Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

In this study, seasonal Mann - Kendall test method was applied to 12 stations of the water quality measurement network of Nam-River based on data of BOD, COD, TN and TP for 11 years from January 2005 to December 2015 The changes of water quality at each station were examined through linear trends and the tendency of water quality change during the study period was analyzed by applying the locally weighted scatter plot smoother (LOWESS) method. In addition, spatial trends of the whole Nam-River were examined by items. The flow-adjusted seasonal Kendall test was performed to remove the flow at the water quality measurement station. As a result, BOD, COD concentration showed "no trand" and TN and TP concentration showed "down trand" in regional Kendall test throughout the study period. BOD and TP concentration in "no trand", COD, and TN concentration showed an "up trand" tendency in Nam-River dam. LOWESS analysis showed no significant water quality change in most of the analysis items and stations, but water quality fluctuation characteristics were shown at some stations such as NR1 (Kyungho-River 1), NR2 (Kyungho-River 2), NR3 (Nam-River), NR6 (Nam-River 2A). In addition, the flow-adjusted seasonal Kendall results showed that the BOD concentration was "up trand" due to the flow at the NR3 (Nam-River) station. The COD concentration was "up trand" due to the flow at NR1 (Kyungho-River 1) and NR2 (Kyungho-River 2) located upstream of the Nam-River. The effect of influent flow on water quality varies according to each site and analysis item. Therefore, for the effective water quality management in the Nam-River, it is necessary to take measures to improve the water quality at the point where the water quality is continuously "up trand" during the study period.

The real-time monitoring of surface vegetation is essential for the management of droughts, vegetation growth, and water resources. The availability of land cover maps based on remotely collected data makes the monitoring of surface vegetation easier. The vegetation index in an area is likely to be proportional to meteorological elements there such as air temperature and precipitation. This study investigated relationship between vegetation index based on Moderate Resolution Image Spectroradiometer (MODIS) and ground-measured meteorological elements at the Yongdam catchment station. To do this, 16-day averaged data were used. It was found that the vegetation index is well correlated to air temperature but poorly correlated to precipitation. The study provides some intuition and guidelines for the study of the droughts and ecologies in the future.

본 연구의 목적은 기상자료(강수량, 최고기온, 최저기온, 평균기온, 평균풍속) 기반의 다중선형 회귀모형을 개발하여 농업용저수지 저수율을 예측 하는 것이다. 나이브 베이즈 분류를 활용하여 전국 1,559개의 저수지를 지리형태학적 제원(유효저수량, 수혜면적, 유역면적, 위도, 경도 및 한발빈도)을 기준으로 30개 군집으로 분류하였다. 각 군집별로, 기상청 기상자료와 한국농어촌공사 저수지 저수율의 13년(2002~2014) 자료를 활용하여 월별 회귀모형을 유도하였다. 저수율의 회귀모형은 결정계수(R2)가 0.76, Nash-Sutcliffe efficiency (NSE)가 0.73, 평균제곱근오차가 8.33%로 나타났다. 회귀모형은 2년(2015~2016) 기간의 기상청 3개월 기상전망자료인 GloSea5 (GS5)를 사용하여 평가되었다. 현재저수율과 평년저수율에 의해 산정되는 저수지 가뭄지수(Reservoir Drought Index, RDI)에 의한 ROC (Receiver Operating Characteristics) 분석의 적중률은 관측값을 이용한 회귀식에서 0.80과 GS5를 이용한 회귀식에서 0.73으로 나타났다. 본 연구의 결과를 이용해 미래 저수율을 전망하여 안정적인 미래 농업용수 공급에 대한 의사결정 자료로 사용할 수 있을 것이다.

This paper is a study on the development of a data analysis platform that constitutes a part of the development task of the constant monitoring system that can prepare against the earthquake disaster by using the regular measurement data of the old school buildings. The data analysis platform is composed of database management software that manages the metrology data acquired by using the instrument and data management software that analyzes the metrology data, analysis tools that can analyze the metrology data in various ways, A data analysis platform can be used to assess the safety of the school building and evaluate the seismic safety of the old school building to build a system for earthquake disaster.

The objectives of this research are to suggest the basic plans for earthquake data construction using data sharing platform, and to design the earthquake information contents based on stakeholder's needs. To strengthen the earthquake disaster response capacity, customized contents for public and local/central government use and specific sharing platform are developed. Finally, the step-by-step data sharing roadmap is suggested.

The comparison of demand and supply is needed for efficient ecosystem services planning. However, the gap between them cannot be analyzed as existing studies mainly dealt with only the supply of ecosystem services. This study compares the demand and supply of ecosystem services in Shiheung using environmental complaints and urban planning by semantic network analysis. As a result, ‘air’ and ‘water’ quality are magnified in demand, ‘energy’ and ‘water’ are crucial in supply. This result presents that citizen ask for the improvement of air quality in regulation services, although local government has plans for energy support in provisioning services. Periodic ecosystem services demand and supply monitoring will be the base of effective ecosystem services planning, which reduce insufficiency and surplus.

