ALBERT

Description: We quantified all components of a fluvial sediment budget for a discrete flood on an aggrading gravel bed river. Bed load transport rates were measured at the upstream and downstream ends of a 4 km study area on the Provo River, Utah, during a dam-controlled flood. We also collected high-resolution measurements of channel topography before and after the controlled flood for the entire reach. Topographic uncertainty in the digital elevation models (DEM) was characterized using a spatially variable approach. The net sediment flux provided unambiguous indication of storage. Sediment input to the reach (319 m3) exceeded output (32 m3), producing a net accumulation of approximately 290 m3. The difference between the scour and fill was also positive (470 m3), but uncertainty in the topographic differencing was larger than the observed net storage. Thus, the budget would have been indeterminate if based on morphologic data alone. Although topographic differencing was not sufficiently accurate to indicate net storage, it was able to demonstrate that internal erosion was a larger sediment source than the net sediment flux. The magnitude of total erosion (1454 m3) and deposition (1926 m3) was considerably larger than net change in storage, showing that internal sources and sinks were the dominant driver of channel change. The findings provide guidance for the development of sediment budgets in settings in which one must choose between a morphological approach and the direct measurement of sediment flux.

Description: Soil erosion can severely degrade landscapes, and concentrated flows such as rills and gullies can be the dominant contributor to the soil losses. This paper examines the growth, development, and spatiotemporal evolution of rills and rill networks using a soil-mantled experimental landscape subjected to simulated rain and downstream base level lowering. Rill incision and network development and extension occurred due to actively migrating headcuts formed at the flume outlet by base level lowering. The communication of this wave of degradation due to this exogenic forcing occurred very quickly in space, and resulted in nearly the same amount of bed incision throughout the network. Rill incision, channel development, and peaks in sediment efflux occurred episodically, yet these were in direct response to the downstream base level adjustments. Although flows were supply limited, most of the sediment efflux was genetically linked to headcut development and migration. The geometry of the eroded rills and the rates of headcut migration were well correlated to overland flow rate. These findings have important implications for the prediction of soil loss, rill network development, and landscape evolution where headcut erosion can occur.

Description: In this study a conceptual model that accounts for the effects of nonequilibrium contaminant transport in a fractured porous media is developed. Present model accounts for both physical and sorption nonequilibrium. Analytical solution was developed using the Laplace transform technique, which was then numerically inverted to obtain solute concentration in the fracture matrix system. The semianalytical solution developed here can incorporate both semi-infinite and finite fracture matrix extent. In addition, the model can account for flexible boundary conditions and nonzero initial condition in the fracture matrix system. The present semianalytical solution was validated against the existing analytical solutions for the fracture matrix system. In order to differentiate between various sorption/transport mechanism different cases of sorption and mass transfer were analyzed by comparing the breakthrough curves and temporal moments. It was found that significant differences in the signature of sorption and mass transfer exists. Applicability of the developed model was evaluated by simulating the published experimental data of Calcium and Strontium transport in a single fracture. The present model simulated the experimental data reasonably well in comparison to the model based on equilibrium sorption assumption in fracture matrix system, and multi rate mass transfer model.

Description: Floodplain channels are important components of river-floodplain systems and are known to play a key role in hydrodynamic exchange and sediment transport. The Amazon floodplain exhibits complex networks of these channels, and despite their potential importance to this globally important wetland system, these floodplain channels are relatively unstudied. The research presented here is the first systematic and detailed study of the network and morphologic characteristics of a large number of these channels in the middle reach of the central Amazon River using analysis of data derived from Landsat Enhanced Thematic Mapper Plus (ETM+) mosaic and field survey. Our findings show that the channels are ubiquitous, their width varies widely, and some of their characteristics can be fitted using power laws, potentially much like the self-similar or fractal-like behavior hypothesized for other types of fluvial networks. In all, 96% of the floodplain channels are not wide enough to be represented well, or at all, in the ∼90 m Shuttle Radar Topography Mission data. Channel depths are tied closely to the local amplitude of the passing main river flood wave (p value of 0.75), except where there are local runoff inputs, which results in substantially deeper channels which provide preferential flow paths across the floodplain. Channel networks imply that areas of the floodplain function for large parts of the flood cycle as separate hydrogeomorphic land units, here termed floodplain hydrological units (FHUs). These hypothesized FHUs also have distinct spatial and pattern characteristics, and it is suggested here that their differences could provide the beginnings of a framework for understanding the detailed hydrodynamics of the floodplain. In particular, different types of FHUs have differences in flood water source, which will have important implications for biogeochemical studies of the wetlands.

Description: Improved predictions of hyporheic exchange based on easily measured physical variables are needed to improve assessment of solute transport and reaction processes in watersheds. Here we compare physically based model predictions for an Indiana stream with stream tracer results interpreted using the Transient Storage Model (TSM). We parameterized the physically based, Multiscale Model (MSM) of stream-groundwater interactions with measured stream planform and discharge, stream velocity, streambed hydraulic conductivity and porosity, and topography of the streambed at distinct spatial scales (i.e., ripple, bar, and reach scales). We predicted hyporheic exchange fluxes and hyporheic residence times using the MSM. A Continuous Time Random Walk (CTRW) model was used to convert the MSM output into predictions of in stream solute transport, which we compared with field observations and TSM parameters obtained by fitting solute transport data. MSM simulations indicated that surface-subsurface exchange through smaller topographic features such as ripples was much faster than exchange through larger topographic features such as bars. However, hyporheic exchange varies nonlinearly with groundwater discharge owing to interactions between flows induced at different topographic scales. MSM simulations showed that groundwater discharge significantly decreased both the volume of water entering the subsurface and the time it spent in the subsurface. The MSM also characterized longer timescales of exchange than were observed by the tracer-injection approach. The tracer data, and corresponding TSM fits, were limited by tracer measurement sensitivity and uncertainty in estimates of background tracer concentrations. Our results indicate that rates and patterns of hyporheic exchange are strongly influenced by a continuum of surface-subsurface hydrologic interactions over a wide range of spatial and temporal scales rather than discrete processes.

Description: Securing water supplies in urban areas is a major challenge for policy makers, both now and into the future. This study aimed to identify the key determinants of household water use, with a view to identifying those factors that could be targeted in water demand management campaigns. Objective water use data and surveys were collected from 1008 households in four local government areas of southeast Queensland, Australia. Results showed that demographic, psychosocial, behavioral, and infrastructure variables all have a role to play in determining household water use. Consistent with past research, household occupancy was the most important predictor of water use. Households in regions recently exposed to drought conditions and higher-level restrictions also used less water than those who had less experience with drought. The effect of water efficient technology was mixed: some water efficient appliances were associated with less water use, while others were associated with more water use. Results also demonstrated the importance of considering water use as a collective behavior that is influenced by household dynamics. Households who reported a stronger culture of water conservation used less water. These findings, along with evidence that good water-saving habits are linked to water conservation, highlight the value of policies that support long-term cultural shifts in the way people think about and use water.

Description: Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change “signal” in the hydrological observations, above the natural internal climate variability “noise” shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

Description: The goal of this study is to diagnose the manner in which radar-rainfall input affects peak flow simulation uncertainties across scales. We used the distributed physically based hydrological model CUENCAS with parameters that are estimated from available data and without fitting the model output to discharge observations. We evaluated the model's performance using (1) observed streamflow at the outlet of nested basins ranging in scale from 20 to 16,000 km2 and (2) streamflow simulated by a well-established and extensively calibrated hydrological model used by the US National Weather Service (SAC-SMA). To mimic radar-rainfall uncertainty, we applied a recently proposed statistical model of radar-rainfall error to produce rainfall ensembles based on different expected error scenarios. We used the generated ensembles as input for the hydrological model and summarized the effects on flow sensitivities using a relative measure of the ensemble peak flow dispersion for every link in the river network. Results show that peak flow simulation uncertainty is strongly dependent on the catchment scale. Uncertainty decreases with increasing catchment drainage area due to the aggregation effect of the river network that filters out small-scale uncertainties. The rate at which uncertainty changes depends on the error structure of the input rainfall fields. We found that random errors that are uncorrelated in space produce high peak flow variability for small scale basins, but uncertainties decrease rapidly as scale increases. In contrast, spatially correlated errors produce less scatter in peak flows for small scales, but uncertainty decreases slowly with increasing catchment size. This study demonstrates the large impact of scale on uncertainty in hydrological simulations and demonstrates the need for a more robust characterization of the uncertainty structure in radar-rainfall. Our results are diagnostic and illustrate the benefits of using the calibration-free, multiscale framework to investigate uncertainty propagation with hydrological models.

Description: Fluid-fluid interfacial areas in porous media are of considerable interest due to the impact they have on a wide range of practical applications involving mass transfer between phases, as well as for their importance in understanding unsaturated and multiphase flow behaviors in porous media. Tracer methods provide a low-cost experimental approach for determining interfacial areas in porous media. Although a number of different tracer methods have been developed, uncertainty remains as to exactly what areas they measure. The work presented here uses pore network model simulations to study the behavior of tracers during simulated tracer measurements for two different specific water-phase tracer methods: the dynamic-interface tracer depletion method and the miscible displacement tracer method. The hypothesis driving this work was that different tracer methods likely measure different areas as a result of the very different ways tracers are used. Experimental data sets for six different porous media were used to validate the model and provide comparison with model-simulated tracer-based area measurements. Results of the work suggest that areas measured using the dynamic-interface tracer depletion method closely match total fluid-fluid interfacial areas, as long as the extent of tracer depletion during the method is relatively small. However, areas measured with the miscible displacement method likely fall somewhere between capillary and total fluid-fluid areas. Calculations conducted with realistic diffusion coefficients and film thicknesses indicate that diffusion and head-driven flow in films are insufficient to allow significant tracer access to film area, suggesting the potential importance of other mechanisms. Calculations conducted as a part of the work suggest that Leverett estimates of maximum area formed during drainage may be closer to total areas than previously reported.

Description: A spatially explicit life cycle water analysis framework is proposed, in which a standardized water footprint methodology is coupled with hydrologic modeling to assess blue water, green water (rainfall), and agricultural grey water discharge in the production of biofuel feedstock at county-level resolution. Grey water is simulated via SWAT, a watershed model. Evapotranspiration (ET) estimates generated with the Penman-Monteith equation and crop parameters were verified by using remote sensing results, a satellite-imagery-derived data set, and other field measurements. Crop irrigation survey data are used to corroborate the estimate of irrigation ET. An application of the concept is presented in a case study for corn-stover-based ethanol grown in Iowa (United States) within the Upper Mississippi River basin. Results show vast spatial variations in the water footprint of stover ethanol from county to county. Producing 1 L of ethanol from corn stover growing in the Iowa counties studied requires from 4.6 to 13.1 L of blue water (with an average of 5.4 L), a majority (86%) of which is consumed in the biorefinery. The county-level green water (rainfall) footprint ranges from 760 to 1000 L L−1. The grey water footprint varies considerably, ranging from 44 to 1579 L, a 35-fold difference, with a county average of 518 L. This framework can be a useful tool for watershed- or county-level biofuel sustainability metric analysis to address the heterogeneity of the water footprint for biofuels.

Description: The D8, D8-LTD, D∞-LTD, D∞, MD∞, and MD8 flow direction methods are evaluated against field observations of overland flow dispersion obtained from novel experimental methods. Thin flows of cold water were released at selected points on a warmer slope and individual overland flow patterns originating from each of these points were observed using a terrestrial laser scanner and a thermal imaging camera. Land microtopography was determined by using laser returns from the dry land surface, whereas overland flow patterns were determined by using either laser returns or infrared emissions from the wetted portions of the land surface. Planar overland flow dispersion is found to play an important role in the region lying immediately downslope of the point source, but attenuates rapidly as flow propagates downslope. In contrast, existing dispersive flow direction methods are found to provide a continued dispersion with distance downslope. Predicted propagation patterns, for all methods considered here, depend critically on the size h of grid cells involved. All methods are found to be poorly sensitive in extremely fine grids (h ≤ 2 cm), and to be poorly specific in coarse grids (h = 2 m). Satisfactory results are, however, obtained in grids having resolutions h that approach the average flow width (50 cm), with the best performances displayed by the MD8 method in the finest grids (5 ≤ h ≤ 20 cm), and by the MD∞, D∞, and D∞-LTD methods in the coarsest grids (20 cm 〈 h ≤ 1 m).

Description: The complexity of hydrological systems and the necessary simplification of models describing these systems remain major challenges in hydrological modeling. Kirchner's (2009) approach of inferring rainfall and evaporation from discharge fluctuations by “doing hydrology backward” is based on the assumption that catchment behavior can be conceptualized with a single storage-discharge relationship. Here we test Kirchner's approach using a densely instrumented hydrologic measurement network spanning 24 geologically diverse subbasins of the Alzette catchment in Luxembourg. We show that effective rainfall rates inferred from discharge fluctuations generally correlate well with catchment-averaged precipitation radar estimates in catchments ranging from less than 10 to more than 1000 km2 in size. The correlation between predicted and observed effective precipitation was 0.8 or better in 23 of our 24 catchments, and prediction skill did not vary systematically with catchment size or with the complexity of the underlying geology. Model performance improves systematically at higher soil moisture levels, indicating that our study catchments behave more like simple dynamical systems with unambiguous storage-discharge relationships during wet conditions. The overall mean correlation coefficient for all subbasins for the entire data set increases from 0.80 to 0.95, and the mean bias for all basins decreases from –0.61 to –0.35 mm d−1. We propose an extension of Kirchner's approach that uses in situ soil moisture measurements to distinguish wet and dry catchment conditions.

