Flood Frequency Analysis Considering Probability Distribution and Return Period under Non-stationary Condition

2015 ◽  
Vol 48 (7) ◽  
pp. 567-579 ◽  
Author(s):  
Sang Ug Kim ◽  
◽  
Yeong Seob Lee
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Stationary Condition

scholarly journals Flood Frequency Analysis at the Downstream of Sg. Perak River Basin using Annual Maximum Flow Discharge Data

2018 ◽  
Vol 7 (4.35) ◽  
pp. 709 ◽  
Author(s):  
Munir Snu ◽  
Sidek L.M ◽  
Haron Sh ◽  
Noh Ns.M ◽  
Basri H ◽  
...  
Keyword(s):  
Probability Distribution ◽  
River Basin ◽  
Frequency Analysis ◽  
Return Period ◽  
Maximum Flow ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
Discharge Data ◽  
Flow Discharge

The recent flood event occurred in 2014 had caused disaster in Perak and Sungai Perak is the main river of Perak which is a major natural drainage system within the state. The aim of this paper is to determine the expected discharge to return period downstream for Sg. Perak River Basin in Perak by using annual maximum flow data. Flood frequency analysis is a technique to assume the flow values corresponding to specific return periods or probabilities along the river at a different site. The method involves the observed annual maximum flow discharge data to calculate statistical information such as standard deviations, mean, sum, skewness and recurrence intervals. The flood frequency analysis for Sg. Perak River Basin was used Log Pearson Type-III probability distribution method. The annual maximum peak flow series data varying over period 1961 to 2016. The probability distribution function was applied to return periods (T) where T values are 2years, 5years, 10years, 25years, 50years, and 100years generally used in flood forecasting. Flood frequency curves are plotted after the choosing the best fits probability distribution for annual peak maximum data. The results for flood frequency analysis shows that Sg. Perak at Jambatan Iskandar much higher inflow discharge  which is 3714.45m3/s at the 100years return period compare to Sg. Plus at Kg Lintang and Sg. Kinta at Weir G. With this, the 100years peak flow at Sg Perak river mouth is estimated to be in the range of 4,000 m3/s. Overall, the analysis relates the expected flow discharge to return period for all tributaries of Sg. Perak River Basin.

Flood Frequency Analysis of the Mahi Basin by Using Log Pearson Type III Probability Distribution

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Uttam Pawar ◽  
Pramodkumar Hire
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Series Data ◽  
Period Range ◽  
Type Iii ◽  
Pearson Type ◽  
Data Points

Flood frequency analysis is one of the techniques of examination of peak stream flow frequency and magnitude in the field of flood hydrology, flood geomorphology and hydraulic engineering. In the present study, Log Pearson Type III (LP-III) probability distribution has applied for flood series data of four sites on the Mahi River namely Mataji, Paderdi Badi, Wanakbori and Khanpur and of three sites on its tributaries such as Anas at Chakaliya, Som at Rangeli and Jakham at Dhariawad. The annual maximum series data for the record length of 26-51 years have been used for the present study. The time series plots of the data indicate that two largest ever recorded floods were observed in the year 1973 and 2006 on the Mahi River. The estimated discharges of 100 year return period range between 3676 m3/s and 47632 m3/s. The return period of the largest ever recorded flood on the Mahi River at Wankbori (40663 m3/s) is 127-yr. The recurrence interval of mean annual discharges (Qm) is between 2.73-yr and 3.95-yr, whereas, the return period of large floods (Qlf) range from 6.24-yr to 9.33-yr. The magnitude-frequency analysis curves represent the reliable estimates of the high floods. The fitted lines are fairly close to the most of the data points. Therefore, it can be reliably and conveniently used to read the recurrence intervals for a given magnitude and vice versa.

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 Comparison Between Bivariate and Trivariate Flood Frequency Analysis Using the Archimedean Copula Functions, A Case Study of the Karun River in Iran

2021 ◽  
Author(s):  
Mohamad Haytham Klaho ◽  
Hamid R. Safavi ◽  
Mohamad H. Golmohammadi ◽  
Maamoun Alkntar
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Goodness Of Fit ◽  
Flood Frequency ◽  
Archimedean Copula ◽  
Flood Frequency Analysis ◽  
Cumulative Probability ◽  
Copula Functions ◽  
Flood Peak ◽  
Multiple Variables

Abstract Historically, severe floods have caused great human and financial losses. Therefore, the flood frequency analysis based on the flood multiple variables including flood peak, volume and duration poses more motivation for hydrologists to study. In this paper, the bivariate and trivariate flood frequency analysis and modeling using Archimedean copula functions is focused. For this purpose, the annual flood data over a 55-year historical period recorded at the Dez Dam hydrometric station were used. The results showed that based on goodness of fit criteria, the Frank function built upon the couple of the flood peak-volume and the couple of the flood peak-duration as well as the Clayton function built upon the flood volume-duration were identified to be the best copula families to be adopted. The trivariate analysis was conducted and the Clayton family was chosen as the best copula function. Thereafter, the common and conditional cumulative probability distribution functions were built and analyzed to determine the periodic "and", "or" and "conditional" bivariate and trivariate flood return periods. The results suggest that the bivariate conditional return period obtained for short-term periods is more reliable than the trivariate conditional return period. Additionally, the trivariate conditional return period calculated for long-term periods is more reliable than the bivariate conditional return period.

scholarly journals Selecting the best probability distribution for at-site flood frequency analysis; a study of Torne River

