A METHOD FOR RECOGNIZING RAINFALL-SENSITIVE URBAN ROADS BASED ON TRAJECTORY DATA

Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization schemes in the Weather Research and Forecasting (WRF) model.

Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-hit bodies during an event, and thus it cannot satisfy the increasingly elaborate modeling and management of urban floods. In this study, a comprehensive method was proposed to simulate dynamic exposure to urban flooding considering human mobility. Several scenarios, including diverse flooding types and various responses of residents to flooding, were considered.