Articles | Volume 16, issue 4
Nat. Hazards Earth Syst. Sci., 16, 915–925, 2016
https://doi.org/10.5194/nhess-16-915-2016

Special issue: Natural hazard event analyses for risk reduction and...

Nat. Hazards Earth Syst. Sci., 16, 915–925, 2016
https://doi.org/10.5194/nhess-16-915-2016

Research article 11 Apr 2016

Research article | 11 Apr 2016

Hazard function theory for nonstationary natural hazards

Laura K. Read and Richard M. Vogel Laura K. Read and Richard M. Vogel
  • Department of Civil and Environmental Engineering, Tufts University, 200 College Avenue, Medford, MA, 02155, USA

Abstract. Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.

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Short summary
The research presented in this manuscript introduces the theory and methods from the hazard function analysis literature to address the probabilistic analysis of natural hazards whose magnitudes show evidence of increasing over time. To the authors' knowledge, this is the first research article to apply the extremely well-developed field of hazard function theory to the problem of nonstationary natural hazards.
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