Participatory Bayesian Network modeling of climate change risks and adaptation regarding water supply: Integration of multi-model ensemble hazard estimates and local expert knowledge
- Local climate change risk assessments (LCCRAs) are best supported by a quantitative integration of physical hazards, exposures and vulnerabilities that includes the characterization of uncertainties. We propose to use Bayesian Networks (BNs) for this task and show how to integrate freely-available output of multiple global hydrological models (GHMs) into BNs, in order to probabilistically assess risks for water supply. Projected relative changes in hydrological variables computed by three GHMs driven by the output of four global climate models were processed using MATLAB, taking into account local information on water availability and use. A roadmap to set up BNs and apply probability distributions of risk levels under historic and future climate and water use was co-developed with experts from the Maghreb (Tunisia, Algeria, Morocco) who positively evaluated the BN application for LCCRAs. We conclude that the presented approach is suitable for application in the many LCCRAs necessary for successful adaptation to climate change world-wide.
Author: | Fabian KneierORCiDGND, Laura WoltersdorfORCiDGND, Thedini Asali PeirisORCiD, Petra DöllORCiDGND |
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URN: | urn:nbn:de:hebis:30:3-790436 |
DOI: | https://doi.org/10.1016/j.envsoft.2023.105764 |
ISSN: | 1364-8152 |
Parent Title (English): | Environmental modelling & software |
Publisher: | Elsevier |
Place of publication: | Amsterdam |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2023/08/08 |
Date of first Publication: | 2023/07/03 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2023/11/13 |
Tag: | Bayesian network; Climate change; Multi-model ensemble; Participatory process; Risk assessment; Roadmap; Uncertainty |
Volume: | 168 |
Issue: | 105764 |
Article Number: | 105764 |
Page Number: | 20 |
HeBIS-PPN: | 514708921 |
Institutes: | Geowissenschaften / Geographie / Geowissenschaften |
Angeschlossene und kooperierende Institutionen / Senckenbergische Naturforschende Gesellschaft | |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften | |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - Namensnennung 4.0 |