共查询到20条相似文献，搜索用时 15 毫秒
1.
The annual peak flow series of the Polish rivers are mixtures of summer and winter flows. In the Part I of a sequence of two papers, theoretical aspects of applicability of seasonal approach to flood frequency analysis (FFA) in Poland are discussed. A testing procedure is introduced for the seasonal model and the data overall fitness. Conditions for objective comparative assessment of accuracy of annual maxima (AM) and seasonal maxima (SM) approaches to FFA are formulated and finally Gumbel (EV1) distribution is chosen as seasonal distribution for detailed investigation. Sampling properties of AM quantile x(F) estimates are analysed and compared for the SM and AM models for equal seasonal variances. For this purpose, four estimation methods were used, employing both asymptotic approach and sampling experiments. Superiority of the SM over AM approach is stated evident in the upper quantile range, particularly for the case of no seasonal variation in the parameters of Gumbel distribution. In order to learn whether the standard two‐ and three‐parameter flood frequency distributions can be used to model the samples generated from the Two‐Component Extreme Value 1 (TCEV1) distribution, the shape of TCEV1 probability density function (PDF) has been tested in terms of bi‐modality. Then the use of upper quantile estimate obtained from the dominant season of extreme floods (DEFS) as AM upper quantile estimate is studied and respective systematic error is assessed. The second part of the paper deals with advantages and disadvantages of SM and AM approach when applied to real flow data of Polish rivers. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
2.
If the maximum annual peak flow series are a mixture of summer and winter flows, a seasonal approach to flood frequency analysis is necessary. While considering seasonal maxima as mutually independent events, the annual maxima distribution is defined as the product of seasonal distributions. However, if the independency assumption does not hold, a bivariate approach with dependent margins should be applied, i.e. the copula approach. The impact of dependency on design quantiles is investigated here in the context of the Fréchet-Hoeffding inequality defining copula bounds and the definition of dependency. The results of the two approaches are compared using six catchments in the San River basin, where in four cases the dependency of seasonal maxima has been identified as positive significant and no strong dominance of any one season is observed. The product model leads to higher estimates of design quantiles than do models where the dependency is taken into account and, therefore, is safe.
EDITOR R. Woods ASSOCIATE EDITOR A. Fiori 相似文献
3.
《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
4.
ABSTRACTFlood quantile estimation based on partial duration series (peak over threshold, POT) represents a noteworthy alternative to the classical annual maximum approach since it enlarges the available information spectrum. Here the POT approach is discussed with reference to its benefits in increasing the robustness of flood quantile estimations. The classical POT approach is based on a Poisson distribution for the annual number of exceedences, although this can be questionable in some cases. Therefore, the Poisson distribution is compared with two other distributions (binomial and Gumbel-Schelling). The results show that only rarely is there a difference from the Poisson distribution. In the second part we investigate the robustness of flood quantiles derived from different approaches in the sense of their temporal stability against the occurrence of extreme events. Besides the classical approach using annual maxima series (AMS) with the generalized extreme value distribution and different parameter estimation methods, two different applications of POT are tested. Both are based on monthly maxima above a threshold, but one also uses trimmed L-moments (TL-moments). It is shown how quantile estimations based on this “robust” POT approach (rPOT) become more robust than AMS-based methods, even in the case of occasional extraordinary extreme events.
Editor M.C. Acreman Associate editor A. Viglione 相似文献
5.
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
6.
As a supplementary method to the conventional flood frequency analysis based on annual peak flows, we propose an approach in this paper to infer the flood frequency distribution on quarterly and semi-annual time scale, which are then converted to annual time scale to obtain the floods corresponding to return periods in unit of year. Two criteria for test of data independence, namely, minimum 7 and 15-day interval between two consecutive peak flows, are tested. The proposed approach was applied to Des Moines River at Fort Dodge, Iowa, USA using its 62 years of observation daily flows. The results show that the estimated floods for given return periods from quarter-annual data series are in general higher than the corresponding estimated floods from semi-annual data series, which is further larger than estimated floods from annual peak flows. The floods estimated from semi-annual data series agree well with the results of previous US Geological Survey study. 相似文献
7.
AbstractFlood frequency analysis (FFA) is essential for water resources management. Long flow records improve the precision of estimated quantiles; however, in some cases, sample size in one location is not sufficient to achieve a reliable estimate of the statistical parameters and thus, regional FFA is commonly used to decrease the uncertainty in the prediction. In this paper, the bias of several commonly used parameter estimators, including L-moment, probability weighted moment and maximum likelihood estimation, applied to the general extreme value (GEV) distribution is evaluated using a Monte Carlo simulation. Two bias compensation approaches: compensation based on the shape parameter, and compensation using three GEV parameters, are proposed based on the analysis and the models are then applied to streamflow records in southern Alberta. Compensation efficiency varies among estimators and between compensation approaches. The results overall suggest that compensation of the bias due to the estimator and short sample size would significantly improve the accuracy of the quantile estimation. In addition, at-site FFA is able to provide reliable estimation based on short data, when accounting for the bias in the estimator appropriately.
