ALBERT

Description: Land use change as conversion pasture to forest produces several changes on hydrological cycle. In this paper we analyze the effects on stream discharge of afforestation of a small watershed devoted to pasture using the HBV hydrological model. Streamflow data obtained over the first ten years after planting were employed to evaluate the capacity of HBV model to simulate hydrological behavior of catchment after afforestation. Obtained results indicate that the estimation of streamflow was accurate as reflected by statistics (R 2  = 0.90, NSC = 0.89 and PBIAS = 0.34). Afterwards, streamflow under pasture land use (if afforestation had not occurred) was simulated using hydro-meteorological data collected during the period of study and model parameters optimized previously, together with two parameters, pcorr and cevpfo , that were adjusted for pasture conditions. HBV model results indicate that afforestation produced a water yield reduction around 2000 mm (22% of total stream discharge) during the first ten years of planting growth. The differences between forest and pasture land cover are increasing in all seasons year by year. The greatest streamflow reduction was observed in wet period (autumn and winter) with 76% of total reduction. In summer, streamflow reduction represents only 3% of total, however, represents 24.7% of discharge in this season. Streamflow reduction was related to increase of rainfall interception (mainly in wet periods) and the increase of evapotranspiration by plantation in dry periods. This article is protected by copyright. All rights reserved.

Description: Air flows from the atmosphere into an unconfined aquifer when the water table falls during pumping tests. Pumping test results in unconfined aquifers may be significantly affected by low-permeability zones (LPZs) near the initial water table position because they restrict the downward movement of air. A transient, three-dimensional (3D) air-water two-phase flow model is employed to investigate numerically the effects of local heterogeneity on pumping test results in unconfined aquifers. Two cases of local heterogeneities are considered herein: a LPZ around the pumping well and on one side of the pumping well. Results show that the drawdown with the LPZ is significantly greater than that of the homogeneous aquifer. The differences in drawdown are the most significant at intermediate times and gradually diminish at later times. The LPZ significantly reduces air flow from the atmosphere to the aquifer. The pore air velocity in the LPZ is very low. The air pressure at the observation point under the LPZ when air begins to enter is significantly lower than the air pressure of the homogeneous aquifer at the same point. After that, the air pressure increases quickly and then increases slowly. The time for the air pressure to reach the atmospheric pressure is significantly longer. This article is protected by copyright. All rights reserved.

Description: Over the last half century, since logging for timber production became intensive, Borneo has lost much of its pristine tropical forests. The long-term consequences of associated decline in precipitation are evident, and might, in turn, cause much more severe deforestation. This article is protected by copyright. All rights reserved.

Description: Accepting the concept of standardization introduced by the standardized precipitation index (SPI), similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well-known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multiscalar calculation for accurate temporal and spatial comparison of the hydro-meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self-calibrated PDSI (SC-PDSI) at most analyzed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly-derived SPDI index in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and alternative for drought assessment and monitoring. This article is protected by copyright. All rights reserved.

Description: Modeled hydrologic processes are represented in a set of numerical equations, the complexity of which can be measured by the total number of variables needed. A single dominant hydrologic process could control the hydrologic response of a watershed, and so the identification of the corresponding dominant variable(s) would aid in identifying a parsimonious model and in collecting more reliable data. By accounting for both model complexity and serial correlation in the variables, a model is used to identify the dominant variables for representing watershed scale streamflow, sediment transport, and phosphorus yields. Long-term water quantity and quality data was used to show that rainfall and non-linear soil water storage were the dominant variables for weekly streamflow, suspended sediment, and particulate phosphorus. Model accuracy did not consistently improve when other statistically significant variables were included. The results suggest that improved model performance may not justify the added model complexity. As such, identification of dominant variables would be the priority for developing parsimonious hydrologic models, especially at watershed scales. This article is protected by copyright. All rights reserved.

