The credibility challenge for global fluvial flood risk analysis
The credibility challenge for global fluvial flood risk analysis
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DOI：
10.1088/1748-9326/11/9/094014
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发表时间：
2016-09
影响因子：
6.7
通讯作者：
M. Trigg;C. Birch;J. Neal;P. Bates;Andrew Smith;C. Sampson;Dai Yamazaki;Y. Hirabayashi;F. Pappenberger;E. Dutra;P. Ward;H. Winsemius;P. Salamon;F. Dottori;R. Rudari;M. Kappes;A. Simpson;G. Hadzilacos;T. Fewtrell
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文献类型：
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作者：
M. Trigg;C. Birch;J. Neal;P. Bates;Andrew Smith;C. Sampson;Dai Yamazaki;Y. Hirabayashi;F. Pappenberger;E. Dutra;P. Ward;H. Winsemius;P. Salamon;F. Dottori;R. Rudari;M. Kappes;A. Simpson;G. Hadzilacos;T. Fewtrell
量化洪水风险是复原力规划、应急响应和缓解措施(包括保险)的重要组成部分。传统上是在集水区和国家范围内进行的，最近加强了评估全球洪水风险的努力，以便更好地做出一致和公平的决策。全球洪水风险模型现在已经成为现实，这要归功于数值算法、全球数据集、计算能力和耦合建模框架的改进。这些模型的输出对于全球洪水风险的一致量化和预测气候变化的影响至关重要。然而，这些任务的紧迫性意味着，产出一旦可用，在对这些方法进行充分测试之前就已投入使用。为了解决这一问题，我们比较了来自六个全球模型的非洲多概率洪水风险地图，发现它们在洪水风险、经济损失和暴露人口估计方面存在巨大差异，这对模型的可信度具有严重影响。虽然洪水范围有30%-40%的一致性，但我们的结果表明，即使在大陆尺度上，不同模型在危险程度和空间格局上也存在显著差异，特别是在三角洲、干旱/半干旱地区和湿地。这项研究是朝着更好地理解全球洪灾模型迈出的重要一步，而全球洪灾模型是当前风险和气候变化预测迫切需要的。
Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%–40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.