Editor D. Koutsoyiannis; Associate editor Sheng Yue 相似文献
8.
T. A. Buishand G. R. Demaré 《Stochastic Environmental Research and Risk Assessment (SERRA)》1990,4(2):89-103
Quantile estimates of the annual maximum distribution can be obtained by fitting theoretical distributions to the maxima in separate seasons, e.g. to the monthly maxima. In this paper, asymptotic expressions for the bias and the variance of such estimates are derived for the case that the seasonal maxima follow a Gumbel distribution. Results from these expressions are presented for a situation with no seasonal variation and for maximum precipitation depths at Uccle/Ukkel (Belgium). It is shown that the bias is often negligible and that the variance reduction by using seasonal maxima instead of just the annual maxima strongly depends on the seasonal variation in the data. A comparison is made between the asymptotic standard error of quantile estimates from monthlymaxima with those from a partial duration series. Much attention is paid to the effect of model misspecification on the resulting quantile estimates of the annual maximum distribution. The use of seasonal maxima should be viewed with caution when the upper tail of this distribution is of interest. 相似文献
9.
William Earl Bardsley 《水文研究》2016,30(20):3730-3732
Multicomponent probability distributions such as the two‐component Gumbel distribution are sometimes applied to annual flood maxima when individual floods are seen as belonging to different classes, depending on physical processes or time of year. However, hydrological inconsistencies may arise if only nonclassified annual maxima are available to estimate the component distribution parameters. In particular, an unconstrained best fit to annual flood maxima may yield some component distributions with a high probability of simulating floods with negative discharge. In such situations, multicomponent distributions cannot be justified as an improved approximation to a local physical reality of mixed flood types, even though a good data fit is achieved. This effect usefully illustrates that a good match to data is no guarantee against degeneracy of hydrological models. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
10.
11.
Spatial and seasonal patterns of flood change across Brazil 总被引：1，自引：1，他引：0
Brazil has some of the largest rivers in the world and has the second greatest flood loss potential among the emergent countries. Despite that, flood studies in this area are still scarce. In this paper, we used flood seasonality and trend analysis at the annual and seasonal scales in order to describe flood regimes and changes across the whole of Brazil in the period 1976–2015. We identified a strong seasonality of floods and a well-defined spatio-temporal pattern for flood occurrence. There are positive trends in the frequency and magnitude of floods in the North, South and parts of Southeast Brazil; and negative trends in the North-east and the remainder of Southeast Brazil. Trends in the magnitude (frequency) were predominant in the winter (summer). Overall, floods are becoming more frequent and intense in Brazilian regions characterized by wet conditions, and less frequent and intense in drier regions. 相似文献
12.
《水文科学杂志》2012,57(15):1867-1892
ABSTRACTThe 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
13.
《水文科学杂志》2013,58(2):367-386
Abstract Extremes of streamflow are usually modelled using heavy tailed distributions. While scrutinising annual flow maxima or the peaks over threshold, the largest elements in a sample are often suspected to be low quality data, outliers or values corresponding to much longer return periods than the observation period. In the case of floods, since the interest is focused mainly on the estimation of the right-hand tail of a distribution function, sensitivity of large quantiles to extreme elements of a series becomes the problem of special concern. This study investigated the sensitivity problem using the log-Gumbel distribution by generating samples of different sizes and different values of the coefficient of L-variation by means of Monte Carlo experiments. Parameters of the log-Gumbel distribution were estimated by the probability weighted moments (PWM) method, both for complete samples and the samples deprived of their largest element. In the latter case Hosking's concept of the “A” type PWM with Type II censoring was employed. The largest value was censored above the random threshold T corresponding to the non-exceedence probability F T. The effect of the F T value on the performance of the quantile estimates was then examined. Experimental results show that omission of the largest sample element need not result in a decrease in the accuracy of large quantile estimates obtained from the log-Gumbel model by the PWM method. 相似文献
14.
