Uncertainty quantification of flood damage estimation for urban drainage risk management

Masaru Morita, Yeou Koung Tung

Research output: Contribution to journalArticle

Abstract

This paper presents a method of quantifying the uncertainty associated with inundation damage data for an urban catchment when undertaking stormwater drainage design and management. Usually flood damage is estimated by multiplying the inundated asset value by the damage rate corresponding to the inundation depth. The uncertainty of the asset value and the damage rate is described by probability distributions estimated from an analysis of actual flood damage data from a national government survey. With the inclusion of uncertainty in the damage rate and asset value, the damage potential curve defining the damage-frequency relationship is no longer a deterministic single-value curve. Through Monte Carlo simulations, which incorporate the uncertainty of the inundation damage from the damage rate and asset value, a probabilistic damage potential relation can be established, which can be expressed in terms of a series of curves with different percentile levels. The method is demonstrated through the establishment of probabilistic damage potential curves for a typical urban catchment, the Zenpukuji river basin in Tokyo Metropolis, under two scenarios, namely, with and without a planned flood control reservoir.

Original languageEnglish
Pages (from-to)478-486
Number of pages9
JournalWater science and technology : a journal of the International Association on Water Pollution Research
Volume80
Issue number3
DOIs
Publication statusPublished - 2019 Aug 1

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Flood damage
urban drainage
flood damage
Risk management
Drainage
Catchments
damage
Flood control
Probability distributions
Rivers
Uncertainty
risk management
catchment
flood control
stormwater
river basin

ASJC Scopus subject areas

  • Environmental Engineering
  • Water Science and Technology

Cite this

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abstract = "This paper presents a method of quantifying the uncertainty associated with inundation damage data for an urban catchment when undertaking stormwater drainage design and management. Usually flood damage is estimated by multiplying the inundated asset value by the damage rate corresponding to the inundation depth. The uncertainty of the asset value and the damage rate is described by probability distributions estimated from an analysis of actual flood damage data from a national government survey. With the inclusion of uncertainty in the damage rate and asset value, the damage potential curve defining the damage-frequency relationship is no longer a deterministic single-value curve. Through Monte Carlo simulations, which incorporate the uncertainty of the inundation damage from the damage rate and asset value, a probabilistic damage potential relation can be established, which can be expressed in terms of a series of curves with different percentile levels. The method is demonstrated through the establishment of probabilistic damage potential curves for a typical urban catchment, the Zenpukuji river basin in Tokyo Metropolis, under two scenarios, namely, with and without a planned flood control reservoir.",
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