Description: Drought is a slow-onset, creeping natural hazard which is an inevitable part of normal climate fluctuation especially in arid and semiarid regions and its variability can be explained in terms of large-scale atmospheric circulation patterns. Standardized streamflow index (SSFI) was utilized to characterize hydrological drought in the west of Iran for the hydrological years of 1969–1970 to 2008–2009. The linkage of atmospheric circulation patterns (ENSO, NAO) to hydrological drought was also used to reveal relations of climate variability affecting hydrological drought. River discharges exhibited negative anomalies during the warm phase of ENSO (El Niño) which caused the extreme and sever droughts in the study area, being strongest during the hydrological years of 2007–2008 and 2008–2009. The analysis also indicated the teleconnection impact of ENSO on the hydrological drought severity in the first half of the hydrological year especially between November and March. Moreover, the concurrent and lag correlations revealed a weak relationship between the SSFI drought severity and the NAO index. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Interception losses in stands of non-native trees in Hawaiian forests and their potential negative impacts on fresh water availability are poorly understood. In this study, a canopy water balance analysis was conducted to estimate interception losses using measurements of rainfall (RF), throughfall (TF), and stemflow (SF) at three locations, each dominated by one or more of the following non-native tree species: Psidium cattleianum Sabine (Strawberry guava), Schinus terebinthifolius Raddi (Christmas berry), Syzygium cumini (L.) Skeels (Java plum), and Coffea arabica L . (Coffee). Mean TF expressed as percentage of total RF was the lowest (43.3%) under a monotypic stand of P. cattleianum and the highest (56.5%) under mixture of S. terebinthifolius , P. cattleianum , and S. cumini . Observed SF was highest (33.9%) under P. cattleianum and lowest (3.6%) under a mixture of S. terebinthifolius , P. cattleianum , and S. cumini . The relatively high SF under P. cattleianum can be attributed to its smooth bark, stem density and steep branching. The mean observed canopy interception varied between 23% under P. cattleianum and 45% at the site dominated by C. arabica . Mean direct TF coefficients from individual events at each location ranged from a low of 0.36 under the canopy dominated by C. arabica to a high of 0.51 under the canopy dominated by S. terebinthifolius , P. cattleianum , and S. cumini . In contrast, the mean SF partitioning coefficients from individual storm events at each location ranged from a low of 0.05 under the canopy dominated by S. terebinthifolius , P. cattleianum , and S. cumini to a high of 0.37 under P. cattleianum . Mean canopy storage capacity was highest (1.90) at the site dominated by S. terebinthifolius , P. cattleianum , and S. cumini whereas trunk storage capacity was highest (0.54) under the P. cattleianum . Copyright © 2012 John Wiley & Sons, Ltd.

Description: Multi-step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3-hours warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context makes the development of real-time rainfall-runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3-hours. In this paper we develop a novel semi-distributed, data-driven, rainfall-runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network-based Fuzzy Inference System solutions is created using various combinations of auto-regressive, spatially-lumped radar and point-based rain gauge predictors. Different levels of spatially-aggregated radar-derived rainfall data are used to generate 4, 8 and 12 sub-catchment input drivers. In general, the semi-distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead-times greater than 3-hours. Performance is found to be optimal when spatial aggregation is restricted to 4 sub-catchments, with up to 30% improvements in the performance over lumped and point-based models being evident at 5-hour lead times. The potential benefits of applying semi-distributed, data-driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, is thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.

Description: We used both time domain (deuterium) and source area (alkalinity) tracers to reduce uncertainty in simple conceptual rainfall-runoff models applied to a larger (749 km2) heterogeneous catchment with both upland and lowland headwaters. Stepwise, tracer-aided model development resulted in different model structures for the uplands and lowlands as representative elementary watersheds (REWs). These were differentiated by the parameterization of a nonlinear overland flow mechanism in the former, and the incorporation of high soil moisture storage capacity in the latter. Use of tracers and recession characteristics also helped to reduce parameter uncertainty and provided models that could simulate flows and tracer responses reasonably well over a full hydrological year. However, it was apparent that other processes (e.g., more complex mixing, fractionation, etc.) would need to be parameterized to explain the full variation in isotope dynamics. It is also evident that the information content of tracer data declines as the intensity of sampling decreases, particularly in the lowlands. The models of the REWs were coupled to provide plausible simulations of the up-scaled flow and tracer response at the outfall of the 749 km2 catchment, though the usefulness of source area tracers decreased markedly at this larger scale. Whereas the approach provides a step toward simple models that are likely to give the “right answer for the right reasons,” further improvements appear to require increased parameterization and/or higher-resolution tracer data.

Description: Hyporheic exchanges in riparian zones induced by stream stage fluctuations, referred to as bank storage, can influence contaminant transport and transformation when mixing of groundwater and surface waters with distinct chemical signatures occur, which might lead to a high biochemical activity. The effect of bank storage on nutrient transport was analyzed here using a two-dimensional, variably saturated and multispecies reactive transport model, which accounted for the water flow and solute transport and reactions within riparian zones. After verification with field observations, our model demonstrated that high biogeochemical activities occurred at the near-stream riparian zone during stage fluctuation, a process referred to as bank storage hot moment (BSHM). We used Monte Carlo simulations to study the uncertainty of BSHM and related nutrient dynamics to biogeochemical and hydrological factors. The results indicated that stream fluctuations can lead to maximum bank storage volume ranging from 0 to 259 m3 m−1 of stream linear length (median = 9.7 m3 and SD = 53.2 m3). Taking denitrification as an example, BSHM can lead to considerable NO3− removal with a median removal rate of 2.1 g d−1 and SD of 17.2 g d−1 per meter of stream linear length. The NO3− uptake velocity (median = 2.7 × 10−5 and SD = 2.4 × 10−4 m min−1) was comparable to that of in-stream transient storage from the literature. This result suggests that BSHM may be a significant process contributing to the nutrient budget at the ecosystem level. Finally, a theoretical framework representing the coupled hydrobiogeochemical controls on riparian hot spots was developed to help predicting when BSHM can become important in a particular stream.

Description: A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

Description: Geological and ecological processes play critical roles in the evolution of desert piedmonts. Feedback between fast cyclic biotic and slow cumulative pedogenic processes on arid alluvial fan systems results in a heterogeneous landscape of interspace and canopy microsites. Defining the spatial extent between these processes will allow a better connection to ecosystem service and climate change. We use a soil chronosequence in the Mojave Desert and high spatial resolution infiltrometer measurements along transects radiating from canopies of perennial shrubs to assess the extent of biotic and abiotic processes and the heterogeneity of soil properties in arid shrublands. Results showed higher saturated conductivity under vegetation regardless of surface age, but it was more conspicuous on older, developed soils. At proximal locations to the shrub, bulk density, soil structure grade, silt, and clay content significantly increased radially from the canopy, while sand and organic material decreased. Soil properties at distal locations 2–5 times the canopy radius had no significant spatial correlation. The extent of the biotic influence of the shrub was 1.34 ± 0.32 times the canopy radius. Hydraulic properties were weakly correlated in space, but 75% of the variance could be attributed to sand content, soil structure grade, mean-particle diameter, and soil organic material, none of which are exclusively biotic or abiotic. The fast cyclic biotic processes occurring under vegetation are clearly overprinted on slow cumulative abiotic processes, resulting in the deterministic variability observed at the plant scale.

Description: Two specific questions are addressed in this study regarding dams (artificial reservoirs). (1) Can a dam (artificial reservoir) and the land use/land cover (LULC) changes triggered by it physically alter extreme precipitation? The term extreme precipitation (EP) is used as a way of representing the model-derived upper bound of precipitation that pertains to the engineering definition of the standard probable maximum precipitation (PMP) used in design of dams. (2) Among the commonly experienced LULC changes due to dams, which type of change leads to the most detectable alteration of extreme precipitation? The American River Basin (ARW) and the Folsom dam were selected as a study region. Four scenarios of LULC change (comprising also various reservoir surface areas) were analyzed in a step by step fashion to elucidate the scenario leading to most significant impact on EP. The Regional Atmospheric Modeling System (RAMS, version 6.0) was used to analyze the impact of these LULC scenarios in two modes. In the first mode (called normal), the probable precipitation pattern due to each LULC scenario was identified. The second mode (called moisture-maximized), the PMP pattern represented from a 100% relative humidity profile was generated as an indicator of extreme precipitation (EP). For the particular case of ARW and Folsom dam, irrigation was found as having the most detectable impact on EP (a 5% increase in 72 h total for the normal mode and a 3% increase for the moisture-maximized mode) in and around the ARW watershed. Doubling the reservoir size, on the other hand, brought only a small change in EP. Our RAMS-simulated results demonstrate that LULC changes driven by surrounding landscape alteration resulting from the dams can, in fact, alter the local to regional hydrometeorology as well as extreme precipitation. There is a strong possibility of a positive feedback mechanism initiated by irrigated landscapes located upwind of orographic rain producing watersheds that are impounded by large dams.

Description: The complex conductivity of porous materials and colloidal suspensions comprises two components: an in-phase conductivity associated with electromigration of the charge carriers and a quadrature conductivity associated with the reversible storage of the charges at some polarization length scales. We developed a quantitative model to investigate the frequency domain induced polarization response of suspensions of bacteria and bacteria growth in porous media. Induced polarization of bacteria (α polarization) is related to the properties of the electrical double layer of the bacteria. Surface conductivity and α polarization are due to the Stern layer of counterions occurring in a brush of polymers coating the surface of the bacteria. These phenomena can be related to their cation exchange capacity. The mobility of the counterions in this Stern layer is found to be very small (4.7 × 10−10 m2 s−1 V−1 at 25°C). This implies a very low relaxation frequency for the α polarization of the bacteria cells (typically around 0.1–5 Hz), in agreement with experimental observations. This new model can be coupled to reactive transport modeling codes in which the evolution of bacterial populations are usually described by Monod kinetics. We show that the growth rate and endogenous decay coefficients of bacteria in a porous sand can be inferred nonintrusively from time-lapse frequency domain induced polarization data.

Description: There has been a long term interest in understanding the incubation environment within salmonid spawning gravels. This focus has been motivated primarily by concerns over the impact of increased fine sediment loadings released from a range of catchment sources including, amongst others, forestry or agricultural activity (Ringer & Hall 1987; Collins et al., 2011). Greig et al.,(2005a;2007a) and Sear et al., (2008a) have shown how the accumulation of fine sediment (〈1 mm) influences the supply of oxygen to incubating salmonid eggs via three main processes; 1) physical occlusion of the micropores on the surface of the egg resulting in reduced oxygen diffusion through the egg wall (Greig et al., 2005b); 2) physical occlusion of the pore spaces between gravel particles in the bed, resulting in reduced interstitial flow velocity and longer flow paths and 3) increased oxygen demand arising from active elements within the infiltrated sediments resulting in a reduction in oxygen concentration; termed Sediment Oxygen Demand (SOD). Copyright © 2012 John Wiley & Sons, Ltd.

Description: Hydrological processes change from the impacts of climate variability and human activities. Runoff in the upper reaches of the Hun-Taizi River basin, which is mainly covered by forests in northeast China, decreased from 1960 to 2006. The data used in this study were based on runoff records from six hydrological stations in the upper reaches of the Hun-Taizi River basin. Nonparametric Mann-Kendall statistic was used to identify change trends and abrupt change points, and consequently analyze the change characteristics in hydrological processes. The abrupt change in the annual runoff in most subcatchments appeared after 1975. Finally, the effects of climate change and land-cover change on water resources were identified using regression analysis and a hydrology model. Results of the regression analysis suggest that the correlation coefficients between precipitation and runoff prior to the abrupt change were higher compared with those after the abrupt change. Moreover, using hydrology model analysis, the water yield was found to increase because of the decrease in forest land. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Beneficiaries of common pool resources (CPRs) may select available noncooperative and regulatory exogenous institutions for managing the resource, as well as cooperative management institutions. All these institutions may increase the long-term gains, prolong the life of the resource, and help to escape the tragedy of the commons trap. Cooperative game theory approaches can serve as the backbone of cooperative CPR management institutions. This paper formulates and applies several commonly used cooperative game theoretic solution concepts, namely, the core, Nash-Harsanyi, Shapley, and nucleolus. Through a numerical groundwater example, we show how CPR users can share the gains obtained from cooperation in a fair and efficient manner based on these cooperative solution concepts (management institutions). Although, based on their fairness rationales, various cooperative management institutions may suggest different allocations that are potentially acceptable to the users, these allocation solutions may not be stable as some users may find them unfair. This paper discusses how different methods, such as application of the plurality rule and power index, stability index, and propensity to disrupt concepts, can help identify the most stable and likely solutions for enforcing cooperation among the CPR beneficiaries. Furthermore, how the noncooperative managerial characteristics of the CPR users can affect the stability and acceptability of the different cooperative CPR management institutions is discussed, providing valuable policy insights for cooperative CPR management at community levels.

Description: Coarse-resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of river networks using fine-scale hydrography inputs. We applied the DRT algorithms using combined HydroSHEDS and HYDRO1k global fine-scale hydrography inputs and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions. The new upscaled results are internally consistent and congruent with the baseline fine-scale inputs and should facilitate improved regional to global scale hydrologic simulations.

Description: Regression-type, hybrid empirical/process-based models (e.g., SPARROW, PolFlow) have assumed a prominent role in efforts to estimate the sources and transport of nutrient pollution at river basin scales. However, almost no attempts have been made to explicitly accommodate interannual nutrient loading variability in their structure, despite empirical and theoretical evidence indicating that the associated source/sink processes are quite variable at annual timescales. In this study, we present two methodological approaches to accommodate interannual variability with the Spatially Referenced Regressions on Watershed attributes (SPARROW) nonlinear regression model. The first strategy uses the SPARROW model to estimate a static baseline load and climatic variables (e.g., precipitation) to drive the interannual variability. The second approach allows the source/sink processes within the SPARROW model to vary at annual timescales using dynamic parameter estimation techniques akin to those used in dynamic linear models. Model parameterization is founded upon Bayesian inference techniques that explicitly consider calibration data and model uncertainty. Our case study is the Hamilton Harbor watershed, a mixed agricultural and urban residential area located at the western end of Lake Ontario, Canada. Our analysis suggests that dynamic parameter estimation is the more parsimonious of the two strategies tested and can offer insights into the temporal structural changes associated with watershed functioning. Consistent with empirical and theoretical work, model estimated annual in-stream attenuation rates varied inversely with annual discharge. Estimated phosphorus source areas were concentrated near the receiving water body during years of high in-stream attenuation and dispersed along the main stems of the streams during years of low attenuation, suggesting that nutrient source areas are subject to interannual variability.

