2020
DOI: 10.3389/feart.2020.534735
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Mapping the Sensitivity of Population Exposure to Changes in Flood Magnitude: Prospective Application From Local to Global Scale

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Cited by 15 publications
(10 citation statements)
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“…But in comparison, local scales such as in controlled communities, can measure accurate data of multiple variables (including precipitation, climate change variations, traffic data etc.) with high resolution; thus, generating flood modeling maps for determining resilience with greater accuracy (Zischg and Bermúdez, 2020). Rapid urbanization and increases in population have led to uncertainties in flood risk assessment like impacts in temporal and spatial variability, model formulation, and parameter estimation, which are difficult to quantify (Ahmad and Simonovic, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…But in comparison, local scales such as in controlled communities, can measure accurate data of multiple variables (including precipitation, climate change variations, traffic data etc.) with high resolution; thus, generating flood modeling maps for determining resilience with greater accuracy (Zischg and Bermúdez, 2020). Rapid urbanization and increases in population have led to uncertainties in flood risk assessment like impacts in temporal and spatial variability, model formulation, and parameter estimation, which are difficult to quantify (Ahmad and Simonovic, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…Floodplains and the species dependent on them are sensitive to the frequency, timing, duration, and intensity of floods (e.g., Takata et al 2017;Zischg and Bermúdez 2020). Climate change alters the timing and duration of inundation.…”
Section: Floodplainmentioning
confidence: 99%
“…This allows for a comparison of methods delineating flood-prone zones, rather than a comparison of underlying terrain model performance. Furthermore, JRC and GAR have been in high demand in flood exposure studies (Alfieri et al, 2017;Ehrlich et al, 2018;UNISDR, 2015;Zischg and Bermúdez, 2020), and included in previous inter-model comparison and validation studies (Aerts et al, 2020;Bernhofen et al, 2018;Trigg et al, 2016). The GAR model has also been referred to by previous literature as the CIMA-UNEP model (Bernhofen et al, 2018;Trigg et al, 2016 The model structure of JRC and GAR differs in the sense that GAR builds upon one-dimensional hydraulic modelling, while JRC builds upon two-dimensional hydrodynamic modelling (Dottori et al, 2016;CIMA Foundation, 2015).…”
Section: Flood Mapsmentioning
confidence: 99%