대부분의 수문분석은 시 단위 강우를 기반으로 확률강우량과 강우시간분포를 산정하고, 확률강우량과 강우시간분포의 자료기간을 달리 적용하는 방법으로 강우-유출분석을 수행하고 있다. 본 연구에서는 자료형태(시 단위와 분 단위 강우자료)와 확률강우량과 강우시간분포의 다른 자료기간 적용에 따른 설계홍수량 변화를 정량화 하고자, 자료형태와 자료기간에 따라 지점빈도해석을 통한 확률강우량 산정과 Huff의 4분위 방법을 통한 강우시간분포를 산정하였다. 또한, 확률강우량과 설계강우 시간분포의 자료기간을 달리 적용한 강우-유출분석으로 설계홍수량 변동분석을 실시하였다. 분석결과, 자료형태에서는 분 단위 강우가 시 단위 강우보다 더욱 정확하고 효과적인 강우분석을 수행할 수 있는 것으로 나타났으며, 확률 강우량과 강우시간분포의 다른 자료기간을 적용하여 산정된 설계홍수량의 차 보다 자료형식에 따른 설계홍수량 결과가 보다 큰 차이를 보이는 것 으로 나타났다. 이는 향후 분 단위 강우를 활용한 수문분석에 크게 기여할 것으로 판단된다.

As the interception of communications infringe the close part of the privacy and the degree of the infringement is very serious, the law of protecting the secrecy of communications limits the group of crimes which can be the cause of the interception. As the result, the purpose of the limitation could not be achieved if the materials of evidence would not be restricted to use in investigation and prosecution only for the crimes within the limited group. We could admit the provision §12(1) of the law of protecting the secrecy of communications reasonable, which restrict the scope of the use of the evidence obtained by the interception of the communications. But the indentification materials of electronic communications includes only the names, the telephone numbers of the parties of the communication, the times fo the communication. It does not include the contents of the communications. The degree of the infringement could be said relatively minor and the law does not limit the scope of the crime which could be the cause of the request for the identification materials. Therefore, there would be no reason to limit the scope of the use of the evidence obtained by the request issued by the court. Nevertheless, the provision §13-5 of the law of protecting the secrecy of communications provides that the provision §12(1) which restrict the use of the evidence obtained by the interception apply correspondingly to the indentification materials of electronic communications. From the point of view of legislation, the provision §13-5 could be said inappropriate and should be eliminated in the future.

The purpose of this study is to identify the effectiveness of satellite images in detecting the areas of rice production in the Barisal of Bangladesh. We also investigated the effect of climate change on the crop production through comparative analysis of rice production area and production statistics with climate data at multi-temporal time scale. This analysis found that the classification of rice fields extracted through satellite image and made as the number of rice cultivation areas did not exceed 10 percent of the statistical data. Climate data analysis showed that the average temperature during the ripening stage has the greatest impact on Boro’s production. It would be more make sense if you can describe the results of how precipitation is also important for rice production in addition to temperature. Therefore, it is believed that this research could serve as a key basis for solving food security issues due to climate change.

원전의 안전한 해체 관리를 위해 원전 해체 비용 평가는 매우 중요하다. 가장 많은 원전 해체 경험을 갖고 있는 미국의 경우 1970년대부터 원자력시설의 해체를 위하여 비용평가 연구를 진행하였다. 미국 NRC는 다양한 로형 및 원자력시설에 대한 해체 기술, 안전성 및 비용에 대한 연구를 수행하였다. 전체 해체 비용에서 운영허가종료비용이 가장 큰 비중을 차지하며, 그 다음으로는 사용후핵연료 관리, 부지복원순으로 평가되었다. 해체비용은 전체비용에 있어 운영허가종료가 제일 큰 비중을 차지하며 사용후핵연료관리, 부지복원 순으로 평가되었다. 즉시해체의 경우 지연해체에 비해 사용후핵연료관리 비용이 증가하였으며 지연 해체의 경우 운영허가종료의 비용이 증가하였다. 전반적으로 즉시해체에 비해 지연해체의 경우가 뚜렷하게 이득이 보이지 않고 있다. 국내 원전 해체 비용 평가시 부지 조건에 따른 평가를 고려해야할 필요가 있다고 판단된다. 또한 국내의 경우 IAEA의 권고사항을 적용하여 방사성폐기물 분류체계를 재정비하였다. 이에 따라 해체시 발생하는 방사성폐기물 물량 산정시, 선행 미국 원전해체 자료를 신분류체계에 적합하게 활용하기 위한 방법을 개발해야할 필요가 있다. 특히 자체처분 대상폐기물 평가 방법론 설정은 해체비용의 정확성을 확보하는 중요한 인자로 작용할 것이다. 또한 국내 원전해체 비용 평가를 위하여 시설 특성과 작업 특성에 적용할 수 있는 정보자료 구축이 필요하다.

