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1.
《水文科学杂志》2013,58(5)
Abstract The problem of selecting appropriate objective functions for the identification of a lumped conceptual rainfall–runoff model is investigated, focusing on the value of the model in an operational setting. A probability-distributed soil moisture model is coupled with a linear parallel routing scheme, and conditioned on rainfall–runoff observations from three catchments in the southeast of England. Using an abstraction control problem, which requires accurate simulation of the intermediate flow range, it is shown that using the traditional RMSE fit criterion, produces operationally sub-optimal predictions. This is true in the identification period, when applied to a testing period, and to proxy catchment data. Using a second case study of the Leaf River in Mississippi (USA), where the focus changes to predicting flood peaks over a specified threshold, also suggests that the relevant flood threshold should govern the objective function choice. It is concluded that, due to limitations in the structure of the employed model, it would be counter-productive to try to achieve a good all-round representation of the rainfall–runoff processes, and that a more empirical approach to identification may be preferred for specific forecasting problems. This leaves us with the question of how far hydrological realism should be sacrificed in favour of purpose-driven objective functions. 相似文献
2.
《水文科学杂志》2013,58(4):511-524
Abstract The design and operation of flood management systems require computation of flood hydrographs for both design floods and flood forecasting purposes, since observed data are usually inadequate for these tasks. This is particularly relevant for most developing countries, i.e. mainly for tropical catchments. One possible way of obtaining information about flood hydrographs is through the use of rainfall—runoff models. Two such models, namely the Bochum model and the Nash Cascade—Diskin Infiltration model, which are semi-distributed and lumped models, respectively, were used in the present study. These models were applied to two catchments in Kenya with drainage areas of 6.71 km2 and 26.03 km2. A set of 13 selected rainfall—runoff events was used to calibrate and validate the models. The physical parameters required by the models were derived from catchment characteristics using GIS and remote sensing data while the conceptual parameters were obtained by optimization. The flood hydrographs simulated using the parameters so derived indicated that it is possible to use the two models in this tropical environment. 相似文献
3.
Hèou Maléki Badjana Manfred Fink Jörg Helmschrot Bernd Diekkrüger Sven Kralisch Abel Akambi Afouda 《水文科学杂志》2017,62(7):1094-1113
This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.
EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest 相似文献
4.
我国东南沿海中小流域洪水模拟研究 总被引：1，自引：1，他引：0
我国东南沿海多为独流入海的中小流域,河流短小,流域调节能力弱.该区洪水历时较短,但危害较大,加之近年来区内经济的迅速发展,洪水造成损失日趋加剧,因此开展此区洪水特性和防洪减灾研究意义重大.本文以中国东南沿海曹娥江流域为典型,根据中小流域洪水的特点,在初步分析流域降雨径流的成因和洪水演进规律的基础上,开展了流域洪水模拟研究, 选择建立了流域降雨径流模型以及洪水演进模型,重点探讨了利用遥感信息和GIS相结合确定水文模型参数的方法和途径,经实验流域资料检验分析,其模拟结果计算精度满足要求.该研究将有助于该区流域降雨径流特性及洪水演变规律的深入研究,同时为东南沿海中小流域洪水模拟预测和防洪减灾研究提供了经验和模式. 相似文献
5.
Abstract Event-based methods are used in flood estimation to obtain the entire flood hydrograph. Previously, such methods adopted in the UK have relied on pre-determined values of the input variables (e.g. rainfall and antecedent conditions) to a rainfall–runoff model, which is expected to result in an output flood of a particular return period. In contrast, this paper presents a method that allows all the input variables to take on values across the full range of their individual distributions. These values are then brought together in all possible combinations as input to an event-based rainfall–runoff model in a Monte Carlo simulation approach. Further, this simulation strategy produces a long string of events (on average 10 per year), where dependencies from one event to the next, as well as between different variables within a single event, are accounted for. Frequency analysis is then applied to the annual maximum peak flows and flow volumes. Citation Svensson, C., Kjeldsen, T.R., and Jones, D.A., 2013. Flood frequency estimation using a joint probability approach within a Monte Carlo framework. Hydrological Sciences Journal, 58 (1), 1–20. 相似文献
6.
