An urban runoff model that is able to compute the runoff, the pollutant loadings, and the concentrations of water-quality constituents in urban drainages during the first flush was developed. This model, which is referred to as FFC-QUAL, was modified from the existing ILLUDAS model and added for use during the water-quality analysis process for dry and rainy periods. For the dry period, the specifications of the coefficients for the discharge and water quality were used. During rainfall, we used the Clark and time-area methods for the runoff analyses of pervious and impervious areas to consider the effects of the subbasin shape; moreover, four pollutant accumulation methods and the washoff equation for computing the water quality each time were used. According to the verification results, FFC-QUAL provides generally similar output as the measured data for the peak flow, total runoff volume, total loadings, peak concentration, and time of peak concentration for three rainfall events in the Gunja subbasin. In comparison with the ILLUDAS, SWMM, and MOUSE models, there is little difference between these models and the model developed in this study. The proposed model should be useful in urban watersheds because of its simplicity and its capacity to model common pollutants (e.g., biological oxygen demand, chemical oxygen demand, Escherichia coli, suspended solids, and total nitrogen and phosphorous) in runoff. The proposed model can also be used in design studies to determine how changes in infrastructure will affect the runoff and pollution loads.

Road surface-runoffs have been analyzed using various approaches, but inaccurate analysis methods lead to overestimation of the drainage capacity, causing unexpected flood damage in low-lying urban areas. Previous studies have highlighted the importance of considering various parameters for accurate road surface-runoff analysis. This study involves road surface-runoff analysis using an enhanced approach considering simplified and modified drainage basin geometries, road surface and gutter flow travel times, and inlet interception efficiency as key parameters under various road conditions. The topographical road conditions were set as follows: Width (6 m), longitudinal slope of road (2–10%), road surface slope (2%), and transverse slope of gutter (2–7%). The results show that using a modified basin considering road slope conditions for estimating actual flow path length and travel time is better for flow analysis than the simplified rectangular basin. Additionally, the runoff analysis should consider the roadside inlet installation conditions, given that the bypass discharge (i.e., rainfall runoff that is not intercepted by upstream inlets) flows downstream and affects the downstream flow characteristics. Based on these results, an optimal road surface-runoff analysis method was developed, which is expected to be useful for road design.

Urban flood damage is increasing globally, particularly in major cities. Factors contributing to flood risk include urban environmental changes, such as watershed development and precipitation variations caused by climate change. Rapid urbanization and weather anomalies further complicate flood management and damage mitigation. Additionally, detailed analyses at small spatial units (e.g., roads, buildings) remain insufficient. Hence, urban flood analysis considering such spatial variations is required. This study analyzed flood risk in Ulsan, Korea, under a severe flood scenario. Land cover changes from the 1980s to 2010s were examined in 10-year intervals, along with the frequency of heavy rainfall and high river water levels that trigger severe floods. Flood risk was structured as a matrix of likelihood and impact. The results revealed that land cover changes, influenced by development policies or regulations, had a minimal impact on urban flood risk, which is likely because effective drainage systems and stringent urban planning regulations mitigated their effects. However, the frequency and intensity of extreme precipitation events had a substantial effect. These findings were validated using a comparative analysis of an inundation damage trace map and flood range simulated by a physical model. The 10 m grid resolution and time-series likelihood-and-impact framework used in this study can inform budget allocation, resource mobilization, disaster prevention planning, and decision-making during disaster response efforts in major cities.

Since the 1990s, efforts have been made to reduce the damage caused by natural disasters, among which the Disaster Impact Assessment (DIA) System implemented in 1995 is noteworthy for its proactive response. The DIA System has undergone various institutional and technological changes to retain its original purpose. However, its operation has become inadequate because of the diversification of business types. This paper presents the improvements required in the DIA System based on an analysis of the problems that have emerged during its institutional development and over 9000 pieces of data collected from 2015 to 2017. The results show that, first, the DIA’s Practical Guidelines should be subdivided, considering the diversity of projects. Second, the system should be strengthened to ensure it is not mistaken for a mere bureaucratic box-ticking exercise. Third, non-structural measures should be expanded to reduce the number of casualties after development. Incorporating the improvements proposed in this study will improve the effectiveness of the DIA. Additionally, the DIA System could be established as an important model for Korea’s disaster risk reduction activities.