首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 520 毫秒
1.
Abstract

Flood frequency estimation is crucial in both engineering practice and hydrological research. Regional analysis of flood peak discharges is used for more accurate estimates of flood quantiles in ungauged or poorly gauged catchments. This is based on the identification of homogeneous zones, where the probability distribution of annual maximum peak flows is invariant, except for a scale factor represented by an index flood. The numerous applications of this method have highlighted obtaining accurate estimates of index flood as a critical step, especially in ungauged or poorly gauged sections, where direct estimation by sample mean of annual flood series (AFS) is not possible, or inaccurate. Therein indirect methods have to be used. Most indirect methods are based upon empirical relationships that link index flood to hydrological, climatological and morphological catchment characteristics, developed by means of multi-regression analysis, or simplified lumped representation of rainfall–runoff processes. The limits of these approaches are increasingly evident as the size and spatial variability of the catchment increases. In these cases, the use of a spatially-distributed, physically-based hydrological model, and time continuous simulation of discharge can improve estimation of the index flood. This work presents an application of the FEST-WB model for the reconstruction of 29 years of hourly streamflows for an Alpine snow-fed catchment in northern Italy, to be used for index flood estimation. To extend the length of the simulated discharge time series, meteorological forcings given by daily precipitation and temperature at ground automatic weather stations are disaggregated hourly, and then fed to FEST-WB. The accuracy of the method in estimating index flood depending upon length of the simulated series is discussed, and suggestions for use of the methodology provided.
Editor D. Koutsoyiannis  相似文献   

2.
Abstract

The 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   

3.
Yi-Ru Chen  Bofu Yu 《水文科学杂志》2013,58(10):1759-1769
Abstract

Over 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   

4.
Abstract

The Kamp River is a particularly interesting case study for testing flood frequency estimation methods, since it experienced a major flood in August 2002. Here, the Kamp catchment is studied in order to quantify the influence of such a remarkable flood event on the calibration of a rainfall–runoff model, in particular when it is used in a stochastic simulation method for flood estimation, by performing numerous rainfall–runoff model calibrations (based on split-sample and bootstrap tests). The results confirmed the usefulness of the multi-period and bootstrap testing schemes for identifying the dependence of model performance and flood estimates on the information contained in the calibration period. The August 2002 event appears to play a dominating role for the Kamp River, since the presence or absence of the event within the calibration sub-periods strongly influences the rainfall–runoff model calibration and the extreme flood estimations that are based on the calibrated model.  相似文献   

5.
Abstract

Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.  相似文献   

6.
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   

7.
ABSTRACT

Discharge observations and reliable rainfall forecasts are essential for flood prediction but their availability and accuracy are often limited. However, even scarce data may still allow adequate flood forecasts to be made. Here, we explored how far using limited discharge calibration data and uncertain forcing data would affect the performance of a bucket-type hydrological model for simulating floods in a tropical basin. Three events above thresholds with a high and a low frequency of occurrence were used in calibration and 81 rainfall scenarios with different degrees of uncertainty were used as input to assess their effects on flood predictions. Relatively similar model performance was found when using calibrated parameters based on a few events above different thresholds. Flood predictions were sensitive to rainfall errors, but those related to volume had a larger impact. The results of this study indicate that a limited number of events can be useful for predicting floods given uncertain rainfall forecasts.  相似文献   

8.
Abstract

The impulse response of a linear convective-diffusion analogy (LD) model used for flow routing in open channels is proposed as a probability distribution for flood frequency analysis. The flood frequency model has two parameters, which are derived using the methods of moments and maximum likelihood. Also derived are errors in quantiles for these parameter estimation methods. The distribution shows that the two methods are equivalent in terms of producing mean values—the important property in case of unknown true distribution function. The flood frequency model is tested using annual peak discharges for the gauging sections of 39 Polish rivers where the average value of the ratio of the coefficient of skewness to the coefficient of variation equals about 2.52, a value closer to the ratio of the LD model than to the gamma or the lognormal model. The likelihood ratio indicates the preference of the LD over the lognormal for 27 out of 39 cases. It is found that the proposed flood frequency model represents flood frequency characteristics well (measured by the moment ratio) when the LD flood routing model is likely to be the best of all linear flow routing models.  相似文献   

9.
Abstract

Flood distributions can have unimodal or multimodal densities due to different flood generation mechanisms such as snowmelt and rainfall in the annual flood series. When applying nonparametric frequency analysis to annual flood data from the province of New Brunswick in Canada, unimodal, bimodal and heavy-tailed distribution shapes were found. By grouping basins with similarly-shaped densities on a geographical basis, homogeneous regions were delineated. Regional equations derived for a homogeneous region gave lower integral square errors than those of province-wide equations.  相似文献   

