Assessing the reliability of probabilistic flood inundation model predictions

An ability to quantify the reliability of probabilistic flood inundation predictions is a requirement not only for guiding model development but also for their successful application. Probabilistic flood inundation predictions are usually produced by choosing a method of weighting the model parameter space, but previous study suggests that this choice leads to clear differences in inundation probabilities. This study aims to address the evaluation of the reliability of these probabilistic predictions. However, a lack of an adequate number of observations of flood inundation for a catchment limits the application of conventional methods of evaluating predictive reliability. Consequently, attempts have been made to assess the reliability of probabilistic predictions using multiple observations from a single flood event. Here, a LISFLOOD‐FP hydraulic model of an extreme (>1 in 1000 years) flood event in Cockermouth, UK, is constructed and calibrated using multiple performance measures from both peak flood wrack mark data and aerial photography captured post‐peak. These measures are used in weighting the parameter space to produce multiple probabilistic predictions for the event. Two methods of assessing the reliability of these probabilistic predictions using limited observations are utilized; an existing method assessing the binary pattern of flooding, and a method developed in this paper to assess predictions of water surface elevation. This study finds that the water surface elevation method has both a better diagnostic and discriminatory ability, but this result is likely to be sensitive to the unknown uncertainties in the upstream boundary condition. Copyright © 2015 John Wiley & Sons, Ltd.     

Multi-method global sensitivity analysis of flood inundation models

Global sensitivity analysis is a valuable tool in understanding flood inundation models and deriving decisions on strategies to reduce model uncertainty. In this paper, a sensitivity analysis of a one-dimensional flood inundation model (HEC-RAS) on the River Alzette, Luxembourg, is presented. It is impossible to define sensitivity in a unique way and different methods can lead to a difference in ranking of importance of model factors. In this paper five different methods (Sobol, Kullback–Leibler entropy, Morris, regionalised sensitivity analysis and regression) are applied and the outcomes on selected examples compared. It is demonstrated that the different methods lead to completely different ranking of importance of the parameter factors and that it is impossible to draw firm conclusions about the relative sensitivity of different factors. Moreover, the uncertainty inherent in the sensitivity methods is highlighted.     

Investigating sea-state effects on flash flood hydrograph and inundation forecasting

A common source of uncertainty in flood inundation forecasting is the hydrograph used. Given the role of sea-air-hydro-land chain processes on the water cycle, flood hydrographs in coastal areas can be indirectly affected by sea state. This study investigates sea-state effects on precipitation, discharge, and flood inundation forecasting implementing atmospheric, ocean wave, hydrological, and hydraulic-hydrodynamic coupled models. The Chemical Hydrological Atmospheric Ocean wave System (CHAOS) was used for coupled hydro-meteorological-wave simulations ‘accounting’ or ‘not accounting’ the impact of sea state on precipitation and, subsequently, on flood hydrograph. CHAOS includes the WRF-Hydro hydrological model and the WRF-ARW meteorological model two-way coupled with the WAM wave model through the OASIS3-MCT coupler. Subsequently, the 2D HEC-RAS hydraulic-hydrodynamic model was forced by the flood hydrographs and map the inundated areas. A flash flood event occurred on 15 November 2017 in Mandra, Attica, Greece, causing 24 fatalities, and damages was selected as case study. The calibration of models was performed exploiting historical flood records and previous studies. Human interventions such as hydraulic works and the urban areas were included in the hydraulic modelling geometry domain. The representation of the resistance caused by buildings was based on Unmanned Aerial System (UAS) data while the local elevation rise method was used in the urban-flood simulation. The flood extent results were assessed using the Critical Success Index (CSI), and CSI penalize. Integrating sea-state affected the forecast of precipitation and discharge peaks, causing up to +24% and from −8% to +36% differences, respectively, improving inundation forecast by 4.5% and flooding additional approximately 70 building blocks. The precipitation forcing time step was also highlighted as significant factor in such a small-scale flash flood. The integrated multidisciplinary methodological approach could be adopted in operational forecasting for civil protection applications facilitating the protection of socio-economic activities and human lives during similar future events.     

