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1.
Abstract

Seasonal design floods which consider information on seasonal variation are very important for reservoir operation and management. The seasonal design flood method currently used in China is based on seasonal maximum (SM) samples and assumes that the seasonal design frequency is equal to the annual design frequency. Since the return period associated with annual maximum floods is taken as the standard in China, the current seasonal design flood cannot satisfy flood prevention standards. A new seasonal design flood method, which considers dates of flood occurrence and magnitudes of the peaks (runoff), was proposed and established based on copula function. The mixed von Mises distribution was selected as marginal distribution of flood occurrence dates. The Pearson Type III and exponential distributions were selected as the marginal distribution of flood magnitude for annual maximum flood series and peak-over-threshold samples, respectively. The proposed method was applied at the Geheyan Reservoir, China, and then compared with the currently used seasonal design flood methods. The case study results show that the proposed method can satisfy the flood prevention standard, and provide more information about the flood occurrence probabilities in each sub-season. The results of economic analysis show that the proposed design flood method can enhance the floodwater utilization rate and give economic benefits without lowering the annual flood protection standard.

Citation Chen, L., Guo, S. L., Yan, B. W., Liu, P. & Fang, B. (2010) A new seasonal design flood method based on bivariate joint distribution of flood magnitude and date of occurrence. Hydrol. Sci. J. 55(8), 1264–1280.  相似文献   

2.
Abstract

The physically-based flood frequency models use readily available rainfall data and catchment characteristics to derive the flood frequency distribution. In the present study, a new physically-based flood frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) method for deriving the probability density function (pdf) of effective rainfall. The effective rainfall-runoff model is based on kinematic-wave theory. The results of application of this derived model to three Indian basins indicate that the model is a useful alternative for estimating flood flow quantiles at ungauged sites.  相似文献   

3.
Abstract

Results of a comprehensive synoptic-hydrological analysis of major flood events in the Negev (1964–2007) are presented. A low threshold for major flood data was set to be the 10-year recurrence interval of peak discharge and/or flood volume magnitude. Altogether, 75 major flood events, or 133 hydrometrically monitored floods, were extracted. These events were categorized according to synoptic oriented classes by verification of the paired databases of: (a) floods in the study area, and (b) synoptic systems over the Eastern Mediterranean. For the study area, two of the most frequent flood-generating synoptic systems are the autumn Red Sea Trough (RST), 31%, and winter cyclones, 49%. The entire RST series consists of 24 major flood events (55 floods). The synoptic definition was corroborated by analysing the specific form of flood hydrographs and the ratio of flood volume to peak discharge. Regional analysis shows increased contribution of RST events southwards from 30% to 90% with a respective decrease in the number of cyclone events. By comparing two 22-year sub-periods (1964–1985 and 1986–2007), a positive trend in the frequency and magnitudes of RST flood events is discerned. There is also an increased tendency for the occurrence of cyclone floods.

Editor Z.W. Kundzewicz

Citation Shentsis, I., Laronne J.B., and Alpert, P., 2012. Red Sea Trough flood events in the Negev, Israel (1964–2007). Hydrological Sciences Journal, 57 (1), 42–51.  相似文献   

4.
The index flood procedure coupled with the L‐moments method is applied to the annual flood peaks data taken at all stream‐gauging stations in Turkey having at least 15‐year‐long records. First, screening of the data is done based on the discordancy measure (Di) in terms of the L‐moments. Homogeneity of the total geographical area of Turkey is tested using the L‐moments based heterogeneity measure, H, computed on 500 simulations generated using the four parameter Kappa distribution. The L‐moments analysis of the recorded annual flood peaks data at 543 gauged sites indicates that Turkey as a whole is hydrologically heterogeneous, and 45 of 543 gauged sites are discordant which are discarded from further analyses. The catchment areas of these 543 sites vary from 9·9 to 75121 km2 and their mean annual peak floods vary from 1·72 to 3739·5 m3 s?1. The probability distributions used in the analyses, whose parameters are computed by the L‐moments method are the general extreme values (GEV), generalized logistic (GLO), generalized normal (GNO), Pearson type III (PE3), generalized Pareto (GPA), and five‐parameter Wakeby (WAK). Based on the L‐moment ratio diagrams and the |Zdist|‐statistic criteria, the GEV distribution is identified as the robust distribution for the study area (498 gauged sites). Hence, for estimation of flood magnitudes of various return periods in Turkey, a regional flood frequency relationship is developed using the GEV distribution. Next, the quantiles computed at all of 543 gauged sites by the GEV and the Wakeby distributions are compared with the observed values of the same probability based on two criteria, mean absolute relative error and determination coefficient. Results of these comparisons indicate that both distributions of GEV and Wakeby, whose parameters are computed by the L‐moments method, are adequate in predicting quantile estimates. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

