Flood Frequency Analysis for Burhi Gandak River Basin
International Journal of Environment and Climate Change,
The study is aimed at finding the best distribution to match the steam ﬂow and calculation of magnitude and frequency of flow. In the current study, we have used several statistical distributions to find the best fit distribution for stream flow and used flood frequency analysis techniques to find the magnitude and frequency of stream flow and non-exceedance probability of peak discharge. The study has been performed at Sikandarpur and Rosera gauging sites of BurhiGandak River. Historical (50 years) maximum annual peak discharge data of each station are used for statistical analysis for estimating maximum peak discharge in 5, 10, 25, 50, 100 year return period. In this study, Lognormal distribution, Galton distribution, Gamma distribution, Log Pearson Type III distribution, Gumbell distribution, Generalised extreme values distribution have been considered to describe the annual maximum stream ﬂow. Flood frequency analysis methods were used for estimating the magnitude of the extreme flow events and their associated return periods. For both Sikandarpur and Rosera stations, Log Pearson type III distributions showed the lowest value of K–S and Chi-square test statistic. The annual probable peak discharge for 5, 10, 25, 50, and 100 years return period is calculated for each distribution. The most suitable distribution for both the stations is found to be the log-Pearson type III distribution.
- Frequency analysis
- return period
- gumbell distribution
- and log pearsontype III distribution.
How to Cite
Hassan MU, Hayat O, Noreen Z. Selecting the best probability distribution for at-site flood frequency analysis; a study of Torne River. SN Applied Sciences. 2019;1(12): 1629.
Hu Q, Tang Z, Zhang L, Xu Y, Wu X, Zhang L. Evaluating climate change adaptation efforts on the US 50 states’ hazard mitigation plans. Natural Hazards. 2018;92(2):783-804.
Sisay D. Flood Risk Analysis in Illu Floodplain, Upper Awash River Basin, Ethiopia (Doctoral dissertation, Addis Ababa University); 2015.
Flynn KM, Kirby WH, Hummel PR. User's manual for program PeakFQ, annual flood-frequency analysis using Bulletin 17B guidelines (No. 4-B4); 2006.
Raes D, Mallants D, Song Z. RAINBOW: A software package for analysing hydrologic data. WIT Transactions on Ecology and the Environment. 1970;18.
Kozanis S, Christofides A, Mamassis N, Efstratiadis A, Koutsoyiannis D. Hydrognomon–open source software for the analysis of hydrological data. European Geophysical Union General Assembly; 2010.
Adlouni S, Bobée B. Hydrological frequency analysis using HYFRAN-PLUS software. ChaireIndusrielle Hydro-Québec/CRSNG enHydrologieStatistique/ Institut National de la Recherche Scientifique (INRS)/Centre Eau, Terre et Environnement: Montréal, QC, Canada. 2015;71.
Garba H, Ismail A, Oriola FOP. Calibration of hydrognomon model for simulating the hydrology of urban catchment. Open Journal of Modern Hydrology. 2013;3(2): 75-78.
Alam MA, Emura K, Farnham C, Yuan J. Best-fit probability distributions and return periods for maximum monthly rainfall in Bangladesh. Climate. 2018;6(1): 9.
Wuensch KL. Chi-Square Tests. In: Lovric M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg; 2011.
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