Temporal and Spatial Characteristics Analysis of Rainfall in Seoul

Son, Ah-Long; Han, Kun-Yeon; Bae, Sung-Hwan

doi:10.9798/kosham.2013.13.3.083

Cited by 2 publications

(2 citation statements)

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“…In Seoul, which was affected by this, the number of occurrences of more than 30 mm/h of rainfall increased by 2.3 times throughout the year compared to before 1990, and that of more than 50 mm/h of rainfall increased by 5.3 times [35]. In addition, Son et al [35] analyzed that rainfall of 75.0 mm and 15.5 mm/h was observed at the Seodaemun (412) and Dobong (406) observatories in Seoul at 14:00 on 21 September 2010, respectively, showing an approximately 5-fold difference between the two observatories. As such, in terms of the temporal distribution of rainfall, the occurrence frequency of concentrated torrential rains (30 mm/h or more) increases, and the spatial distribution also shows a large deviation due to localized heavy rains.…”

Section: Inducing Factormentioning

confidence: 93%

“…Recently, the frequency of localized torrential rains has been increasing due to climate change [34]. In Seoul, which was affected by this, the number of occurrences of more than 30 mm/h of rainfall increased by 2.3 times throughout the year compared to before 1990, and that of more than 50 mm/h of rainfall increased by 5.3 times [35]. In addition, Son et al [35] analyzed that rainfall of 75.0 mm and 15.5 mm/h was observed at the Seodaemun (412) and Dobong (406) observatories in Seoul at 14:00 on 21 September 2010, respectively, showing an approximately 5-fold difference between the two observatories.…”

Section: Inducing Factormentioning

confidence: 99%

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Detecting Areas Vulnerable to Flooding Using Hydrological-Topographic Factors and Logistic Regression

Lee¹,

Kim²

2021

Applied Sciences

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As a result of rapid urbanization and population movement, flooding in urban areas has become one of the most common types of natural disaster, causing huge losses of both life and property. To mitigate and prevent the damage caused by the recent increase in floods, a number of measures are required, such as installing flood prevention facilities, or specially managing areas vulnerable to flooding. In this study, we presented a technique for determining areas susceptible to flooding using hydrological-topographic characteristics for the purpose of managing flood vulnerable areas. To begin, we collected digital topographic maps and stormwater drainage system data regarding the study area. Using the collected data, surface, locational, and resistant factors were analyzed. In addition, the maximum 1-h rainfall data were collected as an inducing factor and assigned to all grids through spatial interpolation. Next, a logistic regression analysis was performed by inputting hydrological-topographic factors and historical inundation trace maps for each grid as independent and dependent variables, respectively, through which a model for calculating the flood vulnerability of the study area was established. The performance of the model was evaluated by analyzing the receiver operating characteristics (ROC) curve of flood vulnerability and inundation trace maps, and it was found to be improved when the rainfall that changes according to flood events was also considered. The method presented in this study can be used not only to reasonably and efficiently select target sites for flood prevention facilities, but also to pre-detect areas vulnerable to flooding by using real-time rainfall forecasting.

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Section: Inducing Factormentioning

confidence: 93%