5.
Abstract

Daily flow records, rainfall data and tropical cyclone maps during 1970–1998 are used to document the impact of tropical cyclones (TCs) on floods in the Rewa River system, Viti Levu, Fiji. Floods are large, brief, isolated events caused by TCs and non-TC tropical rainstorms. More floods are caused by tropical rainstorms than by TCs, but TC floods are larger. The log Pearson Type III distribution consistently provided the best fit to partial duration flood series and the widely-recommended generalized Pareto distribution performed very poorly, underscoring the need to test a variety of distributions for a particular geographic location. Tropical cyclones occur more often in Fiji during negative values of the Southern Oscillation Index (SOI) and all TCs that occurred during El Niño conditions caused floods. Peak flood discharges caused by TCs are inversely correlated with the SOI, reflecting possible links with tropical cyclone frequency and precipitation intensity.  相似文献   

6.
ABSTRACT

Series of observed flood intervals, defined as the time intervals between successive flood peaks over a threshold, were extracted directly from 11 approximately 100-year streamflow datasets from Queensland, Australia. A range of discharge thresholds were analysed that correspond to return periods of approximately 3.7 months to 6.3 years. Flood interval histograms at South East Queensland gauges were consistently unimodal whereas those of the North and Central Queensland sites were often multimodal. The exponential probability distribution (pd) is often used to describe interval exceedence probabilities, but fitting utilizing the Anderson-Darling statistic found little evidence that it is the most suitable. The fatigue life pd dominated sub-year return periods (<1 year), often transitioning to a log Pearson 3 pd at above-year return periods. Fatigue life pd is used in analysis of the lifetime to structural failure when a threshold is exceeded, and this paper demonstrates its relevance also to the elapsed time between above-threshold floods. At most sites, the interval medians were substantially less than the means for sub-year return periods. Statistically the median is a better measure of the central tendency of skewed distributions but the mean is generally used in practice to describe the classical concept of flood return period.
Editor Z.W. Kundzewicz; Associate editor I. Nalbantis  相似文献   

7.
Abstract

Flood frequency analysis based on a set of systematic data and a set of historical floods is applied to several Mediterranean catchments. After identification and collection of data on historical floods, several hydraulic models were constructed to account for geomorphological changes. Recent and historical rating curves were constructed and applied to reconstruct flood discharge series, together with their uncertainty. This uncertainty stems from two types of error: (a) random errors related to the water-level readings; and (b) systematic errors related to over- or under-estimation of the rating curve. A Bayesian frequency analysis is performed to take both sources of uncertainty into account. It is shown that the uncertainty affecting discharges should be carefully evaluated and taken into account in the flood frequency analysis, as it can increase the quantiles confidence interval. The quantiles are found to be consistent with those obtained with empirical methods, for two out of four of the catchments.

Citation Neppel, L., Renard, B., Lang, M., Ayral, P.-A., Coeur, D., Gaume, E., Jacob, N., Payrastre, O., Pobanz, K. & Vinet, F. (2010) Flood frequency analysis using historical data: accounting for random and systematic errors. Hydrol. Sci. J. 55(2), 192–208.  相似文献   

8.
The magnitude, occurrence rate and occurrence timing of floods in the Poyang Lake basin were analysed. The flood series were acquired by annual and seasonal maximum flow (AMF) sampling and peaks-over-threshold (POT) sampling. Nonstationarity and uncertainty were analysed using kernel density estimation and the bootstrap resampling methods. Using the relationships between flood indices and climate indices, i.e. El Niño/Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO), the potential causes of flooding were investigated. The results indicate that (1) the magnitudes of annual and seasonal AMF- and POT-based sampled floods generally exhibit an increasing tendency; (2) the highest occurrence rates of floods identified were during the 1990s, when the flood-affected crop area, flood-damaged crop area and crop failure area reached the highest levels; and (3) ENSO and IOD are the major climate indices that significantly correlate with the magnitude and frequency of floods of the following year.