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

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

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

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

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

Description: We applied graphical methods and multivariate statistics to understand impacts of an unsewered slum catchment on nutrients and hydrochemistry of groundwater in Kampala, Uganda. Data was collected from 56 springs (groundwater), 22 surface water sites and 13 rain samples. Groundwater was acidic and dominated by Na, Cl and NO 3 . These ions were strongly correlated indicating pollution originating from wastewater infiltration from on-site sanitation systems. Results also showed that rain, which was acidic, impacted on groundwater chemistry. Using Q-mode hierarchical cluster analysis, we identified three distinct water quality groups. The first group had springs dominated by Ca-Cl-NO 3 , low values of EC, pH and cations, and relatively high NO 3 values. These springs were shown to have originated from the acidic rains because their chemistry closely corresponded to ion concentrations that would occur from rainfall recharge, which was around 3.3 times concentrated by evaporation. The second group had springs dominated by Na-K-Cl-NO 3 and Ca-Cl-NO 3 , low pH but with higher values of EC, NO 3 and cations. We interpreted these as groundwater affected by both acid rain and infiltration of wastewater from urban areas. The third group had the highest EC values (average of 688 μS/cm), low pH and very high concentrations of NO 3 (average of 2.15 mmol/L) and cations. These springs were exclusively located in slum areas and we interpreted these springs as groundwater affected by infiltration of wastewater from poorly sanitized slums areas. Surface water was slightly reducing and eutrophic due to wastewater effluents, but the contribution of groundwater to nutrients in surface water was minimal because o-PO 4 was absent whereas NO 3 was lost by denitification. Our findings suggest that groundwater chemistry in the catchment is strongly influenced by anthropogenic inputs derived from nitrogen-containing rains and domestic wastewater. This article is protected by copyright. All rights reserved.

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

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

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

Description: We examined the water balance a forested ombrotrophic peatland and adjacent burned peatland in the boreal plain of western Canada over a three-year period. Complete combustion of foliage and fine branches dramatically increased shortwave radiation inputs to the peat surface while halting all tree transpiration at the burned site. End-of-winter snowpack was 7-25% higher at the burned site likely due to decreased ablation from the tree canopy at the unburned site. Shrub regrowth at the burned site was rapid post-fire, and shading by the shrub canopy in the burned site approached that of the unburned site within three years after fire. Site-averaged surface resistance to evaporation was not different between sites, though surface resistance in hollows was lower in the burned site. Water loss at both burned and unburned sites is largely driven by surface evaporative losses. Evaporation at the burned site marginally exceeded the sum of pre-fire transpiration and interception at the unburned site, suggesting that ET during the growing season was 2 0–40  mm greater at the the burned peatland. While the net change in water storage during the growing season was largely unchanged by fire, the lack of low-density surface peat in the burned site appears to have decreased specific yield, leading to greater water table decline at the burned site despite similar net change in storage. This article is protected by copyright. All rights reserved.

Description: The eddy covariance (EC) method was used in a 30-month study to quantify evapotranspiration (ET) and vegetation coefficient (K CW ) for a wetland on a ranch in subtropical south Florida. To evaluate the errors in ET estimates, the EC-based ET (ET C.-EC ) and the Food and Agricultural Organization (FAO) Penman-Monteith (PM) based ET (ET C.-PM ) estimates (with literature crop coefficient K C ) were compared to each other. The ET C.-EC and FAO-PM reference ET were used to develop K CW . Regression models were developed to estimate K CW using climatic and hydrologic variables. Annual and daily ET C.-EC values were 1152 mm and 3.27 mm, respectively. The FAO-PM model underestimated ET by 25% with ET C.-EC being statistically higher than ET C.-PM . The K CW varied from 0.79 (December) to 1.06 (November). The mean K CW for dry (November-April) season (0.95) was much higher than values reported for wetlands in literature, while wet (May-October) season K CW (0.97) was closer to literature values. Higher than expected K CW values during dry season were due to higher temperature, lower humidity and perennial wetland vegetation. Regression analyses showed that factors affecting the K CW were different during the dry (soil moisture, temperature, and relative humidity) and wet (net radiation, inundation, and wind speed) seasons. Separate regression models for the dry and wet seasons were developed. ET and K CW from this study, one of the first for the agricultural wetlands in subtropical environment, will help improve the ET estimates for similar wetlands. This article is protected by copyright. All rights reserved.

Description: Research on runoff processes to date has focused on the differences between the main divisions of runoff partitioning. Indeed, our major advancements in runoff theory have come with new differentiations of different forms of overland flow and subsurface stormflow. These studies of ‘how runoff processes are different’ have resulted in our current summaries of runoff regimes conceptually (e.g. the Variable Source Area (VSA) concept) and codified in our models (e.g. TOPMODEL and its derivatives). This article is protected by copyright. All rights reserved.

