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1.
Cross-shore migratory behavior of nearshore sandbars is commonly studied with nearshore bathymetric-evolution models that represent underlying processes of hydrodynamics and sediment transport. These models, however, struggle to reproduce natural cross-shore sandbar behavior on timescales of a few days to weeks and have uncertain skill on longer scales of months to years. One particular concern for the use of models on prediction timescales that far exceed the timescale of the modeled processes is the exponential accumulation of errors in the nonlinear model equations. The relation between cross-shore sandbar migration, sandbar location and wave height has previously been demonstrated to be weakly nonlinear on timescales of several days, but it is unknown how this nonlinearity affects the predictability of long-term (months to years) cross-shore sandbar behavior. Here we study the role of nonlinearity in the predictability of sandbar behavior on timescales of a few days to several months with data-driven neural network models. Our analyses are based on over 5600 daily-observed cross-shore sandbar locations and daily-averaged wave forcings from the Gold Coast, Australia, and Hasaki, Japan. We find that neural network models are able to hindcast many aspects of cross-shore sandbar behavior, such as rapid offshore migration during storms, slower onshore return during quiet periods, seasonal cycles and annual to interannual offshore-directed trends. Although the relation between sandbar migration, sandbar location and wave height is nonlinear, sandbar behavior can be hindcasted accurately over the entire lifespan of the sandbars at the Gold Coast. Contrastingly, it is difficult to hindcast the long-term offshore-directed trends in sandbar behavior at Hasaki because of exponential accumulation of errors over time. Our results further reveal that during periods with low-wave conditions it becomes increasingly difficult to predict sandbar locations, while during high waves predictions become increasingly accurate. 相似文献
2.
This study investigates the recovery capabilities of a single-barred beach in the Pacific Mexican coast before and after the 2015–2016 El Niño winter. Concurrent hydrodynamic and morphological data collected over a 3-year period (August 2014–2017) were analysed to determine the subaerial-subtidal volumetric exchange and cross-shore subtidal sandbar migrations, in relation to the incident wave forcing. The beach presented a seasonal seaward and landward sandbar migration cycle. The sandbar migrated offshore during the energetic waves between November and February, and onshore during the milder wave period in spring, until welding to the subaerial beach around May. The transfer of sediment towards the subaerial section continued over the summer, reaching a complete recovery by September/October. Prior to El Niño, the subaerial beach successfully recovered by the end of summer 2015 through the landward sandbar migration process. The 2015–2016 energetic winter waves caused a subaerial volume loss of ~ 140 m3 m?1 (from October 2015 to March 2016), more than twice the amount eroded in the other winters, and the sandbar moved further offshore and to deeper depths (3–4 m) than the winter before. In addition, the energetic 2015–2016 winter waves lasted for 2 months longer than in other years, making the 2016 spring shorter. Consequently, during the onshore migration, the sandbar was unable of reaching shallow depths, and a large portion of sand remained in the subtidal beach. The subaerial beach recovered 60 and 65% of the loss in the 2016 and 2017 summers, respectively. It is concluded that the landward migration process of the sandbar during the spring is critical to ensure a full subaerial beach recovery over the mild wave period in summer. The recovery capabilities of the subaerial beach will depend on the cross-shore distance and depth where the sandbar is located, and on the duration of mild wave conditions required for the sandbar to migrate onshore. 相似文献
3.
A 1-D General Ocean Turbulence Model that includes the effects of sediment-induced stratification is shown to simulate the observed onshore and offshore migration of a nearshore sandbar. The only two free parameters of the model, the bed reference concentration and the sediment diffusivity, are taken from the literature, rather than tuned to the data used here. The model results suggest that predictions of onshore bar migration, in which wave-induced sediment transport confined to within a few centimeters of the bottom dominates, are not greatly affected by accounting for buoyancy effects. The model results also suggest that both mean flows and waves transport sediment during offshore bar migration, with different components of transport dominating at different cross-shore locations across the bar-trough bathymetry. Neglecting the effects of sediment-induced stratification results in higher model skill during the largest waves, likely because the excess turbulence production simulated by the non-stratified model is counterbalanced by neglected breaking-wave-generated turbulence. Considering both onshore and offshore migration, the model that includes sediment-induced stratification has higher skill than the model without stratification. 相似文献
4.