EDITOR A. Castellarin ASSOCIATE EDITOR T. Kjeldsen  相似文献   

9.
ABSTRACT

Flood peaks and volumes are essential design variables and can be simulated by precipitation–runoff (P–R) modelling. The high-resolution precipitation time series that are often required for this purpose can be generated by various temporal disaggregation methods. Here, we compare a simple method (M1, one parameter), focusing on the effective precipitation duration for flood simulations, with a multiplicative cascade model (M2, 32/36 parameters). While M2 aims at generating realistic characteristics of precipitation time series, M1 aims only at accurately reproducing flood variables by P–R modelling. Both disaggregation methods were tested on precipitation time series of nine Swiss mesoscale catchments. The generated high-resolution time series served as input for P–R modelling using a lumped HBV model. The results indicate that differences identified in precipitation characteristics of disaggregated time series vanish when introduced into the lumped hydrological model. Moreover, flood peaks were more sensitive than flood volumes to the choice of disaggregation method.  相似文献   

10.
Random variable simulation has been applied to many applications in hydrological modelling, flood risk analysis, environmental impact assessment, etc. However, computer codes for simulation of distributions commonly used in hydrological frequency analysis are not available in most software libraries. This paper presents a frequency‐factor‐based method for random number generation of five distributions (normal, log–normal, extreme‐value type I, Pearson type III and log‐Pearson type III) commonly used in hydrological frequency analysis. The proposed method is shown to produce random numbers of desired distributions through three means of validation: (1) graphical comparison of cumulative distribution functions (CDFs) and empirical CDFs derived from generated data; (2) properties of estimated parameters; (3) type I error of goodness‐of‐fit test. An advantage of the method is that it does not require CDF inversion, and frequency factors of the five commonly used distributions involves only the standard normal deviate. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

11.
Abstract

Floods from the middle part of the River Morava (eastern Czech Republic) are considered over the course of the past three centuries, the study being based on data derived from documentary evidence (1691–1880), measured peak water stages, Hk (1881–1920) and peak discharges, Qk (1916–2009), evaluated with respect to their N-year return period (HN and QN ). Changes in land use and water management (water reservoirs, channel modifications) are discussed, as are factors influencing runoff conditions in the Morava catchment. Decadal synthesis of flood series identifies the highest flood activity in the decades of 1911–1920 and 1961–1970 (11 floods each), 1831–1840, 1891–1900, 1901–1910 and 1931–1940 (10 floods each). Uncertainty in this series is related to some incompleteness of documentary data in the pre-1881 period. Very low flood frequency occurred in the 1990s–2000s, although the most disastrous floods were recorded in this particular period (July 1997 at Q 100 and March/April 2006 at Q 20Q 50). Changes in flood frequency correspond partly to long-term changes in temperature and precipitation patterns.

Citation Brázdil, R., ?ezní?ková, L., Valá?ek, H., Havlí?ek, M., Dobrovolný, P., Soukalová, E., ?ehánek, T. & Skokanová, H. (2011) Fluctuations of floods of the River Morava (Czech Republic) in the 1691–2009 period: interactions of natural and anthropogenic factors. Hydrol. Sci. J. 56(3), 468–485.  相似文献   

12.
Abstract

Flood frequency analysis can be made by using two types of flood peak series, i.e. the annual maximum (AM) and peaks-over-threshold (POT) series. This study presents a comparison of the results of both methods for data from the Litija 1 gauging station on the Sava River in Slovenia. Six commonly used distribution functions and three different parameter estimation techniques were considered in the AM analyses. The results showed a better performance for the method of L-moments (ML) when compared with the conventional moments and maximum likelihood estimation. The combination of the ML and the log-Pearson type 3 distribution gave the best results of all the considered AM cases. The POT method gave better results than the AM method. The binomial distribution did not offer any noticeable improvement over the Poisson distribution for modelling the annual number of exceedences above the threshold.
Editor D. Koutsoyiannis

