CrisAct aims at providing a comprehensive science-based framework for monitoring and managing hydroclimatically driven natural hazard crisis and disaster response, in order to protect society against droughts, floods, and heat waves, occurring separately or in combination or sequence.
CrisAct aims at providing a comprehensive science-based framework for monitoring and managing hydro-climatically driven natural hazard crisis and disaster response, in order to protect society against droughts, floods, and heat waves, occurring separately or in combination or sequence. The research results will provide essential scientific underpinning and support for decision-making on management of such disasters and mitigation of their risks, with focus on exploring the potential of various adaptive solutions/actions in Sweden.
With this aim, we will develop an innovative online system for monitoring and risk quantification of droughts, floods, heat waves, and their spatiotemporal relationships across Sweden. The system development will be combined with consideration and assessment of opportunities for climate-change adaptation and disaster risk mitigation in a preventive and responsive crisis management framework.
The monitoring system will build on the advancement of scientific understanding of current conditions and future projections of drought, flood, and heat wave (co-)occurrence, along with societal vulnerability to these – often compound – hazards. Project results will form a basis for suggesting preparatory, preventive, and responsive solutions to their (co-)occurrences, considering the Swedish context for such hydro-climatic risk mitigation and crisis management. Specific objectives are to:
Four work packages (WPs) will pursue these objectives in a way that moves beyond the current state-of-the-art to generate concrete recommendations with tangible benefits for Swedish societal security. Project outcomes will be systematically communicated with relevant stakeholders, including policy and decision makers, to ensure relevant development directions and promote the application of developed tools and action roadmap.
All project outcomes will also be made available to the broad scientific community through open-access scientific publications in high-impact journals, and to a wider readership through popular science and media publications.
Journal article / This study investigated the use of machine learning methods for predicting key indicators of agricultural drought over Sweden.
Design and development by Soapbox.