10.
Abstract

This article presents a comparison between real-time discharges calculated by a flash-flood warning system and post-event flood peak estimates. The studied event occurred on 15 and 16 June 2010 at the Argens catchment located in the south of France. Real-time flood warnings were provided by the AIGA (Adaptation d’Information Géographique pour l’Alerte en Crue) warning system, which is based on a simple distributed hydrological model run at a 1-km2 resolution using radar rainfall information. The timing of the warnings (updated every 15 min) was compared to the observed flood impacts. Furthermore, “consolidated” flood peaks estimated by an intensive post-event survey were used to evaluate the AIGA-estimated peak discharges. The results indicated that the AIGA warnings clearly identified the most affected areas. However, the effective lead-time of the event detection was short, especially for fast-response catchments, because the current method does not take into account any rainfall forecast. The flood peak analysis showed a relatively good correspondence between AIGA- and field-estimated peak values, although some differences were due to the rainfall underestimation by the radar and rainfall–runoff model limitations.
Editor Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Javelle, P., Demargne, J., Defrance, D., Pansu, J. and Arnaud, P., 2014. Evaluating flash-flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system. Hydrological Sciences Journal, 59 (7), 1390–1402. http://dx.doi.org/10.1080/02626667.2014.923970  相似文献   

11.
Abstract

There has been a trend in recent years towards the development and popularity of physically-based deterministic models. However, the application of such models is not without difficulties. This paper investigates the usefulness of a conceptual single-event model for simulating floods from catchments covering a wide variety of climatic and physiographic areas. The model has been calibrated on a group of catchments and the calibrated parameter values related to physical catchment indices. The resulting quantitative relationships are assessed with respect to their value for estimating the parameter values of the model when calibration is not possible. The results indicate that the technique is likely to provide flood estimations for medium sized catchments (5–150 km2) that are more reliable than several flood estimation methods currently in use in South Africa.  相似文献   

12.
Abstract

There is increasing concern that flood risk will be exacerbated in Antalya, Turkey as a result of global-warming-induced, more frequent and intensive, heavy rainfalls. In this paper, first, trends in extreme rainfall indices in the Antalya region were analysed using daily rainfall data. All stations in the study area showed statistically significant increasing trends for at least one extreme rainfall index. Extreme rainfall datasets for current (1970–1989) and future periods (2080–2099) were then constructed for frequency analysis using the peaks-over-threshold method. Frequency analysis of extreme rainfall data was performed using generalized Pareto distribution for current and future periods in order to estimate rainfall intensities for various return periods. Rainfall intensities for the future period were found to increase by up to 23% more than the current period. This study contributed to better understanding of climate change effects on extreme rainfalls in Antalya, Turkey.  相似文献   

13.
Abstract

Pakistan has suffered a devastating flood disaster in 2010. In the Kabul River basin (92 605 km2), large-scale riverine and flash floods caused destructive damage with more than 1100 casualties. This study analysed rainfall–runoff and inundation in the Kabul River basin with a newly developed model that simulates the processes of rainfall–runoff and inundation simultaneously based on two-dimensional diffusion wave equations. The simulation results showed a good agreement with an inundation map produced based on MODIS for large-scale riverine flooding. In addition, the simulation identified flash flood-affected areas, which were confirmed to be severely damaged based on a housing damage distribution map. Since the model is designed to be used even immediately after a disaster, it can be a useful tool for analysing large-scale flooding and to provide supplemental information to agencies for relief operations.

Editor Z.W. Kundzewicz

Citation Sayama, T., Ozawa, G., Kawakami, T., Nabesaka, S. and Fukami, K., 2012. Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin. Hydrological Sciences Journal, 57 (2), 298–312.  相似文献   

14.
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   

15.
Abstract

Sheet sediment transport was modelled by artificial neural networks (ANNs). A three-layer feed-forward artificial neural network structure was constructed and a back-propagation algorithm was used for the training of ANNs. Event-based, runoff-driven experimental sediment data were used for the training and testing of the ANNs. In training, data on slope and rainfall intensity were fed into the network as inputs and data on sediment discharge were used as target outputs. The performance of the ANNs was tested against that of the most commonly used physically-based models, whose transport capacity was based on one of the dominant variables—flow velocity (V), shear stress (SS), stream power (SP), and unit stream power (USP). The comparison results revealed that the ANNs performed as well as the physically-based models for simulating nonsteady-state sediment loads from different slopes. The performances of the ANNs and the physically-based models were also quantitatively investigated to estimate mean sediment discharges from experimental runs. The investigation results indicated that better estimations were obtained for V over mild and steep slopes, under low rainfall intensity; for USP over mild and steep slopes, under high rainfall intensity; for SP and SS over very steep slopes, under high rainfall intensity; and for ANNs over steep and very steep slopes, under very high rainfall intensities.  相似文献   

