Exploiting global variability to anticipate hydrologic extremes

Abstract

Flooding is one of the most common natural hazards, causing disastrous impacts worldwide. Nonetheless, our ability to anticipate what extremes might happen where, and what damage they might cause, is still poor. Stress-testing the global human-Earth system to understand the sensitivity of floodplains and population exposure to a range of plausible conditions is one strategy to identify where future changes to flooding or exposure might be most critical. We first demonstrate that current large scale hydrologic models still struggle to simulate flood peaks and processes adequately. Accounting for this problem, we present a global analysis of the sensitivity of inundated areas and population exposure to varying flood event magnitudes for 1.2 million river reaches. We show that topography and drainage areas correlate with flood sensitivities as well as with societal behaviour. We find clear settlement patterns in which floodplains most sensitive to frequent, low magnitude events, reveal evenly distributed exposure across hazard zones, suggesting that people have adapted to this risk. In contrast, floodplains most sensitive to extreme magnitude events have a tendency for populations to be most densely settled in these rarely flooded zones, being in significant danger from potentially increasing hazard magnitudes given climate change. In a broader context, these examples show that more information can be extracted from currently available data than previously thought.

Bio

Thorsten Wagener is the Alexander von Humboldt Professor for the Analysis of Hydrologic Systems at the University of Potsdam in Germany. He studies hydrologic systems from catchment to global scales using data- and process-based mathematical models. He has made significant contributions to several scientific areas including catchment classification, hydrologic predictions in ungauged basins, and the diagnostic evaluation of Earth system models. His methods and tools for quantifying and attributing uncertainty in mathematical modelling are widely used. He was previously a faculty member at the University of Bristol (UK) and the Pennsylvania State University (USA). He holds a doctorate from Imperial College London (UK) and degrees from TU Delft (NL) and the University of Siegen (D). He is a fellow of the American Geophysical Union and has been given various awards including a Wolfson Research Merit Award from the UK Royal Society, a Walter L. Huber Engineering Research Prize from the American Society of Civil Engineers, and a President’s International Fellowship for Distinguished Scientists from the Chinese Academy of Sciences.