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pmid: 36274936
pmc: PMC9579022
Climate change impacts are increasingly complex owing to compounding, interacting, and cascading risks across sectors. However, approaches to support Disaster Risk Management (DRM) addressing the underlying (uncertain) risk driver interactions are still lacking. We tailor the approach of Dynamic Adaptive Policy Pathways (DAPP) to DAPP-MR to design DRM pathways for complex, dynamic multi-risk in multi-sector systems. We review the recent multi-hazard and multi-sector research to identify relevant aspects of multi-risk management frameworks and illustrate the suitability of DAPP-MR using a stylized case. It is found that rearranging the analytical steps of DAPP by introducing three iteration stages can help to capture interactions, trade-offs, and synergies across hazards and sectors. We show that DAPP-MR may guide multi-sector processes to stepwise integrate knowledge toward multi-risk management. DAPP-MR can be seen as an analytical basis and first step toward an operational, integrative, and interactive framework for short-to long-term multi-risk DRM.
Climatology, Environmental event, Science, Q, Decision-Making Under Deep Uncertainty, Article, Adaptation Pathways, Earth sciences, Multi-Risk, SDG 13 - Climate Action, General
Climatology, Environmental event, Science, Q, Decision-Making Under Deep Uncertainty, Article, Adaptation Pathways, Earth sciences, Multi-Risk, SDG 13 - Climate Action, General
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 26 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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