• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.239-249
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• 2020

Rice flour varieties have been developed to replace wheat, and consumption of rice flour has been encouraged. damage related to pre-harvest sprouting was occurring due to a weather disaster during the ripening period. Thus, it is necessary to develop pre-harvest sprouting rate prediction system to minimize damage for pre-harvest sprouting. Rice cultivation experiments from 20 17 to 20 19 were conducted with three rice flour varieties at six regions in Gangwon-do, Chungcheongbuk-do, and Gyeongsangbuk-do. Survey components were the heading date and pre-harvest sprouting at the harvest date. The weather data were collected daily mean temperature, relative humidity, and rainfall using Automated Synoptic Observing System (ASOS) with the same region name. Gradient Boosting Machine (GBM) which is a machine learning model, was used to predict the pre-harvest sprouting rate, and the training input variables were mean temperature, relative humidity, and total rainfall. Also, the experiment for the period from days after the heading date (DAH) to the subsequent period (DA2H) was conducted to establish the period related to pre-harvest sprouting. The data were divided into training-set and vali-set for calibration of period related to pre-harvest sprouting, and test-set for validation. The result for training-set and vali-set showed the highest score for a period of 22 DAH and 24 DA2H. The result for test-set tended to overpredict pre-harvest sprouting rate on a section smaller than 3.0 %. However, the result showed a high prediction performance (R2=0.76). Therefore, it is expected that the pre-harvest sprouting rate could be able to easily predict with weather components for a specific period using machine learning.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.182-192
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• 2008

In oder to develop a decision supporting system for oil spill response, the prototype of pollution response support system which has integrated oil spill prediction system and pollution risk prediction system has developed for Incheon-Daesan area. Spill prediction system calculates oil spill aspects based on real-time wind data and real-time water flow and the residual volume of spilt oil and spread pattern are calculated considering the characteristic of spilt oil. In this study, real-time data is created from results of real-time meteorological forecasting model(National Institute of Environmental Research) using ftp, real-time tidal currents datasets are built using CHARRY(Current by Harmonic Response to the Reference Yardstick) model and real-time wind-driven currents are calculated applying the correlation function between wind and wind-driven currents. In order to model the feature which is spilt oil spreading according to real-time water flow is weathered, the decrease ratio by oil kinds was used. These real-time data and real-time prediction information have been integrated with ESI(Environmental Sensitivity Index) and response resources and then these are provided using GIS as a whole system to make the response strategy.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.443-443
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• 2018

새만금유역의 동진강유역에 위치한 동진강제수문은 서해 바닷물 역류에 따른 농경지의 염분피해를 예방하고 고부천과 연계된 부안지역의 농업용수 공급을 위해 설치되었다. 동진제수문은 그간 정읍시 신태인읍, 김제시 부량면, 부안군 백산면의 약 770 ha 농경지에 대해 염분피해를 예방하였고 영농과 한발 시에는 부안군 일대 농경지에 농업용수를 공급할 수 있었다. 하지만 새만금 간척사업등 대규모 국토개발로 주변 자연환경이 크게 변화하여 제수문은 염해방지기능을 상실하게 되었고 현재는 농업용수 공급원으로써의 기능만 남아 있다. 현재 동진강제수문은 관개기에 농업용수 취수를 위해 수문을 닫아 본류의 유량을 저류시키고 있으며, 비관개기에도 대부분 제수문을 닫아놓는 형태로 운영되고 있다. 이러한 갑문폐쇄로 인해 하류의 유입유량이 차단되고 상류 체류시간이 증가되어 수질에 영향을 미칠 것으로 사료된다. 농업용수사용을 위해 저류되어있는 유량을 효율적으로 방류한다면, 외부수자원에 의존하지 않고 유역 내에서 자체적으로 새만금호의 유입량을 확보할 수 있을 뿐만 아니라 동진강 하류의 수질개선에도 기여할 것으로 판단된다. 본 연구에서는 동진강제수문의 내용적을 산정하여 용수공급능력을 파악하였고, 새만금유역과 호 내의 복잡한 수체 형상, 유입 및 유출 구조를 반영하는데 적합한 모델을 적용하였다. 재현성이 검토된 모델 결과를 이용하여 새만금호의 유입부인 동진강 하류의 수질을 모의하였으며, 구성한 모형의 결과와 용수공급능력을 바탕으로 동진강제수문에서의 방류조건을 가정하여 모의를 수행하였다. 방류조건별 수질개선효과를 살펴보면, Scenario 3 > Scenario 2 > Scenario 1의 순서로 수질개선율이 크게 나타났다. 동진강제수문에서의 방류량이 증가할수록 하류의 농도가 점차 감소하는 것으로 나타났으며, 이러한 결과는 동진강제수문의 방류량으로 인해 유황이 개선되고 호 내 오염부하농도가 감소하는 것으로 판단된다. 따라서 농업용수 필요량을 제외한 유량을 하류의 환경유지용수로 확보하고 이를 수질관리취약 시기에 탄력적으로 방류하여 정체수역의 수질오염을 감소시키고 목표수질을 만족하도록 운영되어야 할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.277-277
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• 2023

