Thesis (Ph. D.)--University of Hong Kong, 2001. / Includes bibliographical references.

Risk mitigation decisions for civil infrastructure exposed to rare natural and manmade hazards are often impacted by risk aversion, a behavioral phenomenon in which the decision maker's perception and judgment of risk are systematically distorted, resulting in decisions that might be viewed as excessively conservative when compared to those from a traditional minimum expected cost analysis. This study addresses how decisions regarding structural safety are affected by the attitudes of the decision-maker toward risk using decision models, such as cumulative prospect theory, that allow risk-averse behaviors to be modeled quantitatively. Perspectives on the general characteristics of risk-aversion are first drawn from risk pricing techniques in the insurance industry. These perspectives are then refined for structural engineering applications by investigations of decisions involving seismic retrofit of unreinforced masonry structures in San Francisco, CA and aseismic design of a steel moment frame in Vancouver, BC. Risk attitudes when confronting extreme wind hazards are also assessed using a decision by the North and South Carolina Code Councils to waive a provision in the International Residential Code that would have required additional windborne debris protection in residential construction. An examination of risk attitudes toward competing natural hazards is then introduced by comparing decisions related to wind and seismic effects in areas where both hazards may be significant. These investigations have led to tentative conclusions regarding the role of risk aversion in the assurance of structural safety and in code-related decisions and suggest avenues for future study.

This study is concerned with the manner in which households create strategies to mitigate environmental risks in informal settlements for example Lacey Road which is located in Sydenham in the eThekwini metropolitan area of KwaZulu‐Natal. Informal settlements result from migration and urbanisation trends whereby people from rural areas migrate to the city in search of job opportunities and a better life. Many fail to find the formal employment opportunities they seek and find themselves having to provide their own shelter. These circumstances culminate in the construction of informal settlements in and near the city. People settle on land that is often undesirable for development because of geological or environmental pressures e.g. it has unstable soils, the land is located within flood plains or on very steep slopes. The vulnerability approach and political ecology framework underpin this study. These two approaches have been used in order to understand the capabilities of informal settlers to cope with risks they are faced with. They have been also used to understand how human activities and political systems may be linked to the spread of environmental degradation and risks. Household survey and key informants interviews were used to conduct this study. The findings of the research show that Lacey Road informal settlement is exposed to various risks such as floods, fire, waste disposal, and indoor air pollution and other health risks. It is clear that residents from Lacey Road are regularly exposed to the harsh realities of spatial and environmental marginalisation. The main reason for their vulnerability is the lack of service delivery by the municipality. This is due to a unique set of power relations where the community does not have profile to force the municipality to provide access to basic services. It is within this context that the researcher sought to analyse and explore the interface between environmental risk management and coping strategies of residents within informal settlements. Whilst there are general risks that face all residents of informal settlements, the researcher also considered what is specific to the Lacey Road settlement in Sydenham. The intention of this research is to identify environmental risks being experienced in Lacey Road informal settlements. Furthermore, to understand household strategies employed to mitigate those environmental risks at Lacey Road. / Thesis (M.Sc.U.R.P.)-University of KwaZulu-Natal, Durban, 2010.

Earthquakes are among the most devastating and unpredictable of natural hazards that affect civil infrastructure and have the potential for causing numerous casualties and significant economic losses over large areas. Every region that has the potential for great earthquakes should have an integrated plan for a seismic design and risk mitigation for civil infrastructure. This plan should include methods for estimating the vulnerability of building inventories and for forecasting economic losses resulting from future events. This study describes a methodology to assess risk to distributed civil infrastructure due to large-scale natural hazards with large geographical footprints, such as earthquakes, hurricanes and floods, and provides a detailed analysis and assessment of building losses due to earthquake. The distinguishing feature of this research, in contrast to previous loss estimation methods incorporated in systems such as HAZUS-MH, is that it considers the correlation in stochastic demand on building inventories due to the hazard, as well as correlation in building response and damage due to common materials, construction technologies, codes and code enforcement. These sources of correlation have been neglected, for the most part, in previous research. The present study has revealed that the neglect of these sources of correlation leads to an underestimation of the estimates of variance in loss and in the probable maximum loss (PML) used as a basis for underwriting risks. The methodology is illustrated with a seismic risk assessment of building inventories representing different occupancy classes in Shelby County, TN, considering both scenario earthquakes and earthquakes specified probabilistically. It is shown that losses to building inventories estimated under the common assumption that the individual losses can be treated as statistically independent may underestimate the PML by a factor of range from 1.7 to 3.0, depending on which structural and nonstructural elements are included in the assessment. A sensitivity analysis reveals the statistics and sources of correlation that are most significant for loss estimation, and points the way forward for supporting data acquisition and synthesis.