IJEP 43(3): 227-235 : Vol. 43 Issue. 3 (March 2023)
Suraj Kushwaha and Ramakar Jha*
National Institute of Technology, Department of Civil Engineering, Patna, Bihar – 800 005, India
Flood is the most destructive natural disasters. Estimation of annual maximum discharge for a particular return period T (T-year flood) at a specific location is needed for design of hydraulic structures, nevertheless it has acquired little interest. Its estimation requires appropriate distribution to avoid failure of hydraulic structures. Hence, this paper aims to identify most suitable flood frequency distribution to estimate return period discharge using annual maximum discharge data from two stations of lower Ganga river basin in Bihar. Various probability distributions were applied to fit the annual maximum discharge data. Goodness-of-fit test results show that generalized extreme value distribution gives best results at both stations. The principle of the maximum likelihood estimation method was proposed to estimate the distribution’s parameters. Using developed statistical model, design discharge is estimated at both gauging stations for 5, 10, 25, 50, 100, 200 and 500 years. Results can be very useful for further study on flood risk assessment works in the study area.
Distribution, Flood frequency analysis, Generalized extreme value, Parameter, Return period
- UNDRR. 2019. United Nations Office for Disaster Risk Reduction. Available at : https://gar.unisdr.org.
- Dodangeh, E., et al. 2020. Flood frequency analysis of interconnected rivers by copulas. Water Resour., Manage., 34(11): 3533–3549. doi : 10.1007/s11269-020-02634-0.
- Guru, N. and R. Jha. 2020. Application of soft computing techniques for riverflow prediction in the downstream catchment of Mahanadi river basin using partial duration series, India. Iranian J. Sci. Tech. Transactions Civil Eng., 44(1):279–297. doi: 10.1007/s40996-019-00272-0.
- Guru, N. and R. Jha. 2015. Flood frequency analysis of Tel basin of Mahanadi river system, India using annual maximum and POT flood data. Aquatic Procedia. 4: 427–434. doi: 10.1016/j.aqpro.2015. 02.057.
- Kamal, V., et al. 2017. Flood frequency analysis of Ganga river at Haridwar and Garhmukteshwar. Appl. Water Sci., 7(4) : 1979-1986. doi: 10.1007/s13201-016-0378-3.
- Sahoo, B. B., et al. 2020. Bivariate low flow return period analysis in the Mahanadi river basin, India using copula. Int. J. River Basin Manage., 18(1): 107–116. doi : 10.1080/15715124.2019.1576 698.
- Gellens, D. 2002. Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium. J. Hydrol., 268(1–4) : 113–126. doi: 10.1016/S00 22-1694(02)00160-9.
- Walshaw, D. 2000. Modelling extreme wind speeds in regions prone to hurricanes. J. Royal Statistical Soc. Series C: Appl. Statistics. 49(1) : 51–62. doi: 10.1111/1467-9876.00178.
- Vogel, B.R.M. Jr., W.O.T. and T. Mcmahon. 1993. Southwestern United States. Water Resour., 119(3) : 353–366.
- Kumar, S. and T. Roshni. 2021. Analysis of drought, its impact on landuse/land cover and duration-severity analysis for the Sone river catchment, Bihar. Int. J. Hydrol. Sci. Tech., 12(3): 316. doi: 10.1504/ijhst.2021.10040162.
- Samantaray, S. and A. Sahoo. 2020. Estimation of flood frequency using statistical method: Mahanadi river basin, India. H2Open J., 3(1):189–207. doi: 10.2166/h2oj.2020.004.
- Laio, F. 2004. Cramer-von Mises and Anderson-Darling goodness of fit tests for extreme value
distributions with unknown parameters. Water Resour. Res., 40(9):1-10. doi: 10.1029/2004WR 003204.
- Best, D.J. and J.C.W. Rayner. 1981. Are two classes enough for the X2 goodness-of-fit test? Statistica Neerlandica. 35(3):157-163.
- Ul Hassan, M., O. Hayat and Z. Noreen. 2019. Selecting the best probability distribution for at-site flood frequency analysis: a study of Torne river. SN Appl. Sci., 1(12). doi: 10.1007/s42452-019-1584-z.