Description: The development of spatially continuous fields from sparse observing networks is an outstanding problem in the environmental and Earth sciences. Here we explore an approach to produce spatially continuous fields from discontinuous data that focuses on reconstructing gaps routinely present in satellite-based Earth observations. To assess the utility of the approach, we use synthetic imagery derived from a regional climate model of southeastern Australia. Orbital tracks, scan geometry influences, and atmospheric artifacts are artificially imposed upon these model simulations to examine the techniques' capacity to reproduce realistic and representative retrievals. The imposed discontinuities are reconstructed using a direct sampling technique and are compared against the original continuous model data: a synthetic simulation experiment. Results indicate that the multipoint geostatistical gap-filling approach produces texturally realistic spatially continuous fields from otherwise discontinuous data sets. Reconstruction results are assessed through comparison of spatial distributions, as well as through visual assessment of fine-scale features. Complex spatial patterns and fine-scale structure can be resolved within the reconstructions, illustrating that the often nonlinear dependencies between variables can be maintained. The stochastic nature of the methodology makes it possible to expand the approach within a Monte Carlo framework in order to estimate the uncertainty related to subsequent reconstructions. From a practical perspective, the reconstruction method is straightforward and requires minimum user intervention for parameter adjustment. As such, it can be automated to systematically process real time remote sensing measurements.

Description: In a world of increasing exposure of populations to natural hazards, the mapping of extreme rainfall remains a key subject of study. Such maps are required for both flood risk management and civil engineering structure design, the challenge being to take into account the local information provided by point rainfall series as well as the necessity of some regional coherency. Two approaches based on the extreme value theory are compared here, with an application to extreme rainfall mapping in West Africa. The first approach is a local fit and interpolation (LFI) consisting of a spatial interpolation of the generalized extreme value (GEV) distribution parameters estimated independently at each station. The second approach is a spatial maximum likelihood estimation (SMLE); it directly estimates the GEV distribution over the entire region by a single maximum likelihood fit using jointly all measurements combined with spatial covariates. Five LFI and three SMLE methods are considered, using the information provided by 126 daily rainfall series covering the period 1950–1990. The methods are first evaluated in calibration. Then the predictive skills and the robustness are assessed through a cross validation and an independent network validation process. The SMLE approach, especially when using the mean annual rainfall as covariate, appears to perform better for most of the scores computed. Using the Niamey 104 year time series, it is also shown that the SMLE approach has the capacity to deal more efficiently with the effect of local outliers by using the spatial information provided by nearby stations.

Description: The use of multiphysics computational fluid dynamics (CFD) approaches to simulate surface–subsurface flow processes is evaluated by comparison with flume experiments on current-exposed permeable bed forms. The unique experimental data include measurements of the time-averaged surface water flow velocities, the pressure distribution at the sediment–water interface, and pore water flow paths. The modeling approach first simulates the time-averaged turbulent flow in the channel with CFD and then uses the predicted pressure distribution at the sediment–water interface to drive a flow and transport model for the sediment. The CFD-modeled velocity and pressure distribution and transient particle tracks within the sediment agree reasonably well with observations. Differences that exist between observations and simulations mainly concern the eddies in the wake zone downstream of the ripple crests that are slightly shorter than those predicted by the model. This deviation propagates from the surface to the subsurface domain, appearing in the pressure distribution along the bed and, consequently, the subsurface flow patterns. The good representation of general patterns and rates makes multiphysics CFD modeling a powerful and sufficiently accurate tool that can replace measurements for many studies of surface–subsurface processes involving current-exposed immobile bed forms. The approach can be used for predicting transport processes where they cannot easily be observed, such as in large rivers and coastal systems where boundary conditions such as mean currents and bed forms can be mapped.

Description: Hyporheic zone processes can have significant impact on groundwater and surface water resources. Detailed knowledge of exchange flow patterns is crucial for understanding the ecohydrological and biogeochemical functioning of river corridors. In particular, small-scale hyporheic exchange flow is still poorly understood, partially because of the lack of adequate in situ monitoring technology. This paper investigates the spatial heterogeneity of hyporheic exchange flow in a lowland river at multiple scales. It demonstrates the conjunctive use of active heat pulse tracing at shallow depths (15 cm) and vertical hydraulic gradients (VHG) at 120–150 cm streambed depth for improving the understanding of hyporheic exchange flow processes. Generally positive VHG indicated a regional dominance of groundwater up-welling. High and temporally variable VHG were used to identify confined conditions caused by low conductivity layers in the subsurface (low connectivity), while locations with lower and temporally less variable VHG indicated free groundwater up-welling (high connectivity) in highly conductive sediments. A heat pulse sensor (HPS) was applied for identifying shallow hyporheic flow at three locations representative for high versus low streambed connectivity. Shallow hyporheic flow patterns were found to be spatially heterogeneous. Subsurface flow could only partially be explained by streambed topography. Surface water infiltration and horizontal flow coincided with inhibited groundwater up-welling, whereas locations with high streambed connectivity were characterized by increased up-welling. The combined information of spatiotemporal VHG variability and flow vector frequency distribution by HPS has the potential to improve the understanding of impacts of streambed topography and subsurface stratification on hyporheic flow patterns.

Description: In this article, we investigated the variability of precipitation conditions in the Haihe River basin (HRB) during 1961–2010 by analyzing four daily precipitation scenarios. These scenarios were set with the values of, equal to 0 mm/day, 10–20 mm/day, 20–50 mm/day, and greater than 50 mm/day, which were denoted as P0, P10, P20, and P50, respectively. Results indicate that the mean values of daily precipitation decline and its fluctuation becomes weak with years in HRB. The contour of daily precipitation with the mean value of 1.4 mm/day moves more than 100 km toward southeast in the basin from 1960s to 2000s. The variations of four precipitation scenarios show difference. The Tianjin and Langfang cities were the P0 drought center in HRB after 1980s, and the days and regions without precipitation increase with years. The magnitude of P10 extrema shows no significant changes over the last fifty years, but the rainfall centers vary with areas in HRB. The magnitude of P20 extrema shows no obvious changes in 1961–2000 but increases in 2000s. The magnitude of P50 extrema obviously declines in the last fifty years, with the rainfall center moving from northeast to south of HRB. Urbanization impacts are reflected in some cities in 1980s and 1990s, but after 2000 the urbanization impacts were not clearly detected due to the significant precipitation decreases in HRB. In summary, precipitation decrease is caused by the decreases of P50 extrema rather than P10 and P20 extrema in HRB, which would be favorable for the flood resources utilization through ample-low flow operations over space. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Protection of groundwater-dependent ecosystems (GDEs) is an important criterion in sustainable groundwater management, particularly when human water consumption is in competition with environmental water demands; however, the delineation of GDEs is commonly a challenging task. The Groundwater-dependent Ecosystem Mapping (GEM) method proposed here is based on interpretation of the land surface response to the drying process derived from combined changes in two multispectral indices, the Normalised Difference Vegetation Index (NDVI) and the Normalised Difference Wetness Index (NDWI), both derived from Landsat imagery. The GEM method predicts three land cover classes used for delineation of potential GDEs: vegetation with permanent access to groundwater; vegetation with diminishing access to groundwater; and water bodies that can persist through a prolonged dry period. The method was applied to a study site in the Ellen Brook region of Western Australia, where a number of GDEs associated with localised groundwater, diffuse discharge zones and riparian vegetation were known. The estimated accuracy of the method indicated a good agreement between the predicted and known GDEs; Producer's accuracy was calculated as up to 91% for some areas. The method is most applicable for mapping GDEs in regions with a distinct drying period. Copyright © 2012 John Wiley & Sons, Ltd.

Description: The use of precipitation estimates from weather radar reflectivity has become widespread in hydrologic predictions. However, uncertainty remains in the use of the non-linear reflectivity-rainfall ( Z-R ) relation, in particular for mountainous regions where ground validation stations are often lacking, land surface datasets are inaccurate and the spatial variability in many features is high. In this study, we assess the propagation of rainfall errors introduced by different Z-R relations on distributed hydrologic model performance for four mountain basins in the Colorado Front Range. To do so, we compare spatially-integrated and distributed rainfall and runoff metrics at seasonal and event time scales during the warm season when convective storms dominate. Results reveal that the basin simulations are quite sensitive to the uncertainties introduced by the Z-R relation in terms of streamflow, runoff mechanisms and the water balance components. The propagation of rainfall errors into basin responses follow power law relationships that link streamflow uncertainty to the precipitation errors and streamflow magnitude. Overall, different Z-R relations preserve the spatial distribution of rainfall relative to a reference case, but not the precipitation magnitude, thus leading to large changes in streamflow amounts and runoff spatial patterns at seasonal and event scales. Furthermore, streamflow errors from the Z-R relation follow a typical pattern that varies with catchment scale where higher uncertainties exist for intermediate-sized basins. The relatively high error values introduced by two operational Z-R relations (WSR-57 and NEXRAD) in terms of the streamflow response indicate that site-specific Z-R relations are desirable in the complex terrain region, particularly in light of other uncertainties in the modeling process, such as model parameter values and initial conditions. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of LiDAR technology has provided non-sparse snow depth measurements which we use in this study to address fundamental questions about snow depth inference using both sparse and non-sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional, manual snow depth measurements and to LiDAR observations. Through sampling experiments on high-resolution LiDAR snow depth observations at six separate 1.17  km 2 sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross-validation procedures using three skill metrics: percent error in total snow volume, root mean squared error, and R 2 . Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? While cross validation remains the only option for validating inference from sparse observations, in our experiments the full set of LiDAR-measured snow depths can be considered the “true” spatial distribution and used to understand cross-validation bias at the spatial scale of inference. We model at the 30 m resolution of readily-available predictors which is a popular spatial resolution in the literature. Three regression models are also compared and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count which ranges over 3 orders of magnitude, doubling at each step from 25 up to 3200. While uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100-200 observations, there is considerable uncertainty in the true spatial distribution ( R 2 ) even at medium observation counts (200-800).Weshowthatpercenterrorintotalsnowvolumeisnotsensitivetopredictor quality, though RMSE and R 2 (measures of spatial distribution) often depend critically on it. In accuracies of downloaded predictors (most often the vegetation predictors) caneasily require a quadrupling of observation count to match RMSE and R 2 scores obtained by LiDAR-measured predictors. Under cross validation, the RMSE and R 2 skill measures are consistently biased towards poorer results than the true validation. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30  m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and on sampling design. Sampling designs which maximize independent information maximize cross-validation bias but also maximize true R 2 . The bagging tree model is found to generally out-perform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modeling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometers. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Solute diffusion flux in soil is described by Fick's law along with a tortuosity factor to account for the tortuous and reduced diffusive pathway blocked by soil particles. Predictive models based on empirical or conceptual relationships with other more commonly measured soil attributes have been proposed to replace the time-consuming and multifarious laboratory measurements. However, these models have not been systematically tested and evaluated with soils of different textures under comparable conditions. This study determined solute diffusion coefficients and calculated tortuosity factors of a sand, a sandy clay loam, and a clay at various degrees of water saturation, and used the experimental data to test the predictive capabilities of these models. All the test models can fit the experimental data reasonably well as evidenced by low root mean square errors (RMSEs). When the proposed (fixed) parameter values were used, the widely accepted Millington and Quirk tortuosity model resulted in highest RMSEs for all three test soils. In terms of model efficiency as described by Akaike weight, however, the tortuosity factors of the sand and sandy clay loam soils are best represented by a quadratic function of volumetric soil water content (with the largest Akaike weights), while the combined parallel-series conceptual model assuming different configurations of film and pore water is the best for the clay soil. The Olesen power function tortuosity model has the second largest Akaike weights for the sand and sandy clay loam soils, while the So and Nye linear model has the second largest Akaike weight for the clay soil. The two-region linear model of log (tortuosity factor) versus soil water content uses a similar framework to the conceptual model, and it can satisfactorily fit to the experimental data well (low RMSEs), but with low Akaike weights due to the large number of parameters in the model. Adaption of the findings from this study may substantially improve solute diffusion modeling in unsaturated porous media.

Description: This study investigates numerically the characteristics of upscaling the Manning resistance coefficient (nt) for areas covered by partially submerged vegetation elements, such as shrub or tree stems. A number of high-resolution hydrodynamic simulations were carried out corresponding to scenarios with different domain slopes (S), inflow rates (Q), bed roughness (nb), and vegetation cover fractions (Vf). Using simulations performed at fine space-time scales, two methods were developed for computing the upscaled Manning coefficient, termed “Equivalent Roughness Surface (ERS)” and “Equivalent Friction Slope (EFS).” Results obtained with these two methods indicate that both yield highly correlated estimates of nt. The effects of four independent variables (Vf, S, Q, and nb) on nt were further investigated. First, as Vf increases, nt also grows. Second, two distinct modes of the relationship between S and nt for a fixed Vf and Q emerge: a positive dependence at low-flow rates and a negative dependence at high-flow rates. For a fixed Vf and S, two distinct modes of the relationship between Q and nt are also identified: a positive dependence at mild domain slopes and a negative dependence at steep slopes. A regression analysis shows that the two conflicting trends can occur depending on whether the variability of flow depth with respect to S (or Q) is greater than the ratio of h and S (or Q). Third, a rougher soil bed (i.e., larger values of nb) implies a higher resistance due to vegetation. Last, the study argues that nt increases as h increases and decreases as V increases. A generic regression relation that includes all four of the above variables and the difference nt − nb (i.e., the additional resistance due to partially submerged vegetation representing the sum of the form and wave resistances) was developed. The range of applicability of this relation is given by the following conditions: Vf ≤ 0.5, 0.1 ≤ S ≤ 1.1, and 0.0001 ≤ Q ≤ 0.01. The difference nt − nb computed from the developed regression relation was compared with estimates reported by five different studies. Furthermore, the simulated wave resistance coefficients were compared with those predicted from an equation in a previous study; the estimates were consistent in the range of experimental conditions for which the latter equation was developed. The relationship is sufficiently general and applicable to other flow conditions with partially submerged roughness elements.

