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• Salinity intrusion (SI) is intensified in the Vietnamese Mekong Delta (VMD). • Freshwater exploitability is investigated to cope with SI driven by climate change. • SI in the VMD has progressively increased and started earlier in the dry season. • Early and the late of the dry season are suitable time for freshwater exploitation. • Storing freshwater in the river is a promising strategy. Climate change-driven sea level rise has intensified salinity intrusion (SI) in deltas worldwide, posing significant threats to the exploitation of freshwater resources. In the Vietnamese Mekong Delta (VMD), the third largest delta globally, SI is a recurring challenge along the coastline, degrading freshwater resources for agricultural and domestic use and affecting socio-economic development. In this paper, we investigate the spatiotemporal extent of salinity intrusion in the Ben Tre Province, the hotspot of salinity disaster within the VMD. Long-term salinity monitoring data (25 years from 1996 to 2020) has been analyzed, and a 1D (Mike 11) coupled with 3D hydrodynamic model (Mike 3) was developed. Three scenarios were used to investigate the freshwater resources exploitation: (i) the year of investigation (2021), (ii) 2021 to 2030 climate change impacts, considering different annual exceedance probability of the upstream Mekong discharge (i.e., average flow, relatively low, low and very low), and (iii) extreme salinity intrusion (i.e., the 2016 condition). Our results indicated that salinity patterns are well-stratified at the beginning and end of the dry season but well-mixed during the middle period. Furthermore, over the last 25 years, SI has progressively increased and started earlier in the dry season. The modeling scenarios for SI have also revealed a growing complexity in the exploitation of freshwater resources, highlighting challenges related to timing, depth, and geographical location. The exceedance probability scenarios disclosed higher and deeper salinity intrusion along the channel in VMD, ranging from 50 % to 95 %. This poses significant limitations on the feasibility of freshwater exploitation throughout the Ben Tre Province. Under the current trajectory of climate change, the 2030 scenario anticipates salinity intrusion reaching further inland from the 2021 scenario. This is likely to exacerbate the existing challenges in freshwater resource exploitation, even with comprehensive water infrastructure. We, therefore, propose several management strategies to adapt to salinity intrusion: storing freshwater in main rivers, maintaining consistent operation of water infrastructure systems, and encouraging water-saving distribution and exploitation methods. Moreover, we also recommend supporting the development of new drought-tolerant crop patterns. [ABSTRACT FROM AUTHOR]

We report on measurements of the salinity and temperature in the Yax Chen cave system on the Yuacatan peninsula. This paper is submitted together with Kovacs et al. (2017). Kovacs et al. focuses on the salinity levels of the meteoric lens, while this paper uses the observed results to elucidate the hydrodynamics. The cave passages have water depths on the order of 10 m, with flow on the order of ten centimeters a second, and as such is a hydrodynamic, as opposed to a porous, system. The measurements reveal that episodes of significant mixing between the fresh meteoric lens and the underlying salty water are driven by meteorological events (e.g., Hurricane Rina in 2011, and the twin Hurricanes Ingrid and Manuel in 2013). We find evidence that after the hurricanes in 2013, the water column remains unstable for several months. Through wavelet analysis, we find that the marine Water Mass (WM) exhibits much less low period activity compared to the meteoric WM. We hypothesize that the open cenotes are locations of high mixing intensity, with turbulent fronts propagating away from the sites of direct mixing into the cave network. We perform laboratory experiments and numerical simulations to explore this phenomenon, and find that mixing preferentially occurs on the flanks of regions of strong, stable density stratification (i.e., on the periphery of pycnoclines), and leads to entrainment of fluid into the turbulent region. Using high resolution direct numerical simulation, we explore the detailed manner in which turbulent entrainment can drive flow toward the mixing region, and lead to mixing of passive tracers. Finally, we discuss the implications of these results for the mixing of passive tracers, such as suspended chemicals. [ABSTRACT FROM AUTHOR]

