北京地区城市暴雨积涝灾害风险预评估

该文提出自下而上的城市暴雨积涝灾害风险定量评估方法，即在三级评估指标体系下，由下级指标综合核算上级指标系数。在第2级指标计算中，风险区划的危险性指数由历史降水量资料推算得出，风险预警则用实况及预报降水量来计算致灾因子危险性指数；暴雨敏感性指数综合叠加地形、不透水地表因子及河网密度得出；暴雨积涝的风险暴露因子侧重地均人口密度、地均GDP及重点防汛指标等因子，着重于城市地区人口、经济、防汛重点目标的暴露程度。然后在危险性、敏感性及暴露性指数的基础上叠加得出积涝风险指数。通过对比发现，得到的风险区划结果与2004—2008年北京地区暴雨积涝的历史灾情基本吻合。最后，选用北京2011年“6.23”暴雨作风险预警的实例应用检验及分析，结果表明:采用自下而上的快速风险评估结果与积涝的实际发生情况较为接近，无论是风险变化趋势还是风险区域分布情况均与当天的积涝发生情况基本吻合。即该方法能较为准确、快捷地圈定城市地区各级风险区域，能较好地满足风险评估、区划及风险预警的要求。

The Pre event Risk Assessment of Beijing Urban Flood

A three level index system for urban flood risk assessment is put forward, in which higher level indexes of the system can be calculated from lower level indexes following a bottom to up deducing rule. The possibility estimation of risk zoning can be conducted in two ways. The first way is based on historical data. 100 extreme storms in study areas are selected from historical storm data, and then the precipitation of these rainstorms in the area are interpolated for 100 times, followed by summing up risk values of these storm events for each grid cell. The second way is based on observation and forecasting precipitation data. Sensitive indexes are determined by evaluating the effects of land surface topography, impervious surface area and river network on flood formation. The sensitive index of topography is obtained by considering land relief and elevation in each grid cell, and the measurement transforms land topographical characteristics into flood risk sensitivity. Impervious surface also plays an important role in flood formation since it greatly reduces water infiltration, quickens stream flow peaks, and increases storm flow. On the other hand, population density and GDP per square kilometer as well as distribution of critical areas for flood controlling are indicators for exposure in the flood risk analysis. As a result, the comprehensive flood risk indexes have been deduced by integrating the estimated second level indexes (the precipitation index, the sensitive index and the exposure index). The application of the flood risk zoning with the bottom to up assessment method indicates that the risk zoning areas can be promptly accomplished by this way, estimating the distribution of actual risk areas properly. Meanwhile, it is found that the flood risk in urban is higher than that of rural and suburb, because the urban is flat in topography with much larger areas with impervious surface, and its population and economic entities are more heavily aggregated, and the rainstorm possibility is greater in urban with the analysis of the rainstorm historical data. Referring to the historical loss data of rainstorm floods occurring from 2004 to 2008 in Beijing, it has also been demonstrated that the result is consistent. Application of the model for risk warning is further validated with a storm event happened on 23 June 2011 in Beijing. In this case, quantity precipitation estimation (QPE) is used to estimate flood risk index, combined with the bottom to up assessment framework to estimate potential flood risk. Results of this application suggest that the bottom to up quick risk assessment fits the actual risk condition very well. Besides risk zoning and assessing, it can also be used to provide quickly processed products for flash flood risk warning.