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, Mohammad Zakwan

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1557-1588
JournalNatural Hazards
Volume109
Issue number2
Early online date2021 Jul 19
DOIs
Publication statusPublished - 2021

Subject classification (UKÄ)

  • Physical Geography
  • Water Engineering

Free keywords

  • Design rainfall estimates
  • Parametric bootstrap
  • Stochastic simulation
  • Two-dimensional Monte Carlo framework
  • Variability and uncertainty analysis

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