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

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

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

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

Description: Supraglacial channels are an important mechanism for surface water transport over the ablation zone of western Greenland. The first assessment of the spatio-temporal distribution of surface melt channels and their relationship to supraglacial lakes over the Jakobshavn Isbrae region of Western Greenland was analyzed using Landsat ETM + panchromatic images during the 2007 melt season. A total of 1188 melt channels were delineated and show an increase in the number of melt channels throughout the season, reaching a peak on August 9. Water-filled melt channels advanced to maximum elevation of 1647 m on August 9, and attained a minimum average slope of 0.009 on July 8. The ablation zone demonstrates two hydrologic modes, where crevasse and moulin terminating channels dominate at elevations 〈800 m and higher order channel networks 〉800 m. Development of higher order networks is interrupted by flow divergence due to partitioning of melt water into vertical infiltration through moulins and crevasse fields prevalent at lower elevations. Tributary and Connector networks between 800 to 1200 m in elevation are correlated with fewer lake occurrences, relatively lower surface velocities (~50 ma -1 ) and ice flow dominated by internal deformation over basal sliding. High order channels are associated with lake basins that exceed melt water storage capacity. Evolution of channel networks is coupled to changes in melt water production, runoff, and ice dynamics with implication for the englacial and subglacial environments. This article is protected by copyright. All rights reserved.

Description: This paper reviews the use of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology in the 20 years since the paper by Beven and Binley (1992) in Hydrological Processes, which is now one of the most highly cited papers in hydrology. The original conception, the on-going controversy it has generated, the nature of different sources of uncertainty and the meaning of the GLUE prediction uncertainty bounds, are discussed. The hydrological, rather than statistical, arguments about the nature of model and data errors and uncertainties that are the basis for GLUE are emphasised. The application of the IHDM model to the Gwy catchment at Plynlimon presented in the original paper is revisited, using a much larger sample of models, a wider range of likelihood evaluations and new visualisation techniques. It is concluded that there are good reasons to reject this model for that data set. This is a positive result in a research environment in that it requires improved models or data to be made available. In practice, there may be ethical issues of using outputs from models for which there is evidence for model rejection in decision making. Finally some suggestions for what is needed in the next 20 years are provided. This article is protected by copyright. All rights reserved.

Description: A short-term flood inundation prediction model has been formulated based on the combination of the super-tank model, forced with downscaled rainfall from a global numerical weather prediction model, and a one-dimensional hydraulic model. Different statistical methods for downscaled rainfall have been explored, taking into account the availability of historical data. It has been found that the full implementation of a statistical downscaling model considering physically based corrections to the numerical weather prediction model output for rainfall prediction performs better compared with an altitudinal correction method. The integration of the super-tank model into the one-dimensional hydraulic model demonstrates a minimal requirement for the calibration of rainfall-runoff and flood propagation models. Updating the model with antecedent rainfall and regular forecast renewal has enhanced the model's capabilities as a result of the data assimilation processes of the runoff and numerical weather prediction models. The results show that the predicted water levels demonstrate acceptable agreement with those measured by stream gauges and comparable to those reproduced using the actual rainfall. Moreover, the predicted flood inundation depth and extent exhibit reasonably similar tendencies to those observed in the field. However, large uncertainties are observed in the prediction results in lower, flat portions of the river basin where the hydraulic conditions are not properly analysed by the one-dimensional flood propagation model. This article is protected by copyright. All rights reserved.

Description: This study aims to analyse the combined impacts of future discharges and sea levels on erosion-sedimentation potential, and its seasonal changes, in a ~43 km long coastal river reach of South-West Finland. To our knowledge, this kind of combined study has not been performed before. In addition to surveying the present erosion-sedimentation conditions, the daily erosion-sedimentation potential is simulated with a one dimensional hydrodynamic model for the 1971–2000 and 2070–2099 periods by applying four discharge scenarios. Different sea level stages are also employed in the simulations. All scenarios forecast increasing autumn and winter discharges, but diminishing summer discharges. This indicates increasing river channel erosion, particularly during winters and autumns. Although discharge changes have altogether a greater influence on erosion-sedimentation potential, the importance of sea level changes on sedimentation is noticeable in the estuary. The rising sea level scenarios increase the sedimentation potential. In total, by 2070–2099 the erosion potential may increase in most parts of the study area. This article is protected by copyright. All rights reserved.