Description: This paper explores the use of a mixture model for determining the marginal distribution of hydrological variables, consisting of a truncated central distribution that is representative of the central or main-mass regime, which for the cases studied is a lognormal distribution, and of two generalized Pareto distributions for the maximum and minimum regimes, representing the upper and lower tails, respectively. The thresholds defining the limits between these regimes and the central regime are parameters of the model and are calculated together with the remaining parameters by maximum likelihood. After testing the model with a simulation study we concluded that the upper threshold of the model can be used when applying the peak over threshold method. This will yield an automatic and objective identification of the threshold presenting an alternative to existing methods. The model was also applied to four hydrological data series: two mean daily flow series, the Thames at Kingston (United Kingdom), and the Guadalfeo River at Orgiva (Spain); and two daily precipitation series, Fort Collins (CO, USA), and Orgiva (Spain). It was observed that the model improved the fit of the data series with respect to the fit obtained with the lognormal (LN) and, in particular, provided a good fit for the upper tail. Moreover, we concluded that the proposed model is able to accommodate the entire range of values of some significant hydrological variables.

Description: Hydrologic models are commonly calibrated by optimizing a single objective function target to compare simulated and observed flows, although individual targets are influenced by specific flow modes. Nash-Sutcliffe efficiency (NSE) emphasizes flood peaks in evaluating simulation fit, while modified Nash-Sutcliffe efficiency (MNS) emphasizes lower flows, and the ratio of the simulated to observed standard deviations (RSD) prioritizes flow variability. We investigated tradeoffs of calibrating streamflow on three standard objective functions (NSE, MNS, and RSD), as well as a multiobjective function aggregating these three targets to simultaneously address a range of flow conditions, for calibration of the Soil and Water Assessment Tool (SWAT) daily streamflow simulations in two watersheds. A suite of objective functions was explored to select a minimally redundant set of metrics addressing a range of flow characteristics. After each pass of 2001 simulations, an iterative informal likelihood procedure was used to subset parameter ranges. The ranges from each best-fit simulation set were used for model validation. Values for optimized parameters vary among calibrations using different objective functions, which underscores the importance of linking modeling objectives to calibration target selection. The simulation set approach yielded validated models of similar quality as seen with a single best-fit parameter set, with the added benefit of uncertainty estimations. Our approach represents a novel compromise between equifinality-based approaches and Pareto optimization. Combining the simulation set approach with the multiobjective function was demonstrated to be a practicable and flexible approach for model calibration, which can be readily modified to suit modeling goals, and is not model or location specific.

Description: A model-based approach is implemented to attribute changes in the seasonal extreme river flows to meteorological drivers. A semidistributed model that simulates daily runoff from daily series of meteorological variables was employed together with a multisite, multivariable weather generator. Ensembles of synthetic meteorological variables were synthesized using the weather generator and were used to drive the hydrological model. In order to systematically assess the relative importance of each of the meteorological variables in explaining the detected changes in the flood behavior, the variables were generated by accounting for the year to year variability of the distribution of one of the variables at a time while keeping the distributions of the others temporally stationary. The approach was tested on eight case study catchments from different parts of Germany. The results show the ability of the approach in identifying the meteorological variable that is associated with the detected change in the extreme flow. Changes in precipitation were found to be the major meteorological drivers of the trends detected in the seasonal extreme flows in most of the investigated catchments. Temperature was found to be less important in explaining any of the changes in all catchments.

Description: We analyze the controls on flood duration based on the concept of comparative hydrology. Rather than modeling a single catchment in detail, we compare catchments with contrasting characteristics in order to understand the controls in a holistic way. We analyze the hydrographs of 9223 maximum annual flood events in 396 Austrian catchments ranging from 5 to ∼10,000 km2 as a function of climatic controls such as storm type (synoptic and convective storms, rain-on-snow, snowmelt), and catchment controls such as soils, soil moisture, geology, and land form. The ratio of the flood volume and the flood peak is used as a measure of the flood duration or flood timescale. The results indicate that, spatially, the median flood timescales range from 16 h in the hilly catchments, where convective storms prevail, to 104 h in the lowland catchments where substantial inundation into the floodplain occurs. The range is even larger for different flood types, from 7 h for flash floods in the hilly catchments to 200 h for snowmelt floods in an Alpine area with deeply weathered rocks and deep soils. The results also indicate that the catchment area is not the most important control on the flood timescales. For the range of catchments considered here, climate is very important through storm type and antecedent soil moisture, and geology is very important through soil characteristics. The concept of comparative hydrology is also used to interpret the interplay of the processes controlling the flood duration at timescales from hours to millennia. It is argued that the flood timescale is a rich fingerprint of the hydrological processes in a catchment because it integrates a range of climate and catchment characteristics by a time parameter.

Description: Large wood (LW) exerts an important influence on the geomorphology and ecology of streams and rivers. The magnitudes of flow forces on LW are needed to support stream management activities and are typically computed using time mean lift and drag coefficients determined in laboratory flumes using small, smooth cylinders. Herein we report measurements of forces on LW of varying complexity (simple cylinder, branching, and complex root wad) and surface (bark) roughness made in an outdoor grassed channel under steady and unsteady flows. LW orientation relative to the primary flow direction and LW relative submergence were varied. Drag and lift coefficients for cylindrical (unbranched) LW followed patterns reported by others for metal cylinders in wind tunnels. Drag coefficients for cylindrical (unbranched) LW, corrected for blockage effects, ranged from −0.05 to 1.29, and lift coefficients ranged from −0.88 to 0.52, varying systematically with LW position relative to the channel bed and incident flow direction. Measured drag coefficients for the noncylindrical LW, corrected for blockage effects, ranged from 0.22 to 6.27, while lift coefficients varied from −3.65 to 30.84. Systematic relationships between the relative submergence and orientation of branching LW and the drag and lift coefficients were not observed, but coefficients were greatest for LW with few branches and converged on smaller values typical of blunt bodies as LW complexity increased. For both simple and complex LW, maximum lift and drag forces during the rising limb of unsteady flows were about 2–3 times greater than steady flow temporal mean values.

Description: We report the results of a yearlong noble gas study conducted in 2008–2009 together with continuous physical and chemical measurements collected in a monitoring well in an aquifer in southern Michigan. Conditions near the water table are correlated with noble gas concentrations, corresponding noble gas temperatures (NGTs), and precipitation events. This yearlong study is the first noble gas field test that has employed natural recharge and in situ monitored conditions, with minimal disturbance of the unsaturated zone. This detailed study demonstrates that significant changes in conditions near the water table can occur over a year that can greatly affect NGTs. Results show that precipitation events are detected within hours at the water table, but a lag in pressure response argues for a long time constant for gas transport within the unsaturated zone. There is strong evidence for the depletion of oxygen near the water table, which affects the noble gas air-saturated water component. During reducing conditions there is evidence for significant noble gas degassing. Rain from the passage of Hurricane Ike caused a significant shift in stable isotope ratios and injection of a large quantity of excess air and likely led to a much more oxygen-rich environment in the soil gas. Although individual models can account for NGTs over portions of the record, no single NGT model can account for all features observed over the entire study. It is likely that the NGT temperature proxy must be viewed as an average of recharge conditions over several years.

Description: Processes controlling streamflow generation were determined using geochemical tracers for water years 2004–2007 at eight headwater catchments at the Kings River Experimental Watersheds (KREW) in the Southern Sierra Nevada. Four catchments are snow dominated and four receive a mix of rain and snow. Results of diagnostic tools of mixing models indicate that Ca 2+ , Mg 2+ , K + and Cl - behaved conservatively in streamflow at all catchments, reflecting mixing of three endmembers. Using endmember mixing analysis, the endmembers were determined to be snowmelt runoff (including rain on snow), subsurface flow, and fall storm runoff. In seven of the eight catchments, streamflow was dominated by subsurface flow, with an average relative contribution (% of streamflow discharge) greater than 60%. Snowmelt runoff contributed less than 40% and fall storm runoff less than 6% on average. Streamflow peaked 2–4 weeks earlier at mixed rain-snow than snow-dominated catchments, but relative endmember contributions were not significantly different between the two groups of catchments. Both soil water in the unsaturated zone and regional groundwater were not significant contributors to streamflow. The contributions of snowmelt runoff and subsurface flow, when expressed as discharge, were linearly correlated with streamflow discharge (R 2 of 0.85-0.99). These results suggest that subsurface flow is generated from the soil-bedrock interface through preferential pathways and is not very sensitive to snow-rain proportions. Thus a declining of the snow-rain ratio under a warming climate should not systematically affect the processes controlling the streamflow generation at these catchments. Copyright © 2012 John Wiley & Sons, Ltd.

Description: A lack of empirical evidence impedes assessment of the spatial and temporal extent of critical conditions for recurring high turbidity in large wind-exposed shallow lakes. Here spatiotemporal variation in total suspended matter (TSM) concentration was captured by processing 30 Envisat Medium Resolution Imaging Spectrometer (MERIS) images of a shallow lake (Markermeer) with a spectral matching algorithm. The TSM maps showed elevated downwind concentrations for moderate winds (from 4 to 9 m s−1), which occur 68% of the time. Regressions confirmed the relationship between hourly averaged wind speed and TSM. To explore critical conditions for resuspension, wind speed, linear fetch, and water depth were combined in a spatial model based on simplified linear wave equations. Remotely sensed TSM patterns matched predicted areas of resuspension from these wave equations. On average, over 70% of cells were true positive or negative, with elevated TSM matching the predicted resuspending bottom area and background TSM matching no resuspension. Images acquired during moderate winds register local resuspension. This implies that under these conditions, a critical shear stress threshold for resuspension is passed, followed by upward mixing over the few meters of water column. Images acquired during low wind speeds (≤3 m s−1) either do not show a TSM pattern or display settling because it takes several hours of low wind before all particles are removed from the visible top layer. Because of the good spatial matching, the resuspension model can also be used for future verification of the retrieval capacity of the spectral matching algorithm.

Description: Flash floods are an important component of the semiarid hydrological cycle, and provide the potential for groundwater recharge as well as posing a dangerous natural hazard. A number of catchment models have been applied to flash flood prediction; however, in general they perform poorly. This study has investigated whether the incorporation of light detection and ranging (lidar) derived data into the structure of a 1-D flow routing model can improve the prediction of flash floods in ephemeral channels. Two versions of this model, one based on an existing trapezoidal representation of cross-section morphology (K-Tr), and one that uses lidar data (K-Li) were applied to 5 discrete runoff events measured at two locations on the main channel of The Walnut Gulch Experimental Watershed, United States. In general, K-Li showed improved performance in comparison to K-Tr, both when each model was calibrated to individual events and during an evaluation phase when the models (and parameter sets) were applied across events. Sensitivity analysis identified that the K-Li model also had more consistency in behavioral parameter sets across runoff events. In contrast, parameter interaction within K-Tr resulted in poorly constrained behavioral parameter sets across the multidimensional parameter space. These results, revealed with a modeling focus on the structure of a particular element of a distributed catchment model, suggest that lidar derived cross-section morphology can lead to improved, and more robust flash flood prediction.

Description: Organic waste applications to soil (manure, various wastewaters, and biosolids) are among the most significant sources of bacterial contamination in surface and groundwater. Transport of bacteria through the vadose zone depends on flow path geometry and stability and is mitigated by interaction between soil, soil solution, air-water interfaces, and characteristics of microbial surfaces. After initial entry, the transport through soil depends on continued entrainment of bacteria and resuspension of those retained in the porous structure. We evaluated the retention of bacteria-sized artificial microspheres, varying in diameter and surface charge and applied in different suspending solutions, by a range of sieved soils contained in minicolumns, the transport of hydrophobic bacteria-sized microspheres through undisturbed soil columns as affected by waste type under simulated rainfall, and the field-scale transport of Enterococcus spp. to an unconfined sandy aquifer after the application of liquid manure. Microsphere retention reflected microsphere properties. The soil type and suspending solution affected retention of hydrophilic but not hydrophobic particles. Retention was not necessarily facilitated by manure-microsphere-soil interactions but by manure-soil interactions. Undisturbed column studies confirmed the governing role of waste type on vadose-zone microsphere transport. Filtration theory applied as an integrated analysis of transport across length scales showed that effective collision efficiency depended on the distance of travel. It followed a power law behavior with the power coefficient varying from ∼0.4 over short distances to 〉0.9 over 1 m (i.e., very little filtration for a finite fraction of biocolloids), consistent with reduced influence of soil solution and biocolloid properties at longer travel distances.

Description: Reflectance spectra of carbonate minerals in the shortwave infrared (SWIR) and thermal infrared (TIR) wavelength regions contain a number of diagnostic absorption features. The shape of these features depends on various physical and chemical parameters. To accurately identify carbonate minerals or rocks in pure and mixed form, it is necessary to analyze the effects of the parameters on spectral characteristics. In this study, we analyzed spectral absorption feature characteristics of calcite and dolomite in the SWIR (features at 2.3 and 2.5 μm) and TIR (features at 11.5 and 14 μm) wavelength regions, as a function of grain size and carbonate mineral mixtures. Results showed that varying grain sizes and mineral contents in the sample, influence reflectance values and absorption feature characteristics. Absorption band positions of pure and mixed calcite and dolomite in the SWIR and TIR regions for both features were displaced slightly as observed in previous studies. The band positions of calcite and dolomite varied relative to grain size only in the TIR region. These positions shifted to longer wavelengths for the feature at 11.5 μm and to shorter wavelengths for the feature at 14 μm from fine to coarse grain size. The band positions of calcite-dolomite mixtures in the SWIR and TIR regions were determined by the quantity of calcite and dolomite in the sample. These results can be applied for the identification of pure and mixed calcite and dolomite, as well as estimating the relative abundance of both minerals with different grain size and mineral mixtures in a synthetic sample or rock. They can also be used as a preliminary proxy for assessing dolomitization patterns in carbonate rocks.

Description: The partitioning of available energy into dissipative fluxes over land surfaces is dependent on the state variable of the surface energy balance (land surface temperature) and the state variable of the surface water balance (soil moisture). The direct measurement of the turbulent fluxes is achieved with in situ instruments at tower sites. These point-scale measurements are sparsely distributed. Broader scale mapping of the turbulent fluxes is mostly dependent on land surface temperature (LST) and optical/infrared vegetation that can be sensed remotely. There are several data assimilation approaches currently in use that intake sequences of daytime LST that attain different diurnal amplitudes depending on available energy and the relative efficiency of surface energy balance to infer the magnitude of surface flux components such as latent and sensible heat flux. In this study we perform stability analysis on the evolution of LST in order to provide insights into the physical bases for why LST variations can be used to diagnose surface energy balance (SEB) components. The derived relative efficiencies of SEB components in dissipating available energy at the land surface are tested using two field experiment measurements. The results show that the theoretically derived relative efficiencies of SEB components agree well with field observations. The study provides insight into how LST sequences implicitly contain the signature of partitioning of available energy among SEB components and can be used to infer their magnitudes.