Erosion and deposition are fundamental surface processes, and the Hairsine-Rose (HR) model describing these dynamic processes for individual particle size classes has increasingly been applied at a range of scales. There are no exact solutions of the HR equations for the dynamic erosion of multi-size-classed soil. For numerical solution, upwind explicit schemes which have been applied so far generally require extremely small time intervals (10 −2 –10 −3 s) for numerical stability, thus limiting the computational efficiency. The Preissmann scheme, which is flexible and can be fully implicit, has been widely used to simulate open-channel flows. The objective of the paper was to implement, for the first time, the Preissmann scheme to solve the HR equations, and to verify the accuracy and evaluate the efficiency of the scheme. The paper shows that (1) implementation of the Preissmann scheme, while complex, is straightforward, and the numerical solution of the HR equations can be reduced to a set of 2 I algebraic equations where I is the number of size classes, with no matrix operations or iteration involved; (2) the numerical solution is verified for steady state solutions, and for the only exact solution for uniform grain-sized soil known to exist; (3) for two benchmark tests to simulate dynamic erosion of multi-size-classed soil. The time interval using the Preissmann scheme can be much larger (∼1 s), and there is improvement in overall computational efficiency so long as the time interval for the Preismann scheme is at least 6 times larger than that for upwind explicit schemes for the case of flow-driven erosion. The improvement in computational efficiency can be even more pronounced for overland flows with rainfall where the water depth can be quite small near the upper end of the slope. [ABSTRACT FROM AUTHOR]

Summary The dynamic control operation of reservoir flood limited water level (FLWL) can solve the contradictions between reservoir flood control and beneficial operation well, and it is an important measure to make sure the security of flood control and realize the flood utilization. The dynamic control bound of FLWL is a fundamental key element for implementing reservoir dynamic control operation. In order to optimize the dynamic control bound of FLWL by considering flood forecasting error, this paper took the forecasting error as a fuzzy variable, and described it with the emerging credibility theory in recent years. By combining the flood forecasting error quantitative model, a credibility-based fuzzy chance constrained model used to optimize the dynamic control bound was proposed in this paper, and fuzzy simulation technology was used to solve the model. The FENGTAN reservoir in China was selected as a case study, and the results show that, compared with the original operation water level, the initial operation water level (IOWL) of FENGTAN reservoir can be raised 4 m, 2 m and 5.5 m respectively in the three division stages of flood season, and without increasing flood control risk. In addition, the rationality and feasibility of the proposed forecasting error quantitative model and credibility-based dynamic control bound optimization model are verified by the calculation results of extreme risk theory. [ABSTRACT FROM AUTHOR]

A rivers’ longitudinal gradient (i.e. slope) is a key parameter in fluvial hydrology, hydraulics, and geomorphology. It affects a multitude of fluvial variables such as flow velocity and sediment transport. Limitations in river slope data, both its availability and accuracy, constrain the fidelity of fluvial modeling, particularly at larger or global scales. Traditional slope calculation algorithms cannot accurately predict river slopes as these are based on cell-by-cell calculation, which is only suitable for hillslopes and small mountainous streams. This paper presents a methodology for calculating global river slope and a procedure to upscale it for relatively coarse resolution, suitable for global scale modeling. The methodology is based on a simple principle of calculating slope from elevation depression over the length of a river segment, which is automated to allow global scale calculations. Version 1.0 of the Global River-Slope (GloRS) geospatial dataset is introduced and shown to be a step improvement over a previous product (NHDplus for the contiguous United States) and compares favorably to observed slope data collected from the literature. Statistical analysis of Earth’s continents and large basins highlights interesting spatial trends. A semi-empirical regression analysis between basin-average river slope and other basin-scale parameters show that terrain slope accounts for 67% of the variability in basin-average river slope, with average discharge, sediment load and basin temperature contributing additional improvements to global predictions of 3%, 4%, and 3%, respectively. [ABSTRACT FROM AUTHOR]

In this paper we suggest to innovatively use scaling laws and more specifically Universal Multifractals (UM) to analyse simulated surface runoff and compare the retrieved scaling features with the rainfall ones. The methodology is tested on a 3 km 2 semi-urbanised with a steep slope study area located in the Paris area along the Bièvre River. First Multi-Hydro, a fully distributed model is validated on this catchment for four rainfall events measured with the help of a C-band radar. The uncertainty associated with small scale unmeasured rainfall, i.e. occurring below the 1 km × 1 km × 5 min observation scale, is quantified with the help of stochastic downscaled rainfall fields. It is rather significant for simulated flow and more limited on overland water depth for these rainfall events. Overland depth is found to exhibit a scaling behaviour over small scales (10 m–80 m) which can be related to fractal features of the sewer network. No direct and obvious dependency between the overland depth multifractal features (quality of the scaling and UM parameters) and the rainfall ones was found. [ABSTRACT FROM AUTHOR]

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs. [ABSTRACT FROM AUTHOR]

