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 will facilitate a more accurate assessment of compound flood risk in the coastal regions. This study employed the Delft3D-Flow Flexible Mesh model to simulate the peak coastal water level, consisting of storm surge, astronomical tide, and the relative sea level rise (RSLR) in Shanghai over 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 astronomic tide is the leading driver to peak water level, followed by the contribution of storm surge. In a longer term, the RSLR has significantly amplified the peak water level. This framework could be applied to other coastal cities which face the similar constraint of unavailable water level records.