Regional frequency analysis for consecutive hour rainfall using L-moments approach in Jeju Island, Korea

Abstract

Background: Extreme rainfall events are enormously frequent and abrupt in tropical areas like the Jeju Island of South Korea, impacting the hydrological functions as well as the social and economic situation. Rainfall magnitude and frequency distribution related information are essential for water system design, water resources management and hydro-meteorological emergencies. This study therefore has investigated the use of L-moments approach for hourly regional rainfall frequency estimation so as to ensure better accuracy and efficiency of the estimation process from the usually limited data sets. Results: The Hancheon catchment was considered as the primary study domain and several best fitted statistical tools were used to analyze consecutive hour rainfall data from five hydro-meteorological stations (Jeju, Ara, Eorimok, Witsaeorum and Jindallaebat) adjacent to the area. The cluster analysis and discordancy measure categorized the Hancheon catchment in three regions (1, 2 and 3). Based on the L-moments heterogeneity and goodness-of-fit measure, Gumbel and generalized extreme value (GEV) distribution were identified as robust distributions for the study area. The RMSE ratios for the catchment were found as 0.014 to 0.237 for Gumbel and 0.115 to 0.301 for GEV distribution. The linear regression analysis of the different rainfall quantiles inferred r-square values from 0.842 to 0.974. Conclusions: The L-moments and other statistical information derived from the study can be useful for important hydrological design considerations in connection with flood risk management, mitigation and safety; whereas the methodological framework of the study may be suitable for other small scaled catchment areas with high slope.

Regional flood frequency analysis using L‐moments for geographically defined regions: An assessment in Brazil

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“…Despite the importance of at‐site frequency analysis for design floods estimation at gauged sites or validating other flood estimation methods (Noto & La Loggia, ; Rahman et al, ), Hosking and Wallis () stated that considerable increasing on accuracy can be achieved by means of RFFA, as different sites provide information to be evaluated. In this context, Kar, Yang, Lee, and Khadim () defined RFFA as an approach in continuous development and an important tool for decision makers. Therefore, RFFA has the potential of being an appropriate alternative to the poor hydrological monitoring typically existing in developing countries, especially when analysed along with the L‐moments technique.…”

Homogeneous Regionalization via L-Moments for Mumbai City, India

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