16.
Abstract

Abstract After the destructive flood in 1998, the Chinese government planned to build national weather radar networks and to use radar data for real-time flood forecasting. Hence, coupling of weather radar rainfall data and a hydrological (Xinanjiang) model became an important issue. The present study reports on experience in such coupling at the Shiguanhe watershed. After having corrected the radar reflectivity and the attenuation data, the weather radar rainfall was estimated and then corrected in real time using a Kalman filter. In general, the precipitation estimated from weather radar is reasonably accurate in most of the catchment investigated, after corrections as above. Compared to the results simulated by raingauge data, the simulations based on the weather radar data are of similar accuracy. Present research results show that rainfall estimated from the weather radar, the radar data correction method, the method of coupling, and the Xinanjiang model lend themselves well to application in operational real-time flood forecasting.  相似文献   

17.
E. Volpi  A. Fiori 《水文科学杂志》2013,58(8):1506-1515
Abstract

In the bivariate analysis of hydrological events, such as rainfall storms or flood hydrographs, the choice of an appropriate return period for structure design leads to infinite combinations of values of the related random variables (e.g. peak and volume in the analysis of floods). These combinations are generally not equivalent, from a practical point of view. In this paper, a methodology is proposed to identify a subset of the critical combinations set that includes a fixed and arbitrarily chosen percentage in probability of the events, on the basis of their probability of occurrence. Therefore, several combinations can be selected within the subset, taking into account the specific characteristic of the design problem, in order to evaluate the effects of different hydrological loads on a structure. The proposed method is applicable to any type of bivariate distribution, thus providing a simple but effective rule to narrow down the infinite possible choices for the hydrological design variables. In order to illustrate how the proposed methodology can be easily used in practice, it is applied to a study case in the context of bivariate flood frequency analysis.

Editor Z.W. Kundzewicz; Associate editor Sheng Yue

Citation Volpi, E. and Fiori, A., 2012. Design event selection in bivariate hydrological frequency analysis. Hydrological Sciences Journal, 57 (8), 1506–1515.  相似文献   

18.
Abstract

A modelling scheme is developed for real-time flood forecasting. It is composed of (a) a rainfall forecasting model, (b) a conceptual rainfall-runoff model, and (c) a stochastic error model of the ARMA family for forecast error correction. Initialization of the rainfall-runoff model is based on running this model on a daily basis for a certain period prior to the flood onset while parameters of the error model are updated through the Recursive Least Squares algorithm. The scheme is suitable for the early stages of operation of flood forecasting systems in the presence of inadequate historical data. A validation framework is set up which simulates real-time flood forecasting conditions. Thus, the effects of the procedures for rainfall-runoff model initialization, forecast error correction and rainfall forecasting are assessed. Two well-known conceptual rainfall-runoff models (the Soil Moisture Accounting model of the US National Weather Service River Forecast Service—SMA-NWSRFS and TANK) together with data from a Greek basin are used for illustration purposes.  相似文献   

19.
ABSTRACT

A rainfall–runoff model was employed to identify four major flood-generating processes corresponding to flood events identified from daily discharge data from 614 stations across Europe in the period 1961–2010: long-rain, short-rain, snowmelt, and rain-on-dry-soil flood events. Trend analyses were performed on the frequency of occurrence of each of the flood types continentally and in five geographical regions of Europe. Continentally, the annual frequency of flood events did not show a significant change over the investigation period. However, the frequency of both winter and summer long-rain events increased significantly, while that of summer snowmelt events decreased significantly. Regionally, the frequency of winter short and long-rain events increased significantly in Western Europe, while the frequency of summer snowmelt and short-rain events decreased in Northern Europe. The frequency of summer snowmelt events in Eastern Europe and winter short-rain events in Southern Europe showed a declining trend.  相似文献   

20.
Abstract

An updating technique is a tool to update the forecasts of mathematical flood forecasting model based on data observed in real time, and is an important element in a flood forecasting model. An error prediction model based on a fuzzy rule-based method was proposed as the updating technique in this work to improve one- to four-hour-ahead flood forecasts by a model that is composed of the grey rainfall model, the grey rainfall—runoff model and the modified Muskingum flow routing model. The coefficient of efficiency with respect to a benchmark is applied to test the applicability of the proposed fuzzy rule-based method. The analysis reveals that the fuzzy rule-based method can improve flood forecasts one to four hours ahead. The proposed updating technique can mitigate the problem of the phase lag in forecast hydrographs, and especially in forecast hydrographs with longer lead times.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号