Some Researches on Determination of Return Period for Historical Flood in Analysis of Flood Frequency

1987 ◽  
pp. 191-197
Author(s):  
Minggany Li ◽  
Qiusheng Yang
Keyword(s):  
Return Period ◽  
Flood Frequency

scholarly journals Analysis of Problems Related to the Calculation of Flood Frequency Using Rainfall-Runoff Models: A Case Study in Poland

2020 ◽  
Vol 12 (17) ◽  
pp. 7187
Author(s):  
Dariusz Młyński
Keyword(s):  
Sensitivity Analysis ◽  
Return Period ◽  
Maximum Flow ◽  
High Sensitivity ◽  
Flood Frequency ◽  
Rainfall Runoff ◽  
Model Quality ◽  
Retention Capacity

This work aimed to quantify how the different parameters of the Snyder model influence the errors in design flows. The study was conducted for the Kamienica Nowojowska catchment (Poland). The analysis was carried out according to the following stages: determination of design precipitation, determination of design hyetograph, sensitivity analysis of the Snyder model, and quality assessment of the Snyder model. Based on the conducted research, it was found that the Snyder model did not show high sensitivity to the assumed precipitation distribution. The parameters depending on the retention capacity of the catchment had much greater impact on the obtained flow values. The verification of the model quality showed a significant disproportion in the calculated maximum flow values with the assumed return period.

scholarly journals Determination of return period for flood frequency analysis using normal and related distributions

2017 ◽  
Vol 890 ◽  
pp. 012162 ◽  
Author(s):  
Wan Husna Aini Wan Deraman ◽  
Noor Julailah Abd Mutalib ◽  
Nur Zahidah Mukhtar
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis

scholarly journals A New Empirical Approach to Calculating Flood Frequency in Ungauged Catchments: A Case Study of the Upper Vistula Basin, Poland

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 601 ◽  
Author(s):  
Dariusz Młyński ◽  
Andrzej Wałęga ◽  
Tomasz Stachura ◽  
Grzegorz Kaczor
Keyword(s):  
Empirical Model ◽  
Catchment Area ◽  
Flood Frequency ◽  
Ungauged Catchments ◽  
Volume Determination ◽  
Statistical Verification ◽  
Observation Series ◽  
Data Estimation

The aim of the work was to develop a new empirical model for calculating the peak annual flows of a given frequency of occurrence (QT) in the ungauged catchments of the upper Vistula basin in Poland. The approach to the regionalization of the catchment and the selection of the optimal form of the empirical model are indicated as a novelty of the proposed research. The research was carried out on the basis of observation series of peak annual flows (Qmax) for 41 catchments. The analysis was performed in the following steps: statistical verification of data; estimation of Qmax flows using kernel density estimation; determination of physiographic and meteorological characteristics affecting the Qmax flow volume; determination of the value of dimensionless quantiles for QT flow calculation in the upper Vistula basin; verification of the determined correlation for the calculation of QT flows in the upper Vistula basin. Based on the research we conducted, we found that the following factors have the greatest impact on the formation of flood flows in the upper Vistula basin: the size of catchment area; the height difference in the catchment area; the density of the river network; the soil imperviousness index; and the volume of normal annual precipitation. The verification procedure that we performed made it possible to conclude that the developed empirical model functions correctly.

scholarly journals INNOVATIVE DETERMINATION OF NEARSHORE FLOOD FREQUENCY

1986 ◽  
Vol 1 (20) ◽  
pp. 181
Author(s):  
H. Lee Butler ◽  
Mark D. Prater
Keyword(s):  
New York ◽  
Long Island ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Flood Frequency ◽  
Storm Tide ◽  
Statistical Estimates ◽  
Operation And Maintenance ◽  
Accuracy Of Results

Reliable estimates of coastal flooding from tides and storm surges are required for making sound engineering decisions regarding the design, operation and maintenance of many coastal projects. A recent investigation of flood frequency along the coast and within the bays of southern Long Island, New York, produced new and optimal approaches to obtain meaningful statistical estimates of flood levels. This paper summarizes various elements of the study and concentrates on the problem of stage-frequency computations in the inland bay areas. Methods for optimizing the number of necessary storm/tide simulations and estimating the accuracy of results are presented.