In the last decade, X-ray computed tomography (CT) has become widely used to characterize the geometry and topology of the pore space of soils and natural porous media. Regardless of the resolution of CT images, a fundamental problem associated with their use, for example as a starting point in simulation efforts, is that sub-resolution pores are not detected. Over the last few years, a particular type of modeling method, known as “Grey” or “Partial Bounce Back” Lattice-Boltzmann (LB), has been adopted by increasing numbers of researchers to try to account for sub-resolution pores in the modeling of water and solute transport in natural porous media. In this short paper, we assess the extent to which Grey LB methods indeed offer a workable solution to the problem at hand. We conclude that, in spite of significant computational advances, a major experimental hurdle related to the evaluation of the penetrability of sub-resolution pores, is blocking the way ahead. This hurdle will need to be cleared before Grey LB can become a credible option in the microscale modeling of soils and sediments. A necessarily interdisciplinary effort, involving both modelers and experimentalists, is needed to clear the path forward. [ABSTRACT FROM AUTHOR]

[Display omitted] • Improve the accuracy of LID parameters through physical experiments. • Offer a new perspective on studying the urban hydrological effects in LID regions. • Even a tiny percentage of LID practices can be effective in runoff control. • LID removal or density reduction leads to an increased possibility of flood risk. Global climate change and rapid urbanization led to frequent extreme rainstorms and waterlogging. Low impact development (LID) as an essential measure of urban stormwater control, it is necessary to explore the urban hydrological response under low impact development combined with physical experiment and numerical simulation. This paper takes the Beiyangyuan campus of Tianjin University, where numerous LID practices have been implemented, as the study area. The prototype permeable pavement in the campus was scaled down to a laboratory-scale for infiltration experiments. The results show that the Horton infiltration model could describe the infiltration process of permeable concrete and grass-planting brick. The initial infiltration rate of the permeable concrete is large but decays faster. In contrast, the infiltration process of the grass-planting brick decays slower, and the stable infiltration rate and infiltration capacity are higher than that of the permeable concrete. The mean infiltration rates measured for the permeable concrete and the grass-planting brick were 95 mm/hr and 190 mm/hr, respectively. A SWMM-MIKE21 coupled model was constructed based on the LID experimental results to explore the effects of the removal or density reduction of the LID practices on surface hydrological processes. The results show that permeable pavement performs best in the reduction of runoff volume, inundation area, and inundation depth, while the bio-retention cell takes the second place, and the sunken greenbelt has limited effect. Frequent light rainfall is sensitive to the density of LID practices, and the implementation of even a tiny percentage (4% of the catchment area) of LID practices can be effective in controlling runoff. The removal or density reduction of LID practices has little effect on the inundation region but leads to an increased possibility of flood risk due to increasing inundation depth. [ABSTRACT FROM AUTHOR]

It has been widely recognized that surface runoff from agricultural field is an important non-point pollution source, which however, the chemical transfer amount in the process is very difficult to be quantified in field since some variables and natural factors are hard to control, such as rainfall intensity, temperature, wind speeds and soil spatial heterogeneity, which may significantly affect the field experimental results. Therefore, a physically based nitrogen transport model was developed and tested with the so called semi-field experiments (i.e., artificial rainfall was used instead of natural rainfall, but other conditions were natural) in this paper. Our model integrated the raindrop driven process and diffusion effect with the simplified nitrogen chain reactions. In this model, chemicals in the soil surface layer, or the ‘exchange layer’, were transformed into the surface runoff layer due to raindrop impact. The raindrops also have a significant role on the diffusion process between the exchange layer and the underlying soil. The established mathematical model was solved numerically through the modified Hydrus-1d source code, and the model simulations agreed well with the experimental data. The modeling results indicate that the depth of the exchange layer and raindrop induced water transfer rate are two important parameters for the simulation results. Variation of the water transfer rate, e r , can strongly influence the peak values of the NO − 3 -N and NH + 4 -N concentration breakthrough curves. The concentration of NO − 3 -N is more sensitive to the exchange layer depth, d e , than NH + 4 -N. In general, the developed model well describes the nitrogen loss into surface runoff in a raindrop driven process. Since the raindrop splash erosion process may aggravate the loss of chemical fertilizer, choosing an appropriate fertilization time and application method is very important to prevent the pollution. [ABSTRACT FROM AUTHOR]

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol’ method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework. [ABSTRACT FROM AUTHOR]

