ALBERT

Description: At present continental to global scale flood forecasting predicts at a point discharge, with little attention to detail and accuracy of local scale inundation predictions. Yet, inundation variables are of interest and all flood impacts are inherently local in nature. This paper proposes a large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas. The model was built for the Lower Zambezi River to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. ECMWF ensemble forecast (ENS) data were used to force the VIC (Variable Infiltration Capacity) hydrological model, which simulated and routed daily flows to the input boundary locations of a 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst representing the floodplain at an appropriate scale. The modeling system was calibrated using channel water levels from satellite laser altimetry and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of between one and two model resolutions compared to an observed flood edge and inundation area agreement was on average 86%. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km 2 and at model grid resolutions up to several km 2 .

Description: A class of capillary flows in unsaturated porous media is characterized by quasi-steady viscous flow confined behind curved air-water interfaces and within liquid bodies held by capillary forces along crevices and grain contacts. The geometry of the connected capillary liquid network within the pore space resembles channels that form between adjacent bubbles in foam (Plateau borders) with solid grains representing gas bubbles in foam. For simplified channel geometry we combine expressions for viscous flow with continuity considerations to describe the evolution of the channels cross-sectional area during gravity drainage. This formulation enables modeling of unsaturated flow without invoking the Richards equation and associated hydraulic functions. We adapt a formalism originally developed for foam “free drainage” (drainage under gravity) or “forced drainage” (infiltration front motion) to a class of unsaturated flows in porous media that require a few input parameters only (mean channel corner angle, air entry value and porosity) for certain initial and boundary conditions. We demonstrate that the reduction in capillary channel cross section yields a consistent description of self-regulating internal fluxes towards attainment of the so-called “field capacity” in soil and provides an alternative method for interpretation of outflow experiments for prescribed pressure boundary conditions. Additionally, the geometrically-explicit formulation provides a more intuitive picture of capillary flows across textural boundaries (changes in channel cross-section and number of channels). The foam drainage methodology expands the range of tools available for analyses of unsaturated flow processes and offers more realistic links between liquid configuration and flow dynamics in unsaturated porous media.

Description: Synthetic streamflows at different sites in a river basin are needed for planning, operation and management of water resources projects. Modeling the temporal and spatial dependence structure of monthly streamflow at different sites is generally required. In this study, the maximum entropy copula method is proposed for multisite monthly streamflow simulation, in which the temporal and spatial dependence structure is imposed as constraints to derive the maximum entropy copula. The monthly streamflows at different sites are then generated by sampling from the conditional distribution. A case study for the generation of monthly streamflow at three sites in the Colorado River basin illustrates the application of the proposed method. Simulated streamflow from the maximum entropy copula is in satisfactory agreement with observed streamflow.

Description: The Krycklan Catchment Study (KCS) provides a unique field infrastructure for hillslope to landscape-scale research on short and long-term ecosystem dynamics in boreal landscapes. The site is designed for process-based research assessing the role of external drivers including forest management, climate change, and long-range pollutant transport on forests, mires, soils, streams, lakes and groundwater. The over-arching objectives of KCS are to (1) provide a state-of-the-art infrastructure for experimental and hypothesis driven research, (2) maintain a collection of high quality, long-term climatic, biogeochemical, hydrological and environmental data, and (3) support the development of models and guidelines for research, policy and management.

Description: 3-D Hydraulic Tomography (3-D HT) is a method for aquifer characterization whereby the 3-D spatial distribution of aquifer flow parameters (primarily hydraulic conductivity, K) is estimated by joint inversion of head change data from multiple partially-penetrating pumping tests. While performance of 3-D HT has been studied extensively in numerical experiments, few field studies have demonstrated the real-world performance of 3-D HT. Here we report on a 3-D transient hydraulic tomography (3-D THT) field experiment at the Boise Hydrogeophysical Research Site which is different from prior approaches in that it represents a “baseline” analysis of 3-D THT performance using only a single arrangement of a central pumping well and 5 observation wells with nearly complete pumping and observation coverage at 1m intervals. We jointly analyze all pumping tests using a geostatistical approach based on the quasi-linear estimator of kitanidis [1995]. We reanalyze the system after progressively removing pumping and/or observation intervals; significant progressive loss of information about heterogeneity is quantified as reduced variance of the K field overall, reduced correlation with slug test K estimates at wells, and reduced ability to accurately predict independent pumping tests. We verify that imaging accuracy is strongly improved by pumping and observational densities comparable to the aquifer heterogeneity geostatistical correlation lengths. Discrepancies between K profiles at wells, as obtained from HT and slug tests, are greatest at the tops and bottoms of wells where HT observation coverage was lacking.

Description: Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical post-processing is required. In this work Bayesian model averaging (BMA) is applied to statistically post-process ensemble runoff raw forecasts for a catchment in Switzerland, at lead-times ranging from 1 to 240 hours. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead-time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead-times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead-times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the post-processed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

Description: We derive a series solution for the nonlinear Boussinesq equation in terms of the similarity variable of the Boltzmann transformation in a semi-infinite domain. The first few coefficients of the series have been known for a long time, having been obtained by a truncated inversion of the series solution of the Blasius equation, but no direct recurrence relation was known for the complete series representing the solution of the Boussinesq equation. The series turns out to have a finite radius of convergence, which we estimate with a numerical complex-plane integration method that identifies the singularities of the solution when the equation is extended to the complex plane. The homogeneous condition at the origin produces a singularity which complicates numerical solutions with Runge-Kutta methods. We present two variable transformations that circumvent the problem and that are best suited to the complex-variable and the real-variable versions of the equation, respectively. Using those tools, an approximate solution accurate to 1.75 × 10 -10 and valid for the entire positive real axis is then developed by matching a Padé approximant of the exact series and an asymptotic solution (to overcome the restriction imposed by the finite radius of convergence of the series), along the same lines of the expression proposed by Hogarth and Parlange [1999]. The accuracies of all of the existing and the newly proposed solutions are obtained.

Description: Field sampling in unwadeable and flashy flood events encounters the problem that lateral variability of flow hydraulics and sediment transport cannot be captured adequately, and there is also an accuracy problem because parameters change while being measured. Moreover, event based gravel-sand mixed transport data in rapidly changing conditions are largely missing, in particular for gravel-bed rivers in small catchments. In this study, field measurements of bed load, suspended load, flow velocities, water depths and cross section geometry were collected during flood events at a monitoring station near the mouth of the Versilia river, Italy. Since the observed hydrographs are characterized by short durations, to the order of a few hours, an analysis of the lateral and temporal flow variability was carried out to enable the design of a sampling strategy and to minimize the errors created by the time variations of discharge associated with unsteady flow conditions. The measurements were interpreted using a 1D hydro-morphodynamic numerical model simulating the dynamics of flow and sediment discharges during a flood event for a given return period. The flow and sediment rating curves were then developed through an integrated approach combining different methodologies: field measurements, laboratory analyses and mathematical modeling. The developed approach allows one to capture the main physical mechanisms associated to the transport of sand–gravel mixtures, such as selective transport, and the hysteretic behaviour of sediment transport produced by rapid and intense flood events.

Description: ABSTRACT A study was performed to characterize over land precipitation associated with tropical cyclones (TCs) for basins around the world based upon the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2009, data from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product 3B42, showed that TCs accounted for 5.5%, 7.5%, 6%, 9.5%, and 8.9% of the annual precipitation for impacted over land areas of the Americas, East Asia, South and West Asia, Oceania, and East Africa respectively, and that TC contribution decreased significantly within the first 150-km from the coast. Locally, TCs contributed on average to more than 25% and up to 61% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. East Asia represented the higher and most constant TC rain (118±19% mm y -1 ) normalized over the area impacted, while East Africa presented the highest variability (108±60% mm y -1 ), and the Americas displayed the lowest average TC rain (65±24% mm y -1 ) despite a higher TC activity. Furthermore, the maximum monthly TC contribution (8-11%) was found later in the TC season and depended on the peak of TC activity, TC rainfall, and the domain transition between dry and wet regimes if any. Finally, because of their importance in terms of rainfall amount, the contribution of TCs was provided for a selection of 50 urban areas experiencing cyclonic activity. Results showed that for particularly intense years, urban areas prone to cyclonic activity received more than half of their annual rainfall from TCs.

Description: A multivariate, multi-site daily weather generator is presented for use in decision-centric vulnerability assessments under climate change. The tool is envisioned useful for a wide range of socioeconomic and biophysical systems sensitive to different aspects of climate variability and change. The proposed stochastic model has several components, including 1) a wavelet decomposition coupled to an autoregressive model to account for structured, low-frequency climate oscillations, 2) a Markov Chain and k-nearest-neighbor (KNN) resampling scheme to simulate spatially-distributed, multivariate weather variables over a region, and 3) a quantile mapping procedure to enforce long-term distributional shifts in weather variables that result from prescribed climate changes. The Markov Chain is used to better represent wet and dry spell statistics while the KNN bootstrap resampler preserves the covariance structure between the weather variables and across space. The wavelet-based autoregressive model is applied to annual climate over the region and used to modulate the Markov Chain and KNN resampling, embedding appropriate low-frequency structure within the daily weather generation process. Parameters can be altered in any of the components of the proposed model to enable the generation of realistic time series of climate variables that exhibit changes to both lower-order and higher-order statistics at long-term (inter-annual), mid-term (seasonal), and short-term (daily) timescales. The tool can be coupled with impact models in a bottom-up risk assessment to efficiently and exhaustively explore the potential climate changes under which a system is most vulnerable. An application of the weather generator is presented for the Connecticut River basin to demonstrate the tool's ability to generate a wide range of possible climate sequences over an extensive spatial domain.

Description: The objective of the least cost design problem of a water distribution system is to find its minimum cost with discrete diameters as decision variables and hydraulic controls as constraints. The goal of a robust least cost design is to find solutions which guarantee its feasibility independent of the data (i.e., under model uncertainty). A robust counterpart approach for linear uncertain problems is adopted in this study, which represents the uncertain stochastic problem as its deterministic equivalent. Robustness is controlled by a single parameter providing a trade-off between the probability of constraint violation and the objective cost. Two principal models are developed-uncorrelated uncertainty model with implicit design reliability, and correlated uncertainty model with explicit design reliability. The models are tested on three example applications and compared for uncertainty in consumers’ demands. The main contribution of this study is the inclusion of the ability to explicitly account for different correlations between water distribution systems demand nodes. In particular it is shown that including correlation information in the design phase has a substantial advantage in seeking more efficient robust solutions.

Description: Moving from univariate to multivariate frequency analysis, this study extends the Klemeš' critique of the widespread belief that the increasingly refined mathematical structures of probability functions increase the accuracy and credibility of the extrapolated upper tails of the fitted distribution models. In particular, we discuss key aspects of multivariate frequency analysis applied to hydrological data such as the selection of multivariate design events (i.e., appropriate subsets or scenarios of multiplets that exhibit the same joint probability to be used in design applications) and the assessment of the corresponding uncertainty. Since these problems are often overlooked or treated separately, and sometimes confused, we attempt to clarify properties, advantages, shortcomings and reliability of results of frequency analysis. We suggest a selection method of multivariate design events with prescribed joint probability based on simple Monte Carlo simulations that accounts for the uncertainty affecting the inference results and the multivariate extreme quantiles. It is also shown that the exploration of the p -level probability regions of a joint distribution returns a set of events that is a subset of the p -level scenarios resulting from an appropriate assessment of the sampling uncertainty, thus tending to overlook more extreme and potentially dangerous events with the same (uncertain) joint probability. Moreover, a quantitative assessment of the uncertainty of multivariate quantiles is provided by introducing the concept of joint confidence intervals. From an operational point of view, the simulated event sets describing the distribution of the multivariate p -level quantiles can be used to perform multivariate risk analysis under sampling uncertainty. As an example of the practical implications of this study, we analyse two case studies already presented in the literature.

Description: Sparse geologic dictionaries provide a novel approach for subsurface flow model representation and calibration. Learning sparse dictionaries from prior training datasets is an effective approach to describe complex geologic connectivity patterns in subsurface imaging applications. However, the computational cost of sparse learning algorithms becomes prohibitive for large models. Performing the sparse dictionary learning process on smaller image patches (segments) provides a simple approach to address this problem in image processing applications. However, in underdetermined subsurface flow model calibration inverse problems, reconstruction of a segmented image can introduce significant structural distortion and discontinuity at the boundaries of the segments. This paper proposes an alternative sparse learning approach where the sparse dictionaries are learned from low-rank representations of the large-scale training dataset in spectral domains (e.g., frequency domain). The objective is to develop a computationally efficient dictionary learning approach that emphasizes large-scale spatial connectivity patterns. This is achieved by removing the strong spatial correlations in the training data, thereby eliminating a large number of insignificant components from the sparse learning computation. In addition to improving the computational complexity, sparse learning from low-rank training datasets suppresses the small-scale details from entering the reconstruction of large-scale connectivity patterns, and providing a regularization effect in solving the resulting ill-posed inverse problems. We apply the proposed approach to travel-time tomography inversion and nonlinear subsurface flow model calibration inverse problems to demonstrate its effectiveness and practicality.

Description: A new hybrid wavelet–bootstrap–neural network (WBNN) model is proposed in this study for short term (1, 3 and 5 day; 1 and 2 week; and 1 and 2 month) urban water demand forecasting. The new method was tested using data from the city of Montreal in Canada. The performance of the WBNN method was compared with the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average model with exogenous input variables (ARIMAX), traditional NNs, wavelet analysis based NNs (WNN), bootstrap based NNs (BNN), and a simple naïve persistence index model. The WBNN model was developed as an ensemble of several NNs built using bootstrap resamples of wavelet sub-time series instead of raw datasets. The results demonstrated that the hybrid WBNN and WNN models produced significantly more accurate forecasting results than the traditional NN, BNN, ARIMA and ARIMAX models. It was also found that the WBNN model reduces the uncertainty associated with the forecasts, and the performance of WBNN forecasted confidence bands were found to be more accurate and reliable than BNN forecasted confidence bands. It was found in this study that maximum temperature and total precipitation improved the accuracy of water demand forecasts using wavelet analysis. The performance of WBNN models was also compared for different numbers of bootstrap resamples (i.e., 25, 50, 100, 200, and 500) and it was found that WBNN models produced optimum results with different numbers of bootstrap resamples for different lead time forecasts with considerable variability.