AbstractOver the past century, land-use has changed in southeast Queensland, and when coupled with climatic change, the risk of flooding has increased. This research aims to examine impacts of climate and land-use changes on flood runoff in southeast Queensland, Australia. A rainfall–runoff model, RORB, was calibrated and validated using observed flood hydrographs for one rural and one urbanized catchment, for 1961–1990. The validated model was then used to generate flood hydrographs using projected rainfall based on two climate models: the Geophysical Fluid Dynamics Laboratory Climate Model 2.1 (GFDL CM2.1) and the Conformal-Cubic Atmospheric Model (CCAM), for 2016–2045. Projected daily rainfall for the two contrasting periods was used to derive adjustment factors for a given frequency of occurrence. Two land-use change scenarios were used to evaluate likely impacts. Based on the projected rainfall, the results showed that, in both catchments, future flood magnitudes are unlikely to increase for large flood events. Extreme land-use change would significantly impact flooding in the rural catchment, but not the urbanized catchment.
Editor Z.W. Kundzewicz; Associate editor Y. Gyasi-Agyei 相似文献
7.
本文利用全球陆面数据同化系统与降雨观测数据,以陕西半湿润区陈河流域为研究对象,驱动WRF-Hydro模型,研究该模型的表现和适用性,并在结构、参数、输入输出和模拟结果方面与新安江模型对比.考虑到次表面层与实际包气带的区别,引入土层厚度乘子ZSOILFAC对前者进行等比缩放,发现其与新安江模型反推包气带的厚度有较好的一致性.研究表明:在陈河流域中WRF-Hydro计算步长须在建议值的基础上缩小; WRF-Hydro模型善于模拟洪水细节,新安江模型表现好且稳定;前者的径流深和洪峰合格率平于或略低于后者;在两个指标均合格的洪水中,前者平均均方根误差比后者小21.5%,但对于其他洪水,前者平均均方根误差比后者大56.2%; WRF-Hydro在洪水起涨时刻模拟较好,表现出其在中小流域应用的潜力. 相似文献
8.
《水文科学杂志》2013,58(4):613-625
Abstract Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions. 相似文献
9.
In this paper, the controls of different indicators on the statistical moments (i.e. mean annual flood (MAF), coefficient of variation (CV) and skewness (CS)) of the maximum annual flood records of 459 Austrian catchments are analysed. The process controls are analysed in terms of the correlation of the flood moments within five hydrologically homogeneous regions to two different types of indicators. Indicators of the first type are static catchment attributes, which are associated with long‐term observations such as mean annual precipitation, the base flow index, and the percentage of catchment area covered by a geological unit or soil type. Indicators of the second type are dynamic catchment attributes that are associated with the event scale. Indicators of this type used in the study are event runoff coefficients and antecedent rainfall. The results indicate that MAF and CV are strongly correlated with indicators characterising the hydro‐climatic conditions of the catchments, such as mean annual precipitation, long‐term evaporation and the base flow index. For the catchments analysed, the flood moments are not significantly correlated with static catchment attributes representing runoff generation, such as geology, soil types, land use and the SCS curve number. Indicators of runoff generation that do have significant predictive power for flood moments are dynamic catchment attributes such as the mean event runoff coefficients and mean antecedent rainfall. The correlation analysis indicates that flood runoff is, on average, more strongly controlled by the catchment moisture state than by event rainfall. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
10.
ABSTRACTThe southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.
EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned 相似文献
11.
Patrick Arnaud Jacques Lavabre Catherine Fouchier Stéphanie Diss Pierre Javelle 《水文科学杂志》2013,58(3):397-410
Abstract Different approaches used in hydrological modelling are compared in terms of the way each one takes the rainfall data into account. We examine the errors associated with accounting for rainfall variability, whether in hydrological modelling (distributed vs lumped models) or in computing catchment rainfall, as well as the impact of each approach on the representativeness of the parameters it uses. The database consists of 1859 rainfall events, distributed on 500 basins, located in the southeast of France with areas ranging from 6.2 to 2851 km2. The study uses as reference the hydrographs computed by a distributed hydrological model from radar rainfall. This allows us to compare and to test the effects of various simplifications to the process when taking rainfall information (complete rain field vs sampled rainfall) and rainfall–runoff modelling (lumped vs distributed) into account. The results appear to show that, in general, the sampling effect can lead to errors in discharge at the outlet that are as great as, or even greater than, those one would get with a fully lumped approach. We found that small catchments are more sensitive to the uncertainties in catchment rainfall input generated by sampling rainfall data as seen through a raingauge network. Conversely, the larger catchments are more sensitive to uncertainties generated when the spatial variability of rainfall events is not taken into account. These uncertainties can be compensated for relatively easily by recalibrating the parameters of the hydrological model, although such recalibrations cause the parameter in question to completely lose physical meaning. Citation Arnaud, P., Lavabre, J., Fouchier, C., Diss, S. & Javelle, P. (2011) Sensitivity of hydrological models to uncertainty of rainfall input. Hydrol. Sci. J. 56(3), 397–410. 相似文献
12.