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

Description: Northern peatlands are a large source of atmospheric methane (CH 4 ) and both a source and sink of atmospheric carbon dioxide (CO 2 ). The rate and temporal variability in gas exchanges with peat soils is directly related to the spatial distribution of these free-phase gases within the peat column. In this paper we present results from surface and borehole ground penetrating radar (GPR) surveys – constrained with direct soil and gas sampling – that compare the spatial distribution of gas accumulations in two raised bogs: one in Wales (UK), the other in Maine (USA). Although the two peatlands have similar average thickness, physical properties of the peat matrix differ, particularly in terms of peat type and degree of humification. We hypothesize that these variations in physical properties are responsible for the differences in gas distribution between the two peatlands characterized by: 1) gas content up to 10.8 % associated with woody peat and presence of wood layers in Caribou Bog (Maine), and 2) a more homogenous distribution with gas content up to 5.7 % at the surface (i.e. 〈 0.5 m deep) in Cors Fochno (Wales). Our results highlight the variability in biogenic gas accumulation and distribution across peatlands and suggest that the nature of the peat matrix has a key role in defining how biogenic gas accumulates within, and is released to the atmosphere from, peat soils. This article is protected by copyright. All rights reserved.

Description: The confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann-Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to: 1) formulate a trend analysis approach that considers nonstationarity due to step changes; 2) use this approach to detect trends and extreme occurrences of precipitation in a mid-latitude Eurasian steppe watershed in north China; and 3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low- and high-frequency precipitation events in the study watershed occurred more often after than before 1994, probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation-runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. This article is protected by copyright. All rights reserved.

Description: Hydrological models are useful tools to analyze present and future conditions of water quantity and quality. The integrated modeling of water and nutrients needs an adequate representation of the different discharge components. In common with many lowlands, groundwater contribution to the discharge in the North German lowlands is a key factor for a reasonable representation of the water balance especially in low flow periods. Several studies revealed that the widely used SWAT model performs poorly for low flow periods. This paper deals with the extension of the groundwater module of the SWAT model to enhance low flow representation. The current two-storage concept of SWAT was further developed to a three-storage-concept. This was realized due to modification of the groundwater module by splitting the active roundwater storage into a fast and a slow contributing aquifer. The results of this study show that the groundwater module with three storages leads to good prediction of the overall discharge especially for the recession limbs and the low flow periods. The improved performance is reflected in the signature measures for the mid segment (PBIAS: −2:4% vs. −15:9%) and the low segment (PBIAS: 14:8% vs. 46:8%) of the flow duration curve. The three-storage groundwater module is more process oriented than the original version due to the introduction of a fast and a slow groundwater flow component. The three-storage version includes a modular approach, since groundwater storages can be activated or deactivated independently for subbasin and HRU level. This article is protected by copyright. All rights reserved.

Description: The ecological condition and biodiversity values of floodplain wetlands are highly dependent on the hydrological connectivity of wetlands to adjacent rivers. This paper describes a method for quantifying connectivity between floodplain wetlands and the main rivers in a wet tropical catchment of northern Australia. We used a 1-D hydrodynamic model to simulate time-varying water depths across the stream network (i.e. rivers, streams and man-made drains). The timing and duration of connectivity of seven wetlands (4 natural and 3 artificial) with the two main rivers in the catchment were then calculated for different hydrological conditions. Location and areal extent of the wetlands and the stream network were identified using high resolution laser altimetry (LiDAR) and these data formed key inputs to the hydrodynamic model. The model was calibrated using measured water depths and discharges across the floodplain. An algorithm was developed to identify contiguous water bodies at daily time steps and this gave the temporal history of connection and disconnection between wetlands and the rivers. Simulation results show that connectivity of individual wetlands to both rivers varies from 26 to 365 days during an average hydrological condition. Location, especially proximity to a main river, and wetland type (natural stream or artificial drain) were identified as key factors influencing these levels of connectivity. Some natural wetlands maintain connection with the river for most or all of the year, whereas the connectivity of some artificial wetlands varies from 26 to 36 days according to their patterns of network connection to adjacent rivers – a result that has important implications for the accessibility of these types of wetland to aquatic biota. Using readily available river gauge data, we also show how connectivity modelling can be used to identify periods when connectivity has fallen below critical thresholds for fish movement. These connectivity patterns within the floodplain network are central to the setting of river flows that will meet environmental requirements for biota that use floodplain wetlands during their life history. This article is protected by copyright. All rights reserved.

