Analysis of Relationship Between Short-Duration Heavy Rainfall Water Eepth on Metropolitan Area - A Case Study of Taoyuan City, Taiwan

The Taoyuan area is located at 121.38 degrees east longitude and 24.51 degrees north latitude in northwestern Taiwan. Because of the impact of global climate change, typhoon flood events have become increasingly serious in recent years, and short-duration heavy rainfall events more frequently occur in Taiwan. The temporal and spatial distribution of heavy rainfall events in this area cannot be accurately predicted. Therefore, the basic analysis of hydrological system for the Taoyuan area is necessary. Meteorological research and data collection based on water regime are conducted in terms of the analysis of extreme hydrological events of short-duration heavy rainfall. Under the collaborative operation of hydrological technicians and disaster prevention personnel, the prediction of the impact of rainfall distribution and duration on flooding is unified to achieve the effects of disaster reduction and avoidance in the metropolitan area. This project is aimed at Jianguo Park, Fufeng Bridge Rainfall Station and Da'an Guoxiao Rainfall Station; Kanding Road 1507 Lane Water Level Station and Fufeng Bridge Rainfall Station were used for water level-rainfall analysis. Relevant data shows that it is reasonable to temporarily use the water depth-rainfall relationship between the Jianguo Park Water Level Station and the Da'an Guoxiao Rainfall Station as the basis for estimating the water depth of Jianguo Park. Since the water level station of Lane 1507 of Kanding Road is only adjacent to the Fufengqiao rainfall station, it is reasonable to analyze the relationship between the water depth and rainfall of the two. In addition, after excluding extreme values, the R2 of the water level station in Jianguo Park or Lane 1507 of Kanding Road and its corresponding rainfall station have been improved. However, the current rainfall and water depth data are still insufficient, which has a huge impact on the error of statistical regression. In the future, it is still necessary to continue to import updated data, but continue to discuss and establish standards and thresholds for eliminating extreme values, hoping to make relevant research and analysis data more complete.