Comparing earth observation and inundation models to map flood hazards
| Autor: | Laurence Hawker, Jeffrey Neal, Beth Tellman, Jiayong Liang, Guy Schumann, Colin Doyle, Jonathan A Sullivan, James Savage, Raphael Tshimanga |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Environmental Research Letters, Vol 15, Iss 12, p 124032 (2020) |
| Druh dokumentu: | article |
| ISSN: | 1748-9326 54716896 |
| DOI: | 10.1088/1748-9326/abc216 |
| Popis: | Global flood models (GFMs) and earth observation (EO) play a crucial role in characterising flooding, especially in data-sparse, under-resourced regions of the world. However, validation studies are often limited to a handful of historic events and do not directly assess the ability of these products to simulate flood hazard—the probability that flooding will occur in a given location. As a result, it is difficult for stakeholders to decipher the ability of either models or observations to identify flood hazard and make decisions to mitigate for flooding. Here, we leverage flood observations from 20 years of MODIS data to compare the recorded flooding with what would be expected given the hazard simulated by a GFM. We devise an approach, Flood Expectation Per Pixel, and apply it across four large basins in Africa—Congo, Niger, Nile and Volta representing a variety of biomes. We estimate the uncertainty of EO to capture flood events due to burned areas, cloud cover and vegetation, incorporating uncertainty estimates when comparing to modelled hazard. We found that at lower return periods (RPs) ( |
| Databáze: | Directory of Open Access Journals |
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