Proceedings Article | 3 November 2008
KEYWORDS: Floods, Decision support systems, Data modeling, Geographic information systems, Databases, Remote sensing, Control systems, Data communications, Telecommunications, Natural disasters
Flood disaster is one of the most frequently and the biggest natural disasters in the world, and snowmelt floods which break out in spring often bring enormous social and economic loss, especially in arid and semi-arid areas, such as in Northern Tianshan Mountains in Xinjiang, China. Any effective prevention or mitigation of disasters is built on the basis of forecasting, so the real-time processing, snow information analysis, and weather forecasting, are combined into a system which can provide intelligent reports and prewarning information of snowmelt flood duly and accurately for the government departments or other organizations. So it is of great significance for flood prevention and disaster reduction. Furthermore, effective forecasting and prewarning can generate enormous social, economic and ecological benefits, so the establishment of a real-time, efficient and reliable Flood Forecasting/Prewarning DSS, is an important part of the building of non-engineering measures for flood prevention and disaster reduction. Now the integrated applications of remote sensing(RS), geographic information systems(GIS) and global positioning systems(GPS), named "3S" technologies, have been infiltrated through hydrology and water resource management, and there are rapid developments and extensive applications of Decision Support System (DSS) in recent years in many fields. But there is seldom appearance of mature applications of Snowmelt Flood Forecasting/Prewarning DSS, and a shortage of study on effective Snowmelt Flood Forecasting. In this paper, firstly, a Distributed Snowmelt Runoff Model had been built based on the "3S" technologies, and then a Snowmelt Flood Forecasting DSS based on the B/S (Browser server) and J2EE structure had been established, then introduced the T213 Numerical Forecasting Production from WRF mode and revised it with our synchronous field observation data. Various snow information and other basic geoinformation also had been extracted from RS imagines or other data with RS and GIS tools. At last, snowmelt flood based on "3S" technologies and DSS had been forested in the typical study area, Quergou River Basin, which is located in the middle of the Northern Tianshan Mountains, Xinjiang, China, and is contrasted with the latter measured runoff. Good forecasting results had been achieved, and the average accuracy was up to 0.90.