Description: Pumping tests are one of the most commonly used in-situ testing techniques for assessing aquifer hydraulic properties. Numerous researches have been conducted to predict the effects of aquifer heterogeneity on the groundwater levels during pumping tests. The objectives of the present work were 1) to predict drawdown conditions and estimate aquifer properties during pumping tests undertaken in radially symmetric heterogeneous aquifers and 2) to identify a method for assessing the transmissivity field along the radial coordinate in radially symmetric and fully heterogeneous transmissivity fields. The first objective was achieved by expanding an existing analytical drawdown formulation which was valid for a radially symmetric confined aquifer with two concentric zones around the pumping well to an N concentric zone confined aquifer having a constant transmissivity value within each zone. The formulation was evaluated for aquifers with three and four concentric zones to assess the effects of the transmissivity field on the drawdown conditions. The specific conditions under which aquifer properties could be identified using traditional methods of analysis were also evaluated. The second objective was achieved by implementing the Inverse Solution Algorithm (ISA) which was developed for petroleum reservoirs to groundwater aquifer settings. The results showed that the drawdown values are influenced by a volumetric integral of a weighting function and the transmissivity field within the cone of depression. The weighting function migrates in tandem with the expanding cone of depression. The ability of the ISA to predict radially symmetric and log-normally distributed transmissivity fields was assessed against analytical and numerical benchmarks. The results of this investigation indicated that the ISA method is a viable technique for evaluating the radial transmissivity variations of heterogeneous aquifer settings. This article is protected by copyright. All rights reserved.

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

Description: Stormwater management increasingly recognises the need to emulate, to the maximum extent possible, the flow regime of receiving waters in their pre-development state. Hydrological models play a central role in assessing the catchment-scale impacts of alternative stormwater management strategies. However, because of the complexity of physical processes involved in urban hydrology, particularly subsurface flows, the predictive performance of such models is often low. We investigated how the structure of hydrological models influenced the prediction of urbanisation and stormwater management impacts on baseflow. We calibrated three conceptual models of the same reference catchment and compared the modelled flow regime from different stormwater management scenarios, using each of the three model structures. Scenarios were assessed using six metrics, characterising the whole streamflow regime and in particular baseflow. While the three models of the reference catchment represented the observed hydrograph well, the most complex structure, developed using a thorough diagnostic of the catchment behaviour, better captured the change in hydrological regime during dry years. Predictions of baseflow changes due to urbanisation varied significantly according to the model structure. Similarly, the models showed distinct responses to the stormwater management scenarios applied, especially for scenarios involving infiltration of stormwater at source. Our results confirm the importance of predicting the consequences of land use changes with conceptual models that are consistent with the hydrological behaviour of the study catchment. Future work should help quantify the uncertainties due to model structure, and thus provide practical guidance to the use of catchment models for assessing stormwater management strategies. This article is protected by copyright. All rights reserved.

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

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

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

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

Description: Although fire-induced soil water repellency (SWR) and its effects on soil hydrology and geomorphology have been studied with detail, very few studies have considered the effect of rock fragments resting on the soil surface or partly embedded in soil. In this research, we have studied the effect of rock fragments on the strength and spatial distribution of fire-induced SWR at different fire severities. A fire-affected area was selected for this experiment and classified into different zones according to fire severity (unburned, low, moderate and high) and rock fragment cover (low, 〈20%, and high, 〉60%). During 7 days after fire, SWR and infiltration rates were assessed in the soil surface covered by individual rock fragments and in the midpoint between two adjacent rock fragments (with maximum spacing of 20 cm). SWR increased with fire severity. Rock fragments resting on the soil surface increased the heterogeneity of the spatial distribution of fire-induced SWR. SWR increased significantly with rock fragment cover in bare areas under moderate and high fire severity, but quantitatively important changes were only observed under high fire severity. In areas with a low rock fragment cover, water repellency from soil surfaces covered by rock fragments increased relative to bare soil surfaces, with increasing SWR. In areas with a high rock fragment cover, SWR increased significantly from non-covered to covered soil surfaces only after low-severity burning. Rock fragment cover did not affect infiltration rates, although it decreased significantly in soil surfaces after high-severity burning in areas under low and high rock fragment cover. This article is protected by copyright. All rights reserved.

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

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

Description: Extremely low water level events have frequently occurred in the middle-lower Yangtze River (MLYR) in recent years (2006–2011). Most of these drought events coincided with the initial operation of the Three Gorges Dam (TGD). The TGD was therefore the focus of controversy about the causes of the hydrological droughts of the rivers and lakes of the region. We quantified the effects of the TGD's operation on water levels from 2006 to 2011 using a newly developed hydrodynamic model. The operation of the TGD significantly exacerbated the severe hydrological droughts that occurred in late September to November due to water impoundment, but it increased water levels from April to early June in the MLYR due to the drawdown of TGD water levels. Evidence suggests that the recent extremely low water levels were mainly due to the remarkable decline in inflows to the MLYR resulting from precipitation changes and possible human activities. Nevertheless, it should be noted that the effects of the TGD on downstream rivers and lakes will be intensified in the foreseeable future. This article is protected by copyright. All rights reserved.

