ABSTRACT
Natural variations in the global climate are governed by complex interactions among the atmosphere, oceans, and land cover. Modern climate models suggest that these variations will continue, but with larger magnitudes and greater variability due to human influences. This is expected to increase the risk of flood disaster events. To improve flood risk management, a flood decision support system architecture is proposed that capitalizes on the latest advances in remote sensing, geographic information systems, hydrologic models, numerical weather prediction, information technology, and decision theory. Specifically, the dynamic climate prediction system developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences, is discussed in the context of flood management and planning in the Yangtze River valley, China.
