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HS7.3/CL2.12/NP1.4

Water, climate and health (co-organized)
Convener: Hwa-Lung Yu  | Co-Conveners: Andreas Langousis , Alin Andrei Carsteanu , Antarpreet Jutla , Alexander Kolovos 
Orals
 / Tue, 09 Apr, 10:30–12:00  / 13:30–17:00  / Room R1
Posters
 / Attendance Tue, 09 Apr, 17:30–19:00  / Red Posters

This session is designed to explore the impacts of the hydro-climatic system and its changes on population health. In particular, contributions are sought that shed light on the following issues:

1. Complex inter-linkages of hydrological conditions and population health, including extreme weather events, surface and subsurface water resources, surface temperatures, water- and food-borne illnesses, vector- and rodent-borne diseases, food and water shortages.
2. Quantitative assessments of hydrologic extremes and water-related natural disasters.
3. Relationships between precipitation, surface and subsurface water resources, flooding, droughts, water quality and the effects on human and ecological health.
4. Assessment of the impact of climate change and climate variability on hydrological conditions and water resources and their associated human and ecological health impacts.
5. Modeling tools for organizing integrated solutions to climate-water-health problems.
6. Characterizing and modeling disease spread patterns and their relationships with climatic, weather, and hydrological conditions.
7. Current data and information bases on water resources and climate conditions and variations over a wide range of space-time scales, and health impacts.
8. Development of climate-sensitive adaptive strategies to changing patterns of water availability and variability using analytical and statistical methods.
9. Enhancing understanding of uncertainty measures and their effective use concerning the interacting impacts of climate variability, extreme weather conditions, surface and subsurface water resources, and health issues.
10. Scale compatibility of model linkages, particularly in the linking of atmospheric-hydrologic-health models.