Preprints
https://doi.org/10.5194/nhess-2022-248
https://doi.org/10.5194/nhess-2022-248
 
04 Oct 2022
04 Oct 2022
Status: this preprint is currently under review for the journal NHESS.

Modeling compound flood risk and risk reduction using a globally-applicable framework: A case study in the Sofala region

Dirk Eilander1,2, Anaïs Couasnon1,2, Frederiek C. Sperna Weiland2, Willem Ligtvoet3, Arno Bouwman3, Hessel C. Winsemius2, and Philip J. Ward1 Dirk Eilander et al.
  • 1Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  • 2Deltares, Delft, The Netherlands
  • 3PBL Netherlands Environmental Assessment Agency (PBL), The Hague, The Netherlands

Abstract. In low-lying coastal areas floods occur from (combinations of) fluvial, pluvial, and coastal drivers. If these flood drivers are statistically dependent, their joint likelihood might be misrepresented if dependence is not accounted for. However, few studies have examined flood risk and risk reduction measures while accounting for so-called compound flooding. We present a globally-applicable framework for compound flood risk assessments using combined hydrodynamic, impact and statistical modeling and apply it to a case study in the Sofala province of Mozambique. The framework broadly consists of three steps. First, a large stochastic event set is derived from reanalysis data, taking into account co-occurrence and dependence between all flood drivers based on a vine copula structure. Then, both flood hazard and impact are simulated for different combinations of drivers at non-flood and flood conditions. Finally, the impact of each stochastic event is interpolated from the simulated events to derive a complete flood risk profile. Our case study results show that from all drivers, coastal flooding causes the largest risk in the region despite a more widespread fluvial and pluvial flood hazard. Events with return periods larger than 25 year are more damaging when considering the observed statistical dependence compared to independence, e.g.: 12 % for the 100-year return period. However, the total compound flood risk in terms of expected annual damage is only 0.55 % larger. This is explained by the fact that for frequent events, which contribute most to the risk, limited physical interaction between flood drivers is simulated. We also assess the effectiveness of three measures in terms of risk reduction. For our case, zoning based on the 2-year return period flood plain is as effective as levees with a 10-year return period protection level, while dry proofing up to 1 m does not reach the same effectiveness. As the framework is based on global datasets and is largely automated, it can easily be repeated for many other regions for first order assessments of compound flood risk.

Dirk Eilander et al.

Status: open (until 12 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-248', Anonymous Referee #1, 07 Nov 2022 reply
  • RC2: 'Comment on nhess-2022-248', Anonymous Referee #2, 05 Dec 2022 reply

Dirk Eilander et al.

Dirk Eilander et al.

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Short summary
We present a globally-applicable framework for compound flood risk assessments using combined hydrodynamic, impact and statistical modeling. Our results show the importance of accounting for compound events in risk assessments. We also show how the framework can be used to assess the effectiveness of different risk reduction measures. As the framework is based on global datasets and is largely automated, it can easily be applied in other areas for first-order assessments of compound flood risk.
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