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

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

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

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

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

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

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

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

Description: Water availability is one of the key environmental factors that control ecosystem functions in temperate forests. Changing climate is likely to alter the ecohydrology and other ecosystem processes that affect forest structures and functions. We constructed a multi-year water budget (2004–2010) and quantified environmental controls on an evapotranspiration (ET) in a 70-year-old mixed-oak woodland forest in northwest Ohio, USA. ET was measured using the eddy-covariance (EC) technique along with precipitation (P), soil volumetric water content (VWC), and shallow groundwater table fluctuation. Three biophysical models were constructed and validated to calculate potential ET (PET) for developing predictive monthly ET models. We found that the annual variability in ET was relatively stable and ranged from 578 mm in 2009 to 670 mm in 2010. In contrast, ET/P was more variable and ranged from 0.60 in 2006 to 0.96 in 2010. Mean annual ET/PET_FAO was 0.64 while mean annual PET_FAO/P was 1.15. Annual ET/PET_FAO was relatively stable, varying from 0.60 in 2005 to 0.72 in 2004. Soil water storage and shallow groundwater recharge during the non-growing season were essential in supplying ET during the growing season when ET exceeded P. Spring leaf area index (LAI), summer photosynthetically active radiation (PAR), and autumn and winter air temperatures (T a ) were the most significant controls of monthly ET. Moreover, LAI regulated ET during the whole growing season and higher temperatures increased ET even during dry periods. Our empirical modeling showed that the interaction of LAI and PET explained 〉90% of the variability in measured ET. Altogether we found that increases in T a and shifts in P distribution are likely to impact forest hydrology by altering shallow groundwater fluctuations, soil water storage, and ET and, consequently, alter the ecosystem functions of temperate forests. This article is protected by copyright. All rights reserved.

Description: Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapuños catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (〉 13.3 mm per 30 min) however show large differences between the versions with and without macropores. These model results compared to measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events. This article is protected by copyright. All rights reserved.

Description: The central route of the South-North Water Transfer Project (CTP) is designed to divert approximately 9.5 billion m 3 of water per year from the Han River, a major tributary of the Yangtze River, to the Hai River Basin in the North China. The main purpose of this study is to assess the impact of CTP on groundwater table in the Hai River basin. Our study features a large-scale distributed hydrological model that couples a physically based groundwater module (GWM), which is subbasin-based, with a conceptual surface water module (SWM), which is grid-based. There are several grids in each subbasin and water exchange among grid are considered. Our model couples SWM and GWM, and calculates human water use at the same time. The simulation results indicate that even with the water supply by CTP, the groundwater table will continue to decline in the Hai River basin. However, the CTP water can evidently reduce the decline rate, helping alleviate groundwater over-exploitation in Hai River region. This article is protected by copyright. All rights reserved.

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

Description: Complexity-reduction modelling can be useful for increasing the understanding of how the climate affects basin soil moisture response upon historical times not covered by detailed hydrological data. For this purpose, here is presented and assessed an empirical regression-based model, the European Soil Moisture Empirical Downscaling (ESMED), in which different climatic variables, easily available on the web, are addressed for simplifying the inherent complexity in the long-time studies. To accommodate this simplification, the Palmer Drought Severity Index, the precipitation, the elevation and the geographical location were used as input data in the ESMED model for predicting annual soil moisture budget. The test area was a large region including central Europe and Mediterranean countries and the spatial resolution was initially set at 50 km. ESMED model calibration was made according with the soil moisture values retrieved from the Terrestrial Water Budget Data archive by selecting randomly 285 grid points (out of 2606). Once parameterized, ESMED model was performed at validation stage both spatially and temporally. The spatial validation was made for the grid points not selected in the calibration stage while the comparison with the soil moisture outputs of the GLDAS-NOAH10 simulations upon the period 1950-2010 was carried out for the temporal validation. Moreover, ESMED results were found to be in good agreement with a root-zone soil moisture product obtained from active and passive microwave sensors from various satellite missions. ESMED model was thus found to be reliable for both the temporal and spatial validation and, hence, it might represent a useful tool to characterize the long-term dynamics of soil moisture-weather interaction. This article is protected by copyright. All rights reserved.