Impacts of uncertain river flow data on rainfall‐runoff model calibration and discharge predictions

In order to quantify total error affecting hydrological models and predictions, we must explicitly recognize errors in input data, model structure, model parameters and validation data. This paper tackles the last of these: errors in discharge measurements used to calibrate a rainfall‐runoff model, caused by stage–discharge rating‐curve uncertainty. This uncertainty may be due to several combined sources, including errors in stage and velocity measurements during individual gaugings, assumptions regarding a particular form of stage–discharge relationship, extrapolation of the stage–discharge relationship beyond the maximum gauging, and cross‐section change due to vegetation growth and/or bed movement. A methodology is presented to systematically assess and quantify the uncertainty in discharge measurements due to all of these sources. For a given stage measurement, a complete PDF of true discharge is estimated. Consequently, new model calibration techniques can be introduced to explicitly account for the discharge error distribution. The method is demonstrated for a gravel‐bed river in New Zealand, where all the above uncertainty sources can be identified, including significant uncertainty in cross‐section form due to scour and re‐deposition of sediment. Results show that rigorous consideration of uncertainty in flow data results in significant improvement of the model's ability to predict the observed flow. Copyright © 2010 John Wiley & Sons, Ltd.     

Influence of rainfall spatial variability on flood prediction

This paper deals with the sensitivity of distributed hydrological models to different patterns that account for the spatial distribution of rainfall: spatially averaged rainfall or rainfall field. The rainfall data come from a dense network of recording rain gauges that cover approximately 2000 km² around Mexico City. The reference rain sample accounts for the 50 most significant events, whose mean duration is about 10 h and maximal point depth 170 mm. Three models were tested using different runoff production models: storm-runoff coefficient, complete or partial interception. These models were then applied to four fictitious homogeneous basins, whose sizes range from 20 to 1500 km². For each test, the sensitivity of the model is expressed as the relative differences between the empirical distribution of the peak flows (and runoff volumes), calculated according to the two patterns of rainfall input: uniform or non-uniform. Differences in flows range from 10 to 80%, depending on the type of runoff production model used, the size of the basin and the return period of the event. The differences are generally moderate for extreme events. In the local context, this means that uniform design rainfall combining point rainfall distribution and the probabilistic concept of the areal reduction factor could be sufficient to estimate major flood probability. Differences are more significant for more frequent events. This can generate problems in calibrating the hydrological model when spatial rainfall localization is not taken into account: a bias in the estimation of parameters makes their physical interpretation difficult and leads to overestimation of extreme flows.     

Estimation of uncertainty propagation in flood inundation mapping using a 1‐D hydraulic model

A need for more accurate flood inundation maps has recently arisen because of the increasing frequency and extremity of flood events. The accuracy of flood inundation maps is determined by the uncertainty propagated from all of the variables involved in the overall process of flood inundation modelling. Despite our advanced understanding of flood progression, it is impossible to eliminate the uncertainty because of the constraints involving cost, time, knowledge, and technology. Nevertheless, uncertainty analysis in flood inundation mapping can provide useful information for flood risk management. The twin objectives of this study were firstly to estimate the propagated uncertainty rates of key variables in flood inundation mapping by using the first‐order approximation method and secondly to evaluate the relative sensitivities of the model variables by using the Hornberger–Spear–Young (HSY) method. Monte Carlo simulations using the Hydrologic Engineering Center's River Analysis System and triangle‐based interpolation were performed to investigate the uncertainty arising from discharge, topography, and Manning's n in the East Fork of the White River near Seymour, Indiana, and in Strouds Creek in Orange County, North Carolina. We found that the uncertainty of a single variable is propagated differently to the flood inundation area depending on the effects of other variables in the overall process. The uncertainty was linearly/nonlinearly propagated corresponding to valley shapes of the reaches. In addition, the HSY sensitivity analysis revealed the topography of Seymour reach and the discharge of Strouds Creek to be major contributors to the change of flood inundation area. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of log-transmissivity variogram structure on groundwater flow and transport predictions

