• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.709-721
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• 2008

This paper is to test the applicability of ModKIMSTORM (Modified KIneMatic Wave STOrm Runoff Model) by applying it to Namgangdam watershed of $2,293km^2$. Model inputs (DEM, land use, soil related information) were prepared in 500 m spatial resolution. Using five typhoon events (Saomi in 2000, Rusa in 2002, Maemi in 2003, Megi in 2004 and Ewiniar in 2006) and two storm events (May of 2003 and July of 2004), the model was calibrated and verified by comparing the simulated streamflow with the observed one at the outlet of the watershed. The Pearson's coefficient of determination $R^2$, Nash and Sutcliffe model efficiency E, the deviation of runoff volumes $D_v$, relative error of the peak runoff rate $EQ_p$, and absolute error of the time to peak runoff $ET_p$ showed the average value of 0.984, 0.981, 3.63%, 0.003, and 0.48 hr for 4 storms calibration and 0.937, 0.895, 8.08%, 0.138, and 0.73 hr for 3 storms verification respectively. Among the model parameters, the stream Manning's roughness coefficient was the most sensitive for peak runoff and the initial soil moisture content was highly sensitive for runoff volume fitting. We could look into the behavior of hyrologic components from the spatial results during the storm periods and get some clue for the watershed management by storms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.697-707
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• 2008

The grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) by Kim (1998) predicts the temporal variation and spatial distribution of overland flow, subsurface flow and stream flow in a watershed. The model programmed with C++ language on Unix operating system adopts single flowpath algorithm for water balance simulation of flow at each grid element. In this study, we attempted to improve the model by converting the code into FORTRAN 90 on MS Windows operating system and named as ModKIMSTORM. The improved functions are the addition of GAML (Green-Ampt & Mein-Larson) infiltration model, control of paddy runoff rate by flow depth and Manning's roughness coefficient, addition of baseflow layer, treatment of both spatial and point rainfall data, development of the pre- and post-processor, and development of automatic model evaluation function using five evaluation criteria (Pearson's coefficient of determination, Nash and Sutcliffe model efficiency, the deviation of runoff volume, relative error of the peak runoff rate, and absolute error of the time to peak runoff). The modified model adopts Shell Sort algorithm to enhance the computational performance. Input data formats are accepted as raster and MS Excel, and model outputs viz. soil moisture, discharge, flow depth and velocity are generated as BSQ, ASCII grid, binary grid and raster formats.

• Advances in nano research
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• v.13 no.5
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• pp.417-426
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• 2022

Bisphenol A (BPA) is one of the chemicals used in monomer epoxy resins and polycarbonate plastics. The surface-enhanced Raman spectroscopy (SERS) method is precise for identifying biological materials and chemicals at considerably low concentrations. In the present article, the substrates coated with gold nanoparticles have been studied to identify BPA and control the diseases caused by this chemical. Gold nanoparticles were made by a simple chemical method and by applying gold salt and trisodium citrate dihydrate reductant and were coated on glass substrates by a spin-coat approach. Finally, using these SERS substrates as plasmonic sensors and Raman spectroscopy, the Raman signal enhancement of molecular vibrations of BPA was investigated. Then, the molecular vibrations of BPA in some consumer goods were identified by applying SERS substrates as plasmonic sensors and Raman spectroscopy. The fabricated gold nanoparticles are spherical and quasi-spherical nanoparticles that confirm the formation of gold nanoparticles by observing the plasmon resonance peak at 517 nm. Active SERS substrates have been coated with nanoparticles, which improve the Raman signal. The enhancement of the Raman signal is due to the resonance of the surface plasmons of the nanoparticles. Active SERS substrates, gold nanoparticles deposited on a glass substrate, were fabricated for the detection of BPA; a detection limit of 10-9 M and a relative standard deviation (RSD) equal to 4.17% were obtained for ten repeated measurements in the concentration of 10-9 M. Hence, the Raman results indicate that the active SERS substrates, gold nanoparticles for the detection of BPA along with the developed methods, show promising results for SERS-based studies and can lead to the development of microsensors. In Raman spectroscopy, SERS active substrate coated with gold nanoparticles are of interest, which is larger than gold particles due to the resonance of the surface plasmons of gold nanoparticles and the scattering of light from gold particles since the Raman signal amplifies the molecular vibrations of BPA. By decreasing the concentration of BPA deposited on the active SERS substrates, the Raman signal is also weakened due to the reduction of molecular vibrations. By increasing the surface roughness of the active SERS substrates, the Raman signal can be enhanced due to increased light scattering from rough centers, which are the same as the larger particles created throughout the deposition by the spin-coat method, and as a result, they enhance the signal by increasing the scattering of light. Then, the molecular vibrations of BPA were identified in some consumer goods by SERS substrates as plasmonic sensors and Raman spectroscopy.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.227-237
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• 2020

Microclimatic data were measured, and the human thermal sensation was analyzed at 10 local climate zones based on the major land cover classification to investigate the thermal environment of urban areas during summer nighttime. From the results, the green infrastructure areas (GNIAs) showed an average air temperature of 1.6℃ and up to 2.4℃ lower air temperature than the gray infrastructure areas (GYIAs), and the GNIAs showed an average relative humidity of 9.0% and up to 15.0% higher relative humidity. The wind speed of the GNIAs and GYIAs had minimal difference and showed no significance at all locations, except for the forest location, which had the lowest wind speed owing to the influence of trees. The local winds and the surface roughness, which was determined based on the heights of buildings and trees, appeared to be the main factors that influenced wind speed. At the mean radiant temperature, the forest location showed the maximum value, owing to the influence of trees. Except at the forest location, the GNIAs showed an average decrease of 5.5℃ compared to GYIAs. The main factor that influenced the mean radiant temperature was the sky view factor. In the analysis of the human thermal sensation, the GNIAs showed a "neutral" thermal perception level that was neither hot nor cold, and the GYIAs showed a "slightly warm" level, which was a level higher than those of the GNIAs. The GNIAs showed a 3.2℃ decrease compared to the GYIAs, except at the highest forest location, which indicated a half-level improvement in the human thermal environment.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.