Description: ABSTRACT Although mechanistic reaction networks have been developed to quantify the biogeochemical evolution of subsurface systems associated with bioremediation, it is difficult in practice to quantify the onset and distribution of these transitions at the field scale using commonly collected wellbore datasets. As an alternative approach to the mechanistic methods, we develop a data-driven, statistical model to identify biogeochemical transitions using various time-lapse aqueous geochemical data (e.g., Fe(II), sulfate, sulfide, acetate, and uranium concentrations) and induced polarization (IP) data. We assume that the biogeochemical transitions can be classified as several dominant states that correspond to redox transitions and test the method at a uranium-contaminated site. The relationships between the geophysical observations and geochemical time-series vary depending upon the unknown underlying redox status, which is modeled as a hidden Markov random field. We estimate unknown parameters by maximizing the joint likelihood function using the maximization-expectation algorithm. The case study results show that when considered together aqueous geochemical data and IP imaginary conductivity provide a key diagnostic signature of biogeochemical stages. The developed method provides useful information for evaluating the effectiveness of bioremediation, such as the probability of being in specific redox stages following biostimulation where desirable pathways (e.g., uranium removal) are more highly favored. The use of geophysical data in the approach advances the possibility of using non-invasive methods to monitor critical biogeochemical system stages and transitions remotely and over field relevant scales (e.g., from square meters to several hectares).

Description: In recent years, a number of numerical modelling studies of transient sea-level rise (SLR) and seawater intrusion (SWI) in flux-controlled systems have reported an overshoot phenomenon, whereby the freshwater-saltwater interface temporarily extends further inland than the eventual steady-state position. In this study, we have carried out physical sand tank modelling of SLR-SWI in a flux-controlled unconfined aquifer setting to test if SWI overshoot is a measurable physical process. Photographs of the physical SLR experiments show, for the first time, that an overshoot occurs under controlled laboratory conditions. A sea-level drop (SLD) experiment was also carried out, and overshoot was again observed, whereby the interface was temporarily closer to the coast than the eventual steady-state position. This shows that an overshoot can occur for the case of a retreating interface. Numerical modelling corroborated the physical SLR and SLD experiments. The magnitude of the overshoot for SLR and SLD in the physical experiments was 24% of the change in steady-state interface position, albeit the laboratory setting is designed to maximise overshoot extent by adopting high groundwater flow gradients and large and rapid sea-level changes. While the likelihood of overshoot at the field scale appears to be low, this work has shown that it can be observed under controlled laboratory conditions.

Description: A new analytical solution of the flow equation has been developed to estimate the time to reach a near-equilibrium state in mixed aquifers, i.e. having unconfined and confined portions, following a large hydraulic perturbation. Near-equilibrium is defined as the time for an initial aquifer perturbation to dissipate by an average 95% across the aquifer.The new solution has been obtained by solving the flow system of a simplified conceptual model of a mixed aquifer using Laplace transforms. The conceptual model is based on two assumptions: 1) the groundwater flow can be reduced to a horizontal 1D problem; and 2) the transmissivity, a function of the saturated thickness, is assumed constant on the unconfined portion. This new solution depends on the storativity of the unconfined portion, the lengths of the unconfined and confined portions and the transmissivity, assumed to be constant and equal in both portions of the mixed aquifer. This solution was then tested and validated against a numerical flow model, where the variations of the saturated thickness and therefore variations of the transmissivity were either ignored, or properly modeled. The agreement between the results from the new solution and those from the numerical model is good, validating the use of this new solution to estimate the time to reach near-equilibrium in mixed aquifers. This solution for mixed aquifers, as well as the solutions for a fully confined or fully unconfined aquifer, have been used to estimate the time to reach near-equilibrium in thirteen large aquifers in the world. For those different aquifers, the time to reach near-equilibrium ranges between 0.7 ky to 2.4x10 7 ky. These results suggest that the present hydraulic heads in these aquifers are typically a mixture of responses induced from current and past hydrologic conditions and thus climate conditions. For some aquifers, the modern hydraulic heads may in fact depend upon hydrologic conditions resulting from several past climate cycles.

Description: The impact of contact angle on 2D spatial and temporal water content distribution during infiltration and drainage was experimentally studied. The 0.3-0.5 mm fraction of a quartz dune sand was treated and turned sub-critically repellent (contact angle of 33 0 , 48 0 , 56 0 , and 75 0 for S33, S48, S56, and S75, respectively). The media were packed uniformly in transparent flow chambers and water was supplied to the surface as a point source at different rates (1 to 20 ml/min). A sequence of grey-value images was taken by CCD camera during infiltration and subsequent drainage; grey values were converted to volumetric water content by water volume balance. Narrow and long plumes with water accumulation behind the downward moving wetting front (tip) and negative water gradient above it (tail) developed in the S56 and S75 media during infiltration at lower water application rates. The plumes became bulbous with spatially uniform water content distribution as water application rates increased. All plumes in these media propagated downward at a constant rate during infiltration and were frozen during drainage. In contrast, regular plume shapes were observed in the S33 and S48 media at all flow rates, and drainage profiles were non-monotonic with a transition plane at the depth that water reached during infiltration. Given that the studied media have similar pore-size distributions, the conclusion is that imbibition hindered by the non-zero contact angle induced pressure buildup at the wetting front (dynamic water entry value) that controlled the plume shape and internal water-content distribution during infiltration and drainage.

Description: Estimation of design quantiles of hydro-meteorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on Index-flood approach and L -moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach in predicting quantiles for ungauged sites is demonstrated through Monte-Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the proposed approach outperforms methods based on index-flood approach.

Description: Prediction of microbial surface water contamination is a formidable task because of the inherent randomness of environmental processes driving microbial fate and transport. In this article we develop a theoretical framework of a fully stochastic model of microbial transport in watersheds, and apply the theory to a simple flow network to demonstrate its use. The framework bridges the gap between microscopic behavior of individual microorganisms and macroscopic ensemble dynamics. This scaling is accomplished within a single mathematical framework, where each microorganism behaves according to a continuous-time discrete-space Markov process, and the Markov behavior of individual microbes gives rise to a non-homogeneous Poisson random field that describes microbial population dynamics. Mean value functions are derived, and the spatial and temporal distribution of water contamination risk is computed in a straightforward manner.

Description: The anomalously snowy winter season of 2010/11 in the Sierra Nevada is analyzed in terms of snow water equivalent (SWE) anomalies and the role of atmospheric rivers (ARs)―narrow channels of enhanced meridional water vapor transport between the tropics and extratropics. Mean April 1 SWE was 0.44 m (56%) above normal averaged over 100 snow sensors. AR occurrence was anomalously high during the period, with 20 AR dates during the season and 14 in the month of December 2010, compared to the mean occurrence of 9 dates per season. Fifteen out of the 20 AR dates were associated with the negative phases of the Arctic Oscillation (AO) and the Pacific-North American (PNA) teleconnection pattern. Analysis of all winter ARs in California during water years 1998–2011 indicates more ARs occur during the negative phase of AO and PNA, with the increase between positive and negative phases being ˜90% for AO, and ˜50% for PNA. The circulation pattern associated with concurrent negative phases of AO and PNA, characterized by cyclonic anomalies centered northwest of California, provides a favorable dynamical condition for ARs. The analysis suggests that the massive Sierra Nevada snowpack during the 2010/11 winter season is primarily related to anomalously high frequency of ARs favored by the joint phasing of −AO and −PNA, and that a secondary contribution is from increased snow accumulation during these ARs favored by colder air temperatures associated with −AO, −PNA and La Niña.

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

Description: There are significant uncertainties inherent in precipitation forecasts and these uncertainties can be communicated to users via large ensembles that are generated using stochastic models of forecast error. The Met Office and the Australian Bureau of Meteorology developed the Short Term Ensemble Prediction System (STEPS) which has been operational for a number of years. The initial formulation of Bowler et al. [2006] has been revised and extended to improve the performance over large domains, to include radar observation errors, and to facilitate the combination of forecasts from a number of sources. This paper reviews the formulation of STEPS, discusses those aspects of the formulation that have proved most problematic and presents some solutions. The performance of STEPS nowcasts is evaluated using a combination of case study examples and statistical verification from the UK. Routine forecast verification demonstrates that STEPS is capable of producing near optimal blends of a rainfall nowcast and high resolution NWP forecast. It also shows that the spread of STEPS nowcast ensembles are a good predictor of the error in the control member (unperturbed) nowcast.

Description: In this study seasonal and interannual variability of the main atmospheric moisture sources over eight regions in the Mediterranean basin were investigated along a twenty one year period. The Lagrangian dispersion model FLEXPART, developed by Stohl and James [2004, 2005], was applied to identify the contribution of humidity to the moisture budget of each region. This methodology is used to compute budgets of evaporation minus precipitation (E-P) by calculating changes in the specific humidity along backward trajectories, for the preceding ten-day periods. The results show clear seasonal differences in the moisture sources between wet and dry seasons. The Western Mediterranean Sea is the dominant moisture source for almost all the regions in the Mediterranean basin during the wet season, while the local net evaporation dominates during the dry season. The highest interannual variability is found in contributions to the Iberian Peninsula, Italy and the Eastern Mediterranean. It is seen that the role of teleconnections is more limited than for the precipitation recorded in the region.

Description: We present a new hydrologic model based on the frequency distribution of hillslope landscape elements along the stream network as a basis for simulating landscape-scale hydrologic connectivity and catchment runoff. Hydrologic connectivity describes shallow water table continuity between upland and stream elements of the catchment and is important for the movement of water and solutes to streams. This concept has gained traction in physical hydrology but has received less attention in rainfall-runoff modeling. Our model is based on the empirical studies of Jencso et al. [2009; 2010], who found a strong correlation between the duration of shallow groundwater connectivity across hillslope, riparian, and stream zones and upslope accumulated area. We explored the relationship between catchment form and function by testing the extent to which streamflow generation could be predicted by a model based on the topographic form (distribution of landscape elements) of the catchment. We applied the model to the Stringer Creek catchment of the Tenderfoot Creek Experimental Forest, located in Montana, USA. Detailed field observations collected by Jencso et al. [2009] were used to inform the underpinnings of the model and to corroborate internal consistency of the model simulations. The model demonstrated good agreement between the observed and predicted streamflow and connectivity duration curves. The ability of this model to simulate internal dynamics without conditioning the parameters on these data suggests that it has the potential to be more confidently extrapolated to other shallow, topographically driven catchments than hydrologic models that fail to consistently reproduce internal variables.

Description: Knowledge of hydrological model complexity can aid selection of an optimal prediction model out of a set of available models. Optimal model selection is formalized as selection of the least complex model out of a subset of models that have lower empirical risk. This may be considered equivalent to minimizing an upper bound on prediction error, defined here as the mathematical expectation of empirical risk. In this paper we derive an upper bound that is free from assumptions on data and underlying process distribution as well as on independence of model predictions over time. We demonstrate that hydrological model complexity, as defined in the presented theoretical framework, plays an important role in determining the upper bound. The model complexity also acts as a stabilizer to a hydrological model selection problem if it is deemed ill-posed. We provide an algorithm for computing complexity of any arbitrary hydrological model. We also demonstrate that hydrological model complexity has a geometric interpretation as the size of model output space. The presented theory is applied to quantify complexities of two hydrological model structures: SAC-SMA and SIXPAR. It detects that SAC-SMA is indeed more complex than SIXPAR. We also develop an algorithm to estimate the upper bound on prediction error, which is applied on 5 different rainfall-runoff model structures that vary in complexity. We show that a model selection problem is stabilized by regularizing it with model complexity. Complexity regularized model selection yields models that are robust in predicting future but yet unseen data.

Description: The temporal dynamics and spatial distribution of the concentrations of dissolved gases (He, Ar, Kr, N 2 , O 2 and CO 2 ) in an infiltrating groundwater system fed by the peri-alpine River Thur (Switzerland) were analysed before, during and after a single, well-defined flood event. The analysis was based on measurements taken in five different groundwater observation wells that were located approximately 10 m apart and tapped the same groundwater body, but were situated in three different riparian zones. The input of O 2 into the groundwater as a result of the formation of excess air was found to be of the same order of magnitude as that resulting from the advection of river water, although the amount of excess air formed and the amount of O 2 delivered varied significantly among the riparian zones. The results suggest that the input of O 2 into groundwater as a result of excess air formation is controlled not only by the hydraulic conditions prevailing in the river and the groundwater, but also by the thickness of the confining bed at the top of the aquifer. The sandy gravel aquifer itself is too coarse to trap a significant amount of air during the water level rise. The clay layer confining the aquifer, however, acts as a barrier hindering the escape of air from the subsoil to the surface, and hence is likely to be a key factor controlling the trapping and dissolution of air in groundwater.

Description: Estimation of parameter values in hydrological models has gradually moved from subjective, trial-and-error methods into objective estimation methods. Translation of nature's complexity to bit operations is an uncertain process as a result of data errors, epistemic gaps, computational deficiencies, and other limitations, and relies on calibration to fit model output to observed data. The robustness of the calibrated parameter values to these types of uncertainties is therefore an important concern. In this study, we investigated how the hydrological robustness of the model-parameter values varied within the geometric structure of the behavioral (well-performing) parameter space with a depth function based on α shapes and an in-depth posterior performance analysis of the simulations in relation to the observed discharge uncertainty. The α shape depth is a non-convex measure that may provide an accurate and tight delimitation of the geometric structure of the behavioral space for both uni- and multimodal parameter-value distributions. WASMOD, a parsimonious rainfall-runoff model, was applied to six Honduran and one UK catchment, with differing data quality and hydrological characteristics. Model evaluation was done with two performance measures, the Nash-Sutcliffe efficiency and one based on flow-duration curves. Deep parameter vectors were in general found to be more hydrologically robust than shallow ones in the analyses we performed; model-performance values increased with depth, deviations to the observed data for the high-flow aspects of the hydrograph generally decreased with increasing depth, deep parameter vectors generally transferred in time with maintained high performance values, and the model had a low sensitivity to small changes in the parameter values. The tight delimitation of the behavioral space provided by the α shapes depth function showed a potential to improve the efficiency of calibration techniques that require further exploration. For computational reasons only a three-parameter model could be used, which limited the applicability of this depth measure and the conclusions drawn in this paper, especially concerning hydrological robustness at low flows.

