scholarly journals A Performance-Based Approach to Quantify Atmospheric River Flood Risk

2021 ◽  
Author(s):  
Corinne Bowers ◽  
Katherine A. Serafin ◽  
Jack W. Baker
Keyword(s):  
Risk Analysis ◽  
Flood Risk ◽  
Economic Consequences ◽  
Pinch Point ◽  
Atmospheric River ◽  
Average Annual Loss ◽  
Sonoma County ◽  
Russian River ◽  
The Individual ◽  
Component Models

Abstract. Atmospheric rivers (ARs) are a class of meteorologic phenomena that cause significant precipitation and flooding on the US West Coast. This work presents a new Performance-based Atmospheric River Risk Analysis (PARRA) framework that adapts existing concepts from probabilistic risk analysis and performance-based engineering for application in the context of AR-driven fluvial flooding. The PARRA framework is a chain of physically based models that link the atmospheric forcings, hydrologic impacts, and economic consequences of AR-driven fluvial flood risk together at consistent “pinch point” variables. Organizing around these pinch points makes the framework modular, in that models between pinch points can be updated without affecting the rest of the model chain, and it produces a probabilistic result that quantifies the uncertainty in the underlying system states. The PARRA framework can produce results beyond analyses of individual scenario events and can look towards prospective assessment of events or system changes that have not been seen in the historic record. The utility of the PARRA framework is demonstrated through a series of analyses in Sonoma County, California. Evaluation of a February 2019 case study AR event shows that the individual component models produce simulated distributions that capture the observed precipitation, streamflow, inundation, and damage. The component models are then run in sequence to generate a first-of-its-kind AR flood loss exceedance curve for Sonoma County. The prospective capabilities of the PARRA framework are presented through the evaluation of a hypothetical mitigation action. It was found elevating 150 homes, selected based on their proximity to the Russian River, was able to reduce the average annual loss by half. The loss results from the mitigated building portfolio are compared against the original case. While expected benefits were minimal for the smallest events, the larger, more damaging ARs were expected to see loss reductions of approximately $50 million per event. These results indicate the potential of the PARRA framework for examining other changes to flood risk at the community level, including future changes to the hazard, through climate change; exposure, through development; and/or vulnerability, through flood mitigation investments.

scholarly journals Scenario-Based Extreme Flood Risk of Residential Buildings and Household Properties in Shanghai

2019 ◽  
Vol 11 (11) ◽  
pp. 3202 ◽  
Author(s):  
Xinmeng Shan ◽  
Jiahong Wen ◽  
Min Zhang ◽  
Luyang Wang ◽  
Qian Ke ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Inner City ◽  
Flood Risk ◽  
Residential Buildings ◽  
Total Loss ◽  
Hangzhou Bay ◽  
Inundation Area ◽  
Average Annual Loss ◽  
Extreme Flood ◽  
Extreme Flooding

Extreme flooding usually causes huge losses of residential buildings and household properties, which is critical to flood risk analysis and flood resilience building in Shanghai. We developed a scenario-based multidisciplinary approach to analyze the exposure, losses and risks of residential buildings and household properties, and their spatial patterns at the neighborhood committee level in Shanghai, based on extreme storm flood scenarios of 1/200, 1/500, 1/1000 and 1/5000-year. Our findings show that the inundation area of the residential buildings caused by a 1/200-year storm flood reaches 24.9 km2, and the total loss of residential buildings and household properties is 29.7 billion CNY (Chinese Yuan) (or 4.4 billion USD), while the inundation area of residential buildings and the total loss increases up to 162.4 km2 and 366.0 billion CNY (or 54.2 billion USD), respectively for a 1/5000-year storm flood. The estimated average annual loss (AAL) of residential buildings and household properties for Shanghai is 590 million CNY/year (or 87.4 million USD/year), with several hot spots distributed around the main urban area and on the bank of the Hangzhou Bay. Among sixteen districts, Pudong has the highest exposure and annual expected loss, while the inner city is also subject to extreme flooding with an AAL up to near half of the total. An analysis of flood risk in each of 209 subdistricts/towns finds that those most vulnerable to storm flooding are concentrated in Pudong, Jiading, Baoshan Districts and the inner city. Our work can provide meaningful information for risk-sensitive urban planning and resilience building in Shanghai. The methodology can also be used for risk analysis in other coastal cities facing the threat of storm flooding.

