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Flood Frequency Analysis Using Participatory GIS and Rainfall Data for Two Stations in Narok Town, Kenya

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Civil Engineering Department, Pan African University-Institute for Basics Sciences, Technology and Innovation/Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200 Nairobi, Kenya
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Soil, Water and Environmental Engineering Department/Jomo Kenyatta University of Agriculture & Technology, P.O. Box 62000-00200 Nairobi, Kenya
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Centre for Urban Studies, School of Architecture & Building Sciences/Jomo Kenyatta University of Agriculture & Technology, P.O. Box 62000-00200 Nairobi, Kenya
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School of Civil, Environmental & Geospatial Engineering/Jomo Kenyatta University of Agriculture & Technology P.O. Box 62000-00200 Nairobi, Kenya
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Author to whom correspondence should be addressed.
Hydrology 2019, 6(4), 90; https://doi.org/10.3390/hydrology6040090
Received: 2 September 2019 / Revised: 27 September 2019 / Accepted: 16 October 2019 / Published: 19 October 2019
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. View Full-Text
Keywords: return period; goodness-of-fit; distribution; flood frequency; Narok Town return period; goodness-of-fit; distribution; flood frequency; Narok Town
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Houessou-Dossou, E.A.Y.; Mwangi Gathenya, J.; Njuguna, M.; Abiero Gariy, Z. Flood Frequency Analysis Using Participatory GIS and Rainfall Data for Two Stations in Narok Town, Kenya. Hydrology 2019, 6, 90.

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