Does Subgrid Routing Information Matter for Urban Flood Forecasting? A Multiscenario Analysis at the Land Parcel Scale

Abstract

AbstractThe accessibility of high-resolution surface data enables fine distributed modeling for urban flooding. However, the surface routing processes between nonhomogeneous land cover components remain in most grid units, due to the high spatial heterogeneity of urban surfaces. Limited by the great difficulty in the acquisition, subgrid routing information (SRI) is always ignored in high-resolution urban flood modeling, and more importantly, the potential impacts of missing SRI on flood forecasting are still less understood. In this study, 54 urban-oriented scenarios of subgrid routing schemes are designed at an isolated grid, including three types of land parcels, two routing directions, and nine routing percents. The impacts of missing SRI are evaluated comprehensively under 60 different rainfall scenarios, in terms of the peak runoff (PR) and the runoff coefficient (RC). Furthermore, the influence mechanism is revealed as well to explain the discrepancy of the impacts under different conditions. Results show the missing of the routing process from impervious to pervious areas leads to significant impacts on the simulation of both PR and RC. Overestimated RC is detected, however, the impacts on PR are bidirectional depending on the rainfall intensity. Overestimation of PR due to missing SRI is observed in light rainfall events, but the opposite effect is identified under heavy rainfall conditions. This study highlights the importance of incorporating the SRI for urban flood forecasting to avoid underestimating the hazard risk in heavy rainfall. Simultaneously, it identifies that blindly utilizing infiltration-based green infrastructure is not feasible in urban stormwater management, due to the possible increase in peak runoff.