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

Houessou-Dossou, Eva Audrey Yessito; Gathenya, John Mwangi; Njuguna, Mugwima; Gariy, Zachary Abiero

doi:10.3390/hydrology6040090

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…During the rainy seasons, rainfall amounts, and intensities are usually very high. Nigeria's economy is linked to climate sensitive activities (Houessou-Doussou et al, 2019). Precipitation (rainfall) is formed when saturated air is heated, rises by a mountain, convectional current or frontal action (Ogungbenro and Morakinyo, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…An understanding of historical and current rainfall trends is essential in determining the return periods in a particular area. Factors such as missing data and unknown probability distribution function of annual peaks makes the estimation of return period of real events a tedious task; frequency analysis is thus used to estimate the return periods of specific events (Houessou-Doussou et al, 2019). Consequently, it is important to estimate rainfall return period by modelling its components with real world behaviours and attributes.…”

Section: Introductionmentioning

confidence: 99%

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Parametric modelling of rainfall return periods in south-western Nigeria: Survival analysis approach

Awodutire¹,

Sasanya

Ufuoma³

et al. 2022

F1000Res

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Background: Rainfall is the main source of water on the earth’s surface. It infiltrates and percolates deep into the soil for groundwater recharge. Rainfall patterns, amounts, durations, and intensities can vary daily, monthly, annually, and spatially. It is therefore important to accurately estimate rainfall return periods, which can be employed in hydraulic design and flood control measures. Methods: This research considered the survival analysis approach for the prediction of rainfall return periods including intensity, and months during which these would occur in south-western Nigeria. Twenty years’ of annual rainfall data were obtained from three metrological stations and these were subjected to nine different probability plotting position methods. Results from the plotting positions was further subjected to four survival models using five years of censor time. The Akaike Information Criterion (AIC) was used to determine the best-fitting model for the dataset. Results: The Laplace probability plotting position in conjunction with the log-logistic distribution best describes the datasets, since it gave the lowest AIC value of 22.53. The log-logistic distribution is also suitable for the prediction of return period from the Weibull probability plotting position since the AIC values were 6.934 and -4.332 respectively. The Hirsh plotting position in conjunction with the Weibull distribution is also suitable for the description of the dataset. Conclusion: The established parametric models are suitable for the accurate prediction of return periods of peak rainfall events during any month of the year.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parametric modelling of rainfall return periods in south-western Nigeria: Survival analysis approach

Awodutire¹,

Sasanya

Ufuoma³

et al. 2022

F1000Res

View full text Add to dashboard Cite

show abstract

“…When nothing in the series suggests whether one distribution is more likely to be suitable than another [17], the optimal distribution is selected using the goodness-of-fit test, which measures how well the evaluated distributions match the given data [18]. The Kolmogorov-Smirnov (K-S) and Chi-square tests help in choosing the best distribution [19]. The root mean square error is used to compare various probability distributions and determine which is better for the data over a 24 h period and then for the subintervals [9].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study

2021

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In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have been reported in the Al-Lith region of western Saudi Arabia that took away many lives and caused disruption in services and trade. To find and examine the extremities and IDF curves, daily rainfall data from 1966 to 2018 is used. The IDF curves are created for a variety of return periods and climate scenarios in three terrain variabilities. This research examines various distributions to estimate the maximum rainfall for several metrological stations with varying return periods and terrain conditions. Three main zones are identified based on ground elevation variability and IDF distributions from upstream in the eastern mountainous area to downstream in the western coastal area. These IDF curves can be used to identify vulnerable hotspot areas in arid areas such as the Wadi AL-Lith, and flood mitigation steps can be suggested to minimize flood risk.

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“…Several studies have been reported to be related to the investigation of the most suitable probability distribution for flood frequency analysis in different regions worldwide [2,[7][8][9][10][11][12][13][14][15][26][27][28][29][30][31][32][33]. Ahilan et al [29] compared the family of extreme value distributions using the data from 172 gauging stations in Ireland; they reported that the Gumbel distribution outperformed the other two types of extreme value distributions (i.e., Frechet, and Weibull).…”

Section: Introductionmentioning

confidence: 99%

Flood Frequency Analyses over Different Basin Scales in the Blue Nile River Basin, Ethiopia

Tegegne¹,

Melesse²,

Asfaw³

et al. 2020

Hydrology

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The frequency and intensity of flood quantiles and its attendant damage in agricultural establishments have generated a lot of issues in Ethiopia. Moreover, precise estimates of flood quantiles are needed for efficient design of hydraulic structures; however, quantification of these quantiles in data-scarce regions has been a continuing challenge in hydrologic design. Flood frequency analysis is thus essential to reduce possible flood damage by investigating the most suitable flood prediction model. The annual maximum discharges from six representative stations in the Upper Blue Nile River Basin were fitted to the commonly used nine statistical distributions. This study also assessed the performance evolution of the probability distributions with varying spatial scales, such that three different spatial scales of small-, medium-, and large-scale basins in the Blue Nile River Basin were considered. The performances of the candidate probability distributions were assessed using three goodness-of-fit test statistics, root mean square error, and graphical interpretation approaches to investigate the robust probability distribution for flood frequency analysis over different basin spatial scales. Based on the overall analyses, the generalized extreme value distribution was proven to be a robust model for flood frequency analysis in the study region. The generalized extreme value distribution significantly improved the performance of the flood prediction over different spatial scales. The generalized extreme value flood prediction performance improvement measured in root mean square error varied between 5.84 and 67.91% over other commonly used probability distribution models. Thus, the flood frequency analysis using the generalized extreme value distribution could be essential for the efficient planning and design of hydraulic structures in the Blue Nile River Basin. Furthermore, this study suggests that, in the future, significant efforts should be put to conduct similar flood frequency analyses over the other major river basins of Ethiopia.

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

Cited by 13 publications

References 20 publications

Parametric modelling of rainfall return periods in south-western Nigeria: Survival analysis approach

Parametric modelling of rainfall return periods in south-western Nigeria: Survival analysis approach

Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study

Flood Frequency Analyses over Different Basin Scales in the Blue Nile River Basin, Ethiopia

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