Summary This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using either inlet pressure/outlet pressure measurements (Heller et al., 2002) or actuator position/outlet pressure measurements, where the latter is a novel approach. The solution to the optimization problem reveals that for both measurement methods an optimal excitation frequency, an optimal inlet volume, and an optimal outlet volume exist. We find that under the same parameter variance bounds and actuator constraints, actuator position/outlet pressure measurements result in required experiment times that are a factor fourteen smaller compared to inlet pressure/outlet pressure measurements. This result is analysed in detail and we find that the dominant effect driving this difference originates from an identifiability problem when using inlet–outlet pressure measurements for joint estimation of permeability and porosity. We illustrate our results with numerical simulations, and show excellent agreement with theoretical expectations. [ABSTRACT FROM AUTHOR]

Summary Rainwater harvesting techniques are used worldwide to augment potable water supply, provide water for small-scale irrigation practices, increase rainwater-use efficiency for sustained crop growth in arid and semi-arid regions, decrease urban stormwater flow volumes, and in general to relieve dependency on urban water resources cycles. A number of methods have been established in recent years to estimate reliability of rainwater catchment systems (RWCS) and thereby properly size the components (roof catchment area, storage tank size) of the system for a given climatic region. These methods typically use historical or stochastically-generated rainfall patterns to quantify system performance and optimally size the system, with the latter accounting for possible rainfall scenarios based on statistical relationships of historical rainfall patterns. To design RWCS systems that can sustainably meet water demand under future climate conditions, this paper introduces a method that employs climatic data from general circulation models (GCMs) to develop a suite of catchment area vs. storage size design curves that capture uncertainty in future climate scenarios. Monthly rainfall data for the 2010–2050 time period is statistically downscaled to daily values using a Markov chain algorithm, with results used only from GCMs that yield rainfall patterns that are statistically consistent with historical rainfall patterns. The process is demonstrated through application to two climatic regions of the Federated States of Micronesia (FSM) in the western Pacific, wherein the majority of the population relies on rainwater harvesting for potable water supply. Through the use of design curves, communities can provide household RWCS that achieve a certain degree of storage reliability. The method described herein can be applied generally to any geographic region. It can be used to first, assess the future performance of existing household systems; and second, to design or modify systems that will yield adequate storage for future climate conditions. [ABSTRACT FROM AUTHOR]

Summary Recent increases in computational power have led to the development of more advanced physically-based models which can handle a wide range of environmental processes. Although these models are very useful for increasing our understanding of unsaturated zone flow processes, their outputs usually contain high uncertainty, particularly when the level of complexity is not supported by observations. In this context, the aim of this paper is to compare the performance of three different model conceptualizations of a shallow unsaturated soil zone using the physically-based model HydroGeoSphere (HGS). To accomplish this task, we simulated actual evapotranspiration (ET), water content (WC) and discharge (D) from a weighing lysimeter for each of the conceptual models. Conceptual Model 1 considers the lysimeter as a homogeneous zone with matrix flow, while Conceptual Model 2 has an added preferential flow component. Conceptual Model 3 includes layered heterogeneity in addition to the matrix and preferential flow components. The results indicated that the model performance in reproducing daily ET, WC and D improves when we move from simple models to more complex models. A comparison between event-based, monthly, seasonal and yearly time scales indicates that the simplest conceptual model is not reliable for reproducing event-based discharges. However, it can compete with more complex models at annual scales, although the uncertainty bound for the simple model is very high. While increasing complexity from the simplest to the more complex model leads to lower uncertainty bounds and more reliable values of the lysimeter discharge at monthly and seasonal time scales, uncertainty bounds became larger when complexity increased in the most complex model. This is related to a higher number of unknown model parameters in the calibration which are not supported by the available observation datasets. [ABSTRACT FROM AUTHOR]

Summary Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurface flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible co-dependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged locations must account for both the physics of flow in heterogeneous landscapes, and the co-dependence of soil and topographic properties with climate, including possibly the mediating role of vegetation. [ABSTRACT FROM AUTHOR]

Summary: Yield plays a central role in the processes, practices, management and operation of urban water supply systems. Improved accuracy of the yield estimate is important and can be obtained by improving knowledge of important variables. Yield is typically estimated via computational simulation using the entire sequence of available historic climate data. Sensitivity analysis provides a framework and many techniques that can identify important variables in a computational model. Using the Morris method, this paper investigates the importance of input variables used in the estimation of yield of urban water supply systems. The Barwon urban water supply system in Australia is used as the case study. Using a number of climate scenarios of various lengths, sensitivity analysis showed that the security criteria of the Barwon system was the most important to the yield estimate. The upper restriction rule curve also showed notable importance. Significantly the results showed that the use of a single climate sequence for estimating yield would produce misrepresentative results for another climate scenario. [ABSTRACT FROM AUTHOR]