The Role of Threat and Economic Uncertainty in Support for Scottish Independence

2014 ◽  
Vol 23 (1) ◽  
pp. 103-124 ◽  
Author(s):  
Daniel Kopasker
Keyword(s):  
Economic Consequences ◽  
Perceived Threat ◽  
Constitutional Change ◽  
Lack Of Information ◽  
Economic Expectations ◽  
Scottish Independence ◽  
The Individual ◽  
The Impact ◽  
Levels Of Support

Existing research has consistently shown that perceptions of the potential economic consequences of Scottish independence are vital to levels of support for constitutional change. This paper attempts to investigate the mechanism by which expectations of the economic consequences of independence are formed. A hypothesised causal micro-level mechanism is tested that relates constitutional preferences to the existing skill investments of the individual. Evidence is presented that larger skill investments are associated with a greater likelihood of perceiving economic threats from independence. Additionally, greater perceived threat results in lower support for independence. The impact of uncertainty on both positive and negative economic expectations is also examined. While uncertainty has little effect on negative expectations, it significantly reduces the likelihood of those with positive expectations supporting independence. Overall, it appears that a general economy-wide threat is most significant, and it is conjectured that this stems a lack of information on macroeconomic governance credentials.

scholarly journals A review of modelling methodologies for flood source area (FSA) identification

2021 ◽  
Author(s):  
Amrie Singh ◽  
David Dawson ◽  
Mark Trigg ◽  
Nigel Wright
Keyword(s):  
Flood Risk ◽  
Risk Mitigation ◽  
Ground Cover ◽  
Source Area ◽  
Urban Environments ◽  
Weather Patterns ◽  
Complex Process ◽  
Average Annual Loss ◽  
Flood Source ◽  
Modelling Approaches

AbstractFlooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises.

Correlation models in flood risk analysis

2012 ◽  
Vol 105 ◽  
pp. 64-72 ◽  
Author(s):  
F.L.M. Diermanse ◽  
C.P.M. Geerse
Keyword(s):  
Risk Analysis ◽  
Flood Risk ◽  
Correlation Models ◽  
Flood Risk Analysis

SAR based flood risk analysis: a case study Kerala Flood 2018

2021 ◽  
Author(s):  
Niloy Pramanick ◽  
Rituparna Acharyya ◽  
Sandip Mukherjee ◽  
Sudipta Mukherjee ◽  
Indrajit Pal ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Flood Risk ◽  
Flood Risk Analysis

scholarly journals What happens when the nuclear power plant goes? Social and economic consequences of dismantling for the site and its population

2021 ◽  
Vol 1 ◽  
pp. 265-266
Author(s):  
Caroline Kramer
Keyword(s):  
Nuclear Power ◽  
Best Practice ◽  
Operating Time ◽  
Rapid Change ◽  
Intention To Leave ◽  
Economic Consequences ◽  
Power Station ◽  
Individual Level ◽  
Social Scientific ◽  
The Individual

Abstract. This project deals with the question of what the overall social and economic consequences of dismantling a nuclear power station are for the population and the site. Various disciplines and specialist fields are concerned with questions that touch on the topic of dismantling nuclear technical facilities; however, there are so far no research projects that examined these processes from social scientific, geographic and engineering scientific perspectives. This article concentrates predominantly on the former perspective of the dismantling. Within the framework of this project the affected population and experts from the communities were asked how they deal with the dismantling of the nuclear power stations, which were triggered by the rapid change in energy policy following the accident in Fukushima in 2011. It became clear that there were various strategies for dealing with this process depending on the location. This was the reason to follow up the question of coping with this process at different locations. It could be shown, for example, that the consequences of this event were essentially determined by how the community was already positioned beforehand, e.g. whether the economic situation was a monostructure or whether long-term considerations about the future had already been made during the operating time of the power station. At the individual level, the “prerequisites” in the sense of individual value orientation and the spatially related identity, were also essentially responsible for how the risks of the dismantling and the further development of the community were perceived and evaluated. Furthermore, it was compiled from where the people extracted their information, which sources had a high or low credibility, which worries they have with respect to the near future and whether they have the intention to leave the community. In this project it became clear that there were examples of best practice with respect to dealing with this rapid and fundamental change at the locations.

scholarly journals The impact of a and b value uncertainty on loss estimation in the reinsurance industry

2000 ◽  
Vol 43 (1) ◽  
Author(s):  
D. Liechti ◽  
E. Ruettener ◽  
S. Eugster ◽  
R. Streit
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Loss Estimation ◽  
Earthquake Risk ◽  
Seismic Risk Analysis ◽  
Earthquake Catalogues ◽  
Local Soil ◽  
Average Annual Loss ◽  
The Impact ◽  
Loss Level

In the reinsurance industry different probabilistic models are currently used for seismic risk analysis. A credible loss estimation of the insured values depends on seismic hazard analysis and on the vulnerability functions of the given structures. Besides attenuation and local soil amplification, the earthquake occurrence model (often represented by the Gutenberg and Richter relation) is a key element in the analysis. However, earthquake catalogues are usually incomplete, the time of observation is too short and the data themselves contain errors. Therefore, a and b values can only be estimated with uncertainties. The knowledge of their variation provides a valuable input for earthquake risk analysis, because they allow the probability distribution of expected losses (expressed by Average Annual Loss (AAL)) to be modelled. The variations of a and b have a direct effect on the estimated exceeding probability and consequently on the calculated loss level. This effect is best illustrated by exceeding probability versus loss level and AAL versus magnitude graphs. The sensitivity of average annual losses due to different a to b ratios and magnitudes is obvious. The estimation of the variation of a and b and the quantification of the sensitivity of calculated losses are fundamental for optimal earthquake risk management. Ignoring these uncertainties means that risk management decisions neglect possible variations of the earthquake loss estimations.

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