최근 기후변화의 영향으로 호우의 발생빈도가 증가하고 있는 추세이며, 도시지역의 호우는 돌발적이고 국지적인 특성을 가지고 있어 인명과 재산피해 역시 증가하고 있으며, 급격한 도시화로 인한 구조적으로 홍수에 취약한 실정이다. 국지성 도시호우는 저층(1 km 내외)에서 형성되는 강우가 지배적이며, 기존의 대형레이더는 높은 산 정상에 설치되어 1.5 km 이상의 강우관측을 중심으로 운영됨에 따라 저층강우의 탐지 및 변동성 관측에 취약하여, 이에 대형 레이더에서 뿐만 아니라 도시단위의 국지성 호우관측에 대응할 수 있는 소형 레이더 기반 고정밀 강우관측 마련 및 운영 기술이 필요하다. 현재 K-water는 부산 에코델타 스마트시티에 도시 물재해 플랫폼 구현의 일환으로 돌발강우사전 탐지 및 도시의 신속·정확한 강우 관측을 위하여 높은 시공간 해상도를 제공하는 이중편파X 밴드 소형 강우레이더를 설치하고, 효율적 운용을 위해 각 고도각에서의 빔 차폐율을 확인하고 이를 고려한 최적 관측전략을 수립하였다. 또한 Z-Phi 방법을 이용한 반사도 감쇠 보정 기술을 개발하였으며, 강우 추정을 위해 하이브리드 고도면 합성 기법(HSR) 기법을 적용하고 검증하였다. 이후 소형 레이더의 정량적 추정강수를 이용하여 강우예측 정보를 생산하기 위해 이류모델을 적용하고, 비슬산과 소형 합성 레이더 추정강수로 선행 10분에서 180분까지 예측할 수 있도록 개발하였다. 또한, 지상강우관측 자료와의 정확도 비교 평가를 수행하고, 행정구역 및 표준유역의 예측 평균강우량을 생산하여 부산 에코델타 스마트시티 도시 물재해 통합관리 시스템과 연계운영을 위한 후속 과업을 수행중에 있다.

• Fire Science and Engineering
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• v.23 no.5
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• pp.57-65
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• 2009

This study was intended to conduct a Real-scale fire test to predict the fire behavior by unit space at the apartment building where a huge casualties and injuries are likely. After setting the inflammables inside the house, the test aimed to identify the fire characteristics to each unit item was carried out. The house was divided into 4 unit space such as kitchen, living room, bedroom and a study for a real scale fire test. As a result, bedroom reached to flashover state in 5minutes after setting the fire, indicating a rapid fire growth such as 7433.3kW of maximum thermal emissivity, 578.6ppm of carbon monoxide, 1.25ppm of carbon dioxide and $1,350^{\circ}C$ of maximum indoor temperature. Particularly, the fire growth was made up to critical temperature which might cause a severe damage to the people within 3minutes, if the fire were not extinguished at inflammable space at the early stage of fire, which stressed the need of early response. The result of a real scale fire test could be compared with the outcome of expanded simulation test and used in predicting the fire spread at the space for different use.

• Smart Media Journal
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• v.11 no.7
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• pp.52-60
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• 2022

Due to global warming and changes in the natural environment, flood damage to agricultural land due to wind and flood damage continues. Although disaster prevention projects have been continuously carried out since the founding of the country, progress has been insufficient compared to the sustained period, and huge costs are still being consumed. Therefore, it is necessary to use predictive simulation for pre-emptive response to inundation of farmland. In this paper, a case of immersion analysis simulation using a GIS(Geospatial Information System) based SWMM model was introduced, and the validity was confirmed through the error rate between our simulation result and the results of other models in the US and Korea. In addition, in the direction of using the simulation for agricultural land inundation, we presented various utilization methods to supplement the current agricultural land inundation-based information policy, such as the creation of flood traces. If simulation results from more regions are accumulated in the form of the flood analysis maps in the future, it is expected that they will be able to be utilized in various applications for preemptive response to and prevention of water disasters at the national level.

• Weed & Turfgrass Science
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• v.1 no.4
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• pp.13-17
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• 2012

A field experiment was conducted to investigate the effect of Acalypha australis occurrence on the growth and yield of soybean, to predict the reduction rate of soybean yield caused by competing with A. australis and to establish the economic threshold of A. australis for soybean cultivation. As the density of A. australis increase, the height and stem length of soybean were not affected by the competition with A. australis, however, the yield of soybean was decreased as 11~51% as compared with weed-free condition. The relationship between weed density and soybean yield was established as Y=415.5 / (1+0.003356X) and the reduction rate of soybean yield were predicted from this equation. Compared with the weed-free condition, the reduction rate of soybean yield were calculated as 0.3~9%, 17~29%, and 40~46% when the density of A. australis were 1~30, 60~120, and 200~250 plants $m^{-2}$, respectively. The economic threshold level of A. australis for soybean cultivation was established as 6.3 plants $m^{-2}$ from the Cousens' equation.

• Journal of the Korean Society for Marine Environment & Energy
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• v.10 no.4
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• pp.201-210
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• 2007

Pollution by chemical substances such as POPs, EDCs and PBTs in the ecosystem has become more complex and varied, increasing the possibility of irreversible damage to human health or the ecosystem. It is necessary to have a exposure assessment in a multi-media environment for various chemical substances is required for efficient management. This study applied MUSEM(Multi-media Simplebox-systems Environmental Model), a multimedia environmental model that can simultaneously evaluate the possibility of exposure of hundreds of chemical substances in order to efficiently manage chemical substances that can have negative impact on human health or ecological environment through environmental contamination. MUSEM executed the modeling for Japan by setting all 47 prefectures of japan as the regional area for 62 chemical substances and the rest of the territory of japan, excluding regional area, as the continental area and made the estimation of concentration among environment media in each administrative area and made the sensitivity analysis on Tokyo area. The results of simulation for chemical distribution showed that most of the target chemicals located in water region. The result of sensitivity analysis for octanol-water partition rate showed that the concentration change of soil in urban/industrial area and sediment in freshwater was high. In the case of sensitivity analysis for degradation rate showed that the concentration change of freshwater, soil in urban/industrial area, and sediment in freshwater was high.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.