Summary: The paper concerns the untypical aspect of application of the dissipative numerical methods to solve non-linear hyperbolic partial differential equations used in open channel hydraulics. It is shown that in some cases the numerical diffusion generated by the applied method of solution produces not only inaccurate solution but as well as a balance error. This error may occur even for an equation written in the conservative form not only in the solution containing a shock wave but also for the smooth solution with strong gradients. In order to explain this problem 1-D kinematic wave equation and 1-D system of shallow water equations, both solved by the finite-difference implicit box scheme, are considered. Accuracy analysis carried out using the modified equation approach revealed why the numerical solutions of these equations written in the conservative forms contain the balance errors. It was shown that the balance error is directly connected with the additional source term generated by the numerical diffusion during the solution of equation written in an inadequate conservative form. Consequently the balance error depends on the values of time step, spatial interval and the weighting parameters involved in the applied method of solution. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the results of computer simulations of runoff from 13 major fresh and brackish river basins in south-western Australia (SWA) under climate projections obtained from 15 GCMs with three future global warming scenarios equivalent to global temperature rises of 0.7°C, 1.0°C and 1.3°C by 2030. The objective was to apply an efficient methodology, consistent across a large region, to examine the implications of the best available projections in climate trends for future surface water resources. An ensemble of rainfall-runoff models was calibrated on stream flow data from 1975 to 2007 from 106 gauged catchments distributed throughout the basins of the study area. The sensitivity of runoff to projected changes in mean annual rainfall is examined using the climate ‘elasticity’ concept. Averaged across the study area, all 15 GCMs project declines in rainfall under all global warming scenarios with a median decline of 8% resulting in a median decline in runoff of 25%. Such uniformity in projections from GCMs is unusual. Over SWA the average annual runoff under the 5th wettest and 5th driest of the 45 projections of the 2030 climate declines by 10 and 42%, respectively. Under the 5th driest projection the runoff decline ranges from 53% in the northern region to 40% in the southern region. Strong regional variations in climate sensitivity are found with the proportional decline in runoff greatest in the northern region and the greatest volumetric declines in the wetter basins in the south. Since the mid 1970s stream flows into the major water supply reservoirs in SWA have declined by more than 50% following a 16% rainfall reduction. This has already had major implications for water resources planning and for the preservation of aquatic and riparian ecosystems in the region. Our results indicate that this reduction in runoff is likely to continue if future climate projections eventuate. [Copyright &y& Elsevier]

Summary: While there seems to be consensus that hydrological model outputs should be accompanied with an uncertainty estimate the appropriate method for uncertainty estimation is not agreed upon and a debate is ongoing between advocators of formal statistical methods who consider errors as stochastic and GLUE advocators who consider errors as epistemic, arguing that the basis of formal statistical approaches that requires the residuals to be stationary and conform to a statistical distribution is unrealistic. In this paper we take a formal frequentist approach to parameter estimation and uncertainty evaluation of the modelled output, and we attach particular importance to inspecting the residuals of the model outputs and improving the model uncertainty description. We also introduce the probabilistic performance measures sharpness, reliability and interval skill score for model comparison and for checking the reliability of the confidence bounds. Using point rainfall and evaporation data as input and flow measurements from a sewer system for model conditioning, a state space model is formulated that accounts for three different flow contributions: wastewater from households, and fast rainfall–runoff from paved areas and slow rainfall-dependent infiltration–inflow from unknown sources. We consider two different approaches to evaluate the model output uncertainty, the output error method that lumps all uncertainty into the observation noise term, and a method based on Stochastic Differential Equations (SDEs) that separates input and model structure uncertainty from observation uncertainty and allows updating of model states in real-time. The results show that the optimal simulation (off-line) model is based on the output error method whereas the optimal prediction (on-line) model is based on the SDE method and the skill scoring criterion proved that significant predictive improvements of the output can be gained from updating the states continuously. In an effort to attain residual stationarity for both the output error method and the SDE method transformation of the observations were necessary but the statistical assumptions were nevertheless not 100% justified. The residual analysis showed that significant autocorrelation was present for all simulation models. We believe users of formal approaches to uncertainty evaluation within hydrology and within environmental modelling in general can benefit significantly from adopting the evaluation measures applied here, so the probabilistic performance of their models can be assessed properly. [Copyright &y& Elsevier]

