The session will explore the integration of stakeholder engagement and advanced hydroinformatics techniques such as remote sensing, machine learning, AI, and numerical modeling to address key challenges in hydrological sciences and natural hazards. Emphasizing both theoretical advancements and practical applications, the session will attract contributions from diverse geographic regions and hydrological contexts, particularly those involving the co-development of research with decision-makers.
Key Themes:
1. Hydrological Extremes Monitoring and Prediction:
Utilizing remote sensing and global datasets to monitor and predict droughts, floods, and extreme climatic events, Developing machine learning models for forecasting hydrologic extremes across diverse basins, & Integrating land surface modeling with data assimilation of satellite and in-situ observations.
2. Process Dynamics in Complex Terrain
Modeling land surface hydrology across diverse topographies and climatic zones, Examining the influence of topographic variability on land surface dynamics and hydrological extremes, and Integrating local knowledge with high-resolution data for effective water resource management in mountainous regions.
3. Climate Change Impacts on Hydrology:
Evaluating the influence of climate change on hydrological processes and extremes, including floods and droughts & Applying integrated modeling approaches to understanding the combined effects of land use and climate change on hydrological regimes.
4. Equity in Water Resource Management:
Analyzing trade-offs in water distribution systems, focusing on equity and performance during scarcity & Case studies on the impacts of domestic water storage and rationing under varying climate conditions.
5. Technological Innovations in Hydroinformatics:
Leveraging AI and hydroinformatics tools to enhance water resource management and policymaking & Advances in data assimilation techniques to improve model predictions and decision support systems.
6. Participatory Research and Stakeholder Engagement
Collaborating with decision-makers to co-develop research methods and refine models, ensuring stakeholder-driven processes, Co-designing data analysis and visualization tools to support science-informed decision-making and enhance research relevance, & Case studies that highlight successful science-to-action projects through integrating stakeholder perspectives.