is interesting for dynamical groundwater flow systems, for which measurement data in real-time are available. The Ensemble Kalman Filter (EnKF) approach is used here to update states together with parameters by adopting an augmented state vector approach. The performance of EnKF is investigated in a synthetic study with a two-dimensional transient groundwater flow model where (1) only the recharge rate is spatiotemporally variable, (2) only transmissivity is spatially variable with σlnT2 = 1.0 or (3) with σlnT2 = 2.7, and (4) both recharge rate and transmissivity are uncertain (a combination of (1) and (3)). The performance of EnKF for simultaneous state and parameter estimation in saturated groundwater flow problems is investigated in dependence of the number of stochastic realizations, the updating frequency and updating intensity of log-transmissivity, the amount of measurements in space and time, and the method (iterative versus noniterative EnKF), among others. Satisfactory results were also obtained if both transmissivity and recharge rate were uncertain. However, it was found that filter inbreeding is much more severe if hydraulic heads and transmissivities are jointly updated than if only hydraulic heads are updated. The filter inbreeding problem was investigated in more detail and could be strongly reduced with help of a damping parameter, which limits the intensity of the perturbation of the log-transmissivity field. An additional reduction of filter inbreeding could be achieved by combining two measures: (1) inflating the elements of the predicted state covariance matrix on the basis of a comparison between the model uncertainty and the observed errors at the measurement points and (2) starting the flow simulations with a very large number of realizations and then sampling the desired number of realizations after one simulation time step by minimizing the differences between the local cpdfs (and bivariate cpdfs) of hydraulic head for the large ensemble and the corresponding cpdfs for the reduced ensemble. The two measures, which cause very limited CPU costs, allowed making 100 stochastic realizations for the reproduction of the states as efficient as 200–500 untreated stochastic realizations.

Metrics for Assessing the Downstream Effects of Dams

Abstract: [1] We evaluate three metrics representing the drivers of channel change downstream from dams. A balance between changes in sediment supply and transport capacity identifies conditions of sediment deficit or surplus. A Shields number represents the competence of postdam flows and the potential for incision under conditions of sediment deficit. A ratio of postdam to predam flood discharge provides a metric for the scale and rate of channel change, especially width. The metrics are calculated for more than 4000 km of some of the major rivers in the western United States. More than 60% of these rivers are in sediment deficit, and only a few reaches are in sediment surplus. The sediment balance can be used to assess the relative effort involved in reversing undesired conditions of deficit or surplus.

Coupled modelling of glacier and streamflow response to future climate scenarios

Abstract: [1] This study investigated the sensitivity of streamflow to changes in climate and glacier cover for the Bridge River basin, British Columbia, using a semi-distributed conceptual hydrological model coupled with a glacier response model. Mass balance data were used to constrain model parameters. Climate scenarios included a continuation of the current climate and two transient GCM scenarios with greenhouse gas forcing. Modelled glacier mass balance was used to re-scale the glacier every decade using a volume-area scaling relation. Glacier area and summer streamflow declined strongly even under the steady-climate scenario, with the glacier retreating to a new equilibrium within 100 years. For the warming scenarios, glacier retreat continued with no evidence of reaching a new equilibrium. Uncertainty in parameters governing glacier melt produced uncertainty in future glacier retreat and streamflow response. Where mass balance information is not available to assist with calibration, model-generated future scenarios will be subject to significant uncertainty.

On model selection criteria in multimodel analysis

Abstract: [1] Hydrologic systems are open and complex, rendering them prone to multiple conceptualizations and mathematical descriptions. There has been a growing tendency to postulate several alternative hydrologic models for a site and use model selection criteria to (1) rank these models, (2) eliminate some of them, and/or (3) weigh and average predictions and statistics generated by multiple models. This has led to some debate among hydrogeologists about the merits and demerits of common model selection (also known as model discrimination or information) criteria such as AIC, AICc, BIC, and KIC and some lack of clarity about the proper interpretation and mathematical representation of each criterion. We examine the model selection literature to find that (1) all published rigorous derivations of AIC and AICc require that the (true) model having generated the observational data be in the set of candidate models; (2) though BIC and KIC were originally derived by assuming that such a model is in the set, BIC has been rederived by Cavanaugh and Neath (1999) without the need for such an assumption; and (3) KIC reduces to BIC as the number of observations becomes large relative to the number of adjustable model parameters, implying that it likewise does not require the existence of a true model in the set of alternatives. We explain why KIC is the only criterion accounting validly for the likelihood of prior parameter estimates, elucidate the unique role that the Fisher information matrix plays in KIC, and demonstrate through an example that it imbues KIC with desirable model selection properties not shared by AIC, AICc, or BIC. Our example appears to provide the first comprehensive test of how AIC, AICc, BIC, and KIC weigh and rank alternative models in light of the models' predictive performance under cross validation with real hydrologic data.

