Abstract:To address the complex challenges facing the flood control safety of water-related bridges in the plain tidal river network regions of megacities under the context of global climate change and land subsidence, which aims to construct a set of scientific flood control identification system and dynamic early warning mechanism that integrates hydrological statistics with refined hydrodynamic simulation. Based on the long-sequence measured hydrological data of Shanghai from 1995 to 2024, which have been strictly corrected for ground subsidence, and combined with the characteristics of controlled reciprocating water flow in the river network and dense bridges, the MIKE11 one-dimensional river network hydrodynamic model is introduced to focus on the water-blocking effect of bridge structures. The focus is on utilizing the coupling of the energy equation and the momentum equation to deduce the local water backwater process of the narrowed section of the bridge, achieving dynamic and precise simulation of the water level rise in front of the bridge under complex non-constant current conditions (tidal superposition flood). Based on the simulation results, a radar automatic water level monitoring and early warning system is established. Application verification demonstrates that the inclusion of the local backwater effect significantly improves the calculation accuracy of the characteristic water level and effectively solves the problem of precisely calculating the water level of the controlled river network, which provides an important scientific basis for enhancing the flood control resilience of urban transportation infrastructure.
