| Session Details | |
| Section | HS - Hydrological Sciences |
| Session Title | Risk Assessment Related to Hydrological, Climatic, and Environmental Changes |
| Main Convener | Prof. Tsang-Jung Chang (National Taiwan University, Taiwan) |
| Co-convener(s) | Prof. Hwa-Lung Yu (National Taiwan University, Taiwan) Prof. Yih-Chi Tan (National Taiwan University, Taiwan) |
| Session Description | In recent years, a number of studies have shown evidences of elevated risks resulting from climate change, hydrological extremes, and human activities, in terms of economic loss, health status degradation, or the changes of environmental and ecological indicators. This session is designed to explore the quantitative or qualitative methods for risk assessment and their applications to determine the economic, health, or ecological risks associated to the climatic, hydrological, and environmental systems and their changes. Contributions are sought that shed light on, but not limited to, the following issues: 1) Complex inter-linkages of hydrological and environmental conditions and their associated consequence risks, including adverse health effects, diseases, changes of ecological services and biodiversity, socioeconomic losses, food and water resources shortages, and flooding and droughts. 2) Quantitative risk assessments of water-related natural disasters, e.g. flooding, drought, water quality, on human health, economic, or ecological risks. 3) Assessment of the impact of climate and environmental change and their associated human and ecological health impacts. 4) Development of climate-sensitive adaptive strategies to changing patterns of water availability and variability using analytical and statistical methods. 5) Modeling tools and methods for risk assessment for hydrological and environmental systems. 6) Understanding uncertainty measures and their effective use concerning the interacting impacts of climate variability, extreme weather conditions, surface and subsurface water resources, and health issues. 7) Scale compatibility of model linkages, particularly in the linking of atmospheric-hydrologic-consequence models. |