Methods and technologies to improve efficiency of water use

Abstract: The competition for existing freshwater supplies will require a paradigmatic shift from maximizing productivity per unit of land area to maximizing productivity per unit of water consumed. This shift will, in turn, demand broad systems approaches that physically and biologically optimize irrigation relative to water delivery and application schemes, rainfall, critical growth stages, soil fertility, location, and weather. Water can be conserved at a watershed or regional level for other uses only if evaporation, transpiration, or both are reduced and unrecoverable losses to unusable sinks are minimized (e.g., salty groundwater or oceans). Agricultural advances will include implementation of crop location strategies, conversion to crops with higher economic value or productivity per unit of water consumed, and adoption of alternate drought-tolerant crops. Emerging computerized GPS-based precision irrigation technologies for self-propelled sprinklers and microirrigation systems will enable growers to apply water and agrochemicals more precisely and site specifically to match soil and plant status and needs as provided by wireless sensor networks. Agriculturalists will need to exercise flexibility in managing the rate, frequency, and duration of water supplies to successfully allocate limited water and other inputs to crops. The most effective means to conserve water appears to be through carefully managed deficit irrigation strategies that are supported by advanced irrigation system and flexible, state-of-the-art water delivery systems. Nonagricultural water users will need to exercise patience as tools reflecting the paradigmatic shift are actualized. Both groups will need to cooperate and compromise as they practice more conservative approaches to freshwater consumption.

Geostatistical interpolation using copulas

Abstract: [1] In many applications of geostatistical methods, the dependence structure of the investigated parameter is described solely with the variogram or covariance functions, which are susceptible to measurement anomalies and implies the assumption of Gaussian dependence Moreover the kriging variance respects only observation density, data geometry and the variogram model To address these problems, we borrow the idea from copulas, to depict the dependence structure without the influence of the marginal distribution The methodology and basic hypotheses for application of copulas as geostatistical methods are discussed and the Gaussian copula as well as a non-Gaussian copula are used in this paper Copula parameters are estimated using a division of the observations into multipoint subsets and a subsequent maximization of the corresponding likelihood function The interpolation is carried out with two different copulas, where the expected and median values are calculated from the copulas conditioned with the nearby observations The full conditional copulas provide the estimation distributions for the unobserved locations and can be used to define confidence intervals which depend on both the observation geometry and values Observations of a large scale groundwater quality measurement network in Baden-Wurttemberg are used to demonstrate the methodology Five groundwater quality parameters: chloride, nitrate, pH, sulfate and dissolved oxygen are investigated All five parameters show non-Gaussian dependence The copula-based interpolation results of the five parameters are compared to the results of conventional ordinary and indicator kriging Different statistical measures including mean squared error, relative differences and probability scores are used to compare cross validation and split sampling results of the interpolation methods The non-Gaussian copulas give better results than the geostatistical interpolations Validation of the confidence intervals shows that they are more realistic than the estimation variances obtained by ordinary kriging

When will Lake Mead go dry

Abstract: [1] A water budget analysis shows that under current conditions there is a 10% chance that live storage in Lakes Mead and Powell will be gone by about 2013 and a 50% chance that it will be gone by 2021 if no changes in water allocation from the Colorado River system are made. This startling result is driven by climate change associated with global warming, the effects of natural climate variability, and the current operating status of the reservoir system. Minimum power pool levels in both Lake Mead and Lake Powell will be reached under current conditions by 2017 with 50% probability. While these dates are subject to some uncertainty, they all point to a major and immediate water supply problem on the Colorado system. The solutions to this water shortage problem must be time-dependent to match the time-varying, human-induced decreases in future river flow.

Spatio-temporal combination of MODIS images - potential for snow cover mapping

Abstract: [1] MODIS snow cover products are appealing for hydrological applications because of their good accuracy and daily availability. Their main limitation, however, is cloud obscuration. In this study we evaluate simple mapping methods, termed temporal and spatial filters, that reduce cloud coverage by using information from neighboring non-cloud covered pixels in time or space, and by combining MODIS data from the Terra and Aqua satellites. The accuracy of the filter methods is evaluated over Austria, using daily snow depth observations at 754 climate stations and daily MODIS images in the period 2003–2005. The results indicate that the filtering techniques are remarkably efficient in cloud reduction, and the resulting snow maps are still in good agreement with the ground snow observations. There exists a clear, seasonally dependent, trade off between accuracy and cloud coverage for the various filtering methods. An average of 63% cloud coverage of the Aqua images is reduced to 52% for combined Aqua-Terra images, 46% for the spatial filter, 34% for the 1-day temporal filter and 4% for the 7-day temporal filter, and the corresponding overall accuracies are 95.5%, 94.9%, 94.2%, 94.4% and 92.1%, respectively.

