Abstract
Flood prediction is difficult in urban areas because only sparse gauge data and radar data of low accuracy are usually used to analyze flooding and inundation. Sub-basins of urban areas are extremely small, so rainfall data of high spatial resolution are required for analyzing complex drainage systems with high spatial variability. This study aimed to produce three types of quantitative precipitation estimation (QPE) products using rainfall data that was derived from 190 gauges, including the new high-density rain-gauge network operated by the SK Planet company, and the automated weather stations of the Korea Meteorological Administration, along with weather radar data. This study also simulated urban runoff for the Gangnam District of Seoul, South Korea, using the obtained QPE products to evaluate hydraulic and hydrologic impacts according to three rainfall fields. The accuracy of this approach was assessed in terms of the amount and spatial distribution of rainfall in an urban area. The QPE products provided highly accurate results and simulations of peak runoff and overflow phenomena. They also accurately described the spatial variability of the rainfall fields. Overall, the integration of high-density gauge data with radar data proved beneficial for quantitative rainfall estimation.
Highlights
Recent climate change and abnormal weather phenomena have resulted in increased occurrences of localized torrential rainfall in South Korea, including urban areas
The QPE1 product was derived using the Kriging method, with a combination of the Korea Meteorological Administration (KMA) and SK Planet (SKP) rain-gauge networks, the QPE2 product was derived from the Gwangdeok weather radar rainfall estimate using the Marshall-Palmer equation, and the QPE3 product was derived from all 190 rain gauges using the conditional merging method with the weather radar data
The quantitative accuracy of QPE2, which quantitative accuracy of QPE2, which was only using weather radar data, was found to be was only using weather radar data, was found to be underestimated when compared with the values underestimated when compared with the values that were derived from the ground gauge data
Summary
Recent climate change and abnormal weather phenomena have resulted in increased occurrences of localized torrential rainfall in South Korea, including urban areas. The urban hydrological environment has changed in relation to precipitation, in terms of reduced concentration time, decreased storage rate, and increased peak discharge. These changes have altered and increased the severity of damage to urban areas. The notable recent Seoul floods in 2010 and 2011 are examples of such disasters [1]. Extensive research has been conducted on urban flood forecasting using only point rain gauges; this approach is inadequate for developing efficient disaster prevention measures, as such gauges, can not detect the spatial variations in rainfall [2].
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