Sandbars, submerged ridges of sand parallel to the shoreline, affect surfzone circulation, beach topography and beach width. Under time‐varying wave forcing, sandbars may migrate onshore and offshore, referred to as two‐dimensional (2D) behaviour, and vary in planshape from alongshore uniform ridges to alongshore non‐uniform ridges through the growth and decay of three‐dimensional (3D) patterns, referred to as 3D behaviour. Although 2D and 3D sandbar behaviour is reasonably well understood along straight coasts, this is not the case for curved coasts, where the curvature can invoke spatial variability in wave forcing. Here, we analyse sandbar behaviour along the ～3000 m man‐made curved coastline of the Sand Engine, Netherlands, and determine the wave conditions governing this behaviour. 2D and 3D behaviour was quantified within a box north and west of the Sand Engine's tip, respectively, using a 2.4‐year dataset of daily low‐tide video images and a sparser bathymetric dataset. The northern and western sides behaved similarly in terms of 2D behaviour, with seasonal onshore and offshore migration, resulting in a stable position on inter‐annual timescales. However, both sandbar geometry and 3D behaviour differed substantially between both sides. The geometric differences (bar shape, bar crest depth and wavelength of 3D patterns) are consistent with computed alongshore differences in breaker height due to refraction. The differences in the timing in growth, decay and morphological coupling of 3D patterns in the sandbar and shoreline are likely related to differences in the local wave angle, imposed by the curved coast. Similar dependency of bar behaviour on local wave height and angle may be expected elsewhere along curved coasts, e.g. shoreline sandwaves, cuspate forelands or embayed beaches. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
5.
L. Shawn Matott 《Ground Water Monitoring & Remediation》2012,32(2):66-80
Pump‐and‐treat systems can prevent the migration of groundwater contaminants and candidate systems are typically evaluated with groundwater models. Such models should be rigorously assessed to determine predictive capabilities and numerous tools and techniques for model assessment are available. While various assessment methodologies (e.g., model calibration, uncertainty analysis, and Bayesian inference) are well‐established for groundwater modeling, this paper calls attention to an alternative assessment technique known as screening‐level sensitivity analysis (SLSA). SLSA can quickly quantify first‐order (i.e., main effects) measures of parameter influence in connection with various model outputs. Subsequent comparisons of parameter influence with respect to calibration vs. prediction outputs can suggest gaps in model structure and/or data. Thus, while SLSA has received little attention in the context of groundwater modeling and remedial system design, it can nonetheless serve as a useful and computationally efficient tool for preliminary model assessment. To illustrate the use of SLSA in the context of designing groundwater remediation systems, four SLSA techniques were applied to a hypothetical, yet realistic, pump‐and‐treat case study to determine the relative influence of six hydraulic conductivity parameters. Considered methods were: Taguchi design‐of‐experiments (TDOE); Monte Carlo statistical independence (MCSI) tests; average composite scaled sensitivities (ACSS); and elementary effects sensitivity analysis (EESA). In terms of performance, the various methods identified the same parameters as being the most influential for a given simulation output. Furthermore, results indicate that the background hydraulic conductivity is important for predicting system performance, but calibration outputs are insensitive to this parameter (KBK). The observed insensitivity is attributed to a nonphysical specified‐head boundary condition used in the model formulation which effectively “staples” head values located within the conductivity zone. Thus, potential strategies for improving model predictive capabilities include additional data collection targeting the KBK parameter and/or revision of model structure to reduce the influence of the specified head boundary. 相似文献
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Derek W. T. Jackson J. Andrew G. Cooper Marianne O'Connor Emilia Guisado‐Pintado Carlos Loureiro Giorgio Anfuso 《地球表面变化过程与地形》2016,41(8):1107-1114
Nearshore bars play a pivotal role in coastal behaviour, helping to protect and restore beach systems particularly in post‐storm conditions. Examination of bar behaviour under various forcing conditions is important to help understand the short‐ to medium‐term evolution of sandy beach systems. This study carried out over a nine‐week period examines, the behaviour of three intertidal bars along a high energy sandy beach system in northwest Ireland using high‐frequency topographic surveys and detailed nearshore hydrodynamic modelling. Results show that, in general, there was onshore migration for all the bars during the study period, despite the variability observed between bars, which was driven mostly by wave dominated processes. Under the prevailing conditions migration rates of up to 1.83 m day?1 and as low as 0.07 m day?1 were observed. During higher wave energy events the migration rates of the bars decelerated in their onshore route, however, under lower wave energy conditions, they quickly accelerated maintaining their shoreward migration direction. Tidal influence appears to be subordinate in these conditions, being restricted to moderating the localized wave energy at low tides and in maintaining runnel configurations providing accommodation space for advancing slip faces. The study highlights the intricate behavioural patterns of intertidal bar behaviour along a high energy sandy coastline and provides new insights into the relative importance of wave and tidal forcing on bar behaviour over a relatively short time period. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
8.