scholarly journals On the asymptotic behavior of flood peak distributions

2006 ◽  
Vol 10 (2) ◽  
pp. 233-243 ◽  
Author(s):  
E. Gaume
Keyword(s):  
Frequency Distribution ◽  
Return Period ◽  
Asymptotic Properties ◽  
Flood Frequency ◽  
Point Of View ◽  
Rainfall Runoff ◽  
New Approach ◽  
Flood Peak ◽  
Flood Quantiles ◽  
The Impact

Abstract. This paper presents some analytical results and numerical illustrations on the asymptotic properties of flood peak distributions obtained through derived flood frequency approaches. It confirms and extends the results of previous works: i.e. the shape of the flood peak distributions are asymptotically controlled by the rainfall statistical properties, given limited and reasonable assumptions concerning the rainfall-runoff process. This result is partial so far: the impact of the rainfall spatial heterogeneity has not been studied for instance. From a practical point of view, it provides a general framework for analysis of the outcomes of previous works based on derived flood frequency approaches and leads to some proposals for the estimation of very large return-period flood quantiles. This paper, focussed on asymptotic distribution properties, does not propose any new approach for the extrapolation of flood frequency distribution to estimate intermediate return period flood quantiles. Nevertheless, the large distance between frequent flood peak values and the asymptotic values as well as the simulations conducted in this paper help quantifying the ill condition of the problem of flood frequency distribution extrapolation: it illustrates how large the range of possibilities for the shapes of flood peak distributions is.

Data-based attribution of changes in flood quantiles across Europe between 1960 and 2010

2021 ◽  
Author(s):  
Miriam Bertola ◽  
Alberto Viglione ◽  
Sergiy Vorogushyn ◽  
David Lun ◽  
Bruno Merz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Return Period ◽  
Extreme Precipitation ◽  
Western Europe ◽  
Expert Knowledge ◽  
Flood Frequency ◽  
Antecedent Soil Moisture ◽  
Flood Quantiles ◽  
Comparable Magnitude ◽  
Large Floods

<p>Changes in European floods during past decades have been analysed and detected by several studies. These studies typically focused on the mean flood behaviour, without distinguishing small and large floods. In this work, we investigate the causes of the detected flood trends across Europe over five decades (1960-2010), as a function of the return period. We adopt a regional non-stationary flood frequency approach to attribute observed flood changes to potential drivers, used as covariates of the parameters of the regional probability distribution of floods. The elasticities of floods with respect to the drivers and the regional contributions of the drivers to changes in flood quantiles associated with small and large return periods (i.e. 2-year and 100-year floods, respectively) are estimated by Bayesian inference, with prior information on the elasticity parameters obtained from expert knowledge and the literature. The data-based attribution approach is applied to annual maximum flood discharge seires from 2370 hydrometric stations in Europe. Extreme precipitation, antecedent soil moisture and snowmelt are the potential drivers considered. Results show that extreme precipitation mainly contributes to positive flood changes in North-western Europe. Both antecedent soil moisture and extreme precipitation contribute to negative flood changes in Southern Europe, with relative contributions varying with the return period. Antecedent soil moisture contributes the most to changes in small floods (i.e. T=2-10 years), while the two drivers contribute with comparable magnitude to changes in more extreme events. In eastern Europe, snowmelt clearly drives negative changes in both small and large floods.</p>

scholarly journals Hydro-meteorological characteristics and occurrence probability of extreme flood events in Moroccan High Atlas

2020 ◽  
Vol 11 (S1) ◽  
pp. 310-321 ◽  
Author(s):  
Mohamed El Mehdi Saidi ◽  
Tarik Saouabe ◽  
Abdelhafid El Alaoui El Fels ◽  
El Mahdi El Khalki ◽  
Abdessamad Hadri
Keyword(s):  
Return Period ◽  
Peak Flow ◽  
Extreme Event ◽  
Rare Event ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
High Atlas ◽  
Flood Water ◽  
Extreme Flood ◽  
Water Volumes

