Suchergebnisse

Abstract. Compound flooding is generated when two or more flood
drivers occur simultaneously or in close succession. Multiple drivers can
amplify each other and lead to greater impacts than when they occur in
isolation. A better understanding of the interdependence between flood
drivers would facilitate a more accurate assessment of compound flood risk
in coastal regions. This study employed the D-Flow Flexible Mesh model
to simulate the historical peak coastal water level, consisting of the storm
surge, astronomical tide, and relative sea level rise (RSLR), in Shanghai
over the period 1961–2018. It then applies a copula-based methodology to calculate the joint probability of peak water level and rainfall during historical
tropical cyclones (TCs) and to calculate the marginal contribution of each
driver. The results indicate that the astronomical tide is the leading driver
of peak water level, followed by the contribution of the storm surge. In the
longer term, the RSLR has significantly amplified the peak water level. This
study investigates the dependency of compound flood events in Shanghai on
multiple drivers, which helps us to better understand compound floods and
provides scientific references for flood risk management and for further
studies. The framework developed in this study could be applied to other
coastal cities that face the same constraint of unavailable water level
records.