A simple modelling framework for assessing the response of ungauged catchments to land use change in South‐Western Australia is presented. The framework uses knowledge of transpiration losses from native vegetation and pasture and then partitions the ‘excess’ water (resulting from reduced transpiration after land use change) between runoff and deep storage. The simple partitioning is achieved by using soft information (satellite imagery, previous mapping and field assessment) to delimit the spread of the permanently saturated area close to the stream. Runoff is then assumed to increase in proportion to the saturated area, with the residual difference going to deep storage. The model parameters to describe the annual water yield are obtained a priori and no calibration to streamflow is required. We tested the model using gauged records over 25 years from paired catchment experiments in South‐Western Australia. Very good estimates of runoff were obtained from high rainfall (>1100 mm yr−1) catchments (R2 > 0·9) and for low rainfall (<900 mm yr−1) catchments after clearing (R2 = 0·96) but results were poorer (R2 = 0·55) for an uncleared low rainfall catchment, although overall balances were reasonable. In the drier uncleared catchments, the within‐year distributions of rainfall may exert a substantial influence on runoff response that is not completely captured by the presented model. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
13.
ABSTRACT In many places, magnitudes and frequencies of floods are expected to increase due to climate change. To understand these changes better, trend analyses of historical data are helpful. However, traditional trend analyses do not address issues related to shifts in the relative contributions of rainfall versus snowmelt floods, or in the frequency of a particular flood type. We present a novel approach for quantifying such trends in time series of floods using a fuzzy decision tree for event classification and applied it to maximal annual and seasonal floods in 27 alpine catchments for the period 1980–2014. Trends in flood types were studied with Sen’s slope and double mass curves. Our results reveal a decreasing number of rain-on-snow and an increasing number of short rainfall events in all catchments, with flash floods increasing in smaller catchments. Overall, the results demonstrate the value of incorporating a fuzzy flood-type classification into flood trend analyses. 相似文献
14.
A. SVOBODA 《水文科学杂志》2013,58(5):461-470
Abstract This paper describes the use of a simple two stage rainfall-runoff model in which a curve number (CN) principle is used to calculate the soil water content and, subsequently, the rainfall contribution to direct runoff and groundwater flow. The maximum soil water retention, S, is used to express various characteristics of a catchment (infiltration rate, soil cover and land use, as in the CN method) relevant to flood formation. Using historical flood events, the model is calibrated, and the statistical distribution parameters of peak flows determined. With the same historical input data scenarios (rainfall), sets of flood hydrographs are simulated for various values of the parameter S, and corresponding distribution parameters of peak flows are determined. This procedure is used to demonstrate possible changes in flood regime to be expected due to changes of the catchment soil properties and its vegetation cover. A case study is presented for the River Hron catchment, area 582 km2, in the mountainous region of central Slovakia. 相似文献
15.
Coupling the Xinanjiang model to a kinematic flow model based on digital drainage networks for flood forecasting 总被引：1，自引：0，他引：1
The Xinanjiang model, which is a conceptual rainfall‐runoff model and has been successfully and widely applied in humid and semi‐humid regions in China, is coupled by the physically based kinematic wave method based on a digital drainage network. The kinematic wave Xinanjiang model (KWXAJ) uses topography and land use data to simulate runoff and overland flow routing. For the modelling, the catchment is subdivided into numerous hillslopes and consists of a raster grid of flow vectors that define the water flow directions. The Xinanjiang model simulates the runoff yield in each grid cell, and the kinematic wave approach is then applied to a ranked raster network. The grid‐based rainfall‐runoff model was applied to simulate basin‐scale water discharge from an 805‐km2 catchment of the Huaihe River, China. Rainfall and discharge records were available for the years 1984, 1985, 1987, 1998 and 1999. Eight flood events were used to calibrate the model's parameters and three other flood events were used to validate the grid‐based rainfall‐runoff model. A Manning's roughness via a linear flood depth relationship was suggested in this paper for improving flood forecasting. The calibration and validation results show that this model works well. A sensitivity analysis was further performed to evaluate the variation of topography (hillslopes) and land use parameters on catchment discharge. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
16.