Description: The cosmic-ray neutron probe measures soil moisture over tens of hectares, thus averaging spatially variable soil moisture fields. A previous paper described how variable soil moisture profiles affect the integrated cosmic-ray neutron signal from which depth-average soil moisture is computed. Here, we investigate the effect of horizontal heterogeneity on the relationship between neutron counts and average soil moisture. Observations from a distributed sensor network at a site in southern Arizona indicate that the horizontal component of the total variance of the soil moisture field is less variably in time than the vertical component. Using results from neutron particle transport simulations we show that 1-D binary distributions of soil moisture may affect both the mean and variance of neutron counts of a cosmic-ray neutron detector placed arbitrarily in a soil moisture field, potentially giving rise to an underestimate of the footprint average soil moisture. Similar simulations that used 1 and 2-D Gaussian soil moisture fields indicate consistent mean and variances of a randomly placed detector if the correlation length scales are short (〈˜30 m) and/or the soil moisture field variance is small (〈0.032 m 6 m -6 ). Taken together, these soil moisture observations and neutron transport simulations show that horizontal heterogeneity likely has a small effect on the relationship between mean neutron counts and average soil moisture for soils under natural conditions.

Description: Widespread disturbance within forested catchments typically increases runoff. However, following widespread fire in 1939 throughout south-east Australia Kuczera [1987] reported persistent reductions in runoff that were attributed to increased evapotranspiration from regenerating ‘ash’ forests. Kuczera projected ongoing reductions of water yield for ~150 years. In 2003 widespread fire in the headwaters of the Murray-Darling Basin (MDB) again stimulated extensive regeneration of ash forests, raising the prospect of subsequent water yield reductions. To understand the potential impact of the 2003 bushfires we re-evaluated yield reductions from three of the catchments originally studied by Kuczera using the same calibration period. We also used an expanded pre-fire calibration period (1908-1938) based on data not originally available to Kuczera. The trend of post-fire water yield that we observed in 1939-affected catchments is qualitatively consistent with Kuczera's projections, but the quantitative details were, as expected, sensitive to the pre-fire calibration period used. We then used a simplified method to examine a further five ash-dominated catchments affected by the 2003 fires. We report relative reductions in mean annual stream flow in all five catchments and a statistically significant (α=0.05) post-fire reduction in one of five catchments. Post-fire yield reductions during the austral summer (October-April) were greater in relative magnitude in all five catchments and were statistically significant (α=0.05) in three of five catchments. We conclude that a post-bushfire Kuczera-type response may be widespread in regenerating ash forests. On that basis we anticipate post-fire yield reductions in ash forests elsewhere and conclude that further reductions in stream flow are likely in the MDB for at least another decade.

Description: Drought triggers are patterns in hydro-climatic variables that herald upcoming droughts and form the basis for mitigation plans. This study develops a new method for identification of triggers for hydrologic droughts by examining the association between the various hydro-climatic variables and streamflows. Since numerous variables influence streamflows to varying degrees, Principal Component Analysis (PCA) is utilized for dimensionality reduction in predictor hydro-climatic variables. The joint dependence between the first two principal components, that explain over 98% of the variability in the predictor set, and streamflows is computed by a scale-free measure of association using asymmetric Archimedean copulas over two study watersheds in Indiana, USA, with unregulated streamflows. The M6 copula model is found to be suitable for the data and is utilized to find expected values and ranges of predictor hydro-climatic variables for different streamflow quantiles. This information is utilized to develop drought triggers for one-month lead time over the study areas. For the two study watersheds, soil moisture, precipitation and runoff are found to provide the fidelity to resolve amongst different drought classes. Combining the strengths of PCA for dimensionality reduction and copulas for building joint dependence allows the development of hydrologic drought triggers in an efficient manner.

Description: We present a unified asymptotic theory of rainfall extremes including annual maxima, excesses above high thresholds, and intensity-duration-frequency (IDF) curves that builds on previous findings and derive new non-asymptotic results. The analysis is based on stationary multifractal representations of rainfall and produces extensions of the familiar results from extreme value (EV) and extreme excess (EE) theories. The latter results apply to the T -yr maximum as and the excess above z as . By exploiting the scaling relationship among the distributions of rainfall intensity for different averaging durations d , the multifractal asymptotics include, in addition, results in the small-scale limits and with α 〉 0. In all cases the maximum distributions are of the generalized extreme value (GEV) type, but the index k depends on the limit considered. Multifractal models produce also asymptotic scaling results for the IDF curves. For the non-asymptotic case ( d and T finite), we obtain accurate approximations of the IDF curves and derive a semi-theoretical formula for the index k of the GEV model that best approximates the distribution of the annual maximum over a finite range of return-period intensities. The non-asymptotic analysis explains several observed deviations of rainfall extremes from the asymptotic predictions, such as the tendency of k to decrease as the averaging duration d increases and the tendency of the IDF curves to converge as d or the return period T increase.

Description: Remaining oil saturation established by waterflooding was measured in Indiana limestone in its original, water-wet state and under mixed-wet conditions established by adding organic acid to the oil phase. The porous plate technique was used to establish initial oil saturations ranging from S nwi = 0.23 to 0.93 under capillary-dominated conditions. For water-wet conditions, the residual oil saturation increased linearly with its initial saturation. In contrast, the remaining oil saturation under mixed-wet conditions, S nw , displayed three distinct regimes. First, S nw increased with its initial saturation up to S nwi = 0.58. Next, S nw decreased from S nwi = 0.58 to 0.76. Finally, S nw increased again as S nwi approached one. The non-monotonic dependence of S nw on S nwi at S nwi 〉 0.5 is well described by a concave-up quadratic function, and may be a salient feature of mixed-wet rocks.

Description: We present a general phenomenological formalism for the modeling of hydraulic head behaviour in naturally fractured aquifers. A non local in time version of the double porosity model is developed for Euclidean and fractal reservoirs. In the fractal case, time non-locality allows to find the geometric and topological factors responsible for subdiffusive behaviour in such heterogeneous environments. Opposite to other fractal models presented in the literature Chang and Yortsos [1990], our model include dead-ends-backbone interactions instead of matrix-fracture interactions with clear and well defined scaling exponents, thus giving a better characterization of the reservoir after such parameters are estimated. Applications to field tests are discussed. In particular, a distinctive short time head behaviour during well tests is found.

Description: The publicly available global discharge database is limited in spatial and temporal coverage. Although regional exceptions exist, the population of the database has declined over the past several years. As discharge is one of the most important parameters for modeling hydrological interactions, alternative measuring techniques must be sought. In the recent past, satellite altimetry has been investigated as an alternative for monitoring inland water level. In the present study, altimetry footprints in the vicinity of river gauging stations for the Amazon, Amur, Brahmaputra, Danube, Don, Mekong, Niger, Ob and Vistula rivers are analyzed for a functional relationship between the water level measurements from altimetry and discharge from the gauging stations. Such a functional relationship is conventionally established via a rating curve computed using simultaneous data. This study proposes a statistical approach based on quantile functions to infer this functional relation without the need for having synchronous datasets. The statistical approach provides the opportunity of extracting discharge values from altimetry data for rivers like the Mekong, Brahmaputra, Don and Vistula for which the discharge measurements at the selected gauges were made before the age of satellites. The algorithm is then validated over those rivers which do have discharge measurements available within periods of altimetry. Our validation shows that our algorithm is in the same quality range as the conventional approach. We are thus able to salvage pre-satellite altimetry discharge data and turn them into active use for the satellite altimetry time frame.

Description: While satellite based remote-sensing has provided hydrologists with valuable new datasets, integration of such datasets in operational modeling systems is usually not straightforward due to spatial or temporal resolution issues or because remote sensing does not directly measure the hydrological quantities of interest. This is the case for satellite based radar-altimetry. River level variations can be tracked using radar altimetry at a temporal resolution between 10 and 35 days, depending on the satellite, but hydrologists are typically interested in river flows rather than levels and require predictions at daily or even sub-daily temporal resolutions. One way to exploit satellite radar altimetry is therefore to combine the data with hydrological models in a data assimilation framework. In this study, radar altimetry data from 6 ENVISAT virtual stations were assimilated to a routing model of the main reach of the Brahmaputra River driven by the outputs of a calibrated rainfall runoff model. The Extended Kalman Filter was used to update the routed water volumes for the years 2008 to 2010. Model performance was improved with the Nash-Sutcliffe model efficiency for daily discharge increasing from 0.78 to 0.84. The method uses very little in situ data and is easily implemented as an add-on to hydrological models and it therefore has the potential for large scale application to improve hydrological predictions in many river basins.

Description: Management of water temperatures in the Columbia River Basin (Washington) is critical because water projects have substantially altered the habitat of Endangered Species Act (ESA) listed species, such as salmon, throughout the basin. This is most important in tributaries to the Columbia, such as the Methow River, where the spawning and rearing life stages of these cold water fishes occurs. Climate change projections generally predict increasing air temperatures across the western United States, with less confidence regarding shifts in precipitation. As air temperatures rise, we anticipate a corresponding increase in water temperatures, which may alter the timing and availability of habitat for fish reproduction and growth. To assess the impact of future climate change in the Methow River, we couple historical climate and future climate projections with a statistical modeling framework to predict daily mean stream temperatures. A K -nearest neighbor algorithm is also employed to: (i) adjust the climate projections for biases compared to the observed record and (ii) provide a reference for performing spatiotemporal disaggregation in future hydraulic modeling of stream habitat. The statistical models indicate the primary drivers of stream temperature are maximum and minimum air temperature and streamflow and show reasonable skill in predictability. When compared to the historical reference time period of 1916-2006, we conclude that increases in stream temperature are expected to occur at each subsequent time horizon representative of the year 2020, 2040, and 2080, with an increase of 0.8 ± 1.9 °C by the year 2080.

Description: Thermal remote sensing methods for mapping evapotranspiration (ET) exploit the physical interconnection that exists between land-surface temperature (LST) and evaporative cooling, employing principles of surface energy balance (SEB). Unfortunately, while many applications in water resource management require ET information at daily and field spatial scales, current satellite-based thermal sensors are characterized by either low spatial resolution and high repeatability or by moderate/high spatial resolution and low frequency. Here we introduce a novel approach to ET mapping that fuses characteristics of both classes of sensors to provide optimal spatiotemporal coverage. In this approach, coarse resolution daily ET maps generated with a SEB model using geostationary satellite data are spatially disaggregated using daily MODIS (MODerate resolution Imaging Spectroradiometer) 1-km and bi-weekly Landsat LST imagery sharpened to 30-m. These ET fields are then fused to obtain daily ET maps at 30-m spatial resolution. The accuracy of the fused Landsat-MODIS daily ET maps was evaluated over Iowa using observations collected at 8 flux towers sited in corn and soybean fields during the Soil Moisture Experiment of 2002 (SMEX02), as well as in comparison with a Landsat-only retrieval. A significant improvement in ET accuracy (reducing errors from 0.75 to 0.58 mm/d on average) was obtained by fusing MODIS and Landsat data in comparison with the Landsat-only case, with most notable improvements when a rainfall event occurred between two successive Landsat acquisitions. The improvements are further evident at the seasonal timescale, where a 3% error is obtained using Landsat-MODIS fusion vs. a 9% Landsat-only systematic underestimation.

Description: This study reports on two strategies for accelerating posterior inference of a highly parameterized and CPU-demanding groundwater flow model. Our method builds on previous stochastic collocation approaches [e.g., Marzouk and Xiu , 2009; Marzouk and Najm , 2009] and uses generalized polynomial chaos (gPC) theory to emulate the output of a large-scale groundwater flow model. The resulting surrogate model is CPU-efficient and serves to explore the posterior distribution at a much lower computational cost using two-stage MCMC simulation. The case study reported in this paper demonstrates a 2-5 times speed up in sampling efficiency.

Description: An earlier infiltration equation relied on curve fitting of infiltration data for the determination of one of the parameters, which limits its usefulness in practice. This handicap is removed here and the parameter is now evaluated by linking it directly to soil-water properties. The new predictions of infiltration using this evaluation are quite accurate. Positions and shapes of soil-water profiles are also examined in detail and found to be predicted analytically with great precision.

Description: Fibre-optic Distributed Temperature Sensing (FO-DTS) has been frequently applied for analysing thermal patterns, including the identification of groundwater-surface water exchange fluxes across aquifer-river interfaces. However, the impacts of a) seasonal variability in signal strength (given by the difference between groundwater and surface water temperatures) and b) monitoring modes on the accuracy of FO-DTS surveys has not yet been determined. This study uses a well investigated field site as model system for quantifying the accuracy and uncertainty of FO-DTS surveys in dependency of seasonal signal variation and monitoring mode. The analysis of the relationship between seasonal variability in signal strength and diurnal oscillations in end-member temperatures at the study site revealed that winter conditions, with substantially lower diurnal temperature oscillations provide the highest temporal stability in signal strength. The choice of monitoring mode proved to have significant impact on the accuracy of FO-DTS surveys. The proposed two-way single-ended averaging of FO-DTS surveys had significant advantages compared to single-ended or double-ended surveys, with a higher accuracy in signal detection in particular for small-scale temperature variations. Since FO-DTS surveys in two-way single-ended averaging mode were better suited for detecting the full complexity of spatial temperature patterns for the investigated aquifer-river interface, we recommend its wider application in similarly complex systems with small-scale thermal patterns.