Summary: Soil field experiments usually consist of measurements of soil temperatures, heat fluxes and soil water contents. Accurate determination of the soil thermal field, in particular, prediction of the soil surface temperature and the ground heat, contains the signature to the surface energy partitioning, and is therefore critical to the surface energy balance closure problem. In this paper, we develop a numerical procedure to reconstruct the entire soil thermal field from a single depth measurement of either temperature or heat flux. The new algorithm is based on Green’s function approach by using the fundamental solution of heat conduction in semi-infinite soils and Duhamel’s integral for incorporation of general boundary conditions. It is highlighted that the new approach is capable of accurately reproducing results of some existing numerical approaches, with a more general setting and treatment of the heat diffusion problem, and hence provides a possible unified framework for the estimation of thermal field in soils. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an energy balance modelling approach to predict the nightly water yield and the surface temperature (T f) of two passive radiative dew condensers (RDCs) tilted 30° from horizontal. One was fitted with a white hydrophilic polyethylene foil recommended for dew harvest and the other with a black polyethylene foil widely used in horticulture. The model was validated in south-eastern Spain by comparing the simulation outputs with field measurements of T f and dew yield. The results indicate that the model is robust and accurate in reproducing the behaviour of the two RDCs, especially in what refers to T f, whose estimates were very close to the observations. The results were somewhat less precise for dew yield, with a larger scatter around the 1:1 relationship. A sensitivity analysis showed that the simulated dew yield was highly sensitive to changes in relative humidity and downward longwave radiation. The proposed approach provides a useful tool to water managers for quantifying the amount of dew that could be harvested as a valuable water resource in arid, semiarid and water stressed regions. [Copyright &y& Elsevier]

Summary: The reliability of over-year storage reservoirs has been traditionally estimated by using Monte Carlo simulation (behavior analysis), numerical solution of the stochastic reservoir equation (difference or integral equations), or by using approximations and empirical relationships. The case of persistent inflow, which is the case for most natural streams, adds complexity to the problem. Apart from simulation, which is the most flexible approach, other methods have had partial success in this case, and are mainly limited to the case of Markovian autocorrelation. This paper suggests an alternative method for calculating the reliability of over-year storage reservoirs with persistent gaussian inflow using basic probability principles and the numerical integration of the standard multi-variate normal distribution. It is shown that the classical probabilities of the reservoir being empty and those of spilling can be directly calculated based on the distribution of the critical drawdown and filling periods. The results obtained by the application of the proposed method compare very well with those obtained by Monte Carlo simulation and those reported in previous studies. The proposed method thus offers another alternative that should be useful in handling complex problems. [Copyright &y& Elsevier]

Summary: Hydrological simulation of rain-runoff processes is often performed with lumped models which rely on calibration to generate storm hydrographs and study catchment response to rain. In this paper, a distributed, physically-based numerical model is used for runoff simulation in a mountain catchment. This approach offers two advantages. The first is that by using shallow-water equations for runoff flow, there is less freedom to calibrate routing parameters (as compared to, for example, synthetic hydrograph methods). The second, is that spatial distributions of water depth and velocity can be obtained. Furthermore, interactions among the various hydrological processes can be modeled in a physically-based approach which may depend on transient and spatially distributed factors. On the other hand, the undertaken numerical approach relies on accurate terrain representation and mesh selection, which also affects significantly the computational cost of the simulations. Hence, we investigate the response of a gauged catchment with this distributed approach. The methodology consists of analyzing the effects that the mesh has on the simulations by using a range of meshes. Next, friction is applied to the model and the response to variations and interaction with the mesh is studied. Finally, a first approach with the well-known SCS Curve Number method is studied to evaluate its behavior when coupled with a shallow-water model for runoff flow. The results show that mesh selection is of great importance, since it may affect the results in a magnitude as large as physical factors, such as friction. Furthermore, results proved to be less sensitive to roughness spatial distribution than to mesh properties. Finally, the results indicate that SCS-CN may not be suitable for simulating hydrological processes together with a shallow-water model. [Copyright &y& Elsevier]

Summary: This paper presents an investigation of dam break flow in a channel with lateral contraction. An experiment was carried out in a laboratory flume by instantaneous removal of a plate. The problem was studied in a smooth prismatic channel of rectangular cross-section over horizontal dry bed. At a certain distance downstream from the dam location, two symmetrical triangular-shaped lateral sidewall obstacles were installed to generate converging–diverging channel reach. Thus, it points out the abrupt variation of topography in floodplain for practical applications. Adopted measuring technique, digital image processing, detected the flood wave propagation quite well thereby synchronous recording of the flow through the entire channel with three cameras. The continuous free surface profiles and stage hydrographs were obtained without disturbing the flow. The experimental data were compared with the results of RANS-based numerical simulation. Comparisons between measured and computed results show good agreement. [Copyright &y& Elsevier]