Assessment of the adequacy of the regional relationships between catchment attributes and catchment response dynamics,calibrated by a multi‐objective approach 
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下载免费PDF全文 This study aimed to evaluate the effectiveness of the regionalization method on the basis of a combination of a parsimonious model structure and a multi‐objective calibration technique. For this study, 12 gauged catchments in the Republic of Korea were used. The parsimonious model structure, requiring minimal input data, was used to avoid adverse effects arising from model complexity, over‐parameterization and data requirements. The IHACRES rainfall‐runoff model was applied to represent the dynamic response characteristics of catchments in Korea. A multi‐objective approach was adopted to reduce the predictive uncertainty arising from the calibration of a rainfall‐runoff model, by increasing the amount of information retrieved from the available data. The regional relationships (or models) between the model parameters and the catchment attributes were established via a multiple regression approach, incorporating correlation analysis and stepwise regression on linear and logarithmic scales. The impacts of the parameters, calibrated by the multi‐objective approach, on the adequacy of regional relationships were assessed by comparison with impacts obtained by the single‐objective approach. The regional relationships were well defined, despite limited available data. The drainage area, the effective soil depth, the mean catchment slope and the catchment gradient appeared to be the main factors for describing the hydrologic response characteristics in the areas studied. The overall model performance of the regional models based on the multi‐objective approach was good, producing reasonable results for high and low flows and for the overall water balance, simultaneously. The regional models based on the single‐objective approach yielded accurate predictions in high flows but showed limited predictive capability for low flows and the overall water balance. This was due to the optimal model parameter estimates when using a single‐objective measure. The parameters calibrated by the single‐objective approach decreased the predictability of the regional models. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
9.
Knowledge of the physical processes acting at inlet systems and their interaction with sediments and sediment bodies is important to the understanding of such environments. The objectives of this study are to identify and assess the relative importance of the controlling processes across the complex sandbar system at the Teign inlet (Teignmouth, UK) through the combined application of a numerical model, field data and Argus video images. This allows the determination of the regions dominated by wave processes or by tidal processes and definition of the variability of these regions under different wave, tide and river-discharge conditions. Modelling experiments carried out for one stage of the evolution of the system show that the interaction between tidal motion and waves generates complex circulation patterns that drive the local sediment transport and sandbar dynamics, producing a cyclic morphological behaviour of the sandbars that form the ebb-tidal delta. The relative importance of each physical process on the sediment transport and consequent morphodynamics varies across the region. The main inlet channel is dominated by tidal action that directs the sediment transport as a consequence of the varying tidal flow asymmetry, resulting in net offshore transport. Sediment transport over the shoals and secondary channels at both sides of the main channel is dominated by wave-related processes, displacing sediment in the onshore direction. The interaction between waves and tide-generated currents controls the transport over the submerged sandbar that defines the channels seaward extend. High river discharge events are also proven to be important in this region, as they can change sediment-transport patterns across the area.Responsible Editor: Iris Grabemann 相似文献
10.
Automatic calibration of complex subsurface reaction models involves numerous difficulties, including the existence of multiple plausible models, parameter non-uniqueness, and excessive computational burden. To overcome these difficulties, this study investigated a novel procedure for performing simultaneous calibration of multiple models (SCMM). By combining a hybrid global-plus-polishing search heuristic with a biased-but-random adaptive model evaluation step, the new SCMM method calibrates multiple models via efficient exploration of the multi-model calibration space. Central algorithm components are an adaptive assignment of model preference weights, mapping functions relating the uncertain parameters of the alternative models, and a shuffling step that efficiently exploits pseudo-optimal configurations of the alternative models. The SCMM approach was applied to two nitrate contamination problems involving batch reactions and one-dimensional reactive transport. For the chosen problems, the new method produced improved model fits (i.e. up to 35% reduction in objective function) at significantly reduced computational expense (i.e. 40–90% reduction in model evaluations), relative to previously established benchmarks. Although the method was effective for the test cases, SCMM relies on a relatively ad-hoc approach to assigning intermediate preference weights and parameter mapping functions. Despite these limitations, the results of the numerical experiments are empirically promising and the reasoning and structure of the approach provide a strong foundation for further development. 相似文献
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The use of spatial patterns of flood inundation (often obtained from remotely sensed imagery) to calibrate flood inundation models has been widespread over the last 15 years. Model calibration is most often achieved by employing one or even several performance measures derived from the well‐known confusion matrix based on a binary classification of flooding. However, relatively early on, it has been recognized that the use of commonly reported performance measures for calibrating flood inundation models (such as the F measure) is hampered because the calibration procedure commonly utilizes only one possible solution of a wet/dry classification of a remote sensing image [most often acquired by a synthetic aperture radar (SAR)] to calibrate or validate models and are biased towards either over‐prediction or under‐prediction of flooding. Despite the call in several studies for an alternative statistic, to this date, very few, if any, unbiased performance measure based on the confusion matrix has been proposed for flood model calibration/validation studies. In this paper, we employ a robust statistical measure that operates in the receiver operating characteristics (ROC) space and allows automated model calibration with high identifiability of the best model parameter set but without the need of a classification of the SAR image. The ROC‐based method for flood model calibration is demonstrated using two different flood event test cases with flood models of varying degree of complexity and boundary conditions with varying degree of accuracy. Verification of the calibration results and optional SAR classification is successfully performed with independent observations of the events. We believe that this proposed alternative approach to flood model calibration using spatial patterns of flood inundation should be employed instead of performance measures commonly used in conjunction with a binary flood map. © 2013 California Institute of Technology. Hydrological Processes © 2013 John Wiley & Sons, Ltd. 相似文献
12.
