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 f...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
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Wiley
2025
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| _version_ | 1824458923599462400 |
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| author | Seenath, A Mahadeo, SMR Blackett, M |
| author_facet | Seenath, A Mahadeo, SMR Blackett, M |
| author_sort | Seenath, A |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2025-02-19T04:33:36Z |
| format | Journal article |
| id | oxford-uuid:b5d03271-a51c-42f1-88ec-b257a2e89b0d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2025-02-19T04:33:36Z |
| publishDate | 2025 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:b5d03271-a51c-42f1-88ec-b257a2e89b0d2025-01-20T11:24:38ZDecision-making under flood predictions: a risk perception study of coastal real estateJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b5d03271-a51c-42f1-88ec-b257a2e89b0dEnglishSymplectic ElementsWiley2025Seenath, AMahadeo, SMRBlackett, MFlood 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. |
| spellingShingle | Seenath, A Mahadeo, SMR Blackett, M Decision-making under flood predictions: a risk perception study of coastal real estate |
| title | Decision-making under flood predictions: a risk perception study of coastal real estate |
| title_full | Decision-making under flood predictions: a risk perception study of coastal real estate |
| title_fullStr | Decision-making under flood predictions: a risk perception study of coastal real estate |
| title_full_unstemmed | Decision-making under flood predictions: a risk perception study of coastal real estate |
| title_short | Decision-making under flood predictions: a risk perception study of coastal real estate |
| title_sort | decision making under flood predictions a risk perception study of coastal real estate |
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