Description: Hyporheic hydrodynamics are a control on stream ecosystems, yet we lack a thorough understanding of catchment controls on these flow paths, including valley constraint and hydraulic gradients in the valley bottom. We performed four whole-stream solute tracer injections under steady state flow conditions at the H. J. Andrews Experimental Forest (Oregon, United States) and collected electrical resistivity (ER) imaging to directly quantify the 2-D spatial extent of hyporheic exchange through seasonal base flow recession. ER images provide spatially distributed information that is unavailable for stream solute transport modeling studies from monitoring wells alone. The lateral and vertical extent of the hyporheic zone was quantified using both ER images and spatial moment analysis. Results oppose the common conceptual model of hyporheic “compression” by increased lateral hydraulic gradients toward the stream. We found that the extent of the hyporheic zone increased with decreasing vertical gradients away from the stream, in contrast to expectations from conceptual models. Increasing hyporheic extent was observed with both increasing and decreasing down-valley (i.e., parallel to the valley gradient) and cross-valley (i.e., from the hillslope to the stream, perpendicular to the valley gradient) hydraulic gradients. We conclude that neither cross-valley nor down-valley hydraulic gradients are sufficient predictors of hyporheic exchange flux nor flow path network extent. Increased knowledge of the controls on hyporheic exchange, the temporal dynamics of exchange flow paths, and their the spatial distribution is the first step toward predicting hyporheic exchange at the scale of individual flow paths. Future studies need to more carefully consider interactions between spatiotemporally dynamic hydraulic gradients and subsurface architecture as controls on hyporheic exchange.

Description: High latitude drainage basins are experiencing increases in temperature higher than the global average with snowmelt dominated basins most sensitive to effects in winter due to snowpack's integration of these changes over the season. This may influence the timing of snowmelt onset, the melt-refreeze period, and snowpack accumulation resulting in changes in spring runoff, associated flooding, and drought conditions later in the year, possibly enhancing forest fire potential. Large burned areas cleared of vegetation change discharge dynamics and may affect snowmelt characteristics and discharge in subsequent seasons. Correlations are tested by comparing forest fire occurrence with spring melt onset, the end of melt-refreeze period (after which snow rapidly depletes) and early snowmelt events. Snow characteristics are derived from brightness temperature (T b ) data from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) for 2003–2010. Dates of melt onset, end of melt-refreeze, and early melt events are defined with T b and diurnal amplitude variation thresholds. Areas and intensities of forest fires are from MODIS thermal anomaly data (MOD14) and all data are mapped to an EASE-grid to assess spatial correlations. Earlier melt onset and end of melt-refreeze are found in years and areas of high forest fire occurrence by comparing high (2004–2005) and low (2006–2007) fire years in the Porcupine sub-basin of the Yukon River in northeastern Alaska and the Yukon Territory. The burned areas also correlate with relatively later melt onset and later end of melt-refreeze in subsequent low fire years. Copyright © 2012 John Wiley & Sons, Ltd.

Description: We tested a set of biogenic gas traps combined with time-lapse cameras to investigate the heterogeneous nature of biogenic gas ebullition events in subtropical peat soils at both the laboratory and field scale. The main findings are: (1) ebullition events in peat soils are highly heterogeneous; (2) estimates of flux rate are directly influenced by temporal scale of measurement with rapid (i.e., hourly) releasing events exceeding daily averages by one order of magnitude; and (3) increases in atmospheric pressure result in gas release from shallow peat soils into the atmosphere (i.e., ebullition), as indicated by a positive linear relation between changes in biogenic gas content and changes in atmospheric pressure. These results suggest that biogenic gas releases from shallow subtropical peat soils are not constant with larger than average daily fluxes being potentially released within hours during periods of increased atmospheric pressure. Furthermore, this study also shows the potential of time-lapse cameras for autonomously assessing the temporal variation in biogenic gas flux to the atmosphere from peatlands, and questions what temporal scale of measurement should be appropriate to infer dynamics of biogenic gas release in peat soils.

Description: The prevention of flood risks and the effective planning and management of water resources require river flows to be continuously measured and analyzed at a number of stations. For a given station, a hydrograph can be obtained as a graphical representation of the temporal variation of flow over a period of time. The information provided by the hydrograph is essential to determine the severity of extreme events and their frequencies. A flood hydrograph is commonly characterized by its peak, volume, and duration. Traditional hydrological frequency analysis (FA) approaches focused separately on each of these features in a univariate context. Recent multivariate approaches considered these features jointly in order to take into account their dependence structure. However, all these approaches are based on the analysis of a number of characteristics and do not make use of the full information content of the hydrograph. The objective of the present work is to propose a new framework for FA using the hydrographs as curves: functional data. In this context, the whole hydrograph is considered as one infinite-dimensional observation. This context allows us to provide more effective and efficient estimates of the risk associated with extreme events. The proposed approach contributes to addressing the problem of lack of data commonly encountered in hydrology by fully employing all the information contained in the hydrographs. A number of functional data analysis tools are introduced and adapted to flood FA with a focus on exploratory analysis as a first stage toward a complete functional flood FA. These methods, including data visualization, location and scale measures, principal component analysis, and outlier detection, are illustrated in a real-world flood analysis case study from the province of Quebec, Canada.

Description: Watersheds are drained by river networks, which route materials and energy from headwaters to terminal water bodies. River networks likewise perfuse the terrestrial portion of watershed ecosystems and reroute some of these materials upslope via material exchange between rivers and land. Here we develop a model of resource exchange between rivers and watersheds to predict the spatial extent of material and nutrient fluxes from aquatic portions of watershed ecosystems. The model is based on a geomorphic template that includes river network structure, topography, and channel sinuosity as well as important biological attributes (productivity and dispersal ability). Analysis of this model suggests that the geomorphic template strongly influences the spatial extent of resource flows in watershed ecosystems. The geomorphic template also predicts the location of areas of concentrated resource exchange, typically at ridge crests, in meander bends, and tributary junctions. We contend that these areas represent hotspots of foraging activity for terrestrial consumers, especially those at the reach scale (meander bends). More generally, our model suggests that the spatial extent of aquatic resource flow equal in magnitude to 20% or greater of terrestrial production may encompass as much as 20%–50% of terrestrial portions of watersheds. Resource flow from rivers to terrestrial ecosystems is not merely an edge effect. Instead, the river network may reroute a substantial flux of materials into watershed ecosystems.

Description: High resolution topography, e.g. 1-meter Digital Elevation Model (DEM) from LiDAR (Light Detection and Ranging), offers opportunity for accurate identification of topographic features of relevance for hydrologic and geomorphologic modeling. Yet, the computation of some derived topographic properties, such as the Topographic Index (TI), is characterized by daunting challenges, which hamper the full exploration of topography-based models. Particular problems, for example, arise when a distributed (or semi-distributed) rainfall-runoff model is applied to high-resolution DEMs. Indeed, the characteristic dependency between landscape resolution and the computed TI distribution results in the formation of un-physical, unconnected saturated zones, which in turn cause unrealistic representation of rainfall-runoff dynamics. In this study we present a methodology based on a multi-resolution wavelet transformation which, by means of a soft-thresholding scheme on the wavelet coefficients, filters the noise of high resolution topography to construct regularized sets of locally smoother topography on which the TI is computed. While the methodology needs a somewhat arbitrary definition of the wavelet coefficients threshold, our study shows that when the information content (entropy) of the TI distribution is used as filtering efficiency metric, a critical threshold automatically emerges in the landscape reconstruction. The methodology is demonstrated using 1- m LiDAR data for the Elder Creek River basin in California. While the proposed case study uses a TOPMODEL approach, the methodology can be extended to different topography-based models and is not limited to hydrological applications. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Leakage from geologic carbon sequestration (GCS) sites is inherently challenging to study because CO2, driven by buoyant forces, travels over long distances, undergoing phase changes and encountering numerous connate brine and formation chemistries as it rises to the surface. This work explores the effect that CO2 has on the rheological properties of brine solutions over a range of GCS-relevant temperature, pressure, ionic strength, and shear conditions. Under the fluid-liquid equilibrium conditions that prevail in the deep subsurface, viscosity of CO2-brine mixtures was found to be a function of temperature and pressure alone. Once leakage conditions ensue, discrete CO2 bubbles form in brine, resulting in the vapor-liquid equilibrium (VLE), and these mixtures exhibit complex linear viscoelastic, time dependent, and thixotropic behavior. The presence of CO2(g) bubbles on the flow of the bulk fluid could have important impacts on impeding (via shear drag force) leakage depending on the geometrical, geochemical and geophysical characteristics of a storage site. Under VLE conditions, the effective viscosity of CO2-brine mixtures was found to be up to five times higher than brine alone but the microstructure was easily destroyed, and not readily regained, under high shear conditions. At higher temperatures and higher ionic strength, the effect is less pronounced. These results were considered in the context of flow through porous media, and the effect on buoyancy-driven flow is significant. Understanding this effect is important for developing an accurate constitutive relationship for leaking CO2, which will lead to better capacity to select and monitor GCS sites.

Description: Uncertainty communication is an important topic within hydrological forecasting. Hydrological ensemble prediction systems are established tools for the generation of forecasts including uncertainty information. The interpretation of such forecasts requires new visualization and verification tools to help forecasters and end-users in their decision making. While the visualization of hydrographs is important for estimating flood volumes, little support is provided for the interpretation of peak-flow forecasts. We introduce the “Peak-Box”, a novel visual support that envelops all ensemble peak-timings and peak-discharge, from which specific verification metrics are defined. A user-defined metric quantifies the sharpness concerning peak-timing and peak-discharge and allows communicating a-priori, if the spread of peak-forecasts is acceptable. 18 months of ensemble predictions for four basins have been evaluated. A probabilistic verification which relies on the relationships between the spread and the ROC area indicates the quality of the ensemble predictions in all basins. A sub-sample of 485 events was used for exploring the value of the “Peak-Box”. The combined spread of forecast peak-time and peak-discharge is higher than a tailored reference sharpness for most of the considered events. We show that, depending on the lead-time of the forecasts, 30% to 55% of the observed peaks are found outside the predicted range. Most correct forecasts (hits) were obtained for forecasts having a lead-time of 2 or more days. Further analyses indicate that the median of the ensemble-peak forecast provides reliable estimates on either peak-timing or peak-discharge in more than 80% of the events evaluated. Finally, a score system was defined in order to combine different verification measures and obtain an overall assessment on the quality of both the peak-discharge and peak-timing of the ensemble forecasts. We demonstrate that the “Peak-Box” can be adopted in different ways in order to obtain quantitative and qualitative insights on the quality of peak-forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Fish mortality in the middle reaches of the Pilcomayo River (Bolivia), locally called ‘borrachera’, can be observed almost every year at the onset of the rainy season. In order to study the potential causes of the ‘borrachera’, suspended sediment (SS) and selected water quality parameters have been monitored from mid-September until mid-December 2010. Gill samples were taken and analysed, before and during the ‘borrachera’ event on December 7th 2010. Data on river discharge were obtained from a database. During the sampling period the river hydrology changed dramatically. At the day of the ‘borrachera’ heavy rains in upstream reaches of the river catchment changed the river from a quiet stream into a turbulent river with extremely high concentrations of suspended sediment (SS) (〉 100 g l -1 ). This may be caused by the inundation of the entire riverbed, which causes easily erodible material, left on the riverbanks at the end of the former rainy season, to be transported by the river during the first peak discharges. As concentrations of heavy metals in filtered water samples did not show higher values during the ‘borrachera’ it is concluded that the ‘borrachera’ is unlikely to be caused by heavy metal toxicity. Results showed a strong association between the SS concentration and the ‘borrachera’. Gills of fish collected during the ‘borrachera’ were clogged with sediment to such an extent that oxygen uptake became virtually impossible. High SS concentrations are therefore considered to be the cause of this typical fish mortality phenomenon. Copyright © 2012 John Wiley & Sons, Ltd.

Description: This paper presents a method that uses high-resolution multispectral and thermal infrared imagery from airborne remote sensing for estimating two model parameters within the two-zone in-stream temperature and solute (TZTS) model. Previous TZTS modeling efforts have provided accurate in-stream temperature predictions; however, model parameter ranges resulting from the multiobjective calibrations were quite large. In addition to the data types previously required to populate and calibrate the TZTS model, high-resolution, remotely sensed thermal infrared (TIR) and near-infrared, red, and green (multispectral) band imagery were collected to help estimate two previously calibrated parameters: (1) average total channel width (BTOT) and (2) the fraction of the channel comprising surface transient storage zones (β). Multispectral imagery in combination with the TIR imagery provided high-resolution estimates of BTOT. In-stream temperature distributions provided by the TIR imagery enabled the calculation of temperature thresholds at which main channel temperatures could be delineated from surface transient storage, permitting the estimation of β. It was found that an increase in the resolution and frequency at which BTOT and β were physically estimated resulted in similar objective functions in the main channel and transient storage zones, but the uncertainty associated with the estimated parameters decreased.

Description: The estimation of surface heat fluxes based on the assimilation of land surface temperature (LST) has been achieved within a variational data assimilation (VDA) framework. Variational approaches require the development of an adjoint model, which is difficult to derive and code in the presence of thresholds and discontinuities. Also, it is computationally expensive to obtain the background error covariance for the variational approaches. Moreover, the variational schemes cannot directly provide statistical information on the accuracy of their estimates. To overcome these shortcomings, we develop an alternative data assimilation (DA) procedure based on ensemble Kalman smoother (EnKS) with the state augmentation method. The unknowns of the assimilation scheme are neutral turbulent heat transfer coefficient (that scales the sum of turbulent heat fluxes) and evaporative fraction, EF (that represents partitioning among the turbulent fluxes). The new methodology is illustrated with an application to the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) that includes areal average hydrometeorological forcings and flux observations. The results indicate that the EnKS model not only provides reasonably accurate estimates of EF and turbulent heat fluxes but also enables us to determine the uncertainty of estimations under various land surface hydrological conditions. The results of the EnKS model are also compared with those of an optimal smoother (a dynamic variational model). It is found that the EnKS model estimates are less than optimal. However, the degree of suboptimality is small, and its outcomes are roughly comparable to those of an optimal smoother. Overall, the results from this test indicate that EnKS is an efficient and flexible data assimilation procedure that is able to extract useful information on the partitioning of available surface energy from LST measurements and eventually provides reliable estimates of turbulent heat fluxes.