Summary: Models for water transfer in the crop–soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop–soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop–soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. [Copyright &y& Elsevier]

Summary: This paper investigates transport and fate of reactive compounds in the unsaturated subsoil (vadose zone) using numerical simulations of steady-state and transient flow scenarios. The objective is to investigate whether steady-state flow simulations accurately describe reactive contaminant transport under transient conditions in the field. The focus lies on organic compounds; advection, kinetic sorption and biodegradation are considered as relevant processes. In model scenarios the impact of steady-state and transient seepage water flow on solute concentrations at the groundwater table was evaluated. Sorption and degradation kinetics relative to the advective transport velocity were characterized by dimensionless Damköhler numbers for degradation (Dad ) and sorption (Das ). Compound properties representing two frequent pollutants (Lindane and Phenanthrene) and two types of sources were investigated: a constant inflow concentration (infinite source, with Phenanthrene) and a decreasing concentration due to desorption of the compound (finite source, with Lindane). Total mass degraded vs. cumulative flux to the groundwater (the lower model boundary), as well as the maximum breakthrough concentration at the outflow were evaluated. For each source type, combinations of sorption and degradation kinetics were identified, at which the transient simulation showed deviations from the predictions based on the steady-state simulation. Results are plotted as the difference in the observed maximum breakthrough concentration and the difference in cumulative mass fluxes as functions of degradation and sorption kinetics (“Damköhler plots”). Overall results indicate that steady-state flow conditions are appropriate for most field scenarios; only extreme infiltration events lead to higher pollutant concentrations in transient simulations because of the short residence time of seepage water in the unsaturated zone and thus reduced biodegradation and sorption. [Copyright &y& Elsevier]

Summary: The estimation of urban stormwater runoff volume is usually of fundamental importance in the determination of the relative magnitudes of storage capacity and treatment rate for various storage/treatment facilities and in the evaluation of system runoff quantity and quality control performances. Recognizing the increasingly complex nature of urbanized watersheds, stormwater runoff volumes estimated without adequate consideration of the rainfall–runoff transformation process may be not reliable, and desired levels of system performance control may not be achieved. In contrast to the continuous simulation approach, derived probability distribution theory is employed in the development of event-based analytical probabilistic models for runoff volume. As a key element in the model development, different types of the rainfall–runoff transformations are formulated in light of various hydrological considerations associated with conceptualizing runoff generation mechanisms. The emphasis of this paper is to illustrate methodologies in the development of analytical probabilistic models for runoff volumes and to demonstrate that analytical models can be derived with various degrees of complexity based on different types of rainfall–runoff transformations. The verification of the developed analytical models is performed in case studies. By comparing the results from analytical models to those from continuous simulation, it is concluded that the closed-form analytical models not only demonstrate the capability of providing comparable results to continuous simulation, but also can be highly efficient and flexible in the estimation of urban stormwater runoff volumes. [Copyright &y& Elsevier]

Summary: This paper examines critically the application to a site along the River Crouch, Essex of a river-flow forecasting approach based on a one-dimensional hydraulic flow simulation model updated using real-time data within an ensemble Kalman filtering framework. Given a specified validation location and forecast period the objective of the forecasting model was to estimate water level more accurately with updating than without. The method used to estimate both model state and state uncertainty was evaluated in terms of its forecast accuracy and representation of forecast uncertainty. The ensemble Kalman filter lead to an increase in forecast accuracy of between 50% and 70% depending on location. The hyperparameters of the filter could be calibrated to make estimates of forecast uncertainty at a specific location, where the most data were available. However, the presence of systematic errors in the simulation model and especially measurement data meant that uncertainty estimates were inaccurate at other locations. Although, the major source of uncertainty in this model came from the boundary condition, additional uncertainty within the model domain was required, particularly between channel and floodplain. Changing the temporal sampling rate and spatial density of samples had little effect on the accuracy of forecasts at this site. However, uncertainty was under-estimated when the temporal sampling rate was decreased, indicating that the relative uncertainties prescribed to the simulation model and measurement model were inadequate. [Copyright &y& Elsevier]