Description: The paper presents a semianalytical method to solve the multispecies reactive solute-transport equation coupled with a sequential first-order reaction network under spatially or temporally varying flow velocities and dispersion coefficients. This method employs the generalized integral transform technique (GITT) and general linear transformation method by Clement [2001] to transform the set of coupled multispecies reactive transport equations into a set of independent uncoupled equations and to solve these independent equations for spatially or temporally varying flow velocities and dispersion coefficients, as well for temporally varying inlet concentration. The proposed semianalytical solution is compared against previously published analytical solutions of Srinivasan and Clement [2008b] and van Genuchten [1985]. An example is used to show application of the solution to a hypothetical multilayered medium. The solution of proposed approach is compared also with a numerical solution using the 2DFATMIC. Three scenarios are illustrated to show the capabilities of the proposed semianalytical method to deal with aquifer heterogeneity and transient situations. We also show a practical implementation of the solution to an actual field, single-well push-pull test (PPT) example designed to obtain the concentration distribution of reactants consumed and products formed at the end of the injection phase.

Description: The acquisition of reliable datasets representative of hydrological regimes and their variations is a critical concern for water resource assessment. For the subsurface, traditional approaches based on probe measurements, core analysis and well data can be laborious, expensive, and highly intrusive, while only yielding sparse data sets. For this study, an innovative field survey, merging relative microgravimetry, magnetic resonance soundings and hydrological measurements, was conducted to evaluate both surface and subsurface water storage variations in a semi-arid Sahelian area. The instrumental setup was implemented in the lower part of a typical hillslope feeding to a temporary pond. Weekly measurements were carried out using relative spring gravimeters during three months of the rainy season in 2009 over a 350 × 500 m 2 network of twelve microgravity stations. Gravity variations of small to medium amplitude (≤ 220 nm s 2 ) were measured with accuracies better than 50 nm s -2 , revealing significant variations of the water storage at small time (from one week up to three months) and space (from a couple of meters up to a few hundred meters) scales. Consistent spatial organization of the water storage variations were detected, suggesting high infiltration at the outlet of a small gully. The comparison with hydrological measurements and magnetic resonance soundings involved that most of the microgravity variations came from the heterogeneity in the vadose zone. The results highlights the potential of time lapse microgravity surveys for detecting intraseasonal water storage variations and providing rich space-time datasets for process investigation or hydrological model calibration/evaluation.

Description: The instantaneous turbulent flow fields over a smooth bed and a bed containing large-scale roughness elements are characterized by the presence of elongated low and high streamwise momentum regions, or streaks. If the bed contains large-scale roughness elements (e.g., dunes), the size of the streaks increases and is of the order of the size of these elements and the flow depth. The present large eddy simulation (LES) study focuses on the case of developing flow within wide channels containing at the bottom a long array of spanwise-oriented sinusoidal 2D dunes (2a/h=0.1, λ/h=1, λ is the wavelength, 2a is the dune height, h is the mean flow depth) and, respectively, an array of 2D asymmetric dunes (2a/h=0.25, λ/h=3.75) of closer shape to the ones observed in natural streams. For the case of an incoming steady flow, the instantaneous flow fields, in the region where the flow transitions toward a fully-developed turbulent flow regime, contain arrays of highly-organized hairpin vortices whose dimensions are larger than the dune height. LES shows that for relatively shallow channels (e.g., channels with 2a/h=0.25), the large-scale hairpins and the streaks penetrate regularly up to the free surface, thus affecting mass transport and mixing over the whole water column. The paper explains the mechanism for the formation of these arrays of hairpin vortices and discusses changes between a case with asymmetric dunes that are characterized by a large value of λ/2a (=15) and a long upslope face, and a case with symmetric dunes for which λ/2a=10, the upslope face is relatively short and the rate of change of the bed curvature around the dune's crest is relatively small. The study discusses the main mechanisms through which large-scale hairpin form and how these mechanisms change between two dune geometries (sinusoidal vs. asymmetric dunes). We also show that hairpin eddies play the primary role in the formation of the streaks over the region containing dunes and we characterize the average dimensions of these streaks. The presence of resolved turbulence in the incoming flow reduces the streamwise distance needed for the streaks to develop over region containing dunes, but does not affect qualitatively the transition process toward the fully-developed flow regime, nor the spacing of the streaks in the fully-developed flow region.

Description: Parlange and Brutsaert [1987] derived a modified Boussinesq equation to account for the capillary effect on watertable dynamics in unconfined aquifers. Barry et al . [1996] solved this equation subject to a periodic boundary condition. Their solution shows significant influence of capillarity on watertable fluctuations, which evolve to finite-amplitude standing waves at the high frequency limit. Here, we propose a new governing equation for the watertable, which considers both horizontal and vertical flows in an unsaturated zone of finite thickness. An approximate analytical solution for periodic watertable fluctuations based on the new equation was derived. In agreement with previous results, the analytical solution shows that the unsaturated zone's storage capacity permits watertable fluctuations to propagate more readily than predicted by the Boussinesq equation. Furthermore, the new solution reveals a capping effect of the unsaturated zone on both the amplitude and phase of the watertable fluctuations as well as the watertable overheight. Due to the finite thickness of the unsaturated zone, the capillary effect on watertable fluctuations is modified mainly with reduced amplitude damping and phase shift.

Description: Impacts of rising sea level on the hydraulic balance between aquifers and the ocean threaten fresh water resources and aquatic ecosystems along many world coastlines. Understanding the vulnerability of groundwater systems to these changes and the primary factors that determine the magnitude of system response is critical to developing effective management and adaptation plans in coastal zones. We assessed the vulnerability of two types of groundwater systems, recharge-limited and topography-limited, to changes caused by sea-level rise over a range of hydrogeologic settings. Vulnerability in this context is defined by the rate and magnitude of salinization of coastal aquifers and changes in groundwater flow to the sea. Two-dimensional variable-density groundwater flow and salt transport simulations indicate that the response of recharge-limited systems is largely minimal, whereas topography-limited systems are vulnerable for various combinations of permeability, vertical anisotropy in permeability, and recharge. World coastlines were classified according to system type as a vulnerability indicator. Results indicate that ~70% of world coastlines may be topography-limited, though variability in hydrogeologic conditions strongly affects classification. Future recharge and sea-level rise scenarios have much less influence on the proportion of vulnerable coastlines than differences in permeability, distance to a hydraulic divide, and recharge, indicating that hydrogeologic properties and setting are more important factors to consider in determining vulnerability than uncertainties in the magnitude of sea-level rise and hydrologic shifts associated with future climate change.

Description: ABSTRACT Given the range of future uncertainty, there is increasing interest in developing and evaluating water management strategies that are robust to an uncertain future. As part of a process termed “decision scaling”, a climate response function was developed to isolate the impact of climate change on a water system in terms of hazards identified by stakeholders. The climate response function was then used to evaluate system performance over a wide range of climate conditions and to define robustness indicators. The robustness indicators, which measure system performance as a function of climate state, are conditioned on explicit assumptions about climate variable probability distributions. To illustrate this process, it is applied to the Upper Great Lakes to evaluate system robustness related to water management decisions and assess the impact of climate probability assumptions. The robustness indicators were used to identify decisions that outperformed other courses of action regardless of assumptions of future climate probabilities.

Description: Recent studies suggest that there is a strong linkage between the moisture uptake over the equatorial area of the Somali Low Level Jet (SLLJ) and the rainfall variability over most of continental India. Additionally, the Madden-Julian Oscillation (MJO) strongly modulates the intraseasonal variability of the Indian summer monsoon rainfall, since the northward propagation of the boreal summer MJO is closely associated with the active and break phases of monsoon rainfall. But a question remains open: is there a relationship between the moisture transported by the SLLJ and the MJO evolution?. In this paper a lagrangian approach is used to track the evaporation minus precipitation (E - P) evolution along trajectories of particles initially situated over the equatorial region of SLLJ. The impact of the MJO on the water budget transport of the SLLJ is examined by making composites of the obtained (E - P) fields for the different MJO phases. The spatial structures of the boreal summer intraseasonal oscillation are revealed in our results, which strongly suggest that the main responsible for the rainfall variability associated to the MJO in these regions are the changes in the moisture advected by the SLLJ. In order to assess the MJO - SLLJ interaction, an analysis of the total-column mass and the total-column specific humidity transported by the SLLJ during the MJO life cycle is performed. While a systematic difference between air mass advected to India during active and break phases of MJO is not detected, changes in the moisture of particles are found, with wet (dry) anomalies over enhanced (suppressed) convection region. This result implicitly leads to assume air-sea interaction processes.

Description: Semiarid sedimentary plains occupied by dry forest ecosystems often display low groundwater recharge rates and accumulation of salts in the soil profile. The transformation of these natural systems to rain-fed agriculture has led to raising water tables and a slow, but steady, process of groundwater and soil salinization in vast areas of Australia. In the semiarid plains of Chaco (central South America), unprecedented deforestation rates are taken place. Based on deep soil sampling (0-6 m) in seven paired stands under natural dry forest, rain-fed agriculture and pasture, with different age of clearance (〉30 years, 20 and 3 years) in Salta, Argentina, we provide evidence of groundwater recharge increase and onset of salt mobilization in areas where forests were replaced by annual croplands. Soils with higher water and lower chloride content are evidence of deep percolation and salt leaching. In Salta, stands subject to 30 years of rain fed cultivation had profiles with 30 to 46% higher moisture content and 94% lower chloride stocks compared to dry forest (0.05 ± 0.04 kg/m 2 vs. 0.77 ± 0.4 kg/m 2 ). Estimates of groundwater recharge based on the displacement of chloride peaks suggested values of 27to 87mm/yr for agricultural soybean stands, and 10.4 mm/yr for pastures. While hydrological shifts in the regional groundwater system are poorly monitored and understood, our findings show that it is potentially sensitive to land use changes and to salinization processes.

Description: In regulated river systems, such as the River Murray in Australia, the efficient use of water to preserve and restore biota in the river, wetlands and floodplains is of concern for water managers. Available management options include the timing of river flow releases and operation of wetland flow control structures. However, the optimal scheduling of these environmental flow management alternatives is a difficult task, since there are generally multiple wetlands and floodplains with a range of species, as well as a large number of management options that need to be considered. Consequently, this problem is a multi-objective optimization problem aimed at maximizing ecological benefit while minimizing water allocations within the infrastructure constraints of the system under consideration. This paper presents a multi-objective optimization framework, which is based on a multi-objective ant colony optimization approach, for developing optimal trade-offs between water allocation and ecological benefit. The framework is applied to a reach of the River Murray in South Australia. Two studies are formulated to assess the impact of (i) upstream system flow constraints and (ii) additional regulators on this trade-off. The results indicate that unless the system flow constraints are relaxed, there is limited additional ecological benefit as allocation increases. Furthermore the use of regulators can increase ecological benefits while using less water. The results illustrate the utility of the framework since the impact of flow control infrastructure on the trade-offs between water allocation and ecological benefit can be investigated, thereby providing valuable insight to managers.

Description: ABSTRACT A reactive transport modeling framework is presented that allows simultaneous assessment of groundwater flow, water quality evolution including δ 13 C, and 14 C activity or “age”. Through application of this framework, simulated 14 C activities can be directly compared with measured 14 C activities. This bypasses the need for interpretation of a 14 C age prior to flow simulation through factoring out processes other than radioactive decay, which typically involves simplifying assumptions regarding spatial and temporal variability in reactions, flow, and mixing. The utility of the approach is demonstrated for an aquifer system with spatially variable carbonate mineral distribution, multiple organic carbon sources, and transient boundary conditions for 14 C activity in the recharge water. In this case the simulated 14 C age was shown to be relatively insensitive to isotopic fractionation during DOC oxidation and variations in assumed DOC degradation behaviour. We demonstrate that the model allows quantitative testing of hypotheses regarding controls on groundwater age and water quality evolution for all three carbon isotopes. The approach also facilitates incorporation of multiple environmental tracers and combination with parameter optimization techniques. This article is protected by copyright. All rights reserved.

Description: Water scarcity is likely to increase in the coming years, making improvements in irrigation efficiency increasingly important. An emerging technology that promises to increase irrigation efficiency substantially is a wireless irrigation sensor network that uploads sensor data into irrigation management software, creating an integrated system that allows real-time monitoring and control of moisture status that has been shown in experimental settings to reduce irrigation costs, lower plant loss rates, shorten production times, decrease pesticide application, and increase yield, quality, and profit. We use an original survey to investigate likely initial acceptance, ceiling adoption rates, and profitability of this new sensor network technology in the nursery and greenhouse industry. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. Adoption rates for a base system and demand for expansion components are increasing in specialization in ornamental production: Growers earning greater shares of revenue from greenhouse and nursery operations are willing to pay more for a base system and are willing to purchase larger numbers of expansion components at any given price. We estimate that growers who are willing to purchase a sensor network expect investment in this technology to generate significant profit, consistent with findings from experimental studies. This article is protected by copyright. All rights reserved.

Description: This technical note presents a useful methodology for studying how the variance of hydraulic and/or reactive attributes of an aquifer are linked to the multi-scaled and hierarchical sedimentary architecture of the aquifer. A new recursive equation is derived which quantitatively describes how the variance is related to sedimentary facies defined at all scales across an entire stratal hierarchy. As compared to prior published equations that emphasize differences in means among facies populations within a hierarchical level, it emphasizes differences across levels. Because of the hierarchical relationships among the terms of the equation, we find it to be useful for conducting a holistic analysis of the relative contributions to the variance arising from all facies types defined across all scales. The methodology is demonstrated using appropriate field data, and is shown to be useful in defining parsimonious classification systems.

