Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management.

The shear velocity and friction coefficient for representing the resistance of flow are key factors to determine the flow characteristics of the open-channel flow. Various studies have been conducted in the open-channel flow, but many controversies remain over the form of equation and estimation methods. This is because the equations developed based on theory have not fully interpreted the friction characteristics in an open-channel flow. In this paper, a friction coefficient equation is proposed by using the entropy concept. The proposed equation is determined under the rectangular, the trapezoid, the parabolic round-bottomed triangle, and the parabolic-bottomed triangle open-channel flow conditions. To evaluate the proposed equation, the estimated results are compared with measured data in both the smooth and rough flow conditions. The evaluation results showed that R (correlation coefficient) is found to be above 0.96 in most cases, and the discrepancy ratio analysis results are very close to zero. The advantage of the developed equation is that the energy slope terms are not included, because the determination of the exact value is the most difficult in the open-channel flow. The developed equation uses only the mean velocity and entropy M to estimate the friction loss coefficient, which can be used for maximizing the design efficiency.

The annual average rainfall in Busan area is increasing, causing frequent flooding of Busan’s Suyeong and Oncheon rivers. Due to the increase in urbanized areas and climate change, it is difficult to reduce flood damage. Therefore, new methods are needed to reduce urban inundation. This study models the effects of three flood reduction methods involving Oncheon River, Suyeong River, and the Hoedong Dam, which is situated on the Suyeong. Using EPA-SWMM, a virtual model of the dam and the rivers was created, then modified with changes to the dam’s height, the installation of a floodgate on the dam, and the creation of an underground waterway to carry excess flow from the Oncheon to the Hoedong Dam. The results of this study show that increasing the height of the dam by 3 m, 4 m, or 6 m led to a 27%, 37%, and 48% reduction in flooding, respectively, on the Suyeong River. It was also found that installing a floodgate of 10 × 4 m, 15 × 4 m, or 20 × 4 min the dam would result in a flood reduction of 2.7% and 2.9%, respectively. Furthermore, the construction of the underground waterway could lead to an expected 25% flood reduction in the Oncheon River. Measures such as these offer the potential to protect the lives and property of citizens in densely populated urban areas and develop sustainable cities and communities. Therefore, the modifications to the dam and the underground waterway proposed in this study are considered to be useful.

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.

Korea experiences increasing annual torrential rains owing to climate change and river flooding. The government is expanding a new drainage pump station to minimize flood damage, but the river level has not been adjusted because of torrential rains. Therefore, the river level must be adjusted to operate the drainage pump station, and it can be adjusted through the reservoir of the drainage pump station. In this study, we developed a method for operating drainage pump stations to control the river level and verify the effectiveness of the proposed method. A stormwater management model (SWMM) was used to simulate the Suyeong River and Oncheon River in Busan, Korea. The rainfall data from 2011 to 2021 were investigated. The data were sorted into ten big floods that occurred in Busan. The model was calibrated with actual rainfall data. The water level of the Suyeong River and the Oncheon River was the highest in most simulations. The simulation results showed an average decrease of 3018.2 m³ in Suyeong River flooding, and the Oncheon River needed to be supplemented due to structural problems. As a result of the recombination by simply supplementing the structural problems of the Oncheon River, the average flooding of 194.5 m³ was reduced. The proposed method is economical and efficient for reducing urban stream flooding in areas susceptible to severe damage caused by climate change.

In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management.