Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location-Specific Premiums in the Netherlands

Categorizing and Harmonizing Natural, Technological, and Socio-Economic Perils Following the Catastrophe Modeling Paradigm

The literature on probabilistic hazard and risk assessment shows a rich and wide variety of modeling strategies tailored to specific perils. On one hand, catastrophe (CAT) modeling, a recent professional and scientific discipline, provides a general structure for the quantification of natural (e.g., geological, hydrological, meteorological) and man-made (e.g., terrorist, cyber) catastrophes. On the other hand, peril characteristics and related processes have yet to be categorized and harmonized to enable adequate comparison, limit silo effects, and simplify the implementation of emerging risks. We reviewed the literature for more than 20 perils from the natural, technological, and socio-economic systems to categorize them by following the CAT modeling hazard pipeline: (1) event source → (2) size distribution → (3) intensity footprint. We defined the following categorizations, which are applicable to any type of peril, specifically: (1) point/line/area/track/diffuse source, (2) discrete event/continuous flow, and (3) spatial diffusion (static)/threshold (passive)/sustained propagation (dynamic). We then harmonized the various hazard processes using energy as the common metric, noting that the hazard pipeline's underlying physical process consists of some energy being transferred from an energy stock (the source), via an event, to the environment (the footprint).

A Risk-Informed Decision-Making Framework for Climate Change Adaptation through Robust Land Use and Irrigation Planning

Uncertainty and variability are key challenges for climate change adaptation planning. In the face of uncertainty, decision-making can be addressed in two interdependent stages: make only partial ex ante anticipative actions to keep options open until new information is revealed, and adapt the first-stage decisions with respect to newly acquired information. This decision-making approach corresponds to the two-stage stochastic optimization (STO) incorporating both anticipative ex ante and adaptive ex post decisions within a single model. This paper develops a two-stage STO model for climate change adaptation through robust land use and irrigation planning under conditions of uncertain water supply. The model identifies the differences between decision-making in the cases of perfect information, full uncertainty, and two-stage STO from the perspective of learning about uncertainty. Two-stage anticipative and adaptive decision-making with safety constraints provides risk-informed decisions characterized by quantile-based Value-at-Risk and Conditional Value-at-Risk risk measures. The ratio between the ex ante and ex post costs and the shape of uncertainty determine the balance between the anticipative and adaptive decisions. Selected numerical results illustrate that the alteration of the ex ante agricultural production costs can affect crop production, management technologies, and natural resource utilization.

Analysis of Flood-Vulnerable Areas for Disaster Planning Considering Demographic Changes in South Korea

Regional demographic changes are important regional characteristics that need to be considered for the establishment of disaster prevention policies against climate change worldwide. In this study, we propose urban disaster prevention plans based on the classification and characterization of flood vulnerable areas reflecting demographic changes. Data on the property damage, casualties, and flooded area between 2009 and 2018 in 229 municipalities in South Korea were collected and analyzed, and 74 flood vulnerable areas were selected. The demographic change in the selected areas from 2000 to 2018 was examined through comparative analyses of the population size, rate of population change, and population change proportion by age group and gender. Flood vulnerable areas were categorized into three types through K-mean cluster analysis. Based on the analysis results, a strategic plan was proposed to provide information necessary for establishing regional flood-countermeasure policies.

Determinants of Probability Neglect and Risk Attitudes for Disaster Risk: An Online Experimental Study of Flood Insurance Demand among Homeowners

Little is known about why individuals place either a high or a very low value on mitigating risks of disaster-type events, like floods. This study uses panel data methods to explore the psychological factors affecting probability neglect of flood risk relevant to the zero end-point of the probability weighting function in Prospect Theory, and willingness-to-pay for flood insurance. In particular, we focus on explanatory variables of anticipatory and anticipated emotions, as well as the threshold of concern. Moreover, results obtained under real and hypothetical incentives are compared in an experiment with high experimental outcomes. Based on our findings, we suggest several policy recommendations to overcome individual decision processes, which may hinder flood protection efforts.

Flood Risk Evaluation in Urban Spaces: The Study Case of Tormes River (Salamanca, Spain)

The expansion of cities towards flood zones, and the increasingly frequent episodes of torrential rains arising from global warming, mean that the population is becoming more exposed to floods. Due to this, a correct assessment of flood events is of great help in the development of preventive actions, planning and resource management, or interventions. For this reason, in this work we aim to establish guidelines to assess the hazard, exposure, and vulnerability of the population and its properties to flood events, using Hec-Ras for the simulation of the flood and ArcGis and GeoHecRas to treat geographic information and prepare the cartography. The study was focused on the Tormes River in Salamanca (Spain). We studied three return periods with different probabilities of occurrence and intensity, corresponding to 5, 100, and 500 years. The flow corresponding to each episode was calculated, along with the extension, speed, and depth that would be achieved in each case. Then, the probability of occurrence was delimited, as well as the magnitude, allowing us to obtain different hazard maps. In addition, the areas of greatest hazard to people and property were established for each event. Regarding the exposure, the areas and land use, infrastructure, and buildings that would be flooded in each case were identified, quantifying the extension or length of the affected properties at the different levels of hazard in each case. Additionally, the vulnerability of the different buildings and exposed infrastructure was studied. Finally, the flood risk was estimated by combining these three components.