洪水预测下的决策:沿海房地产风险感知研究。

IF 3 3区 医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Risk Analysis Pub Date : 2025-01-18 DOI:10.1111/risa.17706
Avidesh Seenath, Scott Mark Romeo Mahadeo, Matthew Blackett
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引用次数: 0

摘要

洪水模型虽然代表了我们对自然现象的最佳认识,但也在不断发展。他们的预测,尽管对洪水风险管理具有不可否认的重要性,但包含与模型结构、参数化和输入数据相关的相当大的不确定性。随着在线洪水地图越来越多地提供多种洪水预测来源,这些预测的不确定性带来了与财产贬值有关的相当大的风险。这些风险来自于房地产决策,通过地理位置偏好和购买和租赁房产的意愿来衡量,这是基于对各种洪水预测来源的访问。在这里,我们采用跨学科的方法来评估沿海洪水预测对英国房地产决策的影响,包括洪水建模、英国居民对洪水预测的新型实验性房地产支付意愿调查、统计建模和地理空间分析。我们的主要研究结果表明,相对于对地理位置美学的偏好,获得多种洪水预测来源的机会在房地产决策中占主导地位,反映了对风险规避地点的需求转变。我们还发现,人们在房地产决策中不考虑洪水预测的不确定性,可能是由于无法感知这种不确定性。在使用开放获取的长期洪水风险图的重复实验调查中,这些结果是可靠的。因此,我们建议让洪水模型“正确”,但认识到这是一个有争议的问题,因为它意味着有一个没有错误的模型,这实际上是不可能的。因此,为了减少房地产风险,我们提倡更加重视有效地向非专家传达洪水模型预测及其不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision-making under flood predictions: A risk perception study of coastal real estate.

Flood models, while representing our best knowledge of a natural phenomenon, are continually evolving. Their predictions, albeit undeniably important for flood risk management, contain considerable uncertainties related to model structure, parameterization, and input data. With multiple sources of flood predictions becoming increasingly available through online flood maps, the uncertainties in these predictions present considerable risks related to property devaluation. Such risks stem from real estate decisions, measured by location preferences and willingness-to-pay to buy and rent properties, based on access to various sources of flood predictions. Here, we evaluate the influence of coastal flood predictions on real estate decision-making in the United Kingdom by adopting an interdisciplinary approach, involving flood modeling, novel experimental willingness-to-pay real estate surveys of UK residents in response to flood predictions, statistical modeling, and geospatial analysis. Our main findings show that access to multiple sources of flood predictions dominates real estate decisions relative to preferences for location aesthetics, reflecting a shift in demand toward risk averse locations. We also find that people do not consider flood prediction uncertainty in their real estate decisions, possibly due to an inability to perceive such uncertainty. These results are robust under a repeated experimental survey using an open access long-term flood risk map. We, therefore, recommend getting flood models "right" but recognize that this is a contentious issue because it implies having an error-free model, which is practically impossible. Hence, to reduce real estate risks, we advocate for a greater emphasis on effectively communicating flood model predictions and their uncertainties to non-experts.

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来源期刊
Risk Analysis
Risk Analysis 数学-数学跨学科应用
CiteScore
7.50
自引率
10.50%
发文量
183
审稿时长
4.2 months
期刊介绍: Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include: • Human health and safety risks • Microbial risks • Engineering • Mathematical modeling • Risk characterization • Risk communication • Risk management and decision-making • Risk perception, acceptability, and ethics • Laws and regulatory policy • Ecological risks.
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