Spatially coherent flood risk assessment based on long-term continuous simulation with a coupled model chain

<p>Floods affect people worldwide and account for more than USD 100 billion losses on average every year. Hazard, Exposure and Vulnerability are the three components that influence flood risk. Flood Risk Management (FRM) decisions especially, with respect to new flood defense schemes and resilience initiatives are generally taken based on the assessment of impacts for hazard scenarios. Current large-scale studies are comprehensive in terms of sectors covered in impact assessment. However, these studies often deploy generalized data and methods on the model components resulting in coarse risk estimates with low spatial resolution.</p><p>In this study, we use process-based models with 100m resolution on the national scale within a systems approach to develop and simulate a 5000 year flood event catalogue for Germany. The events are then analyzed per economic sector, including residential, commercial and agriculture sectors. The risk chain includes continuous simulation of high-resolution hazard maps, obtained from coupled hydrology and hydraulic models; NUTS3-level exposure asset values further disaggregated to ATKIS land-use data and calibrated object-level vulnerability models that provide high-resolution quantification of economic damage. Spatial dependence of flood events is addressed by the continuous simulation approach. For each model component in the risk assessment (hazard, exposure and vulnerability), uncertainty in data and methods are integrated into the risk predictions. Based on these simulations, we present a sector-wise flood risk assessment for Germany along with the reliability of the risk estimates. This process-based, systemic flood risk assessment is valuable for policy making, adaptation planning and estimating insurance premiums.</p>

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Stochastic Flood Risk Assessment under Climate Change Scenarios for Toronto, Canada Using CAPRA

Water ◽

10.3390/w14020227 ◽

2022 ◽

Vol 14 (2) ◽

pp. 227

Author(s):

Daniela Rincón ◽

Juan Felipe Velandia ◽

Ioannis Tsanis ◽

Usman T. Khan

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Numerical Models ◽

Social Impacts ◽

Climate Change Scenarios ◽

Flood Risk Assessment ◽

Short Term ◽

Modeling Approach

Amongst all natural disasters, floods have the greatest economic and social impacts worldwide, and their frequency is expected to increase due to climate change. Therefore, improved flood risk assessment is important for implementing flood mitigation measures in urban areas. The increasing need for quantifying the impacts of flooding have resulted in the development of methods for flood risk assessment. The aim of this study was to quantify flood risk under climate change scenarios in the Rockcliffe area within the Humber River watershed in Toronto, Canada, by using the Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) method. CAPRA is a platform for stochastic disaster risk assessment that allows for the characterization of uncertainty in the underlying numerical models. The risk was obtained by integrating the (i) flood hazard, which considered future rainfall based on the Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) for three time periods (short-term: 2020–2049, medium-term: 2040–2069, and long-term: 2070–2099); (ii) exposed assets within a flood-prone region; (iii) vulnerability functions, which quantified the damage to an asset at different hazard levels. The results revealed that rainfall intensities are likely to increase during the 21st century in the study area, leading to an increase in flood hazards, higher economic costs, and social impacts for the majority of the scenarios. The highest impacts were found for the climate scenario RCP 8.5 for the long-term period and the lowest for RCP 4.5 for the short-term period. The results from this modeling approach can be used for planning purposes in a floodplain management study. The modeling approach identifies critical areas that need to be protected to mitigate future flood risks. Higher resolution climate change and field data are needed to obtain detailed results required for a final design that will mitigate these risks.

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