For this study, WRF numerical modeling was performed, using RDAPS information for input data on typhoons affecting the Korean peninsula to produce wind data of 700hPa. RAM numerical modeling was also used to calculate 3-second gusts as the extreme wind speed. After comparing wind speeds at an altitude of 10 m to evaluate the feasibility of WRF numerical modeling, modeled values were found to be similar with measured ones, reflecting change tendencies well. Therefore, the WRF numerical modeling results were verified. As a result of comparing and analyzing these wind speeds, as calculated through RAM numerical modeling, to evaluate applicability for disaster preparedness, change tendencies were observed to be similar between modeled and measured values. In particular, modeled values were slightly higher than measured ones, indicating applicability for the prevention of possible damage due to gales. Our analysis of 3-second gusts during the study period showed a high distribution of 3-second gusts in the southeast region of the Korean peninsula from 2002-2006. The frequency of 3-second gusts increased in the central north region of Korea as time progressed. Our analysis on the characteristics of 3-second gusts during years characterized by El Niño or La Nina showed greater strength during hurricanes that affected the Korean peninsula in El Niño years.

수문순환에서 증발산의 정확한 산정은 수문분석 및 이해에 있어서 매우 중요하다. 특히, 증발산을 산정하는 방법은 다양하며, 각각 방법 마다 장단점을 가지고 있다. 그렇기 때문에, 각 다른 방법으로 산전된 결과를 융합하여 최적의 증발산을 산출해야할 필요가 있다. 본 연구에서는 대표적으로 인공위성 기반의 증발산 모델인 revised RS-PM과 MS-PT 방법에서 산출된 증발산과 모델 자료인 Global Land Data Assimilation System (GLDAS)와 Global Land Evaporation Amsterdam Model (GLEAM)자료들을 융합함으로써 최적의 증발산을 산출하고자 하였다. 연구 지역인 청미천과 설마천에서의 플럭스 타워에서 융합된 증발산에 대해서 검증을 실시하였다. 통계학적인 결과(상관계수, 일치도, MAE, RMSE)를 확인하였을 때, 기존의 인공위성과 모델에서 산출되는 증발산 결과에 비해 향상되는 결괄르 나타내었다. 전반적으로 결과를 확인하였을 때, 융합된 자료가 보다 향상된 결과를 보일 수 있을 것이라는 것을 나타내었으며, 추후에는 더 많은 모델을 사용하여 융합함으로써 보다 정확한 결과를 산출 할 수 있을 것으로 기대된다.

강우는 물순환 시스템을 이해를 증가 시킬 뿐만 아니라, 효율적인 수자원 확보 및 관리에 있어서 가장 핵심적인 인자이다. 본 연구는 2015년을 대상으로 한반도에서의 92개의 ASOS 지점자료와 최근에 발사된 GPM 위성강우 자료의 비교를 통하여 활용가능성을 평가하였다. 또한 지점 자료의 장점과 인공위성 자료의 장점을 융합함으로써 보다 개선된 강우자료를 산출하기 위해 3가지의 상세화 방법(Geographical Differential Analysis, Geographical Ratio Analysis, Conditional Merging)들을 적용하였다. 이 연구에서 도출된 결과는 다음과 같다. 1) ASOS 자료와의 검증을 통해 GPM 강우자료가 약간 과대산정되는 편향을 가지고 있는 것을 확인하였으며, 특히 여름 기간에 오차가 높게 발생하는 것으로 나타났다. 2) Jackknife 방법을 통하여 각 합성방법에 대해서 검증하였을 때, 공간해상도가 높아짐에 따라서 오차가 줄어드는 것을 확인하였으며, 상세화 방법 중 conditional merging 방법이 가장 좋은 성능을 나타내었다.

This study reviewed the applicability of the existing flood discharge calculation method on Jeju Island Han Stream and compared this method with observation results by improving the mediating variables for the Han Stream. The results were as follows. First, when the rain-discharge status of the Han Stream was analyzed using the flood discharge calculation method of the existing design (2012), the result was smaller than the observed flood discharge and the flood hydrograph differed. The result of the flood discharge calculation corrected for the curve number based on the terrain gradient showed an improvement of 1.47 - 6.47% from the existing flood discharge, and flood discharge was improved by 4.39 - 16.67% after applying the new reached time. In addition, the sub-basin was set separately to calculate the flood discharge, which yielded an improvement of 9.92 - 32.96% from the existing method. In particular, the steepness and rainfall-discharge characteristics of