We analyze the impact of the choice of the variogram model adopted to characterize the spatial variability of natural log-transmissivity on the evaluation of leading (statistical) moments of hydraulic heads and contaminant travel times and trajectories within mildly (randomly) heterogeneous two-dimensional porous systems. The study is motivated by the fact that in several practical situations the differences between various variogram types and a typical noisy sample variogram are small enough to suggest that one would often have a hard time deciding which of the tested models provides the best fit. Likewise, choosing amongst a set of seemingly likely variogram models estimated by means of geostatistical inverse models of flow equations can be difficult due to lack of sensitivity of available model discrimination criteria. We tackle the problem within the framework of numerical Monte Carlo simulations for mean uniform and radial flow scenarios. The effect of three commonly used isotropic variogram models, i.e., Gaussian, Exponential and Spherical, is analyzed. Our analysis clearly shows that (ensemble) mean values of the quantities of interest are not considerably influenced by the variogram shape for the range of parameters examined. Contrariwise, prediction variances of the quantities examined are significantly affected by the choice of the variogram model of the log-transmissivity field. The spatial distribution of the largest/lowest values of the relative differences observed amongst the tested models depends on a combination of variogram shape and parameters and relative distance from internal sources and the outer domain boundary. Our findings suggest the need of developing robust techniques to discriminate amongst a set of seemingly equally likely alternative variogram models in order to provide reliable uncertainty estimates of state variables.     

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice.Hence,the limiting velocity should be determined to keep the channel bottom clean from sediment deposits.Recently,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many researchers.The current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology...     

Assessing effects of model complexity and structure on predictions of hydrological responses using serial and parallel model design

By utilizing functional relationships based on observations at plot or field scales, water quality models first compute surface runoff and then use it as the primary governing variable to estimate sediment and nutrient transport. When these models are applied at watershed scales, this serial model structure, coupling a surface runoff sub-model with a water quality sub-model, may be inappropriate because dominant hydrological processes differ among scales. A parallel modeling approach is proposed to evaluate how best to combine dominant hydrological processes for predicting water quality at watershed scales. In the parallel scheme, dominant variables of water quality models are identified based entirely on their statistical significance using time series analysis. Four surface runoff models of different model complexity were assessed using both the serial and parallel approaches to quantify the uncertainty on forcing variables used to predict water quality. The eight alternative model structures were tested against a 25-year high-resolution data set of streamflow, suspended sediment discharge, and phosphorous discharge at weekly time steps. Models using the parallel approach consistently performed better than serial-based models, by having less error in predictions of watershed scale streamflow, sediment and phosphorus, which suggests model structures of water quantity and quality models at watershed scales should be reformulated by incorporating the dominant variables. The implication is that hydrological models should be constructed in a way that avoids stacking one sub-model with one set of scale assumptions onto the front end of another sub-model with a different set of scale assumptions.     

Influence of junction angle on three‐dimensional flow structure and bed morphology at confluent meander bends during different hydrological conditions

Recent field and modeling investigations have examined the fluvial dynamics of confluent meander bends where a straight tributary channel enters a meandering river at the apex of a bend with a 90° junction angle. Past work on confluences with asymmetrical and symmetrical planforms has shown that the angle of tributary entry has a strong influence on mutual deflection of confluent flows and the spatial extent of confluence hydrodynamic and morphodynamic features. This paper examines three‐dimensional flow structure and bed morphology for incoming flows with high and low momentum‐flux ratios at two large, natural confluent meander bends that have different tributary entry angles. At the high‐angle (90°) confluent meander bend, mutual deflection of converging flows abruptly turns fluid from the lateral tributary into the downstream channel and flow in the main river is deflected away from the outer bank of the bend by a bar that extends downstream of the junction corner along the inner bank of the tributary. Two counter‐rotating helical cells inherited from upstream flow curvature flank the mixing interface, which overlies a central pool. A large influx of sediment to the confluence from a meander cutoff immediately upstream has produced substantial morphologic change during large, tributary‐dominant discharge events, resulting in displacement of the pool inward and substantial erosion of the point bar in the main channel. In contrast, flow deflection is less pronounced at the low‐angle (36°) confluent meander bend, where the converging flows are nearly parallel to one another upon entering the confluence. A large helical cell imparted from upstream flow curvature in the main river occupies most of the downstream channel for prevailing low momentum‐flux ratio conditions and a weak counter‐rotating cell forms during infrequent tributary‐dominant flow events. Bed morphology remains relatively stable and does not exhibit extensive scour that often occurs at confluences with concordant beds. Copyright © 2014 John Wiley & Sons, Ltd.     