Description: Tundra snow cover is important to monitor as it influences local, regional, and global scale surface water balance, energy fluxes, as well as ecosystem and permafrost dynamics. Observations are already showing a decrease in spring snow cover duration at high latitudes but the impact of changing winter season temperature and precipitation on variables such as snow water equivalent (SWE) is less clear. A multi-year project was initiated in 2004 with the objective to quantify tundra snow cover properties over multiple years at a scale appropriate for comparison with satellite passive microwave remote sensing data and regional climate and hydrological models. Data collected over seven late winter field campaigns (2004 to 2010) show the patterns of snow depth and SWE are strongly influenced by terrain characteristics. Despite the spatial heterogeneity of snow cover, several inter-annual consistencies were identified. A regional average density of 0.293 g/cm 3 was derived and shown to have little difference with individual site densities when deriving SWE from snow depth measurements. The inter-annual patterns of SWE show that despite variability in meteorological forcing, there were many consistent ratios between the SWE on flat tundra and the SWE on lakes, plateaus, slopes. A summary of representative inter-annual snow stratigraphy from different terrain categories is also presented. This article is protected by copyright. All rights reserved.

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

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

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

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

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

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

Description: The main objective of this paper is to provide comparative-quantitative examinations on capabilities of 2DH and pseudo-3D modelling approaches for simulating spatial and temporal variability of the flow and salinity in Lake Urmia, Iran. The water quality in the lake has been an environmentally important subject partly because this shallow hyper saline aquatic ecosystem is considered to be one of the largest natural habitats of a unique multi-cellular organism, Artemia urmiana . This brine shrimp is the major food source for many of the protected and rare shorebirds that visit the lake. Artemia urmiana can grow and survive in certain ranges of salinity and their disappearance could lead to an alteration of existing equilibria. The lake has also experienced considerable man-made changes during the past 3 decades. A newly built crossing embankment almost divided the lake into two northern and southern halves. A relatively small opening of 1.25kmin the new embankment provides water connections between the two halves. As a result, the flow and salinity regimes have been significantly changed. This might have had adverse serious impacts on the lake ecosystem. In the current study the 2DH hydrodynamic model has been found to provide reasonable predictions for the flow regime in the lake, while its salinity predictions have not been consistent with the field observations.Thepseudo-3D model has produced results fairly close to the salinity measurements and its temporal and spatial variations. The pseudo-3Dmodelhas been used for evaluating the embankment effects on the lake hydrodynamics and on the salinity conditions. The effectiveness of introducing a different number or length of openings in the embankment for restoring the pre-embankment conditions has also been examined. These remedy options have been found not to offer substantial improvements to the lake existing ecosystem. This article is protected by copyright. All rights reserved.

Description: Subsurface flow and heat transport near Freienbrink, NE Germany, was simulated in order to study groundwater-surface water exchange between a floodplains aquifer and a section of the lowland River Spree and an adjacent oxbow. Groundwater exfiltration was the dominant process and only fast surface water level rises resulted in temporary infiltration into the aquifer. The main groundwater flow paths are identified based on a 3D groundwater flow model. To estimate mass fluxes across the aquifer-surface water interfaces, a 2D flow and heat transport modelling approach along a transect of 12 piezometers was performed. Results of steady-state and transient water level simulations show an overall high accuracy with a Spearman coefficient ρ = 0.9996 and RMSE = 0.008 m. Based on small groundwater flow velocities of about 10 -7 to 10 -6  ms -1 mean groundwater exfiltration rates of 233 l m -2 d -1 are calculated. Short periods of surface water infiltration into the aquifer do not exceed 10 days and the infiltration rates are in the same range. The heat transport was modelled with slightly less accuracy (ρ = 0.8359 and RMSE = 0.34 °C). In contrast to the predominant groundwater exfiltration, surface water temperatures determine the calculated temperatures in the upper aquifer below both surface water bodies down to 10 m during the whole simulation period. These findings emphasize prevailing of heat conduction over advection in the upper aquifer zones, which seems to be typical for lowland streams with sandy aquifer materials and low hydraulic gradients. Moreover, this study shows the potential of coupled numerical flow and heat transport modelling to understand groundwater-surface water exchange processes in detail. This article is protected by copyright. All rights reserved.

