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Because of their enclosed nature, underground spaces are more vulnerable to flooding than above-ground structures. As a result, flooding disasters have the potential to cause widespread casualties. Major domestic plan manuals such as ‘Waterproof Standards Plan Manual for Underground Space Flood Prevention’ suggest that the expected flood height is determined and measures are established to ensure safety for underground facilities located in areas where flooding is expected, but no clear methods and standards are presented. In this study, an inundation prediction chart was prepared by performing a one-dimensional (EPA-SWMM) model analysis using the probability rainfall, respectively. Then, data on the depth of inundation where the underground facility is located were extracted using a two-dimensional (FLO2D) model analysis. Using inundation depth and weather data, the probability of inundation for underground facilities and the expected inundation height were quantitatively evaluated through @RISK. Based on the quantitative assessment, it was determined that there was a 7.7% possibility of inundation in an underground space in the case of a 2 h time frame (average inundation depth: 0.1557 m), and a 13.3% possibility in the case of a 3 h time frame (average inundation depth: 0.1655 m). It would be possible to contribute to the development of countermeasures and manuals for underground space flooding using the quantitative assessment described above.

In recent years, the frequency of flooding damage has increased owing to torrential rains caused by abnormal weather and rising sea levels, which can be attributed to global warming. In particular, in the case of low-tide rivers, when a high tide and critical rainfall occur simultaneously, the flood damage will increase due to the increased external water level. The establishment of a disaster prevention plan through a simulation of existing inequality streams may be suitable for general rivers; however, it is inadequate for considering the effects of tide changes over time, such as those in a reduced tide stream. Therefore, in this study, an optimal operation plan is formulated based on unsteady flow simulations in regions where a large number of hydraulic facilities are installed, and an optimal river management plan is derived for the flood season. For the Ara Waterway (Ara Stream) and Gulpo Stream managed by the Korea Water Resources Corporation, various hydraulic facilities (weir, inverted syphon, etc.) are operated in conjunction with the West Sea to mitigate the continuous flood damage. In that context, a West Sea drainage gate has been installed. Correspondingly, it is necessary to optimize the flood exclusion capacity by deriving an optimal operation plan because it directly affects the water level in hydraulic facilities such as the Right No. 1, Left No. 1, and flood gates, which are the most important drainage structures for the Gulpo Stream operation. Herein, through a trial-and-error method, an optimal operation plan is derived to reduce the flood frequency in the Ara Waterway and Gulpo Stream.

Korea’s river design standards set general design standards for river and river-related projects in Korea, which systematize the technologies and methods involved in river-related projects. This includes measurement methods for parts necessary for river design, but do not include information on shear stress. Shear Stress is to one of the factors necessary for river design and operation. Shear stress is one of the most important hydraulic factors used in the fields of water especially for artificial channel design. Shear stress is calculated from the frictional force caused by viscosity and fluctuating fluid velocity. Current methods are based on past calculations, but factors such as boundary shear stress or energy gradient are difficult to actually measure or estimate. The point velocity throughout the entire cross section is needed to calculate the velocity gradient. In other words, the current Korea’s river design standards use tractive force, critical tractive force instead of shear stress because it is more difficult to calculate the shear stress in the current method. However, it is difficult to calculate the exact value due to the limitations of the formula to obtain the river factor called the tractive force. In addition, tractive force has limitations that use empirically identified base value for use in practice. This paper focuses on the modeling of shear stress distribution in open channel turbulent flow using entropy theory. In addition, this study suggests shear stress distribution formula, which can be easily used in practice after calculating the river-specific factor T. and that the part of the tractive force and critical tractive force in the Korea’s river design standards should be modified by the shear stress obtained by the proposed shear stress distribution method. The present study therefore focuses on the modeling of shear stress distribution in open channel turbulent flow using entropy theory. The shear stress distribution model is tested using a wide range of forty-two experimental runs collected from the literature. Then, an error analysis is performed to further evaluate the accuracy of the proposed model. The results revealed a correlation coefficient of approximately 0.95–0.99, indicating that the proposed method can estimate shear stress distribution accurately. Based on this, the results of the distribution of shear stress after calculating the river-specific factors show a correlation coefficient of about 0.86 to 0.98, which suggests that the equation can be applied in practice.

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.

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.

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.

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.

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.