A comment on the continuity equation model of slope profile development and its boundary conditions

The constant base boundary condition used by Kirkby to derive characteristic form solutions to the continuity equation are unlikely in practice. Constant form solutions relying on constant basal erosion are however more probable.     

常用岩土本构模型的选择及对场地动力反应分析结果的影响

合理选择本构模型是土动力学问题数值模拟中的一项重要工作。利用PLAXIS 2D软件的土工实验模拟功能分别对4种常用的岩土本构模型——线弹性模型、摩尔库伦模型、土体硬化模型和小应变土体硬化模型在往复荷载下的理论滞回曲线进行了对比分析,并在此基础上研究了选择不同本构模型对自由场地震反应分析结果的影响以及不同本构模型中各参数的变化对场地动力计算结果的敏感性分析。研究结果为土动力学问题数值模拟中如何选择本构模型和合理判断数值分析结果提供了参考依据。     

Numerical investigation of the impact of uncertainties in satellite rainfall estimation and land surface model parameters on simulation of soil moisture

This study aims at evaluating the uncertainty in the prediction of soil moisture (1D, vertical column) from an offline land surface model (LSM) forced by hydro-meteorological and radiation data. We focus on two types of uncertainty: an input error due to satellite rainfall retrieval uncertainty, and, LSM soil-parametric error. The study is facilitated by in situ and remotely sensed data-driven (precipitation, radiation, soil moisture) simulation experiments comprising a LSM and stochastic models for error characterization. The parametric uncertainty is represented by the generalized likelihood uncertainty estimation (GLUE) technique, which models the parameter non-uniqueness against direct observations. Half-hourly infra-red (IR) sensor retrievals were used as satellite rainfall estimates. The IR rain retrieval uncertainty is characterized on the basis of a satellite rainfall error model (SREM). The combined uncertainty (i.e., SREM + GLUE) is compared with the partial assessment of uncertainty. It is found that precipitation (IR) error alone may explain moderate to low proportion of the soil moisture simulation uncertainty, depending on the level of model accuracy—50–60% for high model accuracy, and 20–30% for low model accuracy. Comparisons on the basis of two different sites also yielded an increase (50–100%) in soil moisture prediction uncertainty for the more vegetated site. This study exemplified the need for detailed investigations of the rainfall retrieval-modeling parameter error interaction within a comprehensive space-time stochastic framework for achieving optimal integration of satellite rain retrievals in land data assimilation systems.     

Influence of boundary conditions on the out‐of‐plane response of brick masonry walls in buildings with RC slabs

In modern unreinforced masonry buildings with stiff RC slabs, walls of the top floor are most susceptible to out‐of‐plane failure. The out‐of‐plane response depends not only on the acceleration demand and wall geometry but also on the static and kinematic boundary conditions of the walls. This paper discusses the influence of these boundary conditions on the out‐of‐plane response through evaluation of shake table test results and numerical modelling. As a novum, it shows that the in‐plane response of flanking elements, which are orthogonal to the wall whose out‐of‐plane response is studied, has a significant influence on the vertical restraint at the top of the walls. The most critical configuration exists if the flanking elements are unreinforced masonry walls that rock. In this case, the floor slabs can uplift, and the out‐of‐plane load‐bearing walls loose the vertical restraint at the top. Numerical modelling confirms this experimentally observed behaviour and shows that slab uplift and the difference in base and top excitation have a strong influence on the out‐of‐plane response of the walls analysed. Copyright © 2016 John Wiley & Sons, Ltd.     