Description: Improvements in our ability to model runoff from glaciers remain an important scientific goal. This paper describes a new temperature-radiation-index glacier melt model specifically enhanced for use in High-Arctic environments, utilising high temporal and spatial resolution datasets while retaining relatively modest data requirements. The model employs several physically constrained parameters and was tuned using a lidar-derived surface elevation model of Midtre Lovénbreen, meteorological data from sites spanning ~70% of the glacier's area-altitude distribution, and periodic ablation surveys during the 2005 melt season. The model explained 80% of the variance in observed ablation across the glacier, an improvement of ~40% on a simplified energy balance model (EBM), yet equivalent to the performance of a full EBM employed at the same location. Model performance was assessed further by comparing potential and measured runoff from the catchment, and through application to an earlier (2004) melt season. The additive model form and consideration of a priori parameters for the Arctic locality were shown to be beneficial, with a planimetry correction eliminating systematic errors in potential runoff. Further parameterisations defining modelled incident radiation failed to yield significant improvements to model output. Our results suggest that such enhanced melt models may perform well for singular melt seasons, yet are highly sensitive to the choice of lapse rates and their transferability to different locations and seasons may be limited. While modelling ablation requires detailed consideration of the transition between snow- and ice-melt, our study suggests that description of the ratio between radiative and turbulent heat fluxes may provide a useful step towards dynamic parameterisation of melt factors in temperature-index models. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Hemispherical photographs of forest canopies can be used to develop sophisticated models that predict incident below canopy shortwave radiation on the surface of interest (i.e. soil, water). Hemispherical photographs were collected on eight dates over the course of a growing season to estimate leaf area index (LAI) and to quantify solar radiation incident on the surface of two stream reaches based on output from Gap Light Analyzer and Hemisfer software. Stream reaches were shaded by a mixed-deciduous Ozark border forested riparian canopy. Hemispherical photo model results were compared to observed solar radiation sensed at climate stations adjacent to each stream reach for the entire 2010 water year. Modeled stream-incident shortwave radiation was validated with above-stream pyranometers for the month of September. On average, the best hemispherical photo models underestimated daily averages of solar radiation by approximately 14 % and 12 % for E-W and N-S flowing stream reaches, respectively (44.7 W/m 2 measured vs. 38.4 W/m 2 modeled E-W, 46.8 W/m 2 vs. 41.1 W/m 2  N-S). The best hemispherical photo models overestimated solar radiation relative to in-stream pyranometers placed in the center of each stream reach by approximately 7% and 17% for E-W and N-S stream reaches respectively (31.3 W/m 2 measured vs. 33.5 W/m 2 modeled E-W, 31.5 W/m 2 vs. 37.1 W/m 2  N-S). The model provides a geographically transferable means for quantifying changes in the solar radiation regime at a stream surface due to changes in canopy density through a growing season, thus providing a relatively simple method for estimating surface and water heating in canopy altered environments (e.g. forest harvest). Copyright © 2012 John Wiley & Sons, Ltd.

Description: An ensemble Kalman Filter (EnKF) is developed to identify a hydraulic conductivity distribution in a heterogeneous medium by assimilating solute concentration measurements of solute transport in the field with a steady state flow. A synthetic case with the mixed Neumann/ Dirichlet boundary conditions is designed to investigate the capacity of the data assimilation methods to identify a conductivity distribution. The developed method is demonstrated in 2-D transient solute transport with two different initial instant solute injection areas. The influences of the observation error and model error on the updated results are considered in this study. The study results indicate that the EnKF method will significantly improve the estimation of the hydraulic conductivity field by assimilating solute concentration measurements. The larger area of the initial distribution and the more observed data obtained, the better the calculation results. When the standard deviation of the observation error varies from 1% to 30% of the solute concentration measurements, the simulated results by the data assimilation method do not change much, which indicates that assimilation results are not very sensitive to the standard deviation of the observation error in this study. When the inflation factor is more than 1.0 to enlarge the model error by increasing the forecast error covariance matrix, the updated results of the hydraulic conductivity by the data assimilation method are not good at all. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Hyporheic and groundwater fluxes typically occur together in permeable sediments beneath flowing stream water. However, streambed water fluxes quantified using the thermal method are usually interpreted as representing either groundwater or hyporheic fluxes. Our purpose was to improve understanding of co-occurring groundwater and hyporheic fluxes using streambed temperature measurements and analysis of one-dimensional heat transport in shallow streambeds. First, we examined how changes in hyporheic and groundwater fluxes affect their relative magnitudes by reevaluating previously published simulations. These indicated that flux magnitudes are largely independent until a threshold is crossed, past which hyporheic fluxes are diminished by much larger (1000-fold) groundwater fluxes. We tested accurate quantification of co-occurring fluxes using one-dimensional approaches that are appropriate for analyzing streambed temperature data collected at field sites. The thermal analytical method, which uses an analytical solution to the one-dimensional heat transport equation, was used to analyze results from a numerical heat transport model, in which hyporheic flow was represented as increased thermal dispersion at shallow depths. We found that co-occurring groundwater and hyporheic fluxes can be quantified in streambeds, although not always accurately. For example, using a temperature time series collected in a sandy streambed, we found that hyporheic and groundwater flow could both be detected when thermal dispersion due to hyporheic flow was significant compared to thermal conduction. We provide guidance for when thermal data can be used to quantify both hyporheic and groundwater fluxes, and we show that neglecting thermal dispersion may affect accuracy and interpretation of estimated streambed water fluxes.

Description: Residual non-wetting phase saturation and wetting-phase permeability were measured in three limestones and four sandstones ranging in porosity from 0.13 to 0.28 and in absolute permeability from 2 × 10−15 to 3 × 10−12 m2. This paper focuses on the residual state established by waterflooding at low capillary number from minimum water saturation achieved using the porous plate technique, which yields the maximum residual under strongly water-wet conditions. The pore coordination number and pore body-throat aspect ratio of each rock were estimated using pore networks extracted from X-ray microtomography images of the rocks. Residual saturation decreases with increasing porosity, with no apparent difference in magnitude between the limestones and sandstones at a given porosity. Thus intraparticle/intra-aggregate microporosity does not significantly alter the efficiency of capillary trapping in the rocks considered presently. Residual saturation broadly decreases as conditions become less favorable for snap-off, i.e., with decreasing pore aspect ratio and increasing coordination number. The measured residual saturations imply that capillary trapping may be an effective mechanism for storing carbon dioxide in both sandstones and carbonates provided that the systems are strongly water-wet.

Description: This study was designed (1) to explore the links between climate variability and the population dynamics of closed-basin surface water bodies of the Prairie Pothole Region (PPR) in North America, and (2) to test the validity of space-for-time (SFT) substitution approach for the analysis of hydrologic systems. Observational results from 1981 to 2000 show that the climate with respect to annual residual moisture (ε, i.e., precipitation minus potential evaporation or evapotranspiration) of the PPR changed across space (over 0.6 m) and time (over 0.3 m in central North Dakota), causing spatiotemporal variability in water areas and water body numbers. Spatial analysis of a suite of surface water complexes along a spatial ε gradient in the Missouri Coteau shows that a four parameter Boltzmann function quantitatively describes how the number of water bodies (N) varied as a function of 5-year average annual ε (R2 = 0.76). Temporal analysis of monthly N data (1931–2005) reconstructed by a hydrologic model also demonstrates that values of temporally varying N were highly correlated with ε and yielded a nearly identical Boltzmann function. This result confirms the validity of SFT substitution and suggests that detailed modern spatial data can be used to interpret hydrologic system behaviors under past or future climate conditions. This study also has important regional-scale implications for water resources management by providing a complete picture of the spatiotemporal water body distribution across the entire PPR and the potential for rapidly converting climate predictions into surface water assessments.

Description: Reference evapotranspiration ( ET 0 ) is an important element in the water cycle that integrates atmospheric demands and surface conditions, and analysis of changes in ET 0 is of great significance for understanding climate change and its impacts on hydrology. As ET 0 is an integrated effect of climate variables, increases in air temperature should lead to increases in ET 0 . However, this effect could be offset by decreases in vapor pressure deficit, wind speed and solar radiation which lead to the decrease in ET 0 . In this study, trends in the Penman–Monteith ET 0 at 80 meteorological stations during 1960–2010 in the driest region of China (Northwest China) were examined. The results show that there was a change point for ET 0 series around the year 1993 based on the Pettitt's test. For the region average, ET 0 decreased from 1960 to 1993 by −2.34 mm yr -2 , while ET 0 began to increase since 1994 by 4.80 mm yr -2 . A differential equation method based on FAO Penman–Monteith formula was used to attribute the change in ET 0 . The attribution results show that the significant decrease in wind speed dominated the change in ET 0 , which offset the effect of increasing air temperature and led to the decrease in ET 0 from 1960 to 1993. However, wind speed began to increase and the amplitude of increase in air temperature also rose significantly since the mid-1990s. Increases in air temperature and wind speed together reversed the trend in ET 0 and led to the increase in ET 0 since 1994. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Wildfire can cause substantial changes to runoff, erosion and downstream sediment delivery processes. In response to these disturbance effects, the main sources of sediment transported within burned catchments may also change. Sediment tracing offers an approach to determine the proportional contributions of fine sediment (typically 〈63 µm) from burned catchment sources. In this paper, we review the application of various sediment tracers to discriminate fine sediment sources following wildfire. Fallout radionuclides provide the most effective tracers for discriminating hillslope surface and sub-surface (usually channel bank) sources. Previous tracer studies quantifying contributions from these sources after wildfire are based exclusively on radionuclides. The potential for fallout radionuclides to discriminate spatial sources defined according to burned and unburned areas depends on burn-related changes in surface soil concentrations. Tracing of burned and unburned source areas will be problematic where most radionuclides in surface material are bound to ash rather than soil. Geochemical properties of surface soils are probably too susceptible to natural and burn-related variability to consistently discriminate burn-defined spatial sources. Mineral magnetic properties have shown potential for discriminating soil burned at different severities as well as unburned areas. More research is needed to assess the use of soil organic compounds as tracers of burned source areas. Linking fallout radionuclide-based hillslope and channel source discrimination with process measurements and monitoring after fire can provide enhanced insight into fine sediment transfer and related water quality impacts. Adopting such integrated and multi-scale approaches would contribute to improved understanding of hydrological and geomorphological responses to wildfire. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Suspended matter is an important indicator of water quality in freshwater systems. The flood-induced turbidity current plays a dominant role in the seasonal dynamic of suspended matter in Liuxihe reservoir (23°45′50″N; 113°46′52″E), a large, stratified reservoir at the Tropic of Cancer in southern China. Field measurements show that loading and distribution of suspended matter in the reservoir differ in typical wet, dry and medium years, as a result of different discharge volumes and water level variation patterns. Using historical data and the practical demand for water supply and flood control, we generalized two feasible reservoir operational modes: flood impounding mode (drawing down the reservoir to a low level before flood events to impound inflow during the flooding season) and moderate level change mode (drawing down the reservoir to a moderate level before flood events, then keeping the level within the flood control level during runoff events). To examine the effects of different operational modes and outlet depths on the reservoir's flood-induced turbidity current, a numerical simulation model was applied in three types of hydrological conditions. The results show that the mode with moderate drawdown and recharge processes can decrease loading of suspended matter in spring and promote turbidity current release during flood events, and upper withdrawal can improve the effects of turbid water release. We suggest that more attention should be focused on water quality management in the reservoir operation stage, severe artificial water level fluctuation being avoided and selective withdrawal becoming an optional management measure. Copyright © 2012 John Wiley & Sons, Ltd.

Description: In recent years, the Xitiaoxi river basin in China has experienced intensified human activity, including city expansion and increased water demand. Climate change also has influenced streamflow. Assessing the impact of climate variability and human activity on hydrological processes is important for water resources planning and, management, and for the sustainable development of eco-environmental systems. The non-parametric Mann-Kendall test was employed to detect the trends of climatic and hydrological variables. The Mann-Kendall-Sneyers test and the moving t-test were used to locate any abrupt change of annual streamflow. A runoff model, driven by precipitation and potential evapotranspiration, was employed to assess the impact of climate change on streamflow. A significant downward trend was detected for annual streamflow from 1975 to 2009, and an abrupt change occurred in 1999, which was consistent with the change detected by the double mass curve test between streamflow and precipitation. The annual precipitation decreased slightly, but upward trends of annual mean temperature and potential evapotranspiration were significant. The annual streamflow during the period 1999-2009 reduced 26.19% compared with the reference stage, 1975-1998. Climate change was estimated to be responsible for 42.8% of the total reduction in annual streamflow, and human activity accounted for 57.2%. Copyright © 2012 John Wiley & Sons, Ltd.

