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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.

References

  1. Alam, A., Emura, K., Farnham, C and Yuan,J. (2018)., Best-Fit Probability Distributions and Return Periods for Maximum Monthly Rainfall in Bangladesh., Climate,6(9). https://doi.org/10.3390/cli6010009
  2. Subramanya, K. (2008)., Engineering Hydrology., 3rd Edition. Tata McGraw-Hill publishing Company limited. New Delhi.
  3. Chhetri, R., and Kumar, P (2018)., Spatial and temporal variability of rainfall distribution in hilly region of Nepal., International Research Journal of Environmental Science. 7(11), 1-10.
  4. Sabarish, R. M., Narasimhan, R., Chandhru, A., Suribabu, C., Sudharsan, J., and Nithiyanantham, S. (2017)., Probability analysis for consecutive-day maximum rainfall for Tiruchirapalli City (south India, Asia)., Applied Water Science. 7(2), 1033-1042.
  5. Dirk, R. (2013)., Frequency analysis of rainfall data., College on Soil Physics-30th Anniversary (1983-2013), The Abdus Salam International Centre for Theoretical Physics, 244-288.
  6. Central Bureau of Statistics (2011)., National Population and Housing Census 2011 (National Report)., Government of Nepal National Planning commission. Kathmandu, Nepal.
  7. Central Bureau of Statistics (2017)., Statistical Year Book of Nepal - 2017., Government of Nepal, National Planning commission. Ramshahpath, Thapathali, Kathmandu.
  8. Shrestha R.M. and Sthapit A.B. (2015)., Temporal Variation of Rainfall in the Bagmati River Basin, Nepal., Nepal Journal of Science and Technology, 16(1), 31-40.
  9. California State Department of Public works (1923)., Flow in California streams., Bulletin 5. Chapter 5 (cited by Haan, 1986).
  10. Chegodayev (1955)., Formulas for the calculation of the confidence of hydrologic quantities by A.G. Alekseyev., In: V.T. Chow (Editor), Handbook of Applied Hydrology, 1964.
  11. Blom, G. (1958)., Statistical Estimates and Transformed Beta Variables., Wiley, New York, N.Y. pp. 65-72; 143-146.
  12. Weibull, W. (1939)., A Statistical Study of The Strength of Material., Ing. Vetenskaps Akad. Handl. (Stockholm) Vol. 151, pp. 15.
  13. WMO (1983)., Guide to climatological practices., World Meteorological Organization, WMO - No. 100. Geneva, Switzerland.
  14. Hazen, A. (1930)., Flood flows: a study of frequencies and magnitudes., In Flood flows: a study of frequencies and magnitudes. John Wiley & Sons.
  15. Sevruk, B. and Geiger, H. (1981). Selection of distribution types for extremes of precipitation. World Meteorological Organisation, Operational Hydrology Report, No. 15, WMO-No. 560, Geneva., undefined, undefined
  16. Arvind, G., Kumar, P. A., Karthi, S. G., &Suribabu, C. R. (2017)., Statistical Analysis of 30 Years Rainfall Data: A Case Study., In IOP Conference Series: Earth and Environmental Science, Vol. 80, No. 1, p. 012067. IOP Publishing.
  17. Urías, H. Q., Garcia, H., & Plata Mendoza, J. S. (2007)., Determination of the relationship between precipitation and return periods to assess flood risks in the city of Juarez, Mexico., Conference Proceedings at Open SIUC. Southern Illinois University Carbondale, 24 July 2007.
  18. Kansakar S.R., Hannah D.M., Gerrard, J. and Rees G. (2004)., Spatial pattern in the precipitation regime in Nepal., Int. J. Climatol., 24, 1645-1659.
  19. Shrestha, M. (2000)., Interannual variation of summer monsoon rainfall over Nepal and its relation to Southern Oscillation Index., Meteorology and Atmospheric Physics, 75(1-2), 21-28.
  20. Babel, M. S., Bhusal, S. P., Wahid, S. M., and Agarwal, A. (2014)., Climate change and water resources in the Bagmati River Basin, Nepal., Theoretical and applied climatology, 115(3-4), 639-654.
  21. Shankar, K. and P.B Shrestha (1985)., Climate., In: Nepal -Nature's Paradise: Insight into diverse facets of Topography, flora and ecology. Ed. TC. Majupuria, White Lotus Co. Ltd, Bangkok, pp. 39-44.
  22. Panthi, J., Dahal, P., Shrestha, M., Aryal, S., Krakauer, N., Pradhanang, S., and Karki, R. (2015)., Spatial and temporal variability of rainfall in the Gandaki River Basin of Nepal Himalaya., Climate, 3(1), 210-226.
  23. Daly, C. (2006)., Guidelines for assessing the suitability of spatial climate data sets., International Journal of Climatology, 26(6), 707-721.
  24. Goovaerts, P. (2000)., Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall., Journal of hydrology, 228(1-2), 113-129.
  25. Rosenberg, E. A., Keys, P. W., Booth, D. B., Hartley, D., Burkey, J., Steinemann, A. C., and Lettenmaier, D. P. (2010)., Precipitation extremes and the impacts of climate change on stormwater infrastructure in Washington State., Climatic Change, 102(1-2), 319.