The Weifang City Flood And Waterlogging Disaster Loss Evaluation Method Research Baseb On GIS

As the rising of global climate change, extreme weather events are too frequenctly. The happening of rainstorm flood frequency is the higest than the other meteorological disasters. It caused great losses of lives and property to human society, and restricted the sustainable development of social economic. The disaster loss assessment of rainstorm flood can provide important basis for setting flood control and disaster relief decisions. It is a basic work and effective way of disaster prevention and mitigation, has the very vital significance.By using GIS technology, realized spatialization technology of population and GDP and simulated respectively evaluation index of33rainstorm floods process in Weifang. The loss rate of direct economic and agricultural economic model can be built based on comprehensive evaluation index. A process of rainstorm flood in August10,2007can be choosed as an example to estimate loss in Weifang, and through compare with statistics data of disaster loss to analysis the error. Research results show that:(1) Simulation to obtain the spatial distribution of population and GDP spatial resolution of100×100meter, the simulation results can reflect the spatial distribution trend of social and economic data, and Conform to the reality.(2) It has a better index of correlation between rainstorm flood evaluation index and rate of direct economic loss, the correlation coefficient is0.872.On the other hand, It has linear relationship between rainstorm flood evaluation index and rate of agriculture economic loss, the correlation coefficient is0.842. So the model of direct economic loss rate and agricultural economic loss rate can be built.(3) A disaster process loss assessment in Weifang by using the loss evaluation model and social economic spatial data, it obtains special distribution of direct economic losse and agricultural economic loss with spatial resolution of100×100meters. The result of evaluation in accord with actual disaster statistics, and the errors are within a reasonable range, the evaluation results reliable.