Bayesian Data-Driven approach enhances synthetic flood loss models
| Autor: | Sally J. Priest, Heidi Kreibich, Alessio Domeneghetti, Dennis Wagenaar, Christophe Viavattene, Nivedita Sairam, Bruno Merz, Kai Schröter, Daniela Molinari, Francesca Carisi, Fabio Brill |
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| Přispěvatelé: | Sairam N., Schroter K., Carisi F., Wagenaar D., Domeneghetti A., Molinari D., Brill F., Priest S., Viavattene C., Merz B., Kreibich H. |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Empirical data
Environmental Engineering 010504 meteorology & atmospheric sciences Computer science Reliability (computer networking) Bayesian probability 0207 environmental engineering 02 engineering and technology computer.software_genre 01 natural sciences Data-driven Flood damage flood loss flood damage models Bayesian Data-Driven models 020701 environmental engineering 0105 earth and related environmental sciences flood loss Flood myth Event (computing) Ecological Modeling Empirical modelling Flood Risk flood hazard Bayesian Data-Driven Flood directive Flood damage Flood loss 13. Climate action flood damage models Data mining Bayesian Data-Driven models computer Software |
| Zdroj: | Environmental Modelling and Software |
| ISSN: | 1364-8152 |
| Popis: | Flood loss estimation models are developed using synthetic or empirical approaches. The synthetic approach consists of what-if scenarios developed by experts. The empirical models are based on statistical analysis of empirical loss data. In this study, we propose a novel Bayesian Data-Driven approach to enhance established synthetic models using available empirical data from recorded events. For five case studies in Western Europe, the resulting Bayesian Data-Driven Synthetic (BDDS) model enhances synthetic model predictions by reducing the prediction errors and quantifying the uncertainty and reliability of loss predictions for post-event scenarios and future events. The performance of the BDDS model for a potential future event is improved by integration of empirical data once a new flood event affects the region. The BDDS model, therefore, has high potential for combining established synthetic models with local empirical loss data to provide accurate and reliable flood loss predictions for quantifying future risk. |
| Databáze: | OpenAIRE |
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