Browsing by Author "Morita, Masaru"

Now showing 1 - 2 of 2

Uncertainty quantification of flood damage estimation for urban drainage risk management
(2019-08-01)
Morita, Masaru
;
Tung, Yeou Koung
;
防災與水環境研究中心
;
Disaster Prevention and Water Environment Research Center
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.
Uncertainty Quantification of Flood Damage Estimation for Urban Drainage Risk Management
(2019-01-01)
Morita, Masaru
;
Tung, Yeou Koung
;
防災與水環境研究中心
;
Disaster Prevention and Water Environment Research Center
The study presents an inundation damage estimation method which quantifies the uncertainty in inundation damage statistical data for urban drainage management. The flood damage is usually estimated by multiplying inundated asset value by damage rate determined by the inundation depth. The dispersions of the asset values and the damage rates related to the uncertainty were expressed quantitatively using probability distributions for the actual flood damage data surveyed by the national government. Monte Carlo simulation was utilized to calculate the damage from the two parameters with probability distributions. Thus the simulations brought about the monetary flood damage not in deterministic but in probabilistic form.