Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Civil and Environmental Engineering

Supervisor

Slobodan P. Simonovic

Abstract

Water resources systems are vulnerable to natural disasters such as floods, wind storms, earthquakes, and various meteorological events. Flooding is the most frequent natural hazard that can cause damage to human life and property. A new methodology presented in this thesis is capable of flood risk management by: (a) addressing various uncertainties caused by variability and ambiguity; (b) integrating objective and subjective flood risk; and (c) assisting the flood risk management based on better understanding of spatial and temporal variability of risk. The new methodology is based on the use of fuzzy reliability theory. A new definition of risk is used and described using three performance indices (i) a combined fuzzy reliability-vulnerability, (ii) fuzzy robustness and (iii) fuzzy resiliency. The traditional flood risk management relies on either temporal or spatial variability, but not both. However, there is a need to understand the dynamic characteristics of flood risk and its spatial variability. The two-dimensional (2-D) fuzzy set that relates the universe of discourse and its membership degree, is not sufficient to address both, spatial and temporal, variations of flood risk. The theoretical contribution of this study is based on the development of a three dimensional (3-D) fuzzy set.

The spatial and temporal variability of fuzzy performance indices – (i) combined reliability-vulnerability, (ii) robustness, and (iii) resiliency – have been implemented to (i) river flood risk analysis and (ii) urban flood risk analysis. The river flood risk analysis is illustrated using the Red River flood of 1997 (Manitoba, Canada) as a case study. The urban flood risk analysis is illustrated using the residential community of Cedar Hollow (London, Ontario, Canada) as a case study. The final results of the fuzzy flood reliability analysis are presented using maps that show the spatial and temporal variation of reliability-vulnerability, robustness and resiliency indices. Maps of fuzzy reliability indices provide additional decision support for (a) land use planning, (b) selection of appropriate flood mitigation strategies, (c) planning emergency management measures, (d) selecting an appropriate construction technology for flood prone areas, and (e) flood insurance.


Share

COinS