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Open AccessArticle

A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration

1
Department of Civil and Environmental Engineering, Pusan National University, Busan 46241, Korea
2
Department of Civil Engineering, Dongseo University, Busan 47011, Korea
3
Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do 10223, Korea
4
School of Civil Engineering, Chungbuk National University, Cheongju 28644, Korea
*
Author to whom correspondence should be addressed.
Water 2019, 11(9), 1883; https://doi.org/10.3390/w11091883
Received: 4 August 2019 / Revised: 2 September 2019 / Accepted: 6 September 2019 / Published: 10 September 2019
Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). Flood concerns are raised around the world in the events of rain. Flood forecasting, a typical nonstructural measure, was developed to help prevent repetitive flood damage. However, it is difficult to apply flood prediction techniques using training processes because training needs to be applied at every usage. Other techniques that use predicted rainfall data are also not appropriate for small watershed, such as single drainage area. Thus, in this paper, a flood prediction method is proposed by improving four criteria (50% water level, 70% water level, 100% water level, and first flooding of water pipes) in an attempt to reduce flooding in urban areas. The four criteria nodes are generated using a rainfall runoff simulation with synthetic rainfall at various durations. When applying real-time rainfall data, these nodes have the advantage of simple application. The improved flood nomograph made in this way is expected to help predict and prepare for rainstorms that can potentially cause flood damage.
Keywords: improved flood nomograph; flood forecasting; rainfall runoff; flood volume improved flood nomograph; flood forecasting; rainfall runoff; flood volume
MDPI and ACS Style

Choo, Y.M.; Jo, D.J.; Yun, G.S.; Lee, E.H. A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration. Water 2019, 11, 1883.

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