Flood forecasting may be improved by coupling atmospheric and hydrological models. To investigate the current potential of such an approach in complex mountain watersheds, the authors carried out a number of combined high-resolution one-way driven model experiments to generate runoff hydrographs for seven extreme flood events which occurred in the Lago Maggiore basin between 1993 and 2000. The Alpine Ticino–Verzasca–Maggia basin (2627 km2) is located directly to the south of the main Alpine ridge embracing a great part of the drainage area of Lago Maggiore. For this basin, the grid-based hydrological catchment model WaSiM-ETH was employed to determine the continuous runoff hydrographs. In the model experiments, two different sets of meteorological input data were used: (1) surface observation data from station measurements and from weather radar, and (2) forecast data from five different high-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km.This paper presents and compares selected results of these flood runoff simulations with particular attention to the experimental design of the model coupling. The configuration and initialization of the hydrological model runs are outlined as well as the down-scale techniques which proved to provide an adequate spatial interpolation of the meteorological variables onto the 500 m×500 m grid of the hydrological model. In order to evaluate the various hydrological model results as generated from the different outputs from the five NWP models, some coupled experiments with ‘non-standard’ NWP model outputs have been carried out. In particular, the results of these sensitivity studies point to inherent limits of high-resolution flood runoff predictions in complex mountain terrain. [Copyright &y& Elsevier]

Field monitoring of natural pipeflow over the last two decades has demonstrated its potential importance both as a hillslope drainage process and as a source of streamflow, yet very few attempts have been made to model the process. The main model designed to simulate pipeflow to date is shown to be unrepresentative of the natural field situation. This paper describes a semi-distributed simulation model with physically based parameters that has been designed around the field situation, as monitored in the longest run field experiment on pipeflow. The results are encouraging, despite the fact that data on a number of relevant parameters can be difficult to obtain at less intensely studied field sites. [Copyright &y& Elsevier]

[Display omitted] • A human-machine interactive method is proposed for real-time reservoir flood control operation. • Modeling, observation, and human experiences are integrated for more effective decision support. • Optimization, simulation, and observation are combined for flood control via data assimilation. Real world reservoir operations are usually not fully automatic based on computer models; instead, reservoir operators conduct the operations based on their experiences, professional justification, as well as modeling support. In this paper, we propose a human-machine interactive method, namely Real-time Optimization Model Enhanced by Data Assimilation (ROMEDA) tested with simple but reasonable rules for direct interaction between operators and a computer model for reservoirs which have complex storage and stage relations (e.g. long and narrow reservoirs). ROMEDA couples 1) an optimization model to search for optimal releases, 2) a reservoir storage-stage simulation and data assimilation schedule to update the storage based on real-time reservoir stage observations, and 3) reservoir operators' choices based on the optimization model solutions, as well as their experiences, knowledge, and behaviors. For every time period and based on the updated storage, ROMEDA provides optimal releases as recommendations and adopts actual releases made by operators. ROMEDA does not assume that operators strictly accept the recommendations, and the storage will be updated based on the actual release at each time period via a data assimilation procedure, which plays a key linkage between human and machine in ROMEDA. Via a case study on-channel reservoir, it is found that for both small and large flood events, ROMEDA, which integrates the advantages of both machine and human, shows better performance on flood risk mitigation and water use (hydropower) benefit than the case with historical operation records (HOR) or optimization with single/multi-objective. ROMEDA is one of the first attempts of a human-machine interactive method for online use of an optimization model for real-time reservoir operation based on integrated modeling, observation, and operators' choice. [ABSTRACT FROM AUTHOR]

• Evaluating environmental effects due to foundation pit dewatering by numerical simulation. • Impact on the environmental effects considering the interaction between the waterproof curtain and pumping wells. • Optimized depth of the waterproof curtain is evaluated, including the effective, suggested and control value. • Determining the optimized depth of the waterproof curtain according to the filter length of the pumping wells. Dewatering using a combination of waterproof curtain and pumping wells is commonly adopted to ensure the stability of foundation pits in multi-aquifer strata. However, dewatering is likely to result in environmental problems. This paper investigates the impact on surroundings owing to the interaction between the waterproof curtain and pumping wells by numerical simulation. The depth of the diaphragm wall penetrating the dewatering aquifer (D) and the filter length of pumping wells (L) are varied in the simulation. The relationship between approximate hydraulic gradient (Δ i) or ground settlement outside the foundation pit (S) with curtain depth ratio R D (D over the thickness of the dewatering confined aquifer H a) or filter length ratio R L (L/H a) can be divided into three change parts, namely initial gradual, middle sharp and final gentle part. Three values of R D and R L , namely effective, suggested and control value, are proposed. R D and R L should vary between the effective and control value. The suggested value of R D and R L is recommended in actual engineering by comprehensive consideration. The effective, suggested and control value of R D can be calculated by a linear equation according to the value of R L. [ABSTRACT FROM AUTHOR]