Bruno Merz, Viet Dung Nguyen, B. Guse, Li Han, Xiaoxiang Guan, Oldrich Rakovec, Luis Samaniego, Bodo Ahrens, Sergiy Vorogushyn
{"title":"Spatial counterfactuals to explore disastrous flooding","authors":"Bruno Merz, Viet Dung Nguyen, B. Guse, Li Han, Xiaoxiang Guan, Oldrich Rakovec, Luis Samaniego, Bodo Ahrens, Sergiy Vorogushyn","doi":"10.1088/1748-9326/ad22b9","DOIUrl":null,"url":null,"abstract":"\n Flood-prone people and decision-makers are often unwilling to discuss and prepare for exceptional events, as such events are hard to perceive and out of experience for most people. Once an exceptional flood occurs, affected people and decision-makers are able to learn from this event and improve their preparedness and risk management. However, this learning is often focussed narrowly on the specific disaster experienced, thus missing an opportunity to explore and prepare for even more severe, or different, events. We propose spatial counterfactual floods as a means to motivate society to discuss exceptional events and suitable risk management strategies. We generate a set of extreme floods across Germany by shifting observed rainfall events in space and then propagating these shifted fields through a flood model. We argue that it is highly plausible that the storm tracks that caused past floods could have been shifted by several tens of km in space. The set of spatial counterfactual floods generated in this way contains events which are more than twice as severe as the most disastrous flood since 1950 in Germany. Moreover, regions that have been spared from havoc in the past should not feel safe, as they could have been badly hit as well. We propose spatial counterfactuals as a suitable approach to overcome society's unwillingness to think about and prepare for exceptional floods expected to occur more frequently in a warmer world.","PeriodicalId":507917,"journal":{"name":"Environmental Research Letters","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Research Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1748-9326/ad22b9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Flood-prone people and decision-makers are often unwilling to discuss and prepare for exceptional events, as such events are hard to perceive and out of experience for most people. Once an exceptional flood occurs, affected people and decision-makers are able to learn from this event and improve their preparedness and risk management. However, this learning is often focussed narrowly on the specific disaster experienced, thus missing an opportunity to explore and prepare for even more severe, or different, events. We propose spatial counterfactual floods as a means to motivate society to discuss exceptional events and suitable risk management strategies. We generate a set of extreme floods across Germany by shifting observed rainfall events in space and then propagating these shifted fields through a flood model. We argue that it is highly plausible that the storm tracks that caused past floods could have been shifted by several tens of km in space. The set of spatial counterfactual floods generated in this way contains events which are more than twice as severe as the most disastrous flood since 1950 in Germany. Moreover, regions that have been spared from havoc in the past should not feel safe, as they could have been badly hit as well. We propose spatial counterfactuals as a suitable approach to overcome society's unwillingness to think about and prepare for exceptional floods expected to occur more frequently in a warmer world.