Deriving global flood hazard maps of fluvial floods through a physical model cascade

Deriving global flood hazard maps of fluvial floods through a physical model cascade
复制标题

DOI:
10.5194/hess-16-4143-2012
复制
发表时间:
2012-11
影响因子:
6.3
通讯作者:
F. Pappenberger;E. Dutra;F. Wetterhall;H. Cloke
F. Pappenberger;E. Dutra;F. Wetterhall;H. Cloke
中科院分区:
地球科学2区
文献类型:
--
作者:
F. Pappenberger;E. Dutra;F. Wetterhall;H. Cloke

文献摘要

被引文献

相似文献

抽象。全球洪水灾害图可用于评估洪水风险的许多不同的应用,包括(再)保险和大规模的洪水准备。这种全球灾害地图可以使用大规模的基于物理的径流和河流路由模型,当与一些后处理方法结合使用时生成。在这项研究中,欧洲中期天气预报中心(ECMWF)的陆面模型耦合到ERA中期再分析气象强迫数据,并将由此产生的径流传递到河流路由算法,模拟洪泛平原和洪水流经全球陆地面积。全球灾害地图是基于30年(1979-2010年)的模拟期。一个Gumbel分布拟合的年最大流量,以获得一些洪水重现期。重现期最初是针对25 × 25 km网格计算的,然后重新投影到1 × 1 km网格上,以获得更高分辨率的地图,并估计单个25 × 25 km单元的淹没部分面积。几个全球和区域的洪水重现期从2到500年的地图。结果比较合理的基准数据集的全球洪水灾害。所开发的方法可应用于全球或区域范围内的其他数据集。
Abstract. Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25 × 25 km grid, which is then reprojected onto a 1 × 1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25 × 25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.