Abstract Flood frequency analysis could be a tool to help decision-makers to size hydraulic structures. To this end, this article aims to compare two analysis methods to see how rare an extreme hydrometeorological event is, and what could be its return period. This event caused many deadly floods in southwestern Morocco. It was the result of unusual atmospheric conditions, characterized by a very low atmospheric pressure off the Moroccan coast and the passage of the jet stream further south. Assessment of frequency and return period of this extreme event is performed in a High Atlas watershed (the Ghdat Wadi) using historical floods. We took into account, on the one hand, flood peak flows and, on the other hand, flood water volumes. Statistically, both parameters are better adjusted respectively to Gamma and Log Normal distributions. However, the peak flow approach underestimates the return period of long-duration hydrographs that do not have a high peak flow, like the 2014 event. The latter is indeed better evaluated, as a rare event, by taking into account the flood water volumes. Therefore, this parameter should not be omitted in the calculation of flood probabilities for watershed management and the sizing of flood protection infrastructure.

scholarly journals Flood frequency analysis for annual maximum streamflow using a non-stationary GEV model

2019 ◽  
Vol 79 ◽  
pp. 03022
Author(s):  
Shangwen Jiang ◽  
Ling Kang
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Yangtze River ◽  
Flood Frequency ◽  
Additive Models ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
The Yangtze River ◽  
Stationary Model ◽  
Risk Of Failure

Under changing environment, the streamflow series in the Yangtze River have undergone great changes and it has raised widespread concerns. In this study, the annual maximum flow (AMF) series at the Yichang station were used for flood frequency analysis, in which a time varying model was constructed to account for non-stationarity. The generalized extreme value (GEV) distribution was adopted to fit the AMF series, and the Generalized Additive Models for Location, Scale and Shape (GAMLSS) framework was applied for parameter estimation. The non-stationary return period and risk of failure were calculated and compared for flood risk assessment between stationary and non-stationary models. The results demonstrated that the flow regime at the Yichang station has changed over time and a decreasing trend was detected in the AMF series. The design flood peak given a return period decreased in the non-stationary model, and the risk of failure is also smaller given a design life, which indicated a safer flood condition in the future compared with the stationary model. The conclusions in this study may contribute to long-term decision making in the Yangtze River basin under non-stationary conditions.

scholarly journals On the role of the runoff coefficient in the mapping of rainfall to flood return periods

2009 ◽  
Vol 13 (5) ◽  
pp. 577-593 ◽  
Author(s):  
A. Viglione ◽  
R. Merz ◽  
G. Blöschl
Keyword(s):  
Monte Carlo ◽  
Return Period ◽  
Threshold Effect ◽  
Flood Frequency ◽  
Runoff Coefficient ◽  
Return Periods ◽  
Runoff Generation ◽  
Design Storm ◽  
Shed Light

Abstract. While the correspondence of rainfall return period TP and flood return period TQ is at the heart of the design storm procedure, their relationship is still poorly understood. The purpose of this paper is to shed light on the controls on this relationship examining in particular the effect of the variability of event runoff coefficients. A simplified world with block rainfall and linear catchment response is assumed and a derived flood frequency approach, both in analytical and Monte-Carlo modes, is used. The results indicate that TQ can be much higher than TP of the associated storm. The ratio TQ /TP depends on the average wetness of the system. In a dry system, TQ can be of the order of hundreds of times of TP. In contrast, in a wet system, the maximum flood return period is never more than a few times that of the corresponding storm. This is because a wet system cannot be much worse than it normally is. The presence of a threshold effect in runoff generation related to storm volume reduces the maximum ratio of TQ /TP since it decreases the randomness of the runoff coefficients and increases the probability to be in a wet situation. We also examine the relation between the return periods of the input and the output of the design storm procedure when using a pre-selected runoff coefficient and the question which runoff coefficients produce a flood return period equal to the rainfall return period. For the systems analysed here, this runoff coefficient is always larger than the median of the runoff coefficients that cause the maximum annual floods. It depends on the average wetness of the system and on the return period considered, and its variability is particularly high when a threshold effect in runoff generation is present.

Sign in / Sign up

Export Citation Format

Share Document