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Analysis of rainfall and return periods to assess flood risks in hilly areas of Nepal

Author Affiliations

  • 1Forest Research Institute Deemed to be University, Dehradun, India
  • 2Kali Gandaki Polytechnic Institute, CTEVT, Ghiring 1, Tanahun, Gandaki Pradesh, Nepal
  • 3Department of Occupational Standard, Ministry of Labour and Human Resources, Thimphu, Bhutan
  • 4Tribhuvan University, Kathmandu, Nepal

Int. Res. J. Environment Sci., Volume 9, Issue (3), Pages 7-14, July,22 (2020)

Abstract

The study analyzed rainfall data for 30 years from 17 meteorological stations to determine flood risk in the hilly areas of Nepal. The probability of occurrence and return period were used as the methods to calculate the flood event. Probability of occurrence was calculated from seven different methods: Chegodayev, Blom, California, Weibull, Gringorten, Hazen and Sevruk and Geiger method and mean probability was taken from these methods. The mean probability was then used to calculate the return period. The common application of these methods involves the ranking of the rainfall data and calculated as a ratio of the ranked values to the length of the samples i.e. number of years. There turn period is an estimation of the expected return of the annual observation i.e. extreme rainfall associated events and the probability determines the chances of occurrence of these events in terms of percentage. The Pansayakhola station and year 1999 has a higher return period of 24 years and 42 years, but the least probability of occurrence (4.13%) and (2.36%) respectively. While, the station Nepalthok and year 1992 has a return period of one year time interval corresponding to the lowest average rainfall, but have more than 95% of probability of occurrence. The study also reported that the highest return period (42 years) was observed in the month of July and least in November. Return periods with higher probability need robust mitigation measures for the occurrence of frequent flood events. Hilly regions of Nepal is highly vulnerable to flood pertaining to a higher share of land coverage and concentration of dense population which demands a pragmatic approach to reduce the risk of floods or hydrological events.

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