Methods for Constructing a Refined Early-Warning Model for Rainstorm-Induced Waterlogging in Historic and Cultural Districts

Abstract

Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts’ waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing’s historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of “1 h rainfall intensity water logging index” and “the waterlogging risk index in historical and cultural districts” were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts.

Analyzing the Mitigation Effect of Urban River Channel Flood Diversion on Waterlogging Disasters Based on Deep Learning

“…Constructing an urban waterlogging warning model is an effective measure for reducing losses from waterlogging disasters. Against the background of increasing impermeable surfaces in urban areas, a warning model is required to achieve both rapid prediction speed and good prediction accuracy [23][24][25]. Given the concentration of populations in urban areas (such as the population on both sides of the Jinshui River in the study area), untimely or inaccurate warnings of waterlogging disasters may lead to severe property damage and casualties.…”