• Journal of Korean Society of Water and Wastewater
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• v.22 no.6
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• pp.697-704
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• 2008

Stormwater runoff from urban road area as non-point source has a tendency of including lots of pollutants at initial rain period. Recently, there are several cases of having installed treatment facilities for reducing pollution discharge from the impervious cover in urban area to prevent watershed environment from getting worse. The filtration type among non-point source treatment systems has been known as one of the most efficient system for treatment of non-point source pollutants. Therefore, various kinds of filter media such as expanded polypropylene(EPP), granular activated carbon, zeolite, perlite, illite, sand, gravel has been developed. This study was conducted to verify performance and hydraulic characteristics of filter media as measures for non-point source. The experiment was carried out to evaluate applicability and variation of 4 kind of most popular filter media(EPP, GAC, Zeolite, Perlite) in headloss with elapsed time and influent flow rate and to obtain data base that could be used to establish management plan for road runoff treatment. In experiment by tap water, it showed that EPP and perlite those are floatable materials showed stable operating performance and lower headloss than the others.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.329-329
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• 2016

Rapid urbanization has taken environmental toll on the surrounding which can be witnessed by the advent of global warming and climate change. Driven by environmental needs, Green Building Index (GBI) was established in Malaysia to drive initiative to lead the property industry towards becoming more environmental friendly. Green roofs (roof with vegetated cover) as one of the assessment criteria of GBI, are gaining attention in the Malaysian society as a versatile new environmental friendly mitigation technology. This paper evaluates the qualitative and quantitative performances of an extensive green roof at Humid Tropics Centre under local tropical climate. Simulations showed that the extensive green roof system could reduce the peak discharge up to 26% in relation to impervious brown roof. Its reduction ability decreased for storms with intense rainfall. Increment of pH was observed for the green roof runoff and the runoff water quality ranged between class I and II under Water Quality Index (WQI). High concentrations of phosphate were noticed in the runoff samples and substrates (fertilized planting soil) might be the potential contributor. Findings indicate that there was a reduction of around $1.5^{\circ}C$ for indoor temperature of the building after installation of the extensive green roof.

• Journal of Environmental Policy
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• v.10 no.1
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• pp.27-47
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• 2011

Used as foundation resources for environment improvement and preservation of single-housing residential area by practicing classification of biotope with the concept of ecological area rate applied and performing urban thermal environment prediction simulation. Biotope is classified as seven types according to classification of biotope which is carried out with the concept of ecological area rate applied. The classification is listed below in descending order: building biotope(48.16%), impervious pavement biotope(39.75%), greenspace biotope(6.23%), crack permeable pavement biotope(3.26%), whole surface permeable pavement biotope(2.51%), parts permeable pavement biotope(0.04%). As a result of analysing prediction of variation and characteristics of thermal environment of single-housing residential area, land surface temperature per types of biotope are evaluated as listed below in descending temperature order: impervious pavement biotope > building biotope > greenspace biotope > permeable pavement biotope. In case 2 where vegetated roof hypothetically covers 100% of the roof area, temperature is predicted to be $33.58^{\circ}C$ Max, $23.85^{\circ}C$ Min, and $27.74^{\circ}C$ Avg. which is Approximately $5.19^{\circ}C$ lower than a non-vegetated roof. Average outdoor temperature for case 2 is studied to be $0.18^{\circ}C$ lower than case 1.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1091-1102
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• 2009

This study developed an integrated approach to climate change and urbanization impact assessment by linking models of SDSM (statistical downscaling model), HSPF (hydrological simulation program?Fortran) and ICM (impervious cover model). A case study of the Anyangcheon watershed illustrated how the proposed framework can be used to analyze the impacts of climate change and urbanization in terms of flood control, water security and water quality. The evaluation criteria were the variations of flow and pollutant concentration duration curves. In this study, nine scenarios including three climate (present condition, A1B and A2) and three urbanization scenarios were analyzed using HSPF model. As a result, climate change is a large influence on the flowrate and the urbanization affects the pollutant concentration. Therefore, the impacts of both climate change and urbanization must be included into the watershed management and water resources planning for sustainable development.