The influence of initial conditions and open boundary conditions on shelf circulation in a 3D ocean-shelf model of the North East Atlantic

Data from climatology (World Ocean Atlas) and two large scale operational ocean models (Forecasting Ocean Assimilation Model (FOAM), UK Met. Office and the Navy Coastal Ocean Model (NCOM), US Naval Research Laboratory) are used to give initial and open boundary conditions for a northeast Atlantic implementation of the Proudman Oceanographic Laboratory Coastal Ocean Model System (POLCOMS). We study the effects of using the different datasets on the temperature fields and the circulation. On the continental shelf, comparisons of POLCOMS output with Advanced Very High Resolution Radiometer sea surface temperature data suggest that the effect of using different ocean model initial and boundary conditions is small and that, after 15 months of model time, the impact of the different initial conditions is negligible. Stronger evidence of influence is seen in the deeper oceanic regions of the domain. Volume fluxes through sections governing flow into and out of the North Sea, through the Irish Sea and along the shelf edge show that the impact of the different boundary conditions is small on the shelf but significant elsewhere. These results are contrasted with the use of climatology to assess the value of these Global Ocean Data Assimilation Experiment ocean model products.     

Sensitivity analysis of influencing parameters on slit-type barrier performance against debris flow using 3D-based numerical approach

Extreme rainfall-induced debris flow can be catastrophic to an urban area,and installation of slit-type barriers can prevent such damage while minimizing negative impact on environments.However,the performance of slit-type barriers against debris flows remains poorly identified partly due to the innate complexity in interactions between debris flow and solid structure.This paper investigated the flow behaviors of debris affected by slit-type barriers using the computational fluid dynamics(CFD)method,in which the numerical model based on the volume of fluid method was verified using the physical modeling results.The sensitivity analysis was performed by building metamodels to determine the primary parameters influencing the barrier performance against debris flows among various variables,in which the effect of input properties and design parameters,particularly the soil concentration in fluidized debris,initial velocity and volume of debris,the barrier height,and the opening ratio,was evaluated from the perspectives of the flow energy reduction and debris trapping.The initial velocity and volume of debris were found to play a significant role in determining the debris flow characteristics.A decrease in the opening ratio in the channel primarily facilitated the energy reduction and trapping due to the reduced opening size.However,the barrier height exhibited a limited effect when the height was sufficiently high to block the debris flow volume.In addition,it was observed that the double barrier system effectively increased the energy reduction while keeping the benefit of open-type barrier.The developed simulation method and obtained results provide an effective tool and an insight that can contribute to an optimum design of the debris-flow barrier.     

Simulating the effects of geologic heterogeneity and transient boundary conditions on streambed temperatures — Implications for temperature-based water flux calculations

Analytical solutions to the one-dimensional heat transport equation for steady-state conditions can provide simple means to quantify groundwater surface water exchange. The errors in exchange flux calculations that are introduced when the underlying assumptions of homogeneous sediments and constant temperature boundary conditions are violated were systematically evaluated in a simulation study. Temperatures in heterogeneous sediments were simulated using a numerical model. Heterogeneity in the sediments was represented by discrete, binary geologic units. High contrasts between the hydraulic conductivities (K) of the geologic units were found to lead to large errors, while the influence of the structural arrangement of the units was smaller. The effects of transient temperature boundary conditions were investigated using an analytical equation. Errors introduced by transient boundary conditions were small for Darcy-velocities > 0.1 m d^− 1 in the period near maximum and minimum annual surface water temperatures. For smaller fluxes, however, errors can be large. Assuming steady-state conditions and vertical flow in homogeneous sediments is acceptable at certain times of the year and for medium to high exchange fluxes, but pronounced geologic heterogeneity can lead to large errors.     

Sensitivity to space and time resolution of a hydrological model using digital elevation data

The space and time resolutions used for the input variables of a distributed hydrological model have a sufficient impact on the model results. This resolution depends on the required accuracy, experimental site and the processes and variables taken into account in the hydrological model. The influence of space and time resolution is studied here for the case of TOPMODEL, a model based on the variable contributing area concept, applied to an experimental 12 km² catchment (Coët-Dan, Brittany, France) during a two month winter period. A sensitivity analysis to space and time resolution is performed first for input variables derived from the digital elevation data, secondly for the optimized values of the TOPMODEL parameters and finally for modelling efficiency. This analysis clearly shows that a relevant domain of space and time resolutions where efficiency is fairly constant can be defined for the input topographic variables, as opposed to another domain of larger resolutions that induces a strong decrease of modelling efficiency. It also shows that the use of a single set of parameters, defined as mean values of parameters on this relevant domain of resolution, does not modify the accuracy of modelling. The sensitivity of the parameters to space and time resolution allows the physical significance of the parameter values to be discussed.