Abstract The use of a physically-based hydrological model for streamflow forecasting is limited by the complexity in the model structure and the data requirements for model calibration. The calibration of such models is a difficult task, and running a complex model for a single simulation can take up to several days, depending on the simulation period and model complexity. The information contained in a time series is not uniformly distributed. Therefore, if we can find the critical events that are important for identification of model parameters, we can facilitate the calibration process. The aim of this study is to test the applicability of the Identification of Critical Events (ICE) algorithm for physically-based models and to test whether ICE algorithm-based calibration depends on any optimization algorithm. The ICE algorithm, which uses the data depth function, was used herein to identify the critical events from a time series. Low depth in multivariate data is an unusual combination and this concept was used to identify the critical events on which the model was then calibrated. The concept is demonstrated by applying the physically-based hydrological model WaSiM-ETH on the Rems catchment, Germany. The model was calibrated on the whole available data, and on critical events selected by the ICE algorithm. In both calibration cases, three different optimization algorithms, shuffled complex evolution (SCE-UA), parameter estimation (PEST) and robust parameter estimation (ROPE), were used. It was found that, for all the optimization algorithms, calibration using only critical events gave very similar performance to that using the whole time series. Hence, the ICE algorithm-based calibration is suitable for physically-based models; it does not depend much on the kind of optimization algorithm. These findings may be useful for calibrating physically-based models on much fewer data. Editor D. Koutsoyiannis; Associate editor A. Montanari Citation Singh, S.K., Liang, J.Y., and Bárdossy, A., 2012. Improving calibration strategy of physically-based model WaSiM-ETH using critical events. Hydrological Sciences Journal, 57 (8), 1487–1505. 相似文献
13.
Calibration is typically used for improving the predictability of mechanistic simulation models by adjusting a set of model parameters and fitting model predictions to observations. Calibration does not, however, account for or correct potential misspecifications in the model structure, limiting the accuracy of modeled predictions. This paper presents a new approach that addresses both parameter error and model structural error to improve the predictive capabilities of a model. The new approach simultaneously conducts a numeric search for model parameter estimation and a symbolic (regression) search to determine a function to correct misspecifications in model equations. It is based on an evolutionary computation approach that integrates genetic algorithm and genetic programming operators. While this new approach is designed generically and can be applied to a broad array of mechanistic models, it is demonstrated for an illustrative case study involving water quality modeling and prediction. Results based on extensive testing and evaluation, show that the new procedure performs consistently well in fitting a set of training data as well as predicting a set of validation data, and outperforms a calibration procedure and an empirical model fitting procedure. 相似文献
14.
IAN LITTLEWOOD 《水文科学杂志》2013,58(5):795-811
Abstract A continuous simulation rainfall-streamflow modelling approach that identifies unit hydrographs for total streamflow has been applied to an 11-year record from a national hydrometric monitoring network catchment in the UK. The model is of the parametrically parsimonious conceptual model (PPCM) type that can make efficient use of rainfall, streamflow and air temperature data readily available from established national and regional monitoring networks. A multiple split-sample model calibration and simulation analysis is presented that reveals some guiding principles for calibrating and applying PPCMs generally. The inadequacy of a one-dimensional objective function for calibrating best PPCMs is demonstrated. A two-dimensional objective function approach is superior but is shown to be unreliable in some cases, confirming the need for additional critical inspection of other model performance statistics, model parameters and time series plots as an integral part of the model calibration process. A strong tendency evident from the multiple split-sample analysis is that, for the catchment studied, models that fit relatively well in calibration mode perform relatively poorly in simulation mode. 相似文献
15.
