@misc{10481/64035,
year = {2020},
month = {9},
url = {http://hdl.handle.net/10481/64035},
abstract = {The floodplains of rivers are relevant living spaces for population globally and provide
favorable locations for economic development. However, these areas are commonly
exposed to floods, and the increasing population together with the changes in storminess
as a result of global warming mean that the risks from flooding are expected to rise. Most
studies investigating the impact that climatic change has on flood risk are based on a
cascade of global climate model simulations coupled with regional climate models,
hydrologic models, inundation models, and flood impact models. However, this
approach is subject to uncertainties. Model results are found to be sensitive to climate
forcing, the structure of the underlying models, the choice of methods used for
downscaling and bias correction, and the use of extreme value analysis for both
current and future climate conditions. Moreover, uncertainties are expected to
propagate through the model cascade. To overcome these problems, we propose a
method for analyzing and mapping the sensitivity of population exposure in floodplains to
changes in flood magnitude. The method is based on downward counterfactuals, namely
perturbations of a selected flood scenario by increasing its magnitude, interpreted in this
case as the worsening of a today’s design flood event as a result of climatic changes. The
increase in the impact of a current design flood compared to its counterfactual illustrates
the sensitivity to changes in hazard. We calculate the normalized gradients of the flood
exposure curves, that is, the increase in the exposure and magnitude of the perturbed
event relative to the exposure and magnitude of the current scenario. We test the
applicability of the method on local, national, and global scale by using existing data
sets, including flood hazard maps, flood protection standards, floodplain delineation, river
network definition, and spatial population distribution. The gradients were found to vary
remarkably across the globe and are overall smaller in the upper range of flood magnitudes
that in the lower range. Based on these results, we compare the drivers of the sensitivity in
different parts of the world and identify river reaches with the highest relative gradients.
These river reaches might be the most affected by climate change and thus deserve an indepth
investigation of the underlying characteristics of the floodplains and the need for
climate change adaptation.},
organization = {Mobiliar Lab for Natural Risks, Oeschger Centre for Climate Change Research, University of Bern},
organization = {European Union (EU)

754446},
organization = {UGR Research and Knowledge Transfer Fund-Athenea},
organization = {University of Granada},
publisher = {Frontiers Media SA},
keywords = {Scenario neutral approach},
keywords = {Climate change},
keywords = {Disaster risk},
keywords = {Projections},
keywords = {Model},
keywords = {Resolution},
keywords = {Framework},
keywords = {Impacts},
keywords = {Variability},
keywords = {Patterns},
title = {Mapping the Sensitivity of Population Exposure to Changes in Flood Magnitude: Prospective Application From Local to Global Scale},
doi = {10.3389/feart.2020.534735},
author = {Zischg, Andreas Paul and Bermúdez Pita, María},
}