Description: Particles eroded from hillslopes and exported to rivers are recognized to be composite particles of high internal complexity. Their architecture and composition is known to influence their transport behaviour within the water column relative to discrete particles. To-date, hillslope erosion studies consider aggregates to be stable once they are detached from the soil matrix. However, lowland rivers and estuaries studies often suggest that particle structure and dynamics are controlled by flocculation within the water column. In order to improve the understanding of particle dynamics along the continuum from hillslopes to the lowland river environment, soil particle behaviour was tested under controlled laboratory conditions. Seven flume erosion and deposition experiments, designed to simulate a natural erosive event, and five shear cell experiments were performed using three contrasting materials: two of them were poorly developed and as such can not be considered as soils, whilst the third one was a calcareous brown soil. These experiments revealed that soil aggregates were prone to disaggregation within the water column and that flocculation may affect their size distribution during transport. Large differences in effective particle size were found between soil types during the rising limb of the bed shear stress sequence. Indeed, at the maximum applied bed shear stress, the aggregated particles median diameter was found to be three times larger for the well-developed soil than for the two others. Differences were smaller in the falling limb, suggesting that soil aggregates underwent structural changes. However, characterization of particles strength parameters showed that these changes did not fully turn soil aggregates into flocs, but rather into hybrid soil aggregate-floc particles. This article is protected by copyright. All rights reserved.

Description: Submarine groundwater discharges (SGD) were investigated in a marine watershed in south-eastern Korea using water budget analysis and a 222 Rn mass balance model. Multi-layered TOPMODEL added hydrological assumption was used to estimate groundwater components in the water budget analysis. Field observations of soil moisture, rainfall, runoff and groundwater fluctuations were used for calibration and validation of the hydrologic model. Based on observed hydrological data and terrain analyses, parameters for the hydrologic model were delineated and used to describe several hydrologic responses in the watershed. SGD estimations by 222 Rn mass balance method were also performed at Il-Gwang bay in July, 2010, and May, June, July and Nov. 2011. The estimated groundwater through hydrologic modeling and water balance analysis was 1.3x10 6  m 3 /year, which rapidly increased during typhoon season due to heavy rainfall and permeable geologic structure. The estimated groundwater was approximately 3.7-27.1 % of SGD as evaluated by 222 Rn mass balance method ranges 3.44 and 17.45 m 3  m -2  year -1 . Even though SGD is predominantly influenced by tide fluctuation, the head gradient (difference) from hydrologic processes associated with heavy rainfalls can also extra significant influences. Comprehensive understanding of SGD evaluation can be improved through a simultaneous application of both these approaches. This article is protected by copyright. All rights reserved.

Description: Fallout radionuclides 137 Cs and 210 Pb are well established as tracers of surface and sub-surface soil erosion contributing sediment to river systems. However without additional information it has not been possible to distinguish sub-surface soil erosion sources. Here we use the fallout radionuclide 7 Be (half-life 53 days) in combination with 137 Cs and excess 210 Pb to trace the form of erosion contributing sediment in large river catchments in eastern Australia; the Logan River (area 3,700 km 2 ), Bowen River (9,400 km 2 ) and Mitchell River (4,700 km 2 ). We show that the combination of 137 Cs, excess 210 Pb and 7 Be can discriminate horizontally-aligned sub-surface erosion sources (rilled and scalded hillslopes and the floors of incised drainage lines and gully ‘badland’ areas) from vertical erosion sources (channel banks and gully walls). Specifically, sub-surface sources of sediment eroded during high rainfall and high river flow events have been distinguished by the ability of rainfall-derived 7 Be to label horizontal soil surfaces, but not vertical. Our results indicate that in the two northern catchments erosion of horizontal sub-surface soil sources contributed almost as much fine river sediment as vertical channel banks, and several times the contribution of hillslope topsoils. This result improves on source discrimination provided previously and indicates that in some areas erosion of hillslope soils may contribute significantly to sediment yield, but not as topsoil loss. We find that in north-eastern Australia scalded areas on hillslopes and incising drainage lines may be sediment sources of comparable importance to vertical channel banks. Previous studies have used the combination of 137 Cs, excess 210 Pb and 7 Be to estimate soils losses at the hillslope scale. Here we show that with timely and judicious sampling of soil and sediment during and immediately after high flow events 7 Be measurements can augment fallout 137 Cs and 210 Pb to provide important erosion source information over large catchments. This article is protected by copyright. All rights reserved.

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