Impermeable materials are used for parking lots at apartment complexes and large stores which are concentrated in urban areas. These materials increase the amount of surface runoff by blocking infiltration, resulting in flood damage, dry stream phenomena in rivers in urban watersheds, and the depletion of ground water. In this study, a parking lot plot was constructed to quantitatively evaluate the efficiency of pavements using various materials (impermeable concrete, permeable concrete, and permeable block pavement). Four scenarios of rainfall intensity were simulated using a rainfall simulator within each plot (36 mm h⁻¹, 48 mm h⁻¹, 60 mm h⁻¹, 72 mm h⁻¹). The flow was observed by monitoring the system with a bucket flow meter. The efficiency and flow characteristics of the permeable concrete and block pavement were analyzed. The results were used to calculate the ratio of the surface flow to the infiltrating flow between impermeable and permeable pavements. The permeable concrete had a ratio of 1:0.9, and the permeable block pavement had a ratio of 1:0.58.

Low Impact Development (LID) techniques have been drawing an increasing attention in recent years as efficient ways of stormwater management. These methods try to mimic nature by providing pervious area which has been decreased due to urbanization. One of the most efficient practices of LID is the use of Green Roof (GR) systems. Although GRs have been traditionally used in the past, their engineering design and construction is a recent trend. Since GR systems, similar to other LID techniques, are supposed to endure local climate and environmental conditions, their design should be accomplished regarding the conditions of the area where they will be installed. In order to systematically examine, design, and construct various LID techniques for Korean climate and environment, the LID & GI Center of Korea is built in Pusan National University. This center tries to hire hardware and software facilities to study and design LID practices; Hydrological Performance Tester for Green Roof (HPT-GR) and Korea Low Impact Development Model (K-LIDM) are made for this purpose. In order to examine the performance of a Green Roof (GR) system composed of layers with different material and size, five trays were made at LID & GI Center of Korea. The size and composition of these trays were: (A) plant + soil + drainage mat with total depth of 15 cm, (B) plant + soil + sand with total depth of 15 cm, (C) plant + soil + sand with total depth of 9 cm, (D) a bare soil with total depth of 15 cm, and (E) a concrete with total depth of 15 cm. All the trays were examined under different uniform precipitations with rates of 50, 80, 100 and 150 mm/h using HPT-GR. The results showed that the use of drainage mat in tray A could significantly improve the performance of the GR by increasing its storage capacity up to 40% of the rainwater, decreasing its saturation rate, and reducing its discharge peak value. Then, as the first use of K-LIDM for simulating a green roof, all the experimental GRs were numerically simulated using this model; the numerical hydrographs were compared to those achieved from the experiment. The results showed that K-LIDM can be used for performance prediction of GR systems with slightly conservative but acceptable results. With an increase in the rainfall intensity, the discharge peak values increased and their times decreased in both numerical and experimental scenarios; however, the peak values were slightly higher in simulation results than those of the corresponding experimental ones.

Urban areas face increasing flood risks due to climate change, intensified rainfall events, and high impervious surface coverage. Blue-Green Roofs (BGR) have emerged as a nature-based solution to retain stormwater, while Smart BGR systems integrate active control functions to enhance performance under varying rainfall conditions. This study evaluated the rooftop-scale runoff reduction efficiency of conventional roofs, BGR, and Smart BGR using 31 monitored rainfall events in 2024, while eight years of historical rainfall data (2017–2024) were used only to characterize long-term rainfall patterns in the study area. A multiple-linear regression analysis was performed for exploratory trend identification between rainfall characteristics and runoff reduction; variables unrelated to short-term storm responses such as evapotranspiration or initial storage were beyond the study scope. Results showed that the annual runoff per unit area was 1.115 m³/m² for conventional roofs, 0.547 m³/m² for BGR, and 0.128 m³/m² for Smart BGR, corresponding to reduction rates of 50.98% and 88.53% for BGR and Smart BGR, respectively. In higher rainfall classes, Smart BGR maintained significantly higher performance: for Class 3 (average 53.00 mm), BGR reduced runoff by 54.89% while Smart BGR achieved 86.71%; for Class 4 (average 121.21 mm), the rates were 54.68% and 90.00%, respectively. These findings indicate that Smart BGR’s storage optimization and controlled discharge enable superior effectiveness during intense and prolonged events. The study highlights Smart BGR’s potential as an advanced stormwater management technology, offering clear advantages over both conventional roofs and passive BGR designs. Limitations include the need for testing under more extreme rainfall scenarios, optimization of operational strategies, and economic feasibility assessments. Nevertheless, Smart BGR represents a promising approach for enhancing urban flood resilience in the context of climate change.

Urbanization and climate change produce distortions in urban water circulation. This issue can be resolved using a stormwater management technique called Low Impact Development (LID), which mimics natural processes and restores the hydrological state as it was before development. This study aims to evaluate the performance of a LID facility and calculate the runoff reduction and delay effect. The test-bed is a green wall of the Korea GI & LID Center. Scenarios for 30 mm/hr, 50 mm/hr, and 70 mm/hr were set based on the percentile of rainfall events from 2012 to 2021 in Geumjeong-gu, Busan. By setting an impervious surface as the control group, runoff reduction was found to be 91%~94% of 30 mm/hr, 50 mm/hr, and 70 mm/hr. The total outflow time increased by 47, 88, and 58 minutes, respectively, demonstrating the effect of reduced runoff and delayed time. A storm water management model (SWMM) was constructed to evaluate this effect quantitatively. Verification and correction were done using the experiment results. R2 was 0.96~0.98 for the test and 0.93~0.94 for the correction. This paper thus verified the retention effectiveness performance of a green wall and analyzed its quantitative effect through a SWMM. The study findings can be used as a guideline to test parameter-wise hydrological performance of the model.

Permeable blocks have been increasingly adopted as climate adaptation technologies to mitigate the impacts of extreme rainfall in urban areas. However, quantitative runoff reduction performance under varying rainfall intensities has not been sufficiently validated. In this study, controlled outdoor artificial rainfall experiments were conducted under three rainfall scenarios (50, 100, and 150 mm/h) to evaluate the effectiveness of permeable blocks in reducing surface runoff. A runoff monitoring system was installed at a testbed site on the Yangsan campus of Pusan National University to quantify outflow characteristics. The experimental data were used to develop a runoff prediction model based on an exponential regression approach. The results showed that the permeable blocks effectively reduced runoff across all rainfall scenarios, with correlation coefficients between the observed and predicted values ranging from 0.991 to 0.995 (p < 0.05). This indicated a strong predictive relationship and verified the reliability of the model. These findings contribute to the establishment of experimental design guidelines for future high-precision climate simulation experiments and support the practical implementation of permeable pavement systems for urban flood mitigation.