Abstract

Flood management requires in-depth computational modelling through assessment of flood return period and river flow data in order to effectively analyze catchment response. The participatory geographic information system (PGIS) is a tool which is increasingly used for collecting data and decision making on environmental issues. This study sought to determine the return periods of major floods that happened in Narok Town, Kenya, using rainfall frequency analysis and PGIS. For this purpose, a number of statistical distribution functions were applied to daily rainfall data from two stations: Narok water supply (WS) station and Narok meteorological station (MS). The first station has a dataset of thirty years and the second one has a dataset of fifty-nine (59) years. The parameters obtained from the Kolmogorov–Smirnov (K–S) test and chi-square test helped to select the appropriate distribution. The best-fitted distribution for WS station were Gumbel L-moment, Pareto L-moment, and Weibull distribution for maximum one day, two days, and three days rainfall, respectively. However, the best-fitted distribution was found to be generalized extreme value L-moment, Gumbel and gamma distribution for maximum one day, two days, and three days, respectively for the meteorological station data. Each of the selected best-fitted distribution was used to compute the corresponding rainfall intensity for 5, 10, 25, 50, and 100 years return period, as well as the return period of the significant flood that happened in the town. The January 1993 flood was found to have a return period of six years, while the April 2013, March 2013, and April 2015 floods had a return period of one year each. This study helped to establish the return period of major flood events that occurred in Narok, and highlights the importance of population in disaster management. The study’s results would be useful in developing flood hazard maps of Narok Town for different return periods.

Highlights

  • Return period is an essential tool in hydrology that is used to estimate the time interval between events of a similar size or intensity

  • An important consideration in flood frequency analysis is the determination of the best-fitted distribution in order to compute the appropriate return period

  • Different probability distribution functions were applied to the time series data of two stations in Narok Town

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Summary

Introduction

Return period is an essential tool in hydrology that is used to estimate the time interval between events of a similar size or intensity. Estimating the return period of such events can become an arduous task due to the fact of various reasons such as missing data, short times data series, or the Hydrology 2019, 6, 90; doi:10.3390/hydrology6040090 www.mdpi.com/journal/hydrology. Frequency analysis is used to estimate the return period of specific events. This method of analysis can be used in the following among other applications, design of dams, bridges, culverts, and storm drainage channels. Peak discharges are used for flood frequency analysis, but in the absence of a long record of discharge gauge data for any watershed, rainfall data series is used [2]. Standard probability distribution functions commonly used in water resources engineering include normal, log-normal, Pearson, log Pearson type III and extreme value Type 1

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