Development of Rainfall Intensity-Duration-Frequency (IDF) Model of Gassol Town in Central Zone, Taraba State, Nigeria

Rainfall intensity has been one of the contributory factors to most frequent yearly flooding. Precipitation data collected by Nigerian Meteorological Agency (NIMET) and other relevant agencies often require refinement and statistical analysis to be effectively utilized. In this study, the precipitation data series gotten from NIMET, Yola office was used to develop the IDF model of the study area under consideration, which is not available. The IDF model will help to predict rainfall events, assist in the designing of urban drainage systems and basin outlets, serve as demonstrative learning aid for engineering students and other related fields. An annual maximum daily rainfall data during the last 43 years (1979 to 2022) obtained from NIMET, Yola office; from which, respective rainfall depths of short durations (10-min, 15-min, 30-min, 2-hr, 6-hr, 12-hr, and 24-hr) using the Indian Meteorological Department one third reduction formulation were determined. Gumbel’s Distribution Method was then adopted to determine a daily rainfall depth corresponding to a given return period and subsequently rainfall intensity for the various duration and return period were determined. Results of the rainfall intensity were then entered into Minitab stat 19 model to determine the coefficients C, K, and in the IDF model. The results indicated that the model has a reliability of 99.98% with an error of 0.5925%. After validation it was found out that the model could assist to predict rainfall intensity for the various duration and frequency in the design of drainage system of Gassol town with errors varying from 0.075% to 1.11%; indicating that there is a good agreement between the observed and the predicted data.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-13
DOI
https://doi.org/10.5281/zenodo.14432531
Primary Topic
Hydrology and Drought Analysis
Type
article
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article

Development of Rainfall Intensity-Duration-Frequency (IDF) Model of Gassol Town in Central Zone, Taraba State, Nigeria

Zenodo (CERN European Organization for Nuclear Research)
Hydrology and Drought Analysis
article

Development of Rainfall Intensity-Duration-Frequency (IDF) Model of Gassol Town in Central Zone, Taraba State, Nigeria

article en

Abstract

Rainfall intensity has been one of the contributory factors to most frequent yearly flooding. Precipitation data collected by Nigerian Meteorological Agency (NIMET) and other relevant agencies often require refinement and statistical analysis to be effectively utilized. In this study, the precipitation data series gotten from NIMET, Yola office was used to develop the IDF model of the study area under consideration, which is not available. The IDF model will help to predict rainfall events, assist in the designing of urban drainage systems and basin outlets, serve as demonstrative learning aid for engineering students and other related fields. An annual maximum daily rainfall data during the last 43 years (1979 to 2022) obtained from NIMET, Yola office; from which, respective rainfall depths of short durations (10-min, 15-min, 30-min, 2-hr, 6-hr, 12-hr, and 24-hr) using the Indian Meteorological Department one third reduction formulation were determined. Gumbel’s Distribution Method was then adopted to determine a daily rainfall depth corresponding to a given return period and subsequently rainfall intensity for the various duration and return period were determined. Results of the rainfall intensity were then entered into Minitab stat 19 model to determine the coefficients C, K, and in the IDF model. The results indicated that the model has a reliability of 99.98% with an error of 0.5925%. After validation it was found out that the model could assist to predict rainfall intensity for the various duration and frequency in the design of drainage system of Gassol town with errors varying from 0.075% to 1.11%; indicating that there is a good agreement between the observed and the predicted data.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 68%
Hydrology and Drought Analysis
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