In this paper the performance of two hydrological‐response models is evaluated and compared based upon simulations for a single rainfall–runoff event. The two models are QPBRRM, a relatively simple model of Horton overland flow, and InHM, a comprehensive physics‐based model of each of the known streamflow generation mechanisms. The rainfall–runoff event focused upon in this study is from the small rangeland catchment in Oklahoma known as R‐5. When calibrated, both QPBRRM and InHM are shown to effectively simulate the R‐5 event. The calibration procedures used in this study for QPBRRM and InHM were quite different. The calibration of QPBRRM was a curve fitting exercise, whereas the calibration of InHM was based upon an internally valid estimate of the continuous head field. In this study QPBRRM did not perform well outside of the calibrated range. The impact of the roads cutting across the R‐5 catchment is simulated with InHM and discussed for the first time in the study reported here. The relative merits of QPBRRM and InHM are each discussed. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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《Continental Shelf Research》2005,25(9):1053-1069
Predictions of nearshore depth evolution using process-based numerical simulation models contain inherent uncertainties owing to model structural deficiencies, measurement errors, and parameter uncertainty. This paper quantifies the parameter-induced predictive uncertainty of the cross-shore depth evolution model Unibest-TC by applying the Bayesian Generalised Likelihood Uncertainty Estimation methodology to modelling depth evolution at Egmond aan Zee (Netherlands). This methodology works with multiple sets of parameter values sampled uniformly in feasible parameter space and assigns a likelihood value to each parameter set. Acceptable simulations (i.e., based on parameter sets with a nonzero likelihood) were found for a wide range of parameter values owing to parameter interdependence and insensitivity. The 95% uncertainty prediction interval of bed levels after the 33 days prediction period was largest (0.5–1 m) near the sandbar crests that characterize the Egmond depth profile, reducing to near-zero values in the sandbar troughs and the offshore area. The prediction interval built up during storms (when sediment transport rates are largest) and remained the same or even reduced slightly during less-energetic conditions. The prediction uncertainty ranges bracket the observations near the inner-bar crest, its seaward flank, and at the seaward flank of the outer bar, suggesting that elsewhere model structural errors (and, potentially, measurement errors) dominate over parameter errors. The interdependence and the non-Gaussian marginal posterior distribution functions of the free model parameters cast doubt on the ability of commonly applied multivariate normal distribution functions to estimate parameter uncertainty. 相似文献
18.
The use of detailed groundwater models to simulate complex environmental processes can be hampered by (1) long run‐times and (2) a penchant for solution convergence problems. Collectively, these can undermine the ability of a modeler to reduce and quantify predictive uncertainty, and therefore limit the use of such detailed models in the decision‐making context. We explain and demonstrate a novel approach to calibration and the exploration of posterior predictive uncertainty, of a complex model, that can overcome these problems in many modelling contexts. The methodology relies on conjunctive use of a simplified surrogate version of the complex model in combination with the complex model itself. The methodology employs gradient‐based subspace analysis and is thus readily adapted for use in highly parameterized contexts. In its most basic form, one or more surrogate models are used for calculation of the partial derivatives that collectively comprise the Jacobian matrix. Meanwhile, testing of parameter upgrades and the making of predictions is done by the original complex model. The methodology is demonstrated using a density‐dependent seawater intrusion model in which the model domain is characterized by a heterogeneous distribution of hydraulic conductivity. 相似文献
19.
Abstract The complexity of distributed hydrological models has led to improvements in calibration methodologies in recent years. There are various manual, automatic and hybrid methods of calibration. Most use a single objective function to calculate estimation errors. The use of multi-objective calibration improves results, since different aspects of the hydrograph may be considered simultaneously. However, the uncertainty of estimates from a hydrological model can only be taken into account by using a probabilistic approach. This paper presents a calibration method of probabilistic nature, based on the determination of probability functions that best characterize different parameters of the model. The method was applied to the Real-time Interactive Basin Simulator (RIBS) distributed hydrological model using the Manzanares River basin in Spain as a case study. The proposed method allows us to consider the uncertainty in the model estimates by obtaining the probability distributions of flows in the flood hydrograph. Citation Mediero, L., Garrote, L. & Martín-Carrasco, F. J. (2011) Probabilistic calibration of a distributed hydrological model for flood forecasting. Hydrol. Sci. J. 56(7), 1129–1149. 相似文献