Citation Bezak, N., Brilly, M., and ?raj, M., 2014. Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis. Hydrological Sciences Journal, 59 (5), 959–977.  相似文献   

13.
Abstract

The reassessment of flood risk at York, UK, is pertinent in light of major flooding in November 2000, and heightened concerns of a perceived increase in flooding nationally. Systematic flood level readings from 1877 and a wealth of documentary records dating back as far as 1263 AD give the City of York a long and rich history of flood records. This extended flood record provides an opportunity to reassess estimates of flood frequency over a time scale not normally possible within flood frequency analysis. This paper re-evaluates flood frequency at York, considering the strengths and weaknesses in estimates resulting from four contrasting methods of analysis and their corresponding data: (a) single-site analysis of gauged annual maxima; (b) pooled analysis of multi-site gauged annual maxima; (c) combined analysis of systematic annual maxima augmented with historical peaks, and (d) analysis of only the very largest peaks using a Generalized Pareto Distribution. Use of the historical information was found to yield risk estimates which were lower and considered to be more credible than those achieved using gauged records alone.

Citation Macdonald, N. & Black, A. R. (2010) Reassessment of flood frequency using historical information for the River Ouse at York, UK (1200–2000). Hydrol. Sci. J. 55(7), 1152–1162.  相似文献   

14.
Abstract

A global flood risk index (FRI) is established, based on both natural and social factors. The advanced flood risk index (AFRI) is the expectation of damage in the case of a single flood occurrence, estimated by a linear regression-based approach as a function of hazard and vulnerability metrics. The resulting equations are used to predict potential flood damage given gridded global data for independent variables. It is new in the aspect that it targets floods by units of events, instead of a long-term trend. Moreover, the value of the AFRI is that it can express relative potential flood risk with the process of flood damage occurrence considered. The significance of this study is that not only the hazard parameters which contribute directly to flood occurrence, but vulnerability parameters which reflect the conditions of the region where flood occurred, including its residential and social characteristics, were shown quantitatively to affect flood damage.

Citation Okazawa, Y., Yeh, P., Kanae, S. & Oki, T. (2011) Development of a global flood risk index based on natural and socioeconomic factors. Hydrol. Sci. J. 56(5), 789–804.  相似文献   

15.
Abstract

The segmentation of flood seasons has both theoretical and practical importance in hydrological sciences and water resources management. The probability change-point analysis technique is applied to segmenting a defined flood season into a number of sub-seasons. Two alternative sampling methods, annual maximum and peaks-over-threshold, are used to construct the new flow series. The series is assumed to follow the binomial distribution and is analysed with the probability change-point analysis technique. A Monte Carlo experiment is designed to evaluate the performance of proposed flood season segmentation models. It is shown that the change-point based models for flood season segmentation can rationally partition a flood season into appropriate sub-seasons. China's new Three Gorges Reservoir, located on the upper Yangtze River, was selected as a case study since a hydrological station with observed flow data from 1882 to 2003 is located 40 km downstream of the dam. The flood season of the reservoir can be reasonably divided into three sub-seasons: the pre-flood season (1 June–2 July); the main flood season (3 July–10 September); and the post-flood season (11–30 September). The results of flood season segmentation and the characteristics of flood events are reasonable for this region.

Citation Liu, P., Guo, S., Xiong, L. & Chen, L. (2010) Flood season segmentation based on the probability change-point analysis technique. Hydrol. Sci. J. 55(4), 540–554.  相似文献   

16.
Abstract

We evaluate flood magnitude and frequency trends across the Mid-Atlantic USA at stream gauges selected for long record lengths and climate sensitivity, and find field significant increases. Fifty-three of 75 study gauges show upward trends in annual flood magnitude, with 12 showing increases at p < 0.05. We investigate trends in flood frequency using partial duration series data and document upward trends at 75% of gauges, with 27% increasing at p < 0.05. Many study gauges show evidence for step increases in flood magnitude and/or frequency around 1970. Expanding our study area to include New England, we find evidence for lagged positive relationships between the winter North Atlantic Oscillation phase and flood magnitude and frequency. Our results suggest hydroclimatic changes in regional flood response that are related to a combination of factors, including cyclic atmospheric variability and secular trends related to climate warming affecting both antecedent conditions and event-scale processes.