Description: This study is aimed at quantifying the difference in aquifer's response to recharge between some different locations in a fan aquifer and a delta aquifer for a preliminary study of revealing mechanisms of water transport in alluvial aquifer. The aquifer's response to recharge is statistically quantified with the two viewpoints: (1) timing and volume of recharge and (2) time length of aquifer's holdig water. For the first point, a statistical model that links precipitation and groundwater level is introduced, and its parameters are identified using correlation analysis. Our results show that the recharge rate at the toe is higher than both that at the apex and that at the delta. For the second point, the concept of “memory effect” of aquifer is adopted and quantified using the autocorrelation and spectral analyses. Our results show that the memory effect is longer at the toe of fan than at the apex, and thus a temporary increase of water level has about five-times as long-term influence on subsequent water levels at the toe of the fan as at the apex. This study demonstrates that the statistical analyses and modeling of hydrological data are useful for characterizing aquifer's hydrodynamics. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Climate change due to global warming is a public concern in Central Asia. Due to specific orography and climate conditions, the republic of Tajikistan is considered as the main glacial center of Central Asia. In this study regional climate change impacts in the two large basins of Tajikistan, Pyanj and Vaksh River basins located in the upstream sector of the Amu Darya River basin are analyzed. A statistical regression method with Model Output Statistics corrections using the ground observation data, Willmott archived dataset and GSMaP satellite driven dataset, was developed and applied to the basins in order to downscale the Global Climate Model Projections at a 0.1 degree grid and to assess the regional climate change impacts at subbasin scale. It was found that snow and glacier melting are of fundamental importance for the state of the future water resources and flooding at the target basins since the air temperature had a clearly increasing trend toward the future. It was also found that the snowfall will decrease but the rainfall will increase due to the gradual increase in the air temperature. Such changes may result in an increase in flash floods during the winter and the early spring, and in significant changes in the hydrologic regime during a year in the future. Furthermore, the risks of floods in the target basins may be slightly increasing due to the increase in the frequencies and magnitudes of high daily precipitation and the increase in the rapid snowmelt with high air temperatures toward the future. Copyright © 2012 John Wiley & Sons, Ltd.

Description: For many practical reasons, the empirical black-box models have become an increasingly popular modeling tool for river-flow forecasting, especially in mountainous areas where have a very few meteorological observatories. In this paper, precipitation data is employed as the only input to estimate river flow. Using five empirical black-box models—the simple linear model (SLM), the linear perturbation model (LPM), the linearly varying gain factor model (LVGFM), the constrained non-linear system model (CNLSM) and the nonlinear perturbation model ( NLPM-API)—modeling results are compared to actual results in three catchments within the Heihe River Basin. The linearly varying gain factor model and the nonlinear perturbation model yielded excellent predictions. For better simulation accuracy, a commonly used multi-layer feed-forward neural network model (NNM) was applied to incorporate the outputs of the individual models. Comparing the performance of these models, it was found that the best results were obtained from the NNM model. The results also suggest that more reliable and precise predictions of river flow can be obtained by using the NNM model while also incorporating the combined outputs of different empirical black-box models. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Localization schemes using devices such as pilot points or anchors (localization devices) are used in inversion schemes as a tool for gleaning information from measurements that can be used to constrain inversion schemes with the added benefit in the form of a potential for reduction in the number of parameters employed in the inversion scheme. This paper proposes and demonstrates a method for strategic placement of the localization devices. The method combines stochastic singular value decomposition with parameter rejection methods to produce a map of “intensity” scores which allows the inverse modeler to place the localization devices at locations defined by their probability for producing informative, probabilistic constraints on the statistical distributions of the target variables. We also show that the method can be used for selecting measurement locations when designing data acquisition campaigns. The method is demonstrated for the case of steady state flow in a heterogeneous conductivity field using MAD (method of anchored distributions). In summary, the proposed localization scheme intends to increase the information gleaned from measurements while reducing the associated computational costs associated with stochastic inversion.

Description: Crowdsourced geodata has been proven to be a rich and major data source for environmental simulations and analysis, as well as the visualization of spatial phenomena. With the increasing size and complexity of public buildings, such as universities or hotels, there is also an increasing demand for information about indoor spaces. Trying to stimulate this growing demand, both researchers and Volunteered Geographic Information (VGI) communities envision to extend established communities towards indoors. It has already been showcased that VGI from OpenStreetMap (OSM) can be utilized for different applications in Spatial Data Infrastructures (SDIs) as well as for simple shortest path computations inside buildings. The here presented research now tries to utilize crowdsourced indoor geodata for more complex indoor routing scenarios of multiple users. Essentially, it will be investigated if, and to what extent, the available data can be utilized for performing indoor evacuation simulations with the simulation framework MATSim. That is, this paper investigates the suitability of crowdsourced indoor information from OSM (IndoorOSM) for evacuation simulations. Additionally, the applicability of MATSim for agent-based indoor evacuation simulations is conducted. The paper discusses the automatic generation simulation-related data, and provides experimental results for two different evacuation scenarios. Furthermore, limitations of the IndoorOSM data and the MATSim framework for indoor evacuation simulations are elaborated and discussed.

Description: Mathematical relationships have been developed for reaeration rate coefficient ( K a ) by various researchers. These relationships have a number of variables such as depth, velocity, width, slope, Froud number, molecular diffusion coefficient, kinematic viscosity and the gas transfer Reynolds number. From these variables, 29 relations have been developed and divided into four groups. To evaluate their predictive capability for highly variable flow rivers receiving high pollution loads form large cities, these relationships have been used to model dissolved oxygen (DO) in the River Ravi. Such rivers are either saturated with DO during high flows or anaerobic during critical low flow conditions. The evaluation is based on the agreement between model DO values calculated using K a obtained from the available equations and the measured DO concentrations in the river samples in terms of sum of square of residuals (SSR) and coefficient of determination (R 2 ). It has been found that in general, the group of equations containing depth and velocity as the only two variables affecting K a performed better than the equations in other groups as reflected by lower SSR and higher R 2 values. The study results also reveal that the turbulence based reaeration rate coefficient equation containing additional variables also resulted in close agreement between DO model results and the measured values. The study results identify, the most important parameters affecting the reaeration rate coefficient, and the suitability of various K a relationships as well for rivers with highly variable flows. Copyright © 2012 John Wiley & Sons, Ltd.

Description: In this paper, we analyze the determinants of the number of large floods reported since 1990. Using the same sample of countries as Bradshaw et al. (2007), and, like them, omitting socioeconomic characteristics from the analysis, we found that a reduction in natural forest cover is associated with an increase in the reported count of large floods. This result does not hold in any of three new analyses we perform. First, we expand the sample to include all the developing countries and all countries for which data were available but were omitted in their study. Second, and more importantly, since forest management is just one possible channel through which humans can influence reported flood frequency, we account for other important human–flood interactions. People are typically responsible for deforestation, but they are also responsible for other land use changes (e.g., urbanization), for floodplain and flood emergency management, and for reporting the floods. Thus, in our analysis we account for population, urban population growth, income, and corruption. Third, we exploit the panel nature of the data to control for unobserved country and time heterogeneity. We conclude that not only is the link between forest cover and reported flood frequency at the country level not robust, it also seems to be driven by sample selection and omitted variable bias. The human impact on the reported frequency of large floods at the country level is not through deforestation.

Description: Previously, Bárdossy and Pegram (2011) achieved downscaling of regional climate model (RCM) rainfall, dependent on circulation patterns (CPs), over 172 areas of the Rhine basin at the 25 km scale. Uneasy about the spatial statistics of the downscaled RCM rainfall, we calculated the spatial cross-correlation coefficients (CCCs) of daily rainfalls of the same set. We found that the CCCs of the RCM precipitations were significantly lower than those of the observations. CP-based downscaling led to an increase of the CCCs which still remained below the observed CCCs. This underestimation of spatial correlation, hence observed clustering, has potentially deleterious consequences for flood calculations over large areas based on RCM outputs, even after full CP-based bias elimination at the 25 km scale. In this paper we therefore describe two novel recorrelation methods designed to correct the CCCs of the RCM estimates back to those of the observed set before undertaking the final quantile-quantile transform. We use two methods of recorrelation: matrix methods and sequential regression. They both produced similar results and were successful in that they captured the observed CCCs almost exactly, coping with problems presented by the high proportion of dry days. In spite of the complete success of the recorrelation techniques (when comparing spatial correlations before and after treatment) the methodology does not solve the reconstitution problem fully: (1) extreme daily rainfall totals on large areas are not recaptured completely and (2) clustering behavior, as computed by entropy on nonoverlapping triple sites, confirms that the two-dimensional covariance dependence measure, although very effective, does not capture all of the clustering observed in natural rainfall.

Description: In analytical modeling of two-phase flow problems in porous media, the saturation profile for a fixed time can be obtained by using the method of characteristics (MOC). One of the basic assumptions in the application of the MOC is that the fractional flow is a function of saturation only. However, when gas is injected, it is often flowing under nonlinear flow conditions and inertial losses are significant in the near-well region. Therefore, in a radial displacement non-Darcy flow applies at the injection well, but as the saturation front gets further away, its velocity will decrease and the fractional flow curve will vary with the distance along the streamline. This paper presents the extension of the Buckley-Leverett analytical solution when the injected gas phase flow is governed by the two-phase extension to the Forchheimer equation and the fractional flow function depends both on the saturation and radial distance from the well. The behavior of a gas-liquid system under non-Darcy flow conditions is shown for carbon dioxide injection into saline aquifers. Finally, this analytical solution is tested against the corresponding finite difference numerical model and the limitations of the approach are discussed.

Description: We present an estimation of the permeability fields of the reservoir at the Enhanced Geothermal System (EGS) at Soultz-sous-Forêts, France, based on the data assimilation technique Ensemble Kalman Filter (EnKF). To this end, we assimilate data from a tracer circulation experiment performed in 2005. Using a 3-D numerical simulation of fluid transport and chemical tracer dispersion, we advance the tracer in time and control the concentration. With the EnKF we obtain reliable fits for concentration data recorded in both existing production boreholes, GPK2 and GPK4. As an alternative to discrete fracture networks, our heterogeneous equivalent porous medium approach thus can also characterize the hydraulically fractured zone of the engineered geothermal system. We present best estimates for permeabilities (10−14 m2–10−12 m2 for the fracture zone) and the corresponding uncertainty which is about one order of magnitude. After comparing our results to results from a massive Monte Carlo and from a gradient-based Bayesian approach, it becomes clear that only the EnKF of this three approaches is able to fit concentrations at GPK2 and GPK4 simultaneously. Based on the EnKF estimates obtained, a long-term performance prediction including an uncertainty analysis for the reservoir (as it was in 2005) yields no thermal breakthrough in the system within at least 50 years of operation. Our study demonstrates the efficiency of the EnKF when estimating the permeability distribution in an EGS reservoir even with sparse data available.

Description: Macroscale hydrologic models (MHMs) were developed to study changes in land surface hydrology due to changing climate over large domains, such as continents or large river basins. However, there are many sources of uncertainty introduced in MHM hydrological simulation, such as model structure error, ineffective model parameters, and low-accuracy model input or validation data. It is hence important to model the uncertainty arising in projection results from an MHM. The objective of this study is to present a Bayesian statistical inference framework for parameter uncertainty modeling of a macroscale hydrologic model. The Bayesian approach implemented using Markov Chain Monte Carlo (MCMC) methods is used in this study to model uncertainty arising from calibration parameters of the Variable Infiltration Capacity (VIC) MHM. The study examines large-scale hydrologic impacts for Indian river basins and changes in discharges for three major river basins with distinct climatic and geographic characteristics, under climate change. Observed/reanalysis meteorological variables such as precipitation, temperature and wind speed are used to drive the VIC macroscale hydrologic model. An objective function describing the fit between observed and simulated discharges at four stations is used to compute the likelihood of the parameters. An MCMC approach using the Metropolis-Hastings algorithm is used to update probability distributions of the parameters. For future hydrologic simulations, bias-corrected GCM projections of climatic variables are used. The posterior distributions of VIC parameters are used for projection of 5th and 95th percentile discharge statistics at four stations, namely, Farakka, Jamtara, Garudeshwar, and Vijayawada for an ensemble of three GCMs and three scenarios, for two time slices. Spatial differences in uncertainty projections of runoff and evapotranspiration for years 2056–2065 for the a1b scenario at the 5th and 95th percentile levels are also projected. Results from the study show increased mean monthly discharges for Farakka and Vijayawada stations, and increased low, mid and high duration flows at Farakka, Jamtara and Vijayawada for the future. However, it is seen that uncertainty introduced due to choice of GCM, is larger than that due to parameter uncertainty for the VIC MHM. The largest effects of runoff predictive uncertainty due to uncertainty in VIC parameters are seen in the Himalayan foothills belt, and the high-precipitation Northeast region of the country. It is demonstrated through the study that it is relevant and feasible to provide Bayesian uncertainty estimates for macroscale models in projection of large-scale and regional hydrologic impacts.

Description: Because the collection of data in water systems is important for making informed decisions, monitoring networks are designed and installed in such systems. Traditionally, the design of hydrometric monitoring networks has been concentrated on measuring streamflow/precipitation at particular key (gauged) sites so that streamflow/precipitation can be estimated accurately at ungauged sites. Although many methods take into account a set of final users of the information, there appears to be no method that explicitly considers them in the mathematical formulation of the decision-making process. This paper presents a novel approach for designing monitoring networks in a water system using the concept of value of information (VOI). This concept takes into account three main factors: (1) the belief that the decision maker has about the state of the water system before having any information; (2) the consequences associated with the decision of having to choose among several possible management actions given the state of the water system; and (3) the evaluation and update of new information when it becomes available. The methodology uses a water level time series generated by a hydrodynamic model at every computational point, each one being a potential monitor site. The method is tested in a polder system in the Netherlands, where monitoring is required to make informed decisions about the operation of a set of hydraulic structures to reduce flood impacts.

Description: Water table variation will result in considerable variation of the weight of the pore water, which has loading effects on the groundwater flow in the underlying confined aquifer. Here we present an analytical solution on such a loading effect in a coastal aquifer system consisting of an unconfined aquifer, a confined aquifer, and an impermeable layer between them, with the two lower layers extending under the sea. The solution generalizes several existing ones in the literature. The water table variation's loading effects tend to enhance the amplitude and to reduce the phase shift of the tide-induced head fluctuation. These effects become considerable when the tidal loading coefficient is large, the aquifer's offshore extending length is long, and the unconfined aquifer has large values of hydraulic conductivity and specific yield. Numerical examination indicated that the assumption of ignoring the density variation causes an error not greater than 2.5% of the tidal amplitude.

