午夜欧美大片免费观看,欧美激情综合五月色丁香,亚洲日本在线视频观看,午夜精品福利在线

In recent years, the problem of urban waterlogging is becoming increasingly serious, and urban waterlogging risk assessment is becoming one of the hotspots and challenges in urban waterlogging disaster research. This article takes the main urban area of Chengdu as an example. Meteorological data, geographic information data, socioeconomic statistical data, and waterlogging disaster information are used. The optimal function for estimating precipitation during the return period is selected by comparing multiple commonly used distribution functions. The hourly rainfall pattern in the study area is calculated with the Pilgrim & Cordery method. Then, an improved FloodArea waterlogging model is developed to simulate waterlogging scenarios with a 24hour rainfall period of 20, 30, 50, and 100 years. Based on the revised risk level standards for waterlogging highways and the revised loss curves for property, the levels of waterlogging traffic risk and the risk of indoor property loss for residents are discussed under the 100year return period precipitation scenario. The results show that: (1) The GEV (Generalized Extreme Value) distribution function is the optimal function for estimating precipitation at the return period in the main urban area of Chengdu. The 24hour hourly rainfall pattern in the main urban area of Chengdu presents a bimodal pattern, and the peak appears at the front of the precipitation process. (2) Based on the FloodArea model, the spatial distribution of urban waterlogging can be well simulated by improving the input data or parameters. The simulation results of various precipitation scenarios show that the proportion of waterlogging inundation areas in Gaoxin South Zone, Gaoxin West Zone, and Qingyang District is higher than in other areas. (3) The 24hour 100year rainfall scenario of waterlogging can cause 86.1% of the road length in the main urban area of Chengdu to be difficult to travel. Among them, the length of first level risk roads accounts for 10.5%, and the length of second and third level risk roads accounts for 27.5% and 28.4% respectively, with the highest risk of waterlogging roads in Chenghua District. (4) The potential loss of indoor property caused by waterlogging during a 24hour 100year rainfall scenario accounts for approximately 0.8% of the GDP (Gross Domestic Product) of the main urban area. Wuhou District has the highest risk of property loss, with potential losses accounting for 1.6% of its GDP. The evaluation results can provide support for the prevention and reduction of waterlogging disasters in Chengdu, and the established methods can provide technical reference for urban waterlogging risk assessment.