Juan Du Jian Fang Wei Xu Peijun Shi 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(2):377-387
Local dry/wet conditions and extreme rainfall events are of great concern in regional water resource and disaster risk management. Extensive studies have been carried out to investigate the change of dry/wet conditions and the adaptive responses to extreme rainfall events within the context of climate change. However, applicable tools and their usefulness are still not sufficiently studied, and in Hunan Province, a major grain-producing area in China that has been frequently hit by flood and drought, relevant research is even more limited. This paper investigates the spatiotemporal variation of dry/wet conditions and their annual/seasonal trends in Hunan with the standardized precipitation index (SPI) at various time scales. Furthermore, to verify the potential usefulness of SPI for drought/flood monitoring, the correlation between river discharge and SPI at multiple time scales was examined, and the relation between extreme SPI and the occurrence of historical drought/flood events is explored. The results indicate that the upper reaches of the major rivers in Hunan Province have experienced more dry years than the middle and lower reaches over the past 57 years, and the region shows a trend of becoming drier in the spring and autumn seasons and wetter in the summer and winter seasons. We also found a strong correlation between river discharge and SPI series, with the maximum correlation coefficient occurred at the time scale of 2 months. SPI at different time scales may vary in its usefulness in drought/flood monitoring, and this highlights the need for a comprehensive consideration of various time scales when SPI is employed to monitor droughts and floods. 相似文献
15.
Flood extremes, affected by climate change and intense human activities, exhibit non-stationary characteristics. As a result, the stationarity assumption of traditional flood frequency analysis (FFA) cannot be satisfied. Generally, the impacts of human activities, especially water conservancy projects (i.e., reservoirs), on extreme flood series are much greater than those of climate change; therefore, new FFA methods must be developed to address the non-stationary flood extremes associated with large numbers of reservoirs. In this study, a new sample reconstruction method is proposed to convert the reservoir-influenced annual maximum flow (AMF) series from non-stationary to stationary, thus warranting the feasibility of the traditional FFA approach for non-stationary cases. To be more specifically, a modified reservoir index (MRI(t)) is proposed and the original non-stationary AMF series are converted to stationary series by multiplying by a scalar factor 1/(1 ? MRI(t)), and thus traditional FFA can be adopted. Besides, Bayesian theory was applied to analyze the effect of uncertainty on the designed reconstructed AMF. As an example, the proposed method was applied to observations from Huangzhuang station located on the Hanjiang River. The original AMF observations from Huangzhuang displayed nonstationarity for the continuous construction of reservoirs in the basin. After applying the new method of sample reconstruction, the original AMF observations became stationary, and the designed AMFs were estimated using the reconstructed series and compared with those estimated based on the original observation series. In addition, Bayesian theory is adopted to quantify the uncertainty of designed reconstructed AMF and provide the expectation of the sampling distribution. 相似文献
16.
Zhongmin Liang Wenjuan Chang Binquan Li 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(5):721-730
The specific objective of the paper is to propose a new flood frequency analysis method considering uncertainty of both probability distribution selection (model uncertainty) and uncertainty of parameter estimation (parameter uncertainty). Based on Bayesian theory sampling distribution of quantiles or design floods coupling these two kinds of uncertainties is derived, not only point estimator but also confidence interval of the quantiles can be provided. Markov Chain Monte Carlo is adopted in order to overcome difficulties to compute the integrals in estimating the sampling distribution. As an example, the proposed method is applied for flood frequency analysis at a gauge in Huai River, China. It has been shown that the approach considering only model uncertainty or parameter uncertainty could not fully account for uncertainties in quantile estimations, instead, method coupling these two uncertainties should be employed. Furthermore, the proposed Bayesian-based method provides not only various quantile estimators, but also quantitative assessment on uncertainties of flood frequency analysis. 相似文献
17.
Lishan Ran Xiankun Yang Mingyang Tian Hongyan Shi Shaoda Liu Ruihong Yu Yuanyuan Zhou 《地球表面变化过程与地形》2020,45(8):1777-1788
Floods have become increasingly important in fluvial export of water, sediment and carbon (C). Using high-frequency sampling, the export of water, sediment and C was examined in the Wuding River catchment on the Chinese Loess Plateau. With groundwater as an important contributor to runoff all year round, floods were relatively less important in the export of water. However, large floods were disproportionately important in exporting sediment and inorganic C (DIC) and organic C (DOC and POC). The three largest floods in each year transported 53.6–97.3 and 41.4–77% of the annual sediment and C fluxes, respectively. An extreme flood in 2017 alone contributed 94.6 and 73.1% of the annual sediment and C fluxes, respectively, in just 7 days, which included 20.3, 92.1 and 35.7% of the annual DOC, POC and DIC fluxes, respectively. A stable carbon isotope (δ13C) analysis of POC indicated that modern soils and C3 plants were its primary source. Furthermore, floods greatly accelerated CO2 degassing due to elevated gas transfer velocity, although stream water CO2 partial pressure (pCO2) exhibited a decreasing trend with flow discharge. Although these results illustrated that increasing runoff diluted pCO2, the timing and magnitude of floods were found to be critical in determining the response of pCO2 to flow dynamics. Low-magnitude floods in the early wet season increased pCO2 because of enhanced organic matter input, while subsequent large floods caused a lower pCO2 due to greatly reduced organic matter supply. Finally, continuous monitoring of a complete flood event showed that the CO2 efflux during the flood (2348 ± 664 mg C m–2 day–1) was three times that under low-flow conditions (808 ± 98 mg C m–2 day–1). Our study suggests that infrequent, heavy storm events, which are predicted to increase under climate change, will greatly alter the transport regimes of sediment and C. © 2020 John Wiley & Sons, Ltd. 相似文献
18.
Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods 总被引：1，自引：1，他引：0
Reservoirs are the most important constructions for water resources management and flood control. Great concern has been paid to the effects of reservoir on downstream area and the differences between inflows and dam site floods due to the changes of upstream flow generation and concentration conditions after reservoir’s impoundment. These differences result in inconsistency between inflow quantiles and the reservoir design criteria derived by dam site flood series, which can be a potential risk and must be quantificationally evaluated. In this study, flood frequency analysis (FFA) and flood control risk analysis (FCRA) methods are used with the long reservoir inflow series derived from a multiple inputs and single output model and a copula-based inflow estimation model. The results of FFA and FCRA are compared and the influences on reservoir flood management are also discussed. The Three Gorges Reservoir (TGR) in China is selected as a case study. Results show that the differences between the TGR inflow and dam site floods are significant which result in changes on its flood control risk rates. The mean values of TGR’s annual maximum inflow peak discharge and 3 days flood volume have increased 5.58 and 3.85% than the dam site ones, while declined by 1.82 and 1.72% for the annual maximum 7 and 15 days flood volumes. The flood control risk rates of middle and small flood events are increased while extreme flood events are declined. It is shown that the TGR can satisfy the flood control task under current hydrologic regime and the results can offer references for better management of the TGR. 相似文献
19.
Mathias J. Collins 《水文研究》2019,33(5):687-698
The New England and Mid‐Atlantic regions of the Northeast United States have experienced climate‐induced increases in both the magnitude and frequency of floods. However, a detailed understanding of flood seasonality across these regions, and how flood seasonality may have changed over the instrumental record, has not been established. The annual timing of river floods reflects the flood‐generating mechanisms operating in a basin, and many aquatic and riparian organisms are adapted to flood seasonality, as are human uses of river channels and flood plains. Changes in flood seasonality may indicate changes in flood‐generating mechanisms, and their interactions, with important implications for habitats, flood plain infrastructure, and human communities. I applied a probabilistic method for identifying flood seasons at a monthly resolution for 90 Northeast U.S. watersheds with natural, or near‐natural, flood‐generating conditions. Historical trends in flood seasonality were also investigated. Analyses were based on peaks‐over‐threshold flood records that have, on average, 85 years of data and three peaks per year—thus providing more information about flood seasonality than annual maximums. The results show rich detail about annual flood timing across the region with each site having a unique pattern of monthly flood occurrence. However, a much smaller number of dominant seasonal patterns emerged when contiguous flood‐rich months were classified into commonly recognized seasons (e.g., Mar–May, spring). The dominant seasonal patterns identified by manual classification were corroborated by unsupervised classification methods (i.e., cluster analyses). Trend analyses indicated that the annual timing of flood‐rich seasons has generally not shifted over the period of record, but 65 sites with data from 1941 to 2013 revealed increased numbers of June–October floods—a trend driving previously documented increases in Northeast U.S. flood counts per year. These months have been historically flood‐poor at the sites examined, so warm‐season flood potential has increased with possible implications for aquatic and riparian organisms. 相似文献
20.
Walter Mangini Alberto Viglione Julia Hall Yeshewatesfa Hundecha Serena Ceola Alberto Montanari 《水文科学杂志》2018,63(4):493-512
This study analyses the differences in significant trends in magnitude and frequency of floods detected in annual maximum flood (AMF) and peak over threshold (POT) flood peak series, for the period 1965–2005. Flood peaks are identified from European daily discharge data using a baseflow-based algorithm and significant trends in the AMF series are compared with those in the POT series, derived for six different exceedence thresholds. The results show that more trends in flood magnitude are detected in the AMF than in the POT series and for the POT series more significant trends are detected in flood frequency than in flood magnitude. Spatially coherent patterns of significant trends are detected, which are further investigated by stratifying the results into five regions based on catchment and hydro-climatic characteristics. All data and tools used in this study are open-access and the results are fully reproducible. 相似文献