Credibility of design rainfall estimates for drainage infrastructures: extent of disregard in Nigeria and proposed framework for practice

Oluwatobi Aiyelokun, Quoc Bao Pham (), Oluwafunbi Aiyelokun, Anurag Malik, S. Adarsh, Babak Mohammadi, Nguyen Thi Thuy Linh and Mohammad Zakwan
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Oluwatobi Aiyelokun: University of Ibadan
Quoc Bao Pham: Thu Dau Mot University
Oluwafunbi Aiyelokun: Olivearc Solutions
Anurag Malik: Regional Research Station
S. Adarsh: TKM College of Engineering
Babak Mohammadi: Lund University
Nguyen Thi Thuy Linh: Thuyloi University
Mohammad Zakwan: IIT

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 109, issue 2, No 10, 1557-1588

Abstract: Abstract Rainfall intensity or depth estimates are vital input for hydrologic and hydraulic models used in designing drainage infrastructures. Unfortunately, these estimates are susceptible to different sources of uncertainties including climate change, which could have high implications on the cost and design of hydraulic structures. This study adopts a systematic literature review to ascertain the disregard of credibility assessment of rainfall estimates in Nigeria. Thereafter, a simple framework for informing the practice of reliability check of rainfall estimates was proposed using freely available open-source tools and applied to the north central region of Nigeria. The study revealed through a synthesis matrix that in the last decade, both empirical and theoretical methods have been applied in predicting design rainfall intensities or depths for different frequencies across Nigeria, but none of the selected studies assessed the credibility of the design estimates. This study has established through the application of the proposed framework that drainage infrastructure designed in the study area using 100–1000-year return periods are more susceptible to error. And that the extent of the credibility of quantitative estimates of extreme rains leading to flooding is not equal for each variability indicator across a large spatial region. Hence, to optimize informed decision-making regarding flood risk reduction by risk assessor, variability and uncertainty of rainfall estimates should be assessed spatially to minimize erroneous deductions.

Keywords: Parametric bootstrap; Variability and uncertainty analysis; Two-dimensional Monte Carlo framework; Stochastic simulation; Design rainfall estimates (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11069-021-04889-1

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