Description: ABSTRACT A primary concern for geologic carbon storage is the potential for leakage of stored carbon dioxide (CO 2 ) into the shallow subsurface where it could degrade the quality of groundwater and surface water. In order to predict and mitigate the potentially negative impacts of CO 2 leakage, it is important to understand the physical processes that CO 2 will undergo as it moves through naturally heterogeneous porous media formations. Previous studies have shown that heterogeneity can enhance the evolution of gas phase CO 2 in some cases, but the conditions under which this occurs have not yet been quantitatively defined, nor tested through laboratory experiments. This study quantitatively investigates the effects of geologic heterogeneity on the process of gas phase CO 2 evolution in shallow aquifers through an extensive set of experiments conducted in a column that was packed with layers of various test sands. Soil moisture sensors were utilized to observe the formation of gas phase near the porous media interfaces. Results indicate that the conditions under which heterogeneity controls gas phase evolution can be successfully predicted through analysis of simple parameters, including the dissolved CO 2 concentration in the flowing water, the distance between the heterogeneity and the leakage location, and some fundamental properties of the porous media. Results also show that interfaces where a less permeable material overlies a more permeable material affect gas phase evolution more significantly than interfaces with the opposite layering.

Description: Fluvial sediment loads are frequently calculated with rating curves fit to measured sediment transport rates. Rating curves are often treated as statistical representations in which the fitted parameters have little or no physical meaning. Such models, however, may produce large errors when extrapolation is needed, and they provide no insight into the sediment transport process. It is shown that log-linear least squares, the usual method for fitting rating curves, does not generally produce physically meaningful parameter values. In addition, it cannot accommodate data that include zero-transport samples. Alternative fitting methods based non-linear least squares and on maximum likelihood parameter estimation are described and evaluated. The maximum likelihood approach is shown to fit synthetic data better than linear or non-linear least squares, and to perform well with data that include zero-transport samples. In contrast, non-linear least squares methods produce large errors in the parameter estimates when zero-transport samples are present or when the variance structure of the data is incorrectly specified. Analyses with fractional bedload data from a mountain stream suggest that bedload transport rates are gamma distributed, that the arrivals of bedload particles in a sampler conform to a Poisson distribution, and that the variance of non-zero samples can be expressed as a power function of the mean. Preliminary physical interpretations of variations in the rating curve parameters fit to fractional bedload data with the maximum likelihood method are proposed, and their relation to some previous interpretations of rating curve parameters are briefly discussed. This article is protected by copyright. All rights reserved.

Description: We use dissolved silicon together with its “geochemical twin” germanium for the first time as a hydrologic tracer to study water delivery to the stream during storm events in the Rio Icacos watershed, Puerto Rico. Ge and Si were measured on base flow, stormflow, springwater, and soil water samples. Compositions of all of these waters appear to reflect varying contributions from three components, which we attribute to solutes released from bedrock weathering (groundwater), from short-term soil-water interaction (quick soil water), and longer-term soil-water interaction (matrix soil water). Base flow stream waters have high Si and moderate Ge (Ge/Si ratio ∼0.29 μmol/mol), consistent with a predominantly bedrock weathering source as indicated by their similarity with water sampled from springs emerging from the saprolite-bedrock boundary on a hillslope landslide scar. During storm events there is a shift toward more dilute compositions (but higher Ge/Si ratios) similar to those measured on water samples from temporary depression storage and overland flow (quick soil water). Geochemical mass balance shows that 80%–90% of the stream chemistry can be explained by mixing groundwater with this quick soil water composition, which we infer to reflect new water traveling as shallow throughflow. Stream water δ18O values decrease to more negative values typical of precipitation supporting rapid delivery of rainwater to the stream channel during stormflow. The third component, with a Ge-rich composition characteristic of soil matrix water sampled by tension lysimeters, is required to explain higher stream water Ge/Si ratios measured during hydrograph recession. We infer from this an additional, slower, and less dominant pathway for delivery of soil water to the stream channel.

Description: We present a predictive, multiscale modeling framework for chemotaxis in porous media. This model results from volume averaging the governing equations for bacterial transport at the microscale and is expressed in terms of effective medium coefficients that are predicted from the solution of the associated closure problems. As a result, the averaged chemotactic velocity is an explicit function of the attractant concentration field and diffusivity, rather than an empirical effective chemotactic sensitivity coefficient. The model was validated by comparing the transverse bacterial concentration profiles with experimental measurements for Escherichia coli HCB1 in a T-sensor. The averaged chemotactic velocity predicted by the model was found to be within the range of values reported in the literature. Reasonable agreement (approximately 10% mean absolute error) between theory and experiments was found for several flow rates. In order to assess the potential for decreasing the computational demands of the model, the macroscale domain was divided into subdomains for the coupling of bacterial transport to that of the attractant. Sensitivity analysis was performed regarding the number of subdomains chosen, and the results indicate that bacterial transport (as measured by concentration profiles) was not highly affected by this choice. Overall, these results suggest that the predictive, multiscale modeling framework is reliable for modeling chemotaxis in porous media when chemotactic transport is significant compared to convective transport.

Description: Water temperature determines the spatial distribution of fish species, including cold-water fish such as trout, and is driven by the balance of the heat flux across the water surface and the heat flux across the sediment surface. In this study, a modified equilibrium temperature model was developed for cold-water streams that includes the effect of groundwater inflow. The modified equilibrium temperature model gives estimates of daily average stream temperature based on climate conditions, riparian shading, stream width, and groundwater input rate and temperature. For a small tributary stream with relatively uniform riparian shading, the modified equilibrium temperature was found to be a good predictor of daily average stream temperature, with a root-mean-square errors (RMSE) of 1.2°C. The modified equilibrium temperature model also gave good estimates (1.4°C RMSE) of daily average stream temperature for a larger stream when riparian shading was averaged over sufficiently long distances. A sensitivity analysis using the modified equilibrium temperature model confirmed that water temperature in cold-water streams varies strongly with riparian shading, stream width, and both groundwater inflow rate and temperature. These groundwater parameters therefore need to be taken into account when climate change impacts on stream temperature are projected. The stream temperature model developed in this study is a useful tool to characterize temperature conditions in cold-water streams with different levels of riparian shading and groundwater inputs and to assess the impact of future land use and climate change on temperature in these streams.

Description: Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%–50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

Description: The focus in the search for more reliable predictions in ungauged basins (PUB) has generally been on reducing uncertainty in watershed models (mainly their parameters). More recently, however, we seem to remember that the ultimate objective is not to define the parameters of a specific model but to understand the watershed: What behavior do we expect the ungauged watershed to exhibit? And what behavior should not occur in a particular ungauged watershed? The answers to these questions actually provide additional information that can be assimilated in watershed models for uncertainty reduction in PUB. This extension to hydrologic modeling approaches provides a quantitative link between watershed modeling and statistical hydrology as well as process hydrology that has to be explored. We witness a convergence of approaches—Bayesian, set theoretic, and optimization based—toward utilizing this link. The result is an opportunity for the (quantitative) dialog between modelers, statistical hydrologists, and experimentalists. We close our discussion of this development by presenting new and exciting research questions that we now have to address.

Description: Concept development simulation with distributed, physics-based models provides a quantitative approach for investigating runoff generation processes across environmental conditions. Disparities within data sets employed to design and parameterize boundary value problems used in heuristic simulation inevitably introduce various levels of bias. The objective was to evaluate the impact of boundary value problem complexity on process representation for different runoff generation mechanisms. The comprehensive physics-based hydrologic response model InHM has been employed to generate base case simulations for four well-characterized catchments. The C3 and CB catchments are located within steep, forested environments dominated by subsurface stormflow; the TW and R5 catchments are located in gently sloping rangeland environments dominated by Dunne and Horton overland flows. Observational details are well captured within all four of the base case simulations, but the characterization of soil depth, permeability, rainfall intensity, and evapotranspiration differs for each. These differences are investigated through the conversion of each base case into a reduced case scenario, all sharing the same level of complexity. Evaluation of how individual boundary value problem characteristics impact simulated runoff generation processes is facilitated by quantitative analysis of integrated and distributed responses at high spatial and temporal resolution. Generally, the base case reduction causes moderate changes in discharge and runoff patterns, with the dominant process remaining unchanged. Moderate differences between the base and reduced cases highlight the importance of detailed field observations for parameterizing and evaluating physics-based models. Overall, similarities between the base and reduced cases indicate that the simpler boundary value problems may be useful for concept development simulation to investigate fundamental controls on the spectrum of runoff generation mechanisms.

Description: Analytical solutions are obtained for optimization formulations that minimize energy used for groundwater pumping. The formulations choose pumping rates at groundwater wells while insuring that total pumpage meets a specified demand. Such formulations might be appropriate for an urban water supply or a large−scale agricultural irrigation system. Solutions are found by applying stationarity conditions. The solutions produce simple and physically meaningful requirements on drawdowns at each well. Under certain conditions, pumping rates are optimal when the sum of the nonpumping lift and two times the drawdown at each pumping well takes a constant value across the domain. The results are examined for steady and transient conditions. The results are based on only a few assumptions on the modeled system: the response of drawdown with head is linear, and all pumping activity occurs during the same time periods. Implications of these results for well field operation are suggested.

Description: Water pricing schedules often contain significant nonlinearities, such as the increasing block tariff (IBT) structure that is abundantly applied for residential users. The IBT is frequently supported as a good tool for achieving the goals of equity, water conservation, and revenue neutrality but seldom has been grounded on efficiency justifications. In particular, existing literature on water pricing establishes that although efficient schedules will depend on demand and supply characteristics, IBT cannot usually be recommended. In this paper, we consider whether the explicit inclusion of scarcity considerations can strengthen the appeal of IBT. Results show that when both demand and costs react to climate factors, increasing marginal prices may come about as a response to a combination of water scarcity and customer heterogeneity. We derive testable conditions and then illustrate their application through an estimation of Portuguese residential water demand. We show that the recommended tariff schedule hinges crucially on the choice of functional form for demand.

Description: In situ laser diffractometers characterize the suspended particle size distribution (PSD) by measuring laser-generated light scattered off small particles over a range of small forward angles. In environments with low particulate concentrations or high ambient light conditions the ratio of natural downwelling sunlight to scattered laser light sensed by the photodetectors is high and measurements are influenced. Here, we evaluate the effect of the ambient light field intensity on measurements made with a Laser In Situ Scattering and Transmissometry (LISST) 100X type B instrument. Paired light-dark scattering distributions are recorded over a range of underwater light intensities in high-turbidity and low-turbidity water. Light measurements displayed large erroneous concentrations of particles in the smallest size bin (1.25–1.48 μm) and showed effects over the full range of the PSD. Ambient light was found to exhibit the same constant distribution over the instrument photodetectors in both water samples, although the magnitude of the response, in laser counts per unit ambient light intensity, was PSD dependent. A technique for postprocessing data to remove the influence of light is presented for moored deployment and vertical profile data collected at Lake Tahoe, California-Nevada, United States. While measurements removed of the light effect were successfully reconstructed, the technique may not be applicable to data where the PSD or the LISST orientation relative to the sun direction change rapidly or when light intensities are high enough to quench the instrument photodetectors. Ambient light was found to have negligible effects on PSD measurements in Lake Tahoe was below intensities of ∼30 W m−2.

Description: Spatial and temporal trends in stream chemistry were investigated in a large (1600 km2) alpine watershed in the southern Rocky Mountains of Colorado to help understand mechanisms of streamflow generation. We observed linear increases of concentrations of chemical constituents in streamflow as accumulated drainage area increased along the main channel of Saguache Creek. We tested two conceptual models of streamflow generation against our stream chemistry observations. One model is essentially two-dimensional and treats streamflow generation at the large watershed scale as the aggregation of runoff responses from individual hillslopes, primarily surface and shallow subsurface flow paths. Alternatively, a fully three-dimensional conceptual model treats streamflow generation as being controlled by a distribution of large-scale groundwater flow paths as well as surface and shallow subsurface flow paths. The structure and magnitude of groundwater contributions in streamflow as a function of increasing scale provided a key distinction between these two conceptual models. End-member mixing analysis and measurements of hydraulic head gradients in streambeds were used to quantify basin-scale groundwater contributions to streamflow with increasing spatial scale in the Saguache Creek watershed. Our data show that groundwater contributions are important in streamflow generation at all scales and, more importantly, that groundwater contributions to streamflow do increase with increasing watershed scale. These results favor the three-dimensional conceptual model in which long groundwater flow paths provide a streamflow generation process at large scales that is not operative at smaller scales. This finding indicates that large watersheds may be more than simply the aggregation of hillslopes and small catchments.

Description: Microbial biodiversity in groundwater and soil presents a unique opportunity for improving characterization and monitoring at sites with multiple contaminants, yet few computational methods use or incorporate these data because of their high dimensionality and variability. We present a systematic, nonparametric decision-making methodology to help characterize a water quality gradient in leachate-contaminated groundwater using only microbiological data for input. The data-driven methodology is based on clustering a set of molecular genetic-based microbial community profiles. Microbes were sampled from groundwater monitoring wells located within and around an aquifer contaminated with landfill leachate. We modified a self-organizing map (SOM) to weight the input variables by their relative importance and provide statistical guidance for classifying sample similarities. The methodology includes the following steps: (1) preprocessing the microbial data into a smaller number of independent variables using principal component analysis, (2) clustering the resulting principal component (PC) scores using a modified SOM capable of weighting the input PC scores by the percent variance explained by each score, and (3) using a nonparametric statistic to guide selection of appropriate groupings for management purposes. In this landfill leachate application, the weighted SOM assembles the microbial community data from monitoring wells into groupings believed to represent a gradient of site contamination that could aid in characterization and long-term monitoring decisions. Groupings based solely on microbial classifications are consistent with classifications of water quality from hydrochemical information. These microbial community profile data and improved decision-making strategy compliment traditional chemical groundwater analyses for delineating spatial zones of groundwater contamination.