Abstract The application of artificial neural network (ANN) methodology for modelling daily flows during monsoon flood events for a large size catchment of the Narmada River in Madhya Pradesh (India) is presented. The spatial variation of rainfall is accounted for by subdividing the catchment and treating the average rainfall of each subcatchment as a parallel and separate lumped input to the model. A linear multiple-input single-output (MISO) model coupled with the ANN is shown to provide a better representation of the rainfall-runoff relationship in such large size catchments compared with linear and nonlinear MISO models. The present model provides a systematic approach for runoff estimation and represents improvement in prediction accuracy over the other models studied herein. 相似文献
17.
C.J.C. Blanco S.S.M. Santos M.C. Quintas M.V.A. Vinagre A.L.A. Mesquita 《水文科学杂志》2013,58(7):1423-1433
AbstractThe objective of this study is to analyse three rainfall–runoff hydrological models applied in two small catchments in the Amazon region to simulate flow duration curves (FDCs). The simple linear model (SLM) considers the rainfall–runoff process as an input–output time-invariant system. However, the rainfall–runoff process is nonlinear; thus, a modification is applied to the SLM based on the residual relationship between the simulated and observed discharges, generating the modified linear model (MLM). In the third model (SVM), the nonlinearity due to infiltration and evapotranspiration is incorporated into the system through the sigmoid variable gain factor. The performance criteria adopted were a distance metric (δ) and the Nash-Sutcliffe coefficient (R2) determined between simulated and observed flows. The good results of the models, mainly the MLM and SVM, showed that they could be applied to simulate FDCs in small catchments in the Amazon region.Editor D. Koutsoyiannis; Associate editor A. MontanariCitation Blanco, C.J.C., Santos, S.S.M., Quintas, M.C., Vinagre, M.V.A., and Mesquita, A.L.A., 2013. Contribution to hydrological modelling of small Amazonian catchments: application of rainfall–runoff models to simulate flow duration curves. Hydrological Sciences Journal, 58 (7), 1–11. 相似文献
18.
Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis. 相似文献
19.
AbstractThe accurate prediction of hourly runoff discharge in a watershed during heavy rainfall events is of critical importance for flood control and management. This study predicts n-h-ahead runoff discharge in the Sandimen basin in southern Taiwan using a novel hybrid approach which combines a physically-based model (HEC-HMS) with an artificial neural network (ANN) model. Hourly runoff discharge data (1200 datasets) from seven heavy rainfall events were collected for the model calibration (training) and validation. Six statistical indicators (i.e. mean absolute error, root mean square error, coefficient of correlation, error of time to peak discharge, error of peak discharge and coefficient of efficiency) were employed to evaluate the performance. In comparison with the HEC-HMS model, the single ANN model, and the time series forecasting (ARMAX) model, the developed hybrid HEC-HMS–ANN model demonstrates improved accuracy in recursive n-h-ahead runoff discharge prediction, especially for peak flow discharge and time. 相似文献
20.
Eleonora Spada Marco Sinagra Tullio Tucciarelli Silvia Barbetta Tommaso Moramarco Giovanni Corato 《水文研究》2017,31(7):1539-1557
The discharge hydrograph estimation in rivers based on reverse routing modeling and using only water level data at two gauged sections is here extended to the most general case of significant lateral flow contribution, without needing to deploy rainfall–runoff procedures. The proposed methodology solves the Saint‐Venant equations in diffusive form also involving the lateral contribution using a “head‐driven” modeling approach where lateral inflow is assumed to be function of the water level at the tributary junction. The procedure allows to assess the discharge hydrograph at ends of a selected river reach with significant lateral inflow, starting from the stage recorded there and without needing rainfall data. Specifically, the MAST 1D hydraulic model is applied to solve the diffusive wave equation using the observed stage hydrograph at the upstream section as upstream boundary condition. The other required data are (a) the observed stage hydrograph at the downstream section, as benchmark for the parameter calibration, and (b) the bathymetry of the river reach, from the upstream section to a short distance after the downstream gauged section. The method is validated with different flood events observed in two river reaches with a significant intermediate basin, where reliable rating curves were available, selected along the Tiber River, in central Italy, and the Alzette River, in Luxembourg. Very good performance indices are found for the computed discharge hydrographs at both the channel ends and along the tributaries. The mean Nash‐Sutcliffe value (NSq) at the channel ends of two rivers is found equal to 0.99 and 0.86 for the upstream and downstream sites, respectively. The procedure is also validated on a longer stretch of the Tiber River including three tributaries for which appreciable results are obtained in terms of NSq for the computed discharge hydrographs at both the channel ends for three investigated flood events. 相似文献