• KIEAE Journal
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• v.13 no.4
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• pp.33-41
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• 2013

The impervious area on the surface of urban area has been increased as buildings and artificial land cover have continually been increased. Urban development has gradually decreased the green zone in downtown and alienated the city from the natural environment on outskirt area devastating the natural ecosystem. There arise the environmental problems to urban area including urban heat island phenomenon, urban flood, air pollution and urban desertification. As one of urban plans to solve such problems, green roof system is attracting attentions. The purpose of this study was to investigate flood discharge and heat reduction effect according to the green roof system and to quantify effect by analyzing through simulation water and heat cycle before and after green roof system. For the analysis, Distributed hydrologic model, WEP (Water and Energy transfer Processes) and WEP+ model were used. WEP was developed by Dr. Jia, the Public Works Research Institute in Japan (Jia et al., 2005), which can simulate water and heat cycle of an urban area with complex land uses including calculation of spatial and temporal distributions of water and heat cycle components. The WEP+ is a visualization and analysis system for the WEP model developed by Korea Institute of Construction Technology (KICT).

• Journal of Korean Society on Water Environment
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• v.24 no.5
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• pp.543-549
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• 2008

Human activities and land-use practices are intensely widening the urban areas. High impervious surface areas cover much of urban landscapes and are the primary pollutant sources which can lead to water quality and habitat degradation in its watershed. As the urban areas expand, transportation land-use such as parking lots, roads, service areas, toll-gates in highways and bridges also increase. These land-uses are significant in urban pollution due to high imperviousness rate and vehicular activities. To regulate the environmental impacts and to improve the water quality of rivers and lakes, the Ministry of Environment (MOE) in Korea developed the Total Pollution Load Management System (TPLMS) program. The main objective is to lead the watershed for a low impact development. On a local scale, some urban land surfaces can be emitting more pollution than others. Consequently, in urban areas, the unit loads are commonly employed to estimate total pollutant loadings emitted from various land-uses including residential, commercial, industrial, transportation, open lands such as parks and golf courses, and other developed land like parking areas as a result of development. In this research, unit pollutant loads derived specifically from transportation land-uses (i.e. branched out from urban areas) will be provided. Monitoring was conducted over 56 storm events at nine monitoring locations during three years. Results for the unit pollutant loads of transportation land-use are determined to be $399.5kg/km^2-day$ for TSS, $12.3kg/km^2-day$ for TN and $2.46kg/km^2-day$ for TP. The values are higher than those of urban areas in Korean MOE and US highways. These results can be used by MOE to separate the pollutant unit load of transportation landuses from urban areas.

• Atmosphere
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• v.29 no.2
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• pp.131-147
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• 2019

On the urban scale, Micro-climate analysis models for urban scale have been developed to investigate the atmospheric characteristics in urban surface in detail and to predict the micro-climate change due to the changes in urban structure. BioCAS (Biometeorological Climate Impact Assessment System) is a system that combines such analysis models and has been implemented internally in the Korea Meteorological Administration. One of role in this system is the analysis of the health impact by heat waves in urban area. In this study, the vegetation cooling models A and B were developed and linked with BioCAS and evaluated by the temperature drop at the vegetation areas during ten selected heat-wave days. Smaller prediction errors were found as a result of applying the vegetation cooling models to the heat-wave days. In addition, it was found that the effects of the vegetation cooling models produced different results according to the distribution of vegetation area in land cover near each observation site - the improvement of the model performance on temperature analysis was different according to land use at each location. The model A was better fitted where the surrounding vegetation ratio was 50% or more, whereas the model B was better where the vegetation ratio was less than 50% (higher building and impervious areas). Through this study, it should be possible to select an appropriate vegetation cooling model according to its fraction coverage so that the temperature analysis around built-up areas would be improved.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1101-1118
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• 2017

Temperatures in urban areas are steadily rising due to rapid urbanization and on-going climate change. Since the spatial distribution of heat in a city varies by region, it is crucial to investigate detailed thermal characteristics of urban areas. Recently, many studies have been conducted to identify thermal characteristics of urban areas using satellite data. However,satellite data are not sufficient for precise analysis due to the trade-off of temporal and spatial resolutions.In this study, in order to examine the thermal characteristics of Daegu Metropolitan City during the summers between 2012 and 2016, Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data at 1 km spatial resolution were downscaled to a spatial resolution of 250 m using a machine learning method called random forest. Compared to the original 1 km LST, the downscaled 250 m LST showed a higher correlation between the proportion of impervious areas and mean land surface temperatures in Daegu by the administrative neighborhood unit. Hot spot analysis was then conducted using downscaled daytime and nighttime 250 m LST. The clustered hot spot areas for daytime and nighttime were compared and examined based on the land cover data provided by the Ministry of Environment. The high-value hot spots were relatively more clustered in industrial and commercial areas during the daytime and in residential areas at night. The thermal characterization of urban areas using the method proposed in this study is expected to contribute to the establishment of city and national security policies.