Description: Legal scholars and jurists have identified several criteria (e.g., hydrology, climate, population, and historical water use) to guide equitable allocation of transboundary rivers among riparian claimants. Are these criteria used in practice, such that a quantitative pattern emerges from actual water-sharing agreements regarding factors affecting allocations? To address this, we study interstate compacts, the principal mechanism for allocating the waters of transboundary rivers within the United States. We develop a georeferenced data set and construct variables representing conditions in state-based watersheds of 14 rivers at the times of compact ratification. A state's water allocation share of a compact serves as the dependent variable, and a set of explanatory variables is derived from legal and political theories. We estimate allocation shares using both ordinary least squares (OLS) and bootstrap regressions, and we apply two alternative specifications of the factors affecting compact allocations, one with and one without political variables. Estimated coefficients on variables for land area, population, prior water use, riparian position, and Congressional committee chair are statistically significant in the OLS regressions. The preferred OLS specification, which includes political variables, provides a good fit (R2 = 0.84). We also find that OLS and bootstrap regressions have a similar ability to predict state allocation shares. We discuss how the results could be used as a reference point in negotiations over new compacts or international river treaties and as a basis to identify existing compacts with statistical outliers.

Description: Transverse mixing of solutes in steady state transport is of utmost importance for assessing mixing-controlled reactions of compounds that are continuously introduced into the subsurface. Classical spatial moments analysis fails to describe mixing because the tortuous streamlines in heterogeneous formations cause plume meandering, squeezing, and stretching, which affect transverse spatial moments even if there is no mass transfer perpendicular to the direction of flow. For transverse solute mixing, however, the decisive process is the exchange of solute mass between adjacent stream tubes. We therefore reformulate the advection-dispersion equation in streamline coordinates (i.e., in terms of the potential and the stream function values) and analyze how flux-related second central moments of plumes increase with dropping hydraulic potential. We compare the ensemble behavior of these second central moments in random two-dimensional heterogeneous flow fields with the moments in an equivalent homogeneous system, thus defining an equivalent effective transverse dispersion coefficient. Unlike transverse macrodispersion coefficients derived by traditional moment analysis, our mixing-relevant, flux-related coefficient does not increase with travel distance. We present closed-form solutions for the mean enhancement of transverse mixing by heterogeneity in two-dimensional isotropic media for linear laws of local-scale transverse dispersion. The mixing enhancement factor increases with the log conductivity variance but remains fairly low. We also evaluate the variance of our cumulative measure of transverse mixing, showing that heterogeneity causes substantial uncertainty of mixing. The analytical expressions are compared to numerical Monte Carlo simulations for various values of log conductivity variance, indicating good agreement with the analytical results at low variability. In the numerical simulations, we also consider nonlinear models of local-scale transverse dispersion.

Description: Hydrologic modelers often need to know which method of quantitative precipitation estimation (QPE) is best suited for a particular catchment. Traditionally, QPE methods are verified and benchmarked against independent rain gauge observations. However, the lack of spatial representativeness limits the value of such a procedure. Alternatively, one could drive a hydrological model with different QPE products and choose the one which best reproduces observed runoff. Unfortunately, the calibration of conceptual model parameters might conceal actual differences between the QPEs. To avoid such effects, we abandoned the idea of determining optimum parameter sets for all QPE being compared. Instead, we carry out a large number of runoff simulations, confronting each QPE with a common set of random parameters. By evaluating the goodness-of-fit of all simulations, we obtain information on whether the quality of competing QPE methods is significantly different. This knowledge is inferred exactly at the scale of interest—the catchment scale. We use synthetic data to investigate the ability of this procedure to distinguish a truly superior QPE from an inferior one. We find that the procedure is prone to failure in the case of linear systems. However, we show evidence that in realistic (nonlinear) settings, the method can provide useful results even in the presence of moderate errors in model structure and streamflow observations. In a real-world case study on a small mountainous catchment, we demonstrate the ability of the verification procedure to reveal additional insights as compared to a conventional cross validation approach.

Description: I address a range of topics that provide the sociopolitical-technological setting for my professional life. I discuss some influential features of post–World War II world geopolitics, landmark technological developments of that era, and the resulting follow-up technologies that have made it possible to approach various problems in hydrology and water resources. I next address societal needs that have driven developments in hydrology and water resources engineering and follow with a discussion of the modern foundations of our science and what I think are the principal issues in hydrology. I pose three community challenges that when accomplished should advance hydrologic science: data network needs for improving the water budgets at all scales, characterizing subsurface water flow paths, and the information archiving and mining needs from instruments that will generate substantially richer data detail than have been used for most hydrologic work to the present. I then discuss several hydrologic and water resource risk-based decision issues that matter to society to illustrate how such risks have been addressed successfully in the past. I conclude with a long-term community “grand challenge,” the coupled modeling of the ocean-atmosphere-landform hydrologic cycle for the purpose of long–lead time hydrologic prediction.

Description: The likely effects of climate change on the water resources of the eastern Mediterranean and Middle East region are investigated using a high-resolution regional climate model (PRECIS) by comparing precipitation simulations of 2040–2069 and 2070–2099 with 1961–1990. The simulations show about a 10% decline in precipitation across the region by both the middle and the end of the century, with considerable variation between countries and international river basins. Results suggest that per capita water resources will not change particularly significantly in southeastern Europe, where they are relatively plentiful and population growth is minimal. However, in much of the Middle East, climate change coupled with population growth is likely to reduce per capita water resources considerably. This will inevitably result in major social, economic, and environmental change in the region. Countries where the required adaptation is likely to be particularly challenging include Turkey and Syria because of the large agricultural workforces, Iraq because of the magnitude of the change and its downstream location, and Jordan because of its meager per capita water resources coupled with limited options for desalination. If the internal water footprint of the region declines in line with precipitation but the total water footprint of the region increases in line with population, then by midcentury, as much as half the total water needs of the region may need to be provided through desalination and imported in the form of virtual water.

Description: We review the human actions, proximal stressors and ecological responses for floodplain forests Australia's largest river system—the Murray-Darling Basin. A conceptual model for the floodplain forests was built from extensive published information and some unpublished results for the system, which should provide a basis for understanding, studying and managing the ecology of floodplains that face similar environmental stresses. Since European settlement, lowlands areas of the basin have been extensively cleared for agriculture and remnant forests heavily harvested for timber. The most significant human intervention is modification of river flows, and the reduction in frequency, duration and timing of flooding, which are compounded by climate change (higher temperatures and reduced rainfall) and deteriorating groundwater conditions (depth and salinity). This has created unfavorable conditions for all life-history stages of the dominant floodplain tree (Eucalyptus camaldulensis Dehnh.). Lack of extensive flooding has led to widespread dieback across the Murray River floodplain (currently 79% by area). Management for timber resources has altered the structure of these forests from one dominated by large, widely spreading trees to mixed-aged stands of smaller pole trees. Reductions in numbers of birds and other vertebrates followed the decline in habitat quality (hollow-bearing trees, fallen timber). Restoration of these forests is dependent on substantial increases in the frequency and extent of flooding, improvements in groundwater conditions, re-establishing a diversity of forest structures, removal of grazing and consideration of these interacting stressors.

Description: There is currently a distinct gap between what climate science can provide and information that is practically useful for (and needed by) natural resource managers. Improved understanding, and model representations, of interactions between the various climate drivers (both regional and global scale), combined with increased knowledge about the interactions between climate processes and hydrological processes at the regional scale, is necessary for improved attribution of climate change impacts, forecasting at a range of temporal scales and extreme event risk profiling (e.g., flood, drought, and bushfire). It is clear that the science has a long way to go in closing these research gaps; however, in the meantime water resource managers in the Murray-Darling Basin, and elsewhere, require hydroclimatic projections (i.e., seasonal to multidecadal future scenarios) that are regionally specific and, importantly, take into account the impacts, and associated uncertainties, of both natural climate variability and anthropogenic change. The strengths and weaknesses of various approaches for supplying this information are discussed in this paper.

Description: We use the Budyko framework to calculate catchment-scale evapotranspiration (E) and runoff (Q) as a function of two climatic factors, precipitation (P) and evaporative demand (Eo = 0.75 times the pan evaporation rate), and a third parameter that encodes the catchment properties (n) and modifies how P is partitioned between E and Q. This simple theory accurately predicted the long-term evapotranspiration (E) and runoff (Q) for the Murray-Darling Basin (MDB) in southeast Australia. We extend the theory by developing a simple and novel analytical expression for the effects on E and Q of small perturbations in P, Eo, and n. The theory predicts that a 10% change in P, with all else constant, would result in a 26% change in Q in the MDB. Future climate scenarios (2070–2099) derived using Intergovernmental Panel on Climate Change AR4 climate model output highlight the diversity of projections for P (±30%) with a correspondingly large range in projections for Q (±80%) in the MDB. We conclude with a qualitative description about the impact of changes in catchment properties on water availability and focus on the interaction between vegetation change, increasing atmospheric [CO2], and fire frequency. We conclude that the modern version of the Budyko framework is a useful tool for making simple and transparent estimates of changes in water availability.

Description: A partially penetrating well of length Lw and radius Rw starts to pump at constant discharge Qw at t = 0 from an unconfined aquifer of thickness D. The aquifer is of random and stationary conductivity characterized by KG (geometric mean), σY2 (log conductivity variance), and I and Iv (the horizontal and vertical integral scales). The flow problem is solved under a few simplifying assumptions commonly adopted in the literature for homogeneous media: Rw/Lw $\ll$ 1, linearization of the free surface condition, and constant drainable porosity n. Additionally, it is assumed that Rw/I 〈 1 and Lw/Iv $\gg$ 1 (to simplify the well boundary conditions) and that a first-order approximation in σY2 (extended to finite σY2 on a conjectural basis) is adopted. The solution is obtained for the mean head field $\langle$H(R, z, t)$\rangle$ and the associated water table equation. The main result of the analysis is that the flow domain can be divided into three zones for $\langle$H$\rangle$: (1) the neighborhood of the well R $\ll$ I, where $\langle$H$\rangle$ = (Qw/LwKA)h0(R, z, tKefuv/nD), with h0 being the zero-order solution pertaining to a homogeneous and isotropic aquifer, KA being the conductivity arithmetic mean, and Kefuv being the effective vertical conductivity in mean uniform flow, (2) an exterior zone R ⪆ I in which $\langle$H$\rangle$ = (Qw/LwKefuh)h0(R$\sqrt{K_{efuv}/K_{efuh}}$, z, tKefuv/nD), with Kefuh being the horizontal effective conductivity, and (3) an intermediate zone in which the solution requires a few numerical quadratures, not carried out here. The application to pumping tests reveals that identification of the aquifer parameters for homogeneous and anisotropic aquifers by commonly used methods can be applied for the drawdown measured in an observation well of length Low $\gg$ Iv (to ensure exchange of space and ensemble head averages) in the second zone in order to identify Kefuh, Kefuv, and n. In contrast, the use of the drawdown in the well (first zone) leads to an overestimation of Kefuh by the factor KA/Kefuh.

Description: Calcium (Ca) has declined to levels threatening aquatic biota in lakes on the eastern Canadian Shield. Predictive models for future changes in lake Ca are generally based on catchment-scale studies, but these models rarely account for unmeasured sources of Ca supply that are common in the nearshore areas of developed lakes. In this study we utilize up to 29 years of hydrological and water chemistry data for three lakes in central Ontario that differ in degree of human intervention to demonstrate that shoreline development may exert large effects on Ca mass balances. In the relative absence of shoreline development, Red Chalk Lake exhibited what we consider to be the normal response, a reduction in Ca load from the catchment over the last three decades, leading to a reduction in lake export and lake Ca concentration. Calcium load, export, and lake water Ca concentration also fell in Harp Lake, but less than in Red Chalk Lake, because Ca loads were elevated by human activities in Harp Lake's moderately developed shoreline area. By contrast, Dickie Lake experienced an exceptional change in Ca dynamics: both export and lake concentrations rose because of elevated load from the shoreline area linked to the use of dust suppressants on gravel roads. Reductions in both stream Ca concentration and flow volume have led to calcium decline in streams and lakes. Long-term soil acidification processes and climatic variability with its link to hydrology can explain the general pattern of Ca decline in lakes on the south-central Canadian Shield. However, given the widespread lakeshore development and use of dust suppressants on gravel roads, predictions of lake Ca levels need to take into account nearshore activities, especially those that augment rates of Ca supply.

Description: Accurate description of the soil water retention curve (SWRC) at low water contents is important for simulating water dynamics and biochemical vadose zone processes in arid environments. Soil water retention data corresponding to matric potentials of less than −10 MPa, where adsorptive forces dominate over capillary forces, have also been used to estimate soil specific surface area (SA). In the present study, the dry end of the SWRC was measured with a chilled-mirror dew point psychrometer for 41 Danish soils covering a wide range of clay (CL) and organic carbon (OC) contents. The 41 soils were classified into four groups on the basis of the Dexter number (n = CL/OC), and the Tuller-Or (TO) general scaling model describing water film thickness at a given matric potential ( 10. A strong correlation between the ratio of the two surface area estimates and the Dexter number was observed and applied as an additional scaling function in the TO model to rescale the soil water retention curve at low water contents. However, the TO model still overestimated water film thickness at potentials approaching ovendry condition (about −800 MPa). The semi–log linear Campbell-Shiozawa-Rossi-Nimmo (CSRN) model showed better fits for all investigated soils from −10 to −800 MPa and yielded high correlations with CL and SA. It is therefore recommended to apply the empirical CSRN model for predicting the dry part of the water retention curve (−10 to −800 MPa) from measured soil texture or surface area. Further research should aim to modify the more physically based TO model to obtain better descriptions of the SWRC in the very dry range (−300 to −800 MPa).

Description: This paper analyzes the effects of different hydrological mechanisms on the solute response in watershed stream networks. Important processes are due to the hydraulic and chemical retention of reactive solutes in transient storage zones and the cumulative consequences of these processes from a single transport pathway as well as from the network of transport pathways. Temporal moments are derived for a distributed stream network and for a compartment-in-series model. The temporal moments are evaluated and are utilized to derive formal expressions for translating the network parameters into compartmental model parameters. The analysis reveals that in addition to the hydraulic and chemical retention processes, the morphological and topological properties of a watershed have a distinct impact on the central temporal moments in terms of averaging of the solute load weighted distances as well as the transport parameters over the network. Kinetic (rate-limited) transient storage affects second-order and higher central temporal moments and thus has a secondary effect on the parameterization of compartmental models. Additional considerable contributions to all temporal moments are introduced when parameter variability along transport pathways is considered. The paper demonstrates an improved model outcome for phosphorus transport in a small Swedish watershed by accounting for the overall network effects when parameterizing a compartment-in-series model.