Manning’s roughness coefficient is one of the most important parameters in establishing the plan, design, operation, and maintenance of the water resource projects for hydraulic engineers, and since the worth of this value has a significant effect on the analysis of the water level and flow rate distribution, it is very important to carry out the calculation of flood stage, design of the stream/river structure, and safety assessment of the stream. Due to the importance of these factors, the calculation of objective and quantitative roughness coefficient has long drawn attention from researchers at home and abroad. Many studies have been conducted to estimate the roughness coefficient based on the actual measurements for various types of streams, such as gravel and sand streams, and many others have produced experience equation for various levels of materials and relative depth. Despite many of these efforts, the roughness coefficient uses constant values when applied to the actual model or real design. This application is a major source of error in simulating flood and unsteady flow. To solve these problems, good results were obtained by attempting to calculate the roughness coefficient applied with the entropy concept in open-channel flow. In particular, the proposed roughness coefficient based on the measurements taken from laboratories under conditions showed very similar to the actual stream flow which was found to be about the same as the value from the unsteady flow. Accordingly, the newly developed roughness coefficient equation, which is the result of this study, is a very practical one formula that can be applied to the flood flow of real natural streams. It can also be used as an alternative to make up for the disadvantages of the Manning’s roughness coefficient.

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.

In fluid mechanics, the shear stress is calculated from the frictional force caused by viscosity and fluctuating velocity. Shear stress equations are used widely because of their simplicity. On the other hand, they have a critical limitation of requiring an energy gradient, which is generally difficult to estimate in practice. In particular, measuring the shear stress and velocity gradient on the boundary layer is difficult. The point velocity throughout the entire cross section is needed to calculate the velocity gradient. This study proposes the shear stress distribution equations for laminar flow based on entropy theory using the mean velocity and entropy coefficient. The proposed equations were compared with the measured shear stress distribution using Nikuradse’s data. The results revealed a correlation coefficient of approximately 0.99, indicating that the proposed method fits the Nikuradse’s data. Therefore, the shear stress distribution can be estimated easily and accurately using the proposed equations, which can be used in future for the management and design of a water pipeline.

The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.

World is experiencing abnormal weather caused by urbanization and industrialization increasing greenhouse gas and one of these phenomenon domestically happening is flood and drought. The increase of green-house gases is due to urbanization and industrialization acceleration which are causing abnormal climate changes such as the El Nino and a La Nina phenomenon. It is expected that there will be many difficulties in water management, especially considering the topography and seasonal circumstances in Korea. Unlike in the past, a variety of water conservation initiatives have been undertaken like the river-management flow and water capacity expansion projects. To meet the increasing demand for water resources, new environmentally-friendly small and medium-sized dams have been built. Therefore, the development of a new paradigm for water resources management is essential. This study shows that additional security is needed for potential water resources through diversion tunnels and is very important to consider for future water supplies and situations. Using RCP 6.0 and RCP 8.5 in representative concentration pathway climate change scenario, specific hydrologic data of study basin was produced to analyze past observed basin rainfall tendency which showed both scenario 5%~9% range increase in rainfall. Through sensitivity analysis using objective function, population in highest goodness was 1000 and cross rate was 80%. In conclusion, it is expected that the results from this study will help to make long-term and stable water supply plans by using the potential water resource evaluation model which was applied in this study.

Discharge is an important factor in river design for water utilization, water control and hydraulic structures; therefore, an accurate estimation of the discharge is required. At present, a rating curve depicting the relationship between a stage and discharge is used to calculate the discharge from river systems. Although the rating curve has an advantage in that it can predict and use the discharge during the flood season in which the measurement is difficult, there is room for improvement as it does not reflect the hydraulic characteristics of rivers. Therefore, in this study, discharge was predicted using the convenient calculation method with empirical mediating variables of the Manning and Chezy equations which were proposed by the author’s previous research as a new methodology for estimating discharge in an open channel. This was proven, based on the data measured in a meandering open channel system in a lab at the Mississippi River in the US and at the Columbia Del Dique Canal, and an accuracy level at a coefficient of 0.8 was demonstrated. Thus, this method, which reflects the hydraulic characteristics and predicts the discharge in a simple manner, is expected to be convenient in practice.

Each of six members of hydrosystem laboratory in Korea University (KU) invented either a new metaheuristic optimization algorithm or an improved version of some optimization methods as a class project for the fall semester 2014. The objective of the project was to help students understand the characteristics of metaheuristic optimization algorithms and invent an algorithm themselves focusing those regarding convergence, diversification, and intensification. Six newly developed/improved metaheuristic algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). This paper describes the details of the six developed/improved algorithms. In a follow-up companion paper, the six algorithms are demonstrated and compared through well-known benchmark functions and a real-life engineering problem.