2019 ◽  
Vol 1 (12) ◽  
Author(s):  
Mahmood Ul Hassan ◽  
Omar Hayat ◽  
Zahra Noreen
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Goodness Of Fit ◽  
Direct Method ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Goodness Of Fit Tests ◽  
Pearson Type

AbstractAt-site flood frequency analysis is a direct method of estimation of flood frequency at a particular site. The appropriate selection of probability distribution and a parameter estimation method are important for at-site flood frequency analysis. Generalized extreme value, three-parameter log-normal, generalized logistic, Pearson type-III and Gumbel distributions have been considered to describe the annual maximum steam flow at five gauging sites of Torne River in Sweden. To estimate the parameters of distributions, maximum likelihood estimation and L-moments methods are used. The performance of these distributions is assessed based on goodness-of-fit tests and accuracy measures. At most sites, the best-fitted distributions are with LM estimation method. Finally, the most suitable distribution at each site is used to predict the maximum flood magnitude for different return periods.

Application of Gumbel’s Distribution Method for Flood Frequency Analysis of Lower Ganga Basin (Farakka Barrage Station), West Bengal, India

2021 ◽  
pp. 51-58
Author(s):  
Kajal Kumar Mandal ◽  
K. Dharanirajan ◽  
Sabyasachi Sarkar
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Flood Hazard ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Ganga Basin ◽  
Distribution Method ◽  
Discharge Data ◽  
Gumbel’S Distribution ◽  
Farakka Barrage

The analysis of flood frequency will depend on the historical peak discharge data for at least 10 years. This study has taken into account peak annual maximum discharge data for 72 years (1949 to 2020). The discharge data was collected from the Farakka Barrage Gauging station (24°48'15.10" N and 87°55'52.70" E) situated in the upper part of lower Ganga basin. The flood frequency analysis of the lower Ganga basin’s upper portions has been carried out using Gumbel’s frequency distribution method. Gumbel’s method (XT) is a prediction analysing statistical approach. The discharge data was tabulated in descending order and rank has been assigned based on the discharge volume. The return period was calculated based on Weibull’s formula (P) for this analysis. The flood frequency data was plotted on a graph where X-axis shows the return period and the Yaxis is the discharge value. The R2 value of this graph is 0.9998 which describe Gumbel’s distribution method is best for the flood frequency analysis. The flood frequency analysis is an essential step to assess the flood hazard.

scholarly journals Flood risk management in Allala River (Algeria) using Flood frequency analysis and hydraulic modeling

2019 ◽  
Vol 135 ◽  
pp. 01093
Author(s):  
Boukhanef Issam ◽  
Anna Khadzhidi ◽  
Lyudmila Kravchenko ◽  
Yuri Tsarev ◽  
Leonid Groshev ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Cross Sections ◽  
Return Period ◽  
Hydraulic Modeling ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Left Bank ◽  
Flood Intensity ◽  
Discharge Record ◽  
Level Profile

The objective of flood frequency analysis (FFA) is to associate flood intensity with a probability of exceedance and for making probabilistic estimates of a future flood event in Allala basin based on the historical discharge record at Sidi Akkacha gauging station, the peak floods discharge of Allala river for 5, 10, 50, 100 years return period are estimated using exponential distribution and the stage at different position of river are calculated using HEC RAS model . Based on the modeling study carried out considering 62 cross sections for 8 km length of river, The Output HEC-RAS model show that the existing embankments system on the banks of Allala River is not sufficient to resist the peak flood discharge of 100 years return period, water level profile shows that a maximum of 1.25m in left bank((at 1.2 km downstream) is needed to protect the inundation of the low laying areas of Old tenes.

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 Flood Frequency Analysis Using Participatory GIS and Rainfall Data for Two Stations in Narok Town, Kenya

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 90 ◽  
Author(s):  
Houessou-Dossou ◽  
Gathenya ◽  
Njuguna ◽  
Gariy
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Computational Modelling ◽  
Flood Frequency ◽  
Meteorological Station ◽  
Distribution Functions ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Return Periods ◽  
Participatory Gis

Flood management requires in-depth computational modelling through assessment of flood return period and river flow data in order to effectively analyze catchment response. The participatory geographic information system (PGIS) is a tool which is increasingly used for collecting data and decision making on environmental issues. This study sought to determine the return periods of major floods that happened in Narok Town, Kenya, using rainfall frequency analysis and PGIS. For this purpose, a number of statistical distribution functions were applied to daily rainfall data from two stations: Narok water supply (WS) station and Narok meteorological station (MS). The first station has a dataset of thirty years and the second one has a dataset of fifty-nine (59) years. The parameters obtained from the Kolmogorov–Smirnov (K–S) test and chi-square test helped to select the appropriate distribution. The best-fitted distribution for WS station were Gumbel L-moment, Pareto L-moment, and Weibull distribution for maximum one day, two days, and three days rainfall, respectively. However, the best-fitted distribution was found to be generalized extreme value L-moment, Gumbel and gamma distribution for maximum one day, two days, and three days, respectively for the meteorological station data. Each of the selected best-fitted distribution was used to compute the corresponding rainfall intensity for 5, 10, 25, 50, and 100 years return period, as well as the return period of the significant flood that happened in the town. The January 1993 flood was found to have a return period of six years, while the April 2013, March 2013, and April 2015 floods had a return period of one year each. This study helped to establish the return period of major flood events that occurred in Narok, and highlights the importance of population in disaster management. The study’s results would be useful in developing flood hazard maps of Narok Town for different return periods.

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