Leveraging earth observation and inundation models to map frequent to rare flood hazards

Abstract:

Global Flood Models (GFMs) and Earth Observation (EO) play a vital role in characterising flooding, especially in data-sparse, under-resourced regions of the world. Yet, validation studies are often limited to a handful of historic events due to limited data and do not directly assess the ability of these products to assess flood hazard, where flood hazard is the probability that a flood event at a certain frequency will occur in a given location. Therefore great swaths of the globe are left unassessed, meaning it is extremely difficult for stakeholders to decipher the ability of either models or observations to correctly identify flood hazard in their (often) unvalidated region of interest, thus hampering the ability to make timely decisions to mitigate the hazard. In this work, we leverage flood frequency from 20 years of EO (MODIS) data to compare the ability of EO and GFMs to characterise flood hazard from frequent to infrequent, or extreme, flood events. We formulate a method, Flood Expectation Per Pixel, and apply it across four large basins in Africa – Congo, Niger, Nile and Volta representing a variety of biomes. Our approach considers 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 identified that at lower return periods (<20 years), the EO data records less flooding than the GFM, suggesting GFMs overpredict frequent flooding. For return periods between 20-100 years, GFM and EO data show consistency given the uncertainties we consider. For large return periods (>100 years) the EO observations show more flooding than expected given the GFM data, although there are insufficient observations in the EO record and we would thus not expect the data sets to agree. Furthermore, EO record indicates that the GFM can differentiate between flood return periods. Ultimately, we find EO and GFM complement each other and thus should be used in tandem to inform strategies to mitigate floods across the hazard spectrum from frequent to extreme flood events.