Near-Real-Time Flood Forecasting Based on Satellite Precipitation Products
Near-Real-Time Flood Forecasting Based on Satellite Precipitation Products
复制标题
基于卫星降水产品的近实时洪水预报
DOI：
10.3390/rs11030252
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发表时间：
2019-02-01
期刊：
影响因子：
5
通讯作者：
Tan, Yumin
中科院分区：
文献类型：
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作者：
Belabid, Nasreddine;Zhao, Feng;Tan, Yumin
洪水、风暴和飓风对人的生命和农田都是毁灭性的。近实时流量估算是避免洪水灾害损失的关键。流量估算的关键输入是降水量。直接利用地面站测量降水量是不有效的，特别是在暴雨期间，因为即使在同一地区，降水量也是变化的。这种不确定性可能导致洪水流量估计和预测模型的稳健性大大降低。与使用地面站相比，使用卫星降水产品可提供更大范围的暴雨覆盖面和更高频率的降水数据。本文提出了一种新的基于SPPs的NRT洪水预报方法，以减少洪水灾害的应急响应时间，最大限度地减少灾害损失。所提出的方法允许我们预测洪水使用的流量过程线，并使用的结果来映射洪水范围通过引入SPPs到的全径流模型。在这项研究中，我们首先评估的能力，估计洪水流量和洪水范围映射的准确性。比较了两种高时间分辨率的SPP，即全球降水测量综合多卫星反演（IMERG）和热带降水测量使命多卫星降水分析（TMPA）。2017年4月10日至2017年5月10日期间，在加拿大渥太华流域对这两种产品进行了评价。使用TMPA的结果表明，观测流量和模拟流量之间的差异非常显著，高流量条件下的Nash-Sutcliffe效率（NSE）为-0.9241，适应NSE（ANSE）为-1.0048。TMPA为基础的模型没有重现的形状观察到的水文。然而，使用IMERG时，观察到的放电和建模放电之间的差异得到改善，NSE等于0.80387，ANSE为0.82874。此外，基于IMERG的模型可以再现观测到的水文线的形状，主要是在高流量条件下。由于IMERG产品提供更好的准确性，他们被用于洪水范围映射在这项研究中。洪水制图结果表明，与雷达卫星2号在洪水事件期间获得的渥太华河洪水基准观测数据相比，误差大多在一个像素之内。新开发的洪水预报方法的基础上SPPs提供了一个解决方案，洪水灾害管理的降雨测量差或完全无资料的流域。这些研究成果可供NRT洪水预报研究和应用参考。
Floods, storms and hurricanes are devastating for human life and agricultural cropland. Near-real-time (NRT) discharge estimation is crucial to avoid the damages from flood disasters. The key input for the discharge estimation is precipitation. Directly using the ground stations to measure precipitation is not efficient, especially during a severe rainstorm, because precipitation varies even in the same region. This uncertainty might result in much less robust flood discharge estimation and forecasting models. The use of satellite precipitation products (SPPs) provides a larger area of coverage of rainstorms and a higher frequency of precipitation data compared to using the ground stations. In this paper, based on SPPs, a new NRT flood forecasting approach is proposed to reduce the time of the emergency response to flood disasters to minimize disaster damage. The proposed method allows us to forecast floods using a discharge hydrograph and to use the results to map flood extent by introducing SPPs into the rainfall–runoff model. In this study, we first evaluated the capacity of SPPs to estimate flood discharge and their accuracy in flood extent mapping. Two high temporal resolution SPPs were compared, integrated multi-satellite retrievals for global precipitation measurement (IMERG) and tropical rainfall measurement mission multi-satellite precipitation analysis (TMPA). The two products are evaluated over the Ottawa watershed in Canada during the period from 10 April 2017 to 10 May 2017. With TMPA, the results showed that the difference between the observed and modeled discharges was significant with a Nash–Sutcliffe efficiency (NSE) of −0.9241 and an adapted NSE (ANSE) of −1.0048 under high flow conditions. The TMPA-based model did not reproduce the shape of the observed hydrographs. However, with IMERG, the difference between the observed and modeled discharges was improved with an NSE equal to 0.80387 and an ANSE of 0.82874. Also, the IMERG-based model could reproduce the shape of the observed hydrographs, mainly under high flow conditions. Since IMERG products provide better accuracy, they were used for flood extent mapping in this study. Flood mapping results showed that the error was mostly within one pixel compared with the observed flood benchmark data of the Ottawa River acquired by RadarSat-2 during the flood event. The newly developed flood forecasting approach based on SPPs offers a solution for flood disaster management for poorly or totally ungauged watersheds regarding precipitation measurement. These findings could be referred to by others for NRT flood forecasting research and applications.