A 30 m Global Flood Inundation Model for Any Climate Scenario

• Published in: Water resources research 2024-08, Vol.60 (8), p.n/a
• Main Authors: Wing, Oliver E. J., Bates, Paul D., Quinn, Niall D., Savage, James T. S., Uhe, Peter F., Cooper, Anthony, Collings, Thomas P., Addor, Nans, Lord, Natalie S., Hatchard, Simbi, Hoch, Jannis M., Bates, Joe, Probyn, Izzy, Himsworth, Sam, Rodríguez González, Josué, Brine, Malcolm P., Wilkinson, Hamish, Sampson, Christopher C., Smith, Andrew M., Neal, Jeffrey C., Haigh, Ivan D.
• Format: Article
• Language: English
• Subjects: Ambient noise; Background noise; Climate change; Climate models; Coastal engineering; Computer models; Earth movements; Flood hazards; Flood mapping; Flood probability; Flooding; Floods; Floodwater; Future climates; hydraulic modeling; Impact analysis; Mathematical models; model validation; Rainfall; Risk assessment; River channels; River discharge; River flow; Rivers; Sea level; Uncertainty; Water discharge; Water levels
• ISSN: 0043-1397; 1944-7973
• DOI: 10.1029/2023WR036460

Global flood mapping has developed rapidly over the past decade, but previous approaches have limited scope, function, and accuracy. These limitations restrict the applicability and fundamental science questions that can be answered with existing model frameworks. Harnessing recently available data and modeling methods, this paper presents a new global ∼30 m resolution Global Flood Map (GFM) with complete coverage of fluvial, pluvial, and coastal perils, for any return period or climate scenario, including accounting for uncertainty. With an extensive compilation of global benchmark case studies—ranging from locally collected event water levels, to national inventories of engineering flood maps—we execute a comprehensive validation of the new GFM. For flood extent comparisons, we demonstrate that the GFM achieves a critical success index of ∼0.75. In the more discriminatory tests of flood water levels, the GFM deviates from observations by ∼0.6 m on average. Results indicating this level of global model fidelity are unprecedented in the literature. With an optimistic scenario of future warming (SSP1‐2.6), we show end‐of‐century global flood hazard (average annual inundation volume) increases are limited to 9% (likely range ‐6%–29%); this is within the likely climatological uncertainty of −8%–12% in the current hazard estimate. In contrast, pessimistic scenario (SSP5‐8.5) hazard changes emerge from the background noise in the 2040s, rising to a 49% (likely range of 7%–109%) increase by 2100. This work verifies the fitness‐for‐purpose of this new‐generation GFM for impact analyses with a variety of beneficial applications across policymaking, planning, and commercial risk assessment. Plain Language Summary Computer models use a variety of data and physical equations to estimate the extent and depth of possible flood events. Global applications of these tools have been developed over the past decade, but they are not very good at simulating the behavior of real floods. In this paper, we address some key problems to make a global model that does a lot better than past ones. We apply new techniques to better understand how much water we need to put into the model for a given flood probability. This movement of water is simulated by the model over a more accurate map of the Earth's terrain than has been available previously, with river channels represented in a smarter way. We look at the projected changes in rainfall, river discharge, and sea levels for given l