Flood detection using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and extreme precipitation data

[摘要] A complete global flood event record would aid researchers toanalyze the distribution of global floods and, thus, better formulate andmanage disaster prevention and reduction policies. This study used Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and precipitation data combined withhigh-frequency filtering, anomaly detection and flood potential indexmethods to successfully extract historical flood days globally between 1 April 2002 and 31 August 2016; these results were then further compared and validated with Dartmouth Flood Observatory (DFO) data, Global Runoff DataCentre (GRDC) discharge data, news reports and social media data. Theresults showed that GRACE-based flood days could cover 81 % of the floodevents in the DFO database, 87 % of flood events extracted by MODIS andsupplement many additional flood events not recorded by the DFO. Moreover,the probability of detection greater than or equal to 0.5 reached 62 %among 261 river basins compared to flood events derived from the GRDCdischarge data. These detection capabilities and detection results are bothgood. Finally, we provided flood day products with a 1 ∘ spatialresolution covering the range between 60 ∘  S and 60 ∘  N from 1 April 2002 to 31 August 2016; these products can be obtained from https://doi.org/10.5281/zenodo.6831384 (Zhang et al., 2022b). Thus, this research contributes a data foundation forthe mechanistic analysis and attribution of global flood events.

[学科分类] 眼科学