5 datasets found

The CRIDA approach provides a crucial framework to enable water managers and policy makers to assess the impact of climate uncertainty and change on their water resources and work towards effective adaptation strategies. This multi-step process embraces a participatory, bottom-up approach to identify water security hazards, and is sensitive to indigenous and gender-related water vulnerabilities. By engaging local communities in the design of the analysis, the information provided by scientific modeling and climate analysis can be tailored and thus provide more useful answers to the challenges they are facing. They are also providing a more informed starting point to assess the different options for adaptation, and design robust adaptation pathways, in line with the local needs.

This publication aims to bridge the gap between climate and disasters, in the face of the uncertainties that climate change poses to water managers and policymakers. Composed of a compilation of worldwide case studies, it provides examples of innovative water management and climate risk assessment approaches. The publication also highlights the National Determined Contributions (NDCs) and National Adaptation Plans (NAPs) with the aim of identifying links between these high-level frameworks, DRR and water issues, and describing how the policy-practice linkages can be turned into action.

This publication has laid out a strategic framework to integrate Open Science into hydrology, illustrating its true potential to enhance research transparency, collaboration, and accessibility within water management practices. The six pillars — open data, open source, open publishing, open infrastructure, open education, and open participation — constitute the structure of the Open Hydrology framework designed to promote transparency and reproducibility.

This publication reviews the current state-of-the-art of AI and Machine Learning (ML) applications within water management, introducing some of the main concepts and providing the reader with a general understanding of different technologies and concepts. Further, it features examples of the most influential applications of AI within water management and highlights the ethical challenges when streamlining AI for water resources management.