Permanent scatterer InSAR reveals seasonal and long‐term aquifer‐system response to groundwater pumping and artificial recharge

Abstract: Received 4 May 2007; revised 30 July 2007; accepted 10 October 2007; published 5 February 2008. [1] Permanent scatterer InSAR (PSInSARk )p rovides an ew high-resolution methodology for detecting and precisely measuring long-term and seasonal aquifer-system response to pumping and recharge. In contrast to conventional InSAR, the permanent scatterer methodology utilizes coherent radar phase data from thousands of individual radar reflectors on the ground to develop displacement time series and to produce velocity field maps that depict aquifer-system response with a high degree of spatial detail. In this study, we present the first results of a prototype study in Las Vegas Valley, Nevada, that demonstrate how this methodology can be utilized in heavily pumped groundwater basins to analyze aquifer-system response to long-term and seasonal pumping. We have developed a series of velocity field maps of the valley for the 1992‐1996, 1996‐ 2000, and 2003‐2005 time periods that show that despite rising water levels associated with an artificial recharge program, long-term, residual, inelastic aquifer-system compaction (subsidence) is continuing in several parts of the valley. In other areas, however, long-term subsidence has been arrested and locally reversed. The seasonal, elastic responses to alternating pumping and recharge cycles were segregated from the long-term trends and analyzed for spatial and temporal patterns. The results show oscillations in which the maximum seasonal responses are associated with the late stages of the annual artificial recharge cycles, and that similar seasonal subsidence signals are related to summer pumping cycles. The differentiation of the seasonal response through the use of time series data further allows the estimation of elastic and inelastic skeletal storage coefficients, providing a basis for future work that could characterize the storage properties of an aquifer system with a high degree of spatial resolution.

Bifurcation dynamics and avulsion duration in meandering rivers by one-dimensional and three-dimensional models

Abstract: At river bifurcations, water and sediment are divided over two branches. The dynamics of the bifurcation determine the long-term evolution (centuries) of the downstream branches, potentially leading to avulsion, but the dynamics are poorly understood. The long-term evolution can only be studied by one-dimensional models because of computational costs. For such models, a relation describing the sediment division is necessary, but only few relations are available and these remain poorly tested so far. We study the division of sediment and the morphodynamics on a timescale of decades to centuries by idealized three-dimensional modeling of bifurcations with upstream meanders and dominantly bed load transport. An upstream meander favors one bifurcate with more sediment and the other with more water, leading to destabilization. The bifurcations commonly attain a highly asymmetrical division of discharge and sediment after a few decades to a few centuries, depending on combinations of the relevant parameters. Although past work on avulsions focused on slope advantage, we found that bifurcations can be quasibalanced by opposing factors, such as a bifurcate connected to the inner bend with a downstream slope advantage. Nearly balanced bifurcations develop much slower than unbalanced bifurcations, which explains the observed variation in avulsion duration in natural systems. Which branch becomes dominant and the timescale to attain model equilibrium are determined by the length of the downstream bifurcates, the radius of the upstream bend, a possible gradient advantage for one bifurcate and, notably, the width–depth ratio. The latter determines the character of the bars which may result in overdeepening and unstable bars. The distance between the beginning of the upstream bend and the bifurcation determines the location of such bars and pools, which may switch the dominant bifurcate. In fact, when the bifurcation is quasibalanced by opposing factors, any minor disturbance or a different choice of roughness or sediment transport predictor may switch the dominant bifurcate. The division of sediment is nearly the same as the division of flow discharge in most runs until the discharge division becomes very asymmetrical, so that a bifurcate does not close off entirely. This partly explains the sustained existence of residual channels and existence of anastomosing rivers and the potential for reoccupation of old channel courses. We develop a new relation for sediment division at bifurcations in one-dimensional models incorporating the effect of meandering. The flow and sediment divisions predicted by two existing relations and the new relation for one-dimensional models are in qualitative agreement with the three-dimensional model. These one-dimensional relations are however of limited value for wider rivers because they lack the highly three-dimensional bar dynamics that may switch the direction of bifurcation evolution. The potential effects of bed sediment sorting, bank erosion, and levee formation on bifurcation stability and avulsion duration are discussed.