Uncertainties in coastal flood risk assessments in small island developing states

Matteo U Parodi,Alessio Giardino,Stuart G Pearson,Jeremy D Bricker,Ad J H M Reniers,Ap Van Dongeren

doi:10.5194/nhess-20-2397-2020

Matteo U Parodi, Alessio Giardino + Show 4 more

Open Access

https://doi.org/10.5194/nhess-20-2397-2020

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Abstract

Abstract. Considering the likely increase in coastal flooding in small island developing states (SIDSs) due to climate change, coastal managers at the local and global levels have been developing initiatives aimed at implementing disaster risk reduction (DRR) and adaptation measures. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which in the case of insular states are often subject to input uncertainty. We analysed the impact of a number of uncertain inputs on coastal flood damage estimates: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models, and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with a direct impact model (Delft-FIAT) for a case study of a number of villages on the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDFs) and digital elevation models (DEMs) dominate the overall damage estimation uncertainty. When introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive uncertainty in CFR assessments in SIDSs. The findings of this research can help to prioritize the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

Highlights

Small island developing states (SIDSs) are increasingly under threat of coastal flooding, hindering the growth of their economies and challenging the safety of their societies (OECD World Bank, 2016)
We considered the following scenario as the “baseline”: offshore extreme sea level (ESL) described by the 50th percentile of storm surge, Hs and sea level rise (SLR), the locally measured bathymetry, the digital elevation models (DEMs) derived by unmanned aerial vehicle (UAV) aerial imagery, the depth damage functions (DDFs) developed for São Tomé and Príncipe, and the “business as usual” Shared Socioeconomic Pathways (SSPs) 3
This study aims to better understand uncertainty of input data in coastal flood risk (CFR) in small island developing states (SIDSs)

Summary

Introduction

Small island developing states (SIDSs) are increasingly under threat of coastal flooding, hindering the growth of their economies and challenging the safety of their societies (OECD World Bank, 2016). The consequences that they will face due to climate-change-induced coastal flooding may overwhelm their intrinsic resilience. Sea level rise (SLR) will exacerbate the impacts and frequency of coastal hazards for many islands around the world (Storlazzi et al, 2018; UN-OHRLLS, 2015) This situation has recently led to initiatives (e.g. Small Island States Resilience Initiatives SISRI by the World Bank) aiming to increase the resilience of insular communities by using robust coastal flood risk (CFR) assessments using hydrodynamical models as a necessary first step to develop sustainable adaptation strategies. To estimate the overall CFR, damage assessments for every possible coastal flood event must be performed

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