Description: Year-to-year dynamics in weather affect both the timing of application and potential hydrologic transport of pesticides. Further, most commonly used pesticides dissipate in the environment during the growing season. Interactions among these factors – hydrology, timing of application, and dissipation kinetics – hinder the detection of temporal trends in transport. It is increasingly important to be able to discern such trends, to judge effectiveness of management practices or to determine whether observed changes were caused by management or weather. In previous work, a cumulative vulnerability index (CVI) was developed to account for these three factors. It explained 63% of annual variation in atrazine load in the Goodwater Creek Experimental Watershed (GCEW). The objectives of the current work were to 1) generalize the CVI to explicitly account for variation in watershed size, area treated with atrazine, and average application rate; 2) test the overall performance on watersheds showing such variation, and 3) test whether the generalized index properly accounted for the additional input parameters. The generalized index was tested using data from GCEW (73.7 km 2 ) and 7 additional watersheds in the northeast Missouri claypan region that varied in size from 212 to 1180 km 2 and from 4% to 23% of watershed area planted to corn or sorghum. Across 32 site-years, the generalized index explained 84% of variation in annual atrazine load. Further, tests of residuals showed no dependence on either watershed area or fraction of area planted to corn and sorghum, indicating that these parameters were properly integrated into the index. The performance of the index supports the conclusion that data obtained from GCEW is representative of the Mark Twain Lake Basin and likely the entire Central Claypan Major Land Resource Area. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Since the Three Gorges Reservoir (TGR) was put into operation in June 2003, the impacts of the TGR on downstream hydrology and water resources have become the focus of public attention. This paper examines the impacts of the TGR on the hydrological droughts at the downstream Yichang hydrological station during the period of 2003-2011. The two-parameter monthly water balance (TPMWB) model was employed to generate the monthly discharges at Yichang station for the period of 2003-2011 to represent the unregulated flow regime, and thus to provide a comparison benchmark for the observed flow series at Yichang station after the operation of the TGR. To provide a reference series for the observed monthly discharge series of the entire study period of 1951-2011, the naturalized monthly discharge series at Yichang station was constructed by joining the observed monthly discharge at Yichang station for the period of 1951-2002 and the TPMWB simulated monthly runoff at Yichang station for the period of 2003-2011. For both the observed and naturalized monthly discharge series of 1951-2011, the hydrological drought index series were calculated using the standardized streamflow index ( SSI ) method. By comparing the drought indices of these two monthly discharge series, we investigated the impacts of the TGR on the hydrological droughts at the downstream Yichang station during the period of 2003-2011. The results show that the hydrological droughts at the downstream Yichang station are slightly aggravated by the TGR's initial operation from 2003 to 2011. The river flow reduction at Yichang station after impoundment of the TGR might account for the downstream drought aggravation. Copyright © 2012 John Wiley & Sons, Ltd.

Description: This paper explores the relationship between temperature, evaporation and soil moisture using a planetary boundary layer (PBL) model. It focuses on illustrating and quantifying the effect of soil moisture on the evolution of daytime temperatures. A simple convective PBL model coupled with the Penman-Monteith equation is used to estimate evapotranspiration. Following calibration and sensitivity analysis, the model was used to simulate the relative impact of dry and wet soil moisture conditions on daytime temperatures by changing the surface resistance parameter in the Penman-Monteith equation. It was found that the maximum temperature that can be reached during a day is constrained by the amount of soil moisture and the available net radiation, confirming previously published results. Higher temperatures can be reached with greater net radiation and dry soil moisture conditions. Copyright © 2012 John Wiley & Sons, Ltd.

Description: The past decade has seen significant progress in characterizing uncertainty in environmental systems models, through statistical treatment of incomplete knowledge regarding parameters, model structure, and observational data. Attention has now turned to the issue of model structural adequacy (MSA, a term we prefer over model structure “error”). In reviewing philosophical perspectives from the groundwater, unsaturated zone, terrestrial hydrometeorology, and surface water communities about how to model the terrestrial hydrosphere, we identify several areas where different subcommunities can learn from each other. In this paper, we (a) propose a consistent and systematic “unifying conceptual framework” consisting of five formal steps for comprehensive assessment of MSA; (b) discuss the need for a pluralistic definition of adequacy; (c) investigate how MSA has been addressed in the literature; and (d) identify four important issues that require detailed attention—structured model evaluation, diagnosis of epistemic cause, attention to appropriate model complexity, and a multihypothesis approach to inference. We believe that there exists tremendous scope to collectively improve the scientific fidelity of our models and that the proposed framework can help to overcome barriers to communication. By doing so, we can make better progress toward addressing the question “How can we use data to detect, characterize, and resolve model structural inadequacies?”

Description: A tracer test using both bromide and heat tracers conducted at the Integrated Field Research Challenge site in Hanford 300 Area (300A), Washington, provided an instrument for evaluating the utility of bromide and heat tracers for aquifer characterization. The bromide tracer data were critical to improving the calibration of the flow model complicated by the highly dynamic nature of the flow field. However, most bromide concentrations were obtained from fully screened observation wells, lacking depth-specific resolution for vertical characterization. On the other hand, depth-specific temperature data were relatively simple and inexpensive to acquire. However, temperature-driven fluid density effects influenced heat plume movement. Moreover, the temperature data contained “noise” caused by heating during fluid injection and sampling events. Using the hydraulic conductivity distribution obtained from the calibration of the bromide transport model, the temperature depth profiles and arrival times of temperature peaks simulated by the heat transport model were in reasonable agreement with observations. This suggested that heat can be used as a cost-effective proxy for solute tracers for calibration of the hydraulic conductivity distribution, especially in the vertical direction. However, a heat tracer test must be carefully designed and executed to minimize fluid density effects and sources of noise in temperature data. A sensitivity analysis also revealed that heat transport was most sensitive to hydraulic conductivity and porosity, less sensitive to thermal distribution factor, and least sensitive to thermal dispersion and heat conduction. This indicated that the hydraulic conductivity remains the primary calibration parameter for heat transport.

Description: In this study, a dual-permeability approach is discussed for modeling preferential flow in shrinking soils by accounting for shrinking effects on macropore and matrix domain hydraulic properties. Conceptually, the soil is treated as a dual-permeability bulk porous medium consisting of two dynamic interacting pore domains: (1) the fracture (from shrinkage) pore domain and (2) the aggregate (interparticles plus structural) or matrix pore domain. The model assumes that the swell-shrink dynamics is represented by the inversely proportional volume changes of the fracture and matrix domains, while the overall porosity of the total soil, and hence the layer thickness, remains constant. This assumption can be justified for soils with dominant horizontal soil deformation in the swelling-shrinkage process (shrinkage geometry factor, rs 〉 3). The swell-shrink dynamics was included in a one-dimensional dual-permeability model in which water flow in both domains was described with the Richards' equation. Swell-shrink dynamics was incorporated in the model partly by changing the coupled domain-specific hydraulic properties according to the shrinkage characteristics of the matrix and partly by allowing the fractional contribution of the two domains to change with the pressure head. As a first step, the hysteresis in the swell-shrink dynamics was not included. We also assumed that the aggregate behavior and its hydraulic properties depend only on the average aggregate water content and not on its internal real distribution. The model proved, describing successfully effects of shrinkage on the spatial and temporal evolution of water contents measured in a silty loam soil in the field.

Description: A new multiscale routing framework is developed and coupled with the Hydrologically based Three-layer Variable Infiltration Capacity (VIC-3L) land surface model (LSM). This new routing framework has a characteristic of reducing impacts of different scales (both in space and time) on the routing results. The new routing framework has been applied to three different river basins with six different spatial resolutions and two different temporal resolutions. Their results have also been compared to the D8-based (eight direction based) routing scheme, whose flow network is generated from the widely used eight direction (D8) method, to evaluate the new framework's capability of reducing the impacts of spatial and temporal resolutions on the routing results. Results from the new routing framework show that they are significantly less affected by the spatial resolutions than those from the D8-based routing scheme. Comparing the results at the basins' outlets to those obtained from the instantaneous unit hydrograph (IUH) method which has, in principle, the least spatial resolution impacts on the routing results, the new routing framework provides results similar to those by the IUH method. However, the new routing framework has an advantage over the IUH method of providing routing information within the interior locations of a basin and along the river channels, while the IUH method cannot. The new routing framework also reduces impacts of different temporal resolutions on the routing results. The problem of spiky hydrographs caused by a typical routing method, due to the impacts of different temporal resolutions, can be significantly reduced.

Description: We studied 34 global reservoirs for which good quality surface elevation data could be obtained from a combination of five satellite altimeters for the period from 1992 to 2010. For each of these reservoirs, we used an unsupervised classification approach using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 250 m vegetation product to estimate the surface water areas over the MODIS period of record (2000 to 2010). We then derived elevation-area relationships for each of the reservoirs by combining the MODIS-based estimates with satellite altimeter-based estimates of reservoir water elevations. Through a combination of direct observations of elevation and surface area along with documented reservoir configurations at capacity, we estimated storage time histories for each reservoir from 1992 to 2010. We evaluated these satellite-based data products in comparison with gauge observations for the five largest reservoirs in the United States (Lakes Mead, Powell, Sakakawea, Oahe, and Fort Peck Reservoir). The storage estimates were highly correlated with observations (R = 0.92 to 0.99), with values for the normalized root mean square error (NRMSE) ranging from 3% to 15%. The storage mean absolute error (expressed as a percentage of reservoir capacity) for the reservoirs in this study was 4%. The multidecadal reconstructed reservoir storage variations are in accordance with known droughts and high flow periods on each of the five continents represented in the data set.

Description: Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.

Description: Stream temperature will be subject to changes due to atmospheric warming in the future. We investigated the effects of the diurnal timing of air temperature changes – daytime warming vs. nighttime warming – on stream temperature. Using the physically-based model, Heat Source, we performed a sensitivity analysis of summer stream temperatures to 3 diurnal air temperature distributions of +4 °C mean air temperature: 1) uniform increase over the whole day; 2) warmer daytime; and 3) warmer nighttime. The stream temperature model was applied to a 37-km section of the Middle Fork John Day River in northeastern Oregon, USA. The 3 diurnal air temperature distributions generated 7-day average daily maximum (7dADM) stream temperatures increases of approximately +1.8 ±0.1 °C at the downstream end of the study section. The 3 air temperature distributions, with the same daily mean, generated different ranges of stream temperatures, different 7dADM temperatures, different durations of stream temperature changes, and different average daily temperatures in most parts of the reach. The stream temperature changes were out of phase with air temperature changes and, therefore in many places, the greatest daytime increase in stream temperature was caused by nighttime warming of air temperatures. Stream temperature changes tended to be more extreme and of longer duration when driven by air temperatures concentrated in either daytime or nighttime instead of uniformly distributed across the diurnal cycle. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Infiltration along ephemeral channels plays an important role in groundwater recharge in arid regions. A model is presented for estimating spatial variability of seepage due to streambed heterogeneity along channels based on measurements of streamflow-front velocities in initially dry channels. The diffusion-wave approximation to the Saint-Venant equations, coupled with Philip's equation for infiltration, is connected to the groundwater model MODFLOW, and is calibrated by adjusting the saturated hydraulic conductivity of the channel bed. The model is applied to portions of two large water delivery canals, which serve as proxies for natural ephemeral streams. Estimated seepage rates compare well with previously published values. Possible sources of error stem from uncertainty in Manning's roughness coefficients, soil hydraulic properties, and channel geometry. Model performance would be most improved through more frequent longitudinal estimates of channel geometry and thalweg elevation, and with measurements of stream stage over time to constrain wave timing and shape. This model is a potentially valuable tool for estimating spatial variability in longitudinal seepage along intermittent and ephemeral channels over a wide range of bedslopes, and the influence of seepage rates on groundwater levels. Copyright © 2012 John Wiley & Sons, Ltd.

Description: The overexploitation and impairment of our freshwater resources require land management strategies that support the preservation of green and blue water flow and various ecosystem services. Historical landscape analysis and the influential driving factors of landscape development provide an essential basis for tackling current environmental questions in land and water management. Hence, this paper investigates the influence of historical land use pattern on the hydrological processes and provision of blue and green water flow and storage for man and ecosystems under current climate conditions. Moreover, we discuss in how far these findings could be used to predict or optimise future land management options or as a reference for future land and water management. We used digitalized historical land use maps from 1787, 1827, 1940, 1984 and a digital land use map of present situation from 2009 for our study areas, which are two small scale Slovenian catchments (Reka and Dragonja). The integrated river basin model Soil and Water Assessment Tool (SWAT) was used to simulate the land use change impacts on blue and green water flow. The results showed for both catchments that the influence of land use change on total and green water quantity would be statistically insignificant, but would have considerable impacts on the seasonal flows. In the Reka catchment, historical situations indicate impacts on spring and summer blue and green water flow due to decreased percentage of forest and increased percentage of grassland and vineyards in the past. Results for the Dragonja catchment indicate past shift from arable land use to forest as decrease in summer green water flow and increase in blue water flow. Possible effects are also increased levels of blue water flow and decreased levels of green water flow during the growing period of the year. Copyright © 2012 John Wiley & Sons, Ltd.

Description: The scaling analysis of temporal rainfall produces very different results if one uses the entire rainfall record inclusive of rainstorms and dry interstorm periods (continuous analysis) or only intrastorm data (within-storm analysis). We show that the continuous results reflect mainly the alternation of dry and wet periods and that the rain support is not fractal. Therefore, the continuous results are spurious. This conclusion is significant since continuous analysis is the most popular scaling analysis method for rainfall. The literature on within-storm analysis is much more limited, and standard methods do not exist. We develop such methods and show how their bias can be corrected and the accuracy maximized. The results from within-storm analysis show higher intermittency (higher-intensity fluctuations) than continuous analysis. This result has important implications on downscaling and the evaluation of rainfall extremes. Frequently used multifractal models for rainfall are of the log-Levy (“universal”) type. A key parameter of those models is the stability index 0 〈 α ≤ 2, with α = 2 corresponding to lognormal models. To account for the alternation of dry and wet periods (also inside the storms), one can add a “beta component,” obtaining beta-log-Levy and beta-lognormal models. By using simulations with α = 2, we show that standard estimators of α are negatively biased and that the hypothesis of beta-lognormal multifractality inside the storms is statistically acceptable.

Description: The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models which are used within an operational real-time forecasting chain such as HQsim. The objectives of this investigation are to i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the i) Regional Sensitivity Analysis (RSA), ii) Morris analysis and iii) State Dependent Parameter (SDP) modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity while most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor ( meltfunc_max ) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.