Description: The estimation of hydrological model parameters by calibration to field data is a critical step in the modeling process. However, calibration often fails because of parameter correlation. Here it is shown that time-lapse gravity data can be combined with hydraulic head data in a coupled hydrogeophysical inversion to decrease parameter correlation in groundwater models. This is demonstrated for a model of riverbank infiltration where combined inversion successfully constrains hydraulic conductivity and specific yield in both an analytical and a numerical groundwater model. A sensitivity study shows that time-lapse gravity data are especially useful to constrain specific yield. Furthermore, we demonstrate that evapotranspiration, and riverbed conductance are better constrained by coupled inversion to gravity and head data than to head data alone. When estimating the four parameters simultaneously, the six correlation coefficients were reduced from unity when only head data were employed to significantly lower values when gravity and head data were combined. Our analysis reveals that the estimated parameter values are not very sensitive to the choice of weighting between head and gravity data over a large interval of relative weights.

Description: Horizontal acoustic Doppler current profilers (H-ADCPs) can be employed to estimate river discharge based on water level measurements and flow velocity array data across a river transect. A new method is presented that accounts for the dip in velocity near the water surface, which is caused by sidewall effects that decrease with the width to depth ratio of a channel. A boundary layer model is introduced to convert single-depth velocity data from the H-ADCP to specific discharge. The parameters of the model include the local roughness length and a dip correction factor, which accounts for the sidewall effects. A regression model is employed to translate specific discharge to total discharge. The method was tested in the River Mahakam, representing a large river of complex bathymetry, where part of the flow is intrinsically three-dimensional and discharge rates exceed 8000 m3 s−1. Results from five moving boat ADCP campaigns covering separate semidiurnal tidal cycles are presented, three of which are used for calibration purposes, whereas the remaining two served for validation of the method. The dip correction factor showed a significant correlation with distance to the wall and bears a strong relation to secondary currents. The sidewall effects appeared to remain relatively constant throughout the tidal cycles under study. Bed roughness length is estimated at periods of maximum velocity, showing more variation at subtidal than at intratidal time scales. Intratidal variations were particularly obvious during bidirectional flow conditions, which occurred only during conditions of low river discharge. The new method was shown to outperform the widely used index velocity method by systematically reducing the relative error in the discharge estimates.

Description: Seven high-resolution (0.3–0.6 m depth intervals), 1-D vertical profiles of the δ²H of pore water were collected across a 300 km2 study area in southern Saskatchewan, Canada, to define the vertical controls on solute transport in a 〉120 m thick, two-layered aquitard system. The 1-D profiles were augmented with an existing δ²H profile collected from a previous study. The surficial aquitard in the area consists of Quaternary deposits (either glacial till or lacustrine deposits; 13 to 128 m thick) underlain by an upper Cretaceous claystone aquitard (80–110 m thick). The shape of the individual δ²H profiles and associated 1-D transport modeling suggest diffusion is the regionally dominant vertical transport mechanism across the aquitards. The profile shape is controlled by the thickness of the Quaternary deposit and the δ²H value at the upper boundary, which coincides with the depth of the water table. The upper boundary δ²H value varies considerably across the area (−149‰ to −101‰), perhaps due to differences in local hydrological conditions (e.g., slope, aspect, infiltration) across the landscape. Modeling of all profiles shows the timing for till deposition and the timing of climate change during the Holocene are consistent across the area (∼30 ka and 7–10 ka before the present, respectively), corroborating other studies. This study provides insights into the hydrogeologic controls on solute transport in an aquitard system and associated geologic and climatic changes for a prairie region over the past 30 ka, and improves our understanding of initial and time-dependent transport boundary conditions for the study of aquitards.

Description: We develop a novel method of parameterization for spatial hydraulic property characterization to mitigate the challenges associated with the nonlinear inverse problem of subsurface flow model calibration. The parameterization is performed by the projection of the estimable hydraulic property field onto an orthonormal basis derived from the grid connectivity structure. The basis functions represent the modal shapes or harmonics of the grid, are defined by a modal frequency, and converge to special cases of the discrete Fourier series under certain grid geometries and boundary assumptions; therefore, hydraulic property updates are performed in the spectral domain and merge with Fourier analysis in ideal cases. Dependence on the grid alone implies that the basis may characterize any grid geometry, including corner point and unstructured, is model independent, and is constructed off-line and only once prior to flow data assimilation. We apply the parameterization in an adaptive multiscale model calibration workflow for three subsurface flow models. Several different grid geometries are considered. In each case the prior hydraulic property model is updated using a parameterized multiplier field that is superimposed onto the grid and assigned an initial value of unity at each cell. The special case corresponding to a constant multiplier is always applied through the constant basis function. Higher modes are adaptively employed during minimization of data misfit to resolve multiscale heterogeneity in the geomodel. The parameterization demonstrates selective updating of heterogeneity at locations and spatial scales sensitive to the available data, otherwise leaving the prior model unchanged as desired.

Description: We present a new technique for identifying and quantifying the discharge of long residence time, regional groundwater to rivers using naturally occurring tracers measured within the river. Terrigenic 4He and 222Rn, synoptically sampled along a 100 km reach in the Fitzroy River in northern Western Australia, are used to identify areas of groundwater inflow to the river and to distinguish shallow, local and deep, regional groundwater. Models of tracer transport in the river can be numerically optimized to calculate total groundwater discharge and to separate regional and local discharge fractions. Discharge of regional groundwater composes close to 15% of the total groundwater discharge along the entire reach, varying spatially along the reach from 0% to 100% of total groundwater discharge. This method should be applicable in river systems where groundwater with elevated terrigenic helium could be discharging to the river. The ability to separate locally from regionally derived groundwater discharge has significant implications for calculating catchment water budgets, for predicting catchment response to changes in precipitation, and for sustainable management of the catchment.

Description: Mean May–September Potomac River streamflow was reconstructed from 950–2001 using a network of tree ring chronologies (n = 27) representing multiple species. We chose a nested principal components reconstruction method to maximize use of available chronologies backward in time. Explained variance during the period of calibration ranged from 20% to 53% depending on the number and species of chronologies available in each 25 year time step. The model was verified by two goodness of fit tests, the coefficient of efficiency (CE) and the reduction of error statistic (RE). The RE and CE never fell below zero, suggesting the model had explanatory power over the entire period of reconstruction. Beta weights indicated a loss of explained variance during the 1550–1700 period that we hypothesize was caused by the reduction in total number of predictor chronologies and loss of important predictor species. Thus, the reconstruction is strongest from 1700–2001. Frequency, intensity, and duration of drought and pluvial events were examined to aid water resource managers. We found that the instrumental period did not represent adequately the full range of annual to multidecadal variability present in the reconstruction. Our reconstruction of mean May–September Potomac River streamflow was a significant improvement over the Cook and Jacoby (1983) reconstruction because it expanded the seasonal window, lengthened the record by 780 years, and better replicated the mean and variance of the instrumental record. By capitalizing on variable phenologies and tree growth responses to climate, multispecies reconstructions may provide significantly more information about past hydroclimate, especially in regions with low aridity and high tree species diversity.

Description: Well-validated rainfall-runoff models are able to capture the relationships between rainfall and streamflow and to reliably estimate initial catchment states. While future streamflows are mainly dependent on initial catchment states and future rainfall, use of the rainfall-runoff models together with estimated future rainfall can produce skilful forecasts of future streamflows. This is the basis for the ensemble streamflow prediction system, but this approach has not been explored in Australia. In this paper, two conceptual rainfall-runoff models, together with rainfall ensembles or analogues based on historical rainfall and the Southern Oscillation index (SOI), were used to forecast streamflows at monthly and 3-monthly scales at two catchments in east Australia. The results showed that both models forecast monthly streamflow well when forecasts for all months were evaluated together, but their performance varied significantly from month to month. Best forecasting skills were obtained (both monthly and 3 monthly) when the models were coupled with ensemble forcings on the basis of long-term historical rainfall. SOI-based resampling of forcings from historical data led to improved forecasting skills only in the period from September to December at the catchment in Queensland. For 3 month streamflow forecasts, best skills were in the period from April to June at the catchment in Queensland and in the period from October to January for the catchment in New South Wales, both of which were the periods after the rainy season. The forecasting skills are indicatively comparable to the statistical forecasting skills using a Bayesian joint probability approach. The potential approaches for improved hydrologic modeling through conditional parameterization and for improved forecasting skills through advanced model updating and bias corrections are also discussed.

Description: Sediments are a pervasive source of fecal indicator bacteria (FIB) in rivers, lakes, estuaries, and oceans and may constitute a long-term reservoir of human disease. Previous attempts to quantify the flux of FIB across the sediment-water interface (SWI) are limited to extreme flow events, for which the primary mechanism of bacterial release is disruption and/or erosion of the sediment substrate. Here we report measurements of FIB flux across the SWI in a turbulent stream that is not undergoing significant erosion. The stream is formed by the steady discharge of bacteria-free disinfected and highly treated wastewater effluent to an earthen channel harboring high concentrations of FIB in the sediment from in situ growth. The flux j″ of FIB across the SWI, estimated from mass balance on FIB measurements in the water column, scales linearly with the concentration of bacteria in sediment pore fluids Cpore over a 3 decade change in both variables: $j^{\,\prime\prime}\; = \;k_m^{\rm obs} C_{\rm pore}.$ The magnitude of the observed mass transfer velocity ($\[k_m^{\rm obs}\, = \; 5\times{10^{ - 5}}\]$ m s−1) is significantly larger than values predicted for either the diffusion of bacteria across a concentration boundary layer ($k_m^{\rm diff}\, = \;8\; \times \;{10^{ - 6}}$ m s−1) or sweep and eject fluid motions at the SWI ($\[k_m^{\rm sweep}\, = \; {10^{ - 6}}\]$ m s−1) but is similar to the flux of water between the stream and its hyporheic zone estimated from dye injection experiments. These results support the hypothesis that hyporheic exchange controls the trafficking of bacteria, and perhaps other types of particulate organic matter, across the SWI in turbulent streams.

Description: Reactive transport modeling is a critical element in assessing the potential of natural attenuation of groundwater pollutants. In the present study, we developed a comprehensive quantitative model that incorporates the key processes affecting the long-term fate of complex organic compound mixtures released from coal tar–type dense nonaqueous phase liquid sources. The model framework addresses the simulation of the long-term dynamics of source zone depletion, the fate of the released compounds during reactive transport in the groundwater, the evolution of the aquifer's biogeochemical response, in particular its redox conditions, and the redox-dependent carbon isotope fractionation of selected organic compounds. The modeling framework was applied for the interpretation of observed biogeochemical and isotopic data from a well-characterized coal tar–contaminated site in northern Germany. The simulations highlight the diversity of fates of the individual compounds, which result from their widely varying physicochemical characteristics, and also how complex interactions develop over the lifetime of the contamination. The highly transient release of contaminants from the coal tar as pool and as heterogeneously distributed blobs in the source zone triggers continuously changing biogeochemical conditions and isotope signatures. The modeling results illustrate how difficult and uncertain the assessment of contaminant fate can be if the collected data cover only a small time window relative to the transport time scale. This emphasizes the need for a holistic understanding of the governing processes that control the effectiveness of monitored natural attenuation before it is implemented as a passive remediation strategy at nonaqueous phase liquid–contaminated sites.

Description: In recent years local, national, and international authorities have showed an increasing awareness of flood and inundation hazard, likely due to the large floods which occurred in the past years in many regions of the world. In this context, the estimation of the design flood values to be adopted for flood risk assessment or floodplain management represents a crucial factor. In the case of ungauged or scarcely gauged catchments where a sufficiently long discharge time series is missing, a relevant uncertainty is involved in the flood frequency analysis and a possible solution to reduce this uncertainty is the application of continuous simulation (CS) approaches. Because of the complex structure of this type of approaches and pursuing the parameters parsimony criteria, in the hydrological practice the approaches based on the design storm (DS) estimation are more widely known and applied, mainly for their simplicity. However, one major limit of the DS method is the choice of the “design soil moisture” conditions, representing a critical parameter for assessing the initial wetness of the basin. To that end, this study of investigating six subcatchments of the upper Tiber River basin (Central Italy), with drainage area ranging from 13 to 284 km2, proposes a procedure based on the application of the CS approach as a tool to define the design soil moisture to be afterwards incorporated into the more simple DS method. For each catchment, the procedure consists of (1) stochastic generation of long synthetic rainfall and temperature series starting from observed hourly data; (2) application of a lumped continuous rainfall-runoff model to generate synthetic discharge series and, hence, to obtain the corresponding flood frequency curves; (3) estimation of the design soil moisture, for each return period, by varying in the DS approach the initial wetness conditions of the catchment so that the peak discharge estimated by the DS method matches the one given by the synthetic flood frequency curve. Moreover, in order to apply the more simple DS approach avoiding the use of the CS one, a preliminary analysis to regionalize the design soil moisture as a function of the geo-morphological characteristics and the return period is also shown.