Editor Z.W. Kundzewicz; Associate editor H. Lins  相似文献   

17.
Abstract

For a long time now, the hydrologist has been faced with the problem of finding which of the many possible probability distribution functions can be used most effectively in flood frequency analyses. This problem has been mainly due to the insufficiency of the conventional goodness-of-fit procedures when used with the typically skewed flood probability distributions. In this study, the Akaike Information Criterion (AIC) goodness-of-fit test is used to identify more objectively the optimum model for flood frequency analysis in Kenya from a class of competing models. The class is comprised of (a) seven three-parameter density functions, namely, log-normal, Pearson, log-Pearson, Fisher-Tippet, log-Fisher-Tippet, Walter Boughton and log-Walter Boughton; and (b) two five-parameter density functions, namely, Wakeby and log-Wakeby. The AIC is also used in this study as a method of testing for the existence of outlier peak-flow values in the peak annual data used. A modified version of the chi-square goodness-of-fit test is also used, but only for the sake of comparison with the AIC.  相似文献   

18.
《水文科学杂志》2013,58(5):974-991
Abstract

The aim is to build a seasonal flood frequency analysis model and estimate seasonal design floods. The importance of seasonal flood frequency analysis and the advantages of considering seasonal design floods in the derivation of reservoir planning and operating rules are discussed, recognising that seasonal flood frequency models have been in use for over 30 years. A set of non-identical models with non-constant parameters is proposed and developed to describe flows that reflect seasonal flood variation. The peak-over-threshold (POT) sampling method was used, as it is considered to provide significantly more information on flood seasonality than annual maximum (AM) sampling and has better performance in flood seasonality estimation. The number of exceedences is assumed to follow the Poisson distribution (Po), while the peak exceedences are described by the exponential (Ex) and generalized Pareto (GP) distributions and a combination of both, resulting in three models, viz. Po-Ex, Po-GP and Po-Ex/GP. Their performances are analysed and compared. The Geheyan and the Baiyunshan reservoirs were chosen for the case study. The application and statistical experiment results show that each model has its merits and that the Po-Ex/GP model performs best. Use of the Po-Ex/GP model is recommended in seasonal flood frequency analysis for the purpose of deriving reservoir operation rules.  相似文献   

19.
《水文科学杂志》2013,58(5):863-877
Abstract

The method of L-moment ratio diagrams and the average weighted distance (AWD) are used to determine the probability distribution type of annual, seasonal and monthly precipitation in Japan. For annual precipitation, the log-Pearson type III (LP3) distribution provides the best fit to the observations with the generalized-extreme value (GEV), three-parameter lognormal (LN3) and Pearson type III (P3) distributions as potential alternatives. For seasonal precipitation, the P3 distribution shows the best fit to the observations of spring precipitation; the LP3 the best fit for summer and winter precipitation; and the LN3 the best fit for autumn precipitation with the LP3 as a potential alternative. For monthly precipitation, the P3 distribution fits the precipitation best for January, February, March, May, July, October and December; the LP3 for June; and the LN3 for April, August, September and November. The identified probability distribution types of annual, seasonal and monthly precipitation are basically consistent. Overall, the P3 and LP3 distributions are acceptable distribution types for representing statistics of precipitation in Japan with the LN3 distribution as a potential alternative.  相似文献   

20.
《水文科学杂志》2012,57(15):1867-1892
ABSTRACT

The flood peak is the dominating characteristic in nearly all flood-statistical analyses. Contrary to the general assumptions of design flood estimation, the peak is not closely related to other flood characteristics. Differentiation of floods into types provides a more realistic view. Often different parts of the probability distribution function of annual flood peaks are dominated by different flood types, which raises the question how shifts in flood regimes would modify the statistics of annual maxima. To answer this, a distinction into five flood types is proposed; then, temporal changes in flood-type frequencies are investigated. We show that the frequency of floods caused by heavy rain has increased significantly in recent years. A statistical model is developed that simulates peaks for each event type by type-specific peak–volume relationships. In a simulation study, we show how changes in frequency of flood event type lead to changes in the quantiles of annual maximum series.  相似文献   

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