Description: Hydrologists routinely analyze pumping test data using conventional interpretation methods that are based on the assumption of homogeneity and that, consequently, yield single estimates of representative flow parameters. However, natural subsurface formations are intrinsically heterogeneous, and hence, the flow parameters influencing the drawdown vary as the cone of depression expands in time. In this paper a novel procedure for the analysis of pumping tests in heterogeneous confined aquifers is developed. We assume that a given heterogeneous aquifer can be represented by a homogeneous system whose flow parameters evolve in time as the pumping test progresses. At any point in time, the interpreted flow parameters are estimated using the ratio of the drawdown and its derivative observed at that particular time. The procedure is repeated for all times, yielding time-dependent estimates of transmissivity Ti(t) and storativity, Si(t). Based on the analysis of the sensitivity of drawdown to inhomogeneities in the T field, the time-dependent interpreted transmissivity values are found to be a good estimate of Tg(r), the geometric mean of the transmissivity values encompassed within a progressively increasing radius r from the well. The procedure is illustrated for Gaussian heterogeneous fields with ln(T) variances up to a value of 2. The impact of the separation distance between the pumping well and observation point on data interpretation is discussed. The results show that information about the spatial variability of the transmissivity field can be inferred from time-drawdown data collected at a single observation point.

Description: Flooding affects ecosystems by transporting water and solutes across aquatic-terrestrial interfaces, removing nutrient and organic substrate limitations, and spurring biogeochemical activity. Few studies have considered the influence of flooding on surface water–groundwater interactions. This research examines the temporally variable water storage and exchange in a stream in the McMurdo Dry Valleys (MDV) of Antarctica, where diel flood pulses occur due to glacial melt. Several MDV streams display truncated discharge peaks, suggesting water storage between the source glacier and the gauging station. We tested the hypothesis that stream braids and subsurface water storage contribute to the difference between glacial melt and stream outflow hydrographs by constructing a coupled surface water routing and subsurface water flow model. This model routes water into stream braids at high flows and allows this water to infiltrate and return to the stream via subsurface flow paths as flows recede. Our simulation demonstrates the importance of surface–subsurface water interactions in controlling the hydrograph shape. Maximum simulated discharge was sensitive to storage parameters including aquifer depth and the flooding threshold, while minimum discharge was sensitive to hydraulic conductivity. Subsurface storage volume varied by 38% over a diel cycle and stream-subsurface exchange rates varied from 0 to 0.19 m3 h−1 m−1, with exchange from the stream to the subsurface during high flows, and vice versa at low flows. These results underscore how unsteady flow can increase hyporheic interactions and ecosystem productivity, and provide support for maintaining natural stream morphology and flow regimes.

Description: Bayesian theory of model calibration provides a coherent framework for distinguishing and encoding multiple sources of uncertainty in probabilistic predictions of flooding. This paper demonstrates the use of a Bayesian approach to computer model calibration, where the calibration data are in the form of spatial observations of flood extent. The Bayesian procedure involves generating posterior distributions of the flood model calibration parameters and observation error, as well as a Gaussian model inadequacy function, which represents the discrepancy between the best model predictions and reality. The approach is first illustrated with a simple didactic example and is then applied to a flood model of a reach of the river Thames in the UK. A predictive spatial distribution of flooding is generated for a flood of given severity.

Description: Evapotranspiration rates at the catchment scale are very difficult to quantify. One possible manner to continuously observe this variable could be the estimation of sensible heat fluxes (H) across large distances (in the order of kilometers) using a large aperture scintillometer (LAS), and inverting these observations into evapotranspiration rates, under the assumption that the LAS observations are representative for the entire catchment. The objective of this paper is to assess whether measured sensible heat fluxes from a LAS over a long distance (9.5 km) can be assumed to be valid for a 102.3 km2 heterogeneous catchment. Therefore, a fully process-based water and energy balance model with a spatial resolution of 50 m has been thoroughly calibrated and validated for the Bellebeek catchment in Belgium. A footprint analysis has been performed. In general, the sensible heat fluxes from the LAS compared well with the modeled sensible heat fluxes within the footprint. Moreover, as the modeled H within the footprint has been found to be almost equal to the modeled catchment averaged H, it can be concluded that the scintillometer measurements over a distance of 9.5 km and an effective height of 68 m are representative for the entire catchment.

Description: The primary aim of this paper is to present a fuzzy probabilistic approach for optimal design and rehabilitation of water distribution systems, combining aleatoric and epistemic uncertainties in a unified framework. The randomness and imprecision in future water consumption are characterized using fuzzy random variables whose realizations are not real but fuzzy numbers, and the nodal head requirements are represented by fuzzy sets, reflecting the imprecision in customers' requirements. The optimal design problem is formulated as a two-objective optimization problem, with minimization of total design cost and maximization of system performance as objectives. The system performance is measured by the fuzzy random reliability, defined as the probability that the fuzzy head requirements are satisfied across all network nodes. The satisfactory degree is represented by necessity measure or belief measure in the sense of the Dempster-Shafer theory of evidence. An efficient algorithm is proposed, within a Monte Carlo procedure, to calculate the fuzzy random system reliability and is effectively combined with the nondominated sorting genetic algorithm II (NSGAII) to derive the Pareto optimal design solutions. The newly proposed methodology is demonstrated with two case studies: the New York tunnels network and Hanoi network. The results from both cases indicate that the new methodology can effectively accommodate and handle various aleatoric and epistemic uncertainty sources arising from the design process and can provide optimal design solutions that are not only cost-effective but also have higher reliability to cope with severe future uncertainties.

Description: This paper discusses issues arising when Tropical Rainfall Measuring Mission (TRMM) estimates of rainfall characteristics are calculated for the sparsely gauged Brazilian Amazon. The particular issue considered is the calculation of statistical uncertainty in (1) comparisons between TRMM estimates of rainfall characteristics and their corresponding rain gauge estimates and (2) interpolated estimates of rainfall characteristics, which are conditional on local TRMM estimates near ungauged sites. Three characteristics selected for particular comparison are (1) mean annual rainfall, 1998–2005, (2) mean value, over these years, of the 95% quantile of within-year daily rainfall, and (3) mean number of days in the year with rainfall of 2 mm or more. The paper demonstrates how positive spatial correlation leads to underestimation of the uncertainty in the comparisons (i.e., the standard errors of differences), so that the significance of differences, when observed, is likely to be overestimated if spatial correlation is ignored. For the three characteristics mentioned, the Matérn spatial correlation function with shape parameter $\kappa$ = 1/2, giving an exponential correlation function, was found to be adequate for modeling spatial correlation. It is also argued that the statistic 1 − b, where b is the slope of the regression of a rain gauge estimate of a rainfall characteristic on its counterpart derived from satellite instrumentation, is a measure of the errors in the satellite (spatially averaged) estimates. Finally, although issues of spatial correlation are discussed with particular reference to rainfall, it is argued that the same issues arise whenever satellite-derived estimates of a component of the water cycle must be combined with ground-based measurements.

Description: The ensemble Kalman filter (EnKF) has recently been proposed as a promising parameter estimation approach for constraining the description of rock flow properties, such as permeability and porosity, to reproduce flow measurements that are modeled as nonlinear functions of these properties. One of the key factors that strongly affect the performance of the EnKF is the quality or representativeness of the prior ensemble of property fields used to initialize the EnKF assimilation procedure. The initial ensemble is commonly constructed by assuming a known geological continuity model such as a variogram. However, geologic continuity models are derived from incomplete information and imperfect modeling assumptions, which can introduce a significant level of uncertainty into the produced models. Neglecting this important source of uncertainty can lead to systematic errors and questionable estimation results. In this paper, we investigate the performance of the EnKF under varying levels of uncertainty in the variogram model parameters. We first attempt to directly estimate variogram model parameters from flow data and show that the complex and nonunique relation they have with the flow data provides little sensitivity for an effective inversion with the EnKF. We then assess the performance of the EnKF for estimation of permeability values under uncertain and incorrect initial variogram parameters and show that any bias in specifying variogram parameters tends to persist throughout the EnKF analysis even though locally reasonable permeability updates may be obtained near observation points. More importantly, we show that when variogram parameters are specified probabilistically to account for the full range of structural variability in the initial permeability ensemble, the EnKF update results are quite promising. The results suggest that under uncertain geologic continuity, the EnKF tends to perform better if a very diverse set of property fields is used to form the initial ensemble than when a deterministic and potentially erroneous variogram model is used. Therefore, in applying the EnKF to model calibration problems, it is preferable to overestimate the uncertainty in geologic continuity and to initialize the EnKF procedure with a wide range of variability in property description than to overlook the variogram uncertainty at the risk of introducing systematic bias that cannot be corrected by the EnKF updates. The practical implications of the results in this paper are significant for designing the EnKF for realistic ensemble model calibration problems where the level of uncertainty in the initial ensemble is usually not known a priori.

Description: This paper presents a theoretical investigation of the effects of spatial heterogeneity of runoff generation on the scaling behavior of runoff timing responses. A previous modeling study on the Illinois River Basin in Oklahoma had revealed a systematic spatial trend in the relative dominance of different runoff generation mechanisms, attributable to corresponding systematic trends in landscape properties. Considering the differences in the timing of hillslope responses between the different runoff mechanisms, this paper explores their impacts on the catchment-scale runoff routing responses, including how they change with spatial scale. For this purpose we utilize a distributed, physically based hydrological model, with a fully hydraulic stream network routing component. The model is used to generate instantaneous response functions (IRF) for nested catchments of a range of sizes along the river network and quantitative measures of their shape, e.g., peak and time to peak. In order to separate the effects of soil heterogeneity from those due to basin geomorphology, the model simulations are carried out for three hypothetical cases that make assumptions regarding landscape properties (uniform, a systematic trend, and heterogeneity plus the trend), repeating these simulations under wet and dry antecedent conditions. The simulations produced expected and also surprising results. The power law relationship between the peak of the IRF and drainage area is shown to be flatter under wet conditions than under dry conditions, even though the (faster) saturation excess mechanism is more dominant under wet conditions. This result appears to be caused by partial area runoff generation: under wet conditions, the fraction of saturation area is about 30%, while under dry conditions it is less than 10% for the same input of rainfall. This means travel times associated with overland flow (which mostly contributes to the peak and time to peak) are, in fact, longer during wet conditions than during dry conditions. The power law relationship between peak and drainage area also exhibits a scaling break at around 1000 km2, which can be shown to be related to the peculiar geomorphology of the catchment.

Description: This study is focused on Pseudomonas putida bacteria transport in porous media in the presence of suspended kaolinite clay particles. Experiments were performed with bacteria and kaolinite particles separately to determine their individual transport characteristics in water-saturated columns packed with glass beads. The results indicated that the mass recovery of bacteria and clay particles decreased as the pore water velocity decreased. Batch experiments were carried out to investigate the attachment of Pseudomonas putida onto kaolinite particles. The attachment process was adequately described by a Langmuir isotherm. Finally, bacteria and kaolinite particles were injected simultaneously into a packed column in order to investigate their cotransport behavior. The experimental data suggested that the presence of clay particles significantly inhibited the transport of bacteria in water-saturated porous media. The observed reduction of Pseudomonas putida recovery in the column outflow was attributed to bacteria attachment onto kaolinite particles, which were retained onto the solid matrix of the column. A mathematical model was developed to describe the transport of bacteria in the presence of suspended clay particles in one-dimensional water-saturated porous media. Model simulations were in good agreement with the experimental results.

Description: A recently introduced measurement approach allows in situ determination of subsurface soil water evaporation by means of heat-pulse probes (HPP). The latent heat component of subsurface evaporation is estimated from the residual of the sensible heat balance. This heat balance method requires measurement of vertical soil temperature and estimates of thermal properties for soil water evaporation determination. Our objective was to employ numerically simulated thermal and hydraulic processes using constant or diurnally cycled surface boundary conditions to evaluate and understand this technique. Three observation grid spacings, namely, 6 mm (tri-needle HPP), 3 mm (penta-needle HPP) and 1 mm, along with three soil textures (sand, silt, and silty clay) were used to test the heat balance method. The comparison of heat balance–based evaporation rate estimates with an independent soil profile water balance revealed substantial errors when thermal conductivity $(\lambda)$ was averaged spatially across the evaporation front. Since the conduction component of heat flux is the dominant process at the evaporation front, the estimation of evaporation rate was significantly improved using depth-dependent $\lambda$ instead of a space-averaged $\lambda$. A near-surface “undetectable zone” exists, where the heat balance calculation is irreconcilable, resulting in underestimation of total subsurface evaporation. The method performs better for medium- and coarse-textured soils than for fine-textured soils, where portions of the drying front may be maintained longer within the undetectable zone. Using smaller temperature sensor spacing near the soil surface minimized underestimation from the undetectable zone and improved accuracy of total subsurface evaporation rate estimates.

Description: Skillful and reliable forecasts of seasonal streamflows are highly valuable to water management. In a previous study, we developed a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites. The approach has been adopted by the Australian Bureau of Meteorology for seasonal streamflow forecasting in Australia. This study extends the applicability of the BJP modeling approach to streams with zero flow occurrences. The aim is to produce forecasts for these streams in the form of probabilities of zero seasonal flows and probability distributions of above zero seasonal flows. We turn a difficult mathematical problem of mixed discrete-continuous multivariate probability distribution modeling into one of continuous multivariate probability distribution modeling by treating zero flow occurrences as censored data. This paper presents the mathematical formulation and implementation of the modeling approach, methods for forecast verification, and results of a test application to the Burdekin river catchment in northern Queensland, Australia.

Description: We report observed short-term (3 years) channel adjustment in an incised, semiarid stream to the removal of invasive plants, tamarisk (Tamarix spp.) and Russian olive (Elaeagnus angustifolia) by (1) removing the above-ground portion of the plant (cut-stump method) and (2) removing the entire plant (whole-plant method). The stream flows through Canyon de Chelly National Monument in Arizona, USA., draining an ∼1500 km2 catchment. Average channel width is 13 m; average thalweg depth is 2–3 m, although channel banks exceed 8 m locally. Channels adjusted primarily through widening, with significantly larger changes occurring in whole-plant removal reaches; however, neither plant removal method elicited large-scale bank destabilization, and the channels remained entrenched. Particular site conditions limiting large-scale destabilization include the absence of sufficient streamflow magnitudes, the presence of clay layers at the bank toe, the remaining presence of native vegetation, and the entrenched morphology. Our findings serve as a cautionary note regarding the temporal and spatial variability in channel response to invasive plant removal and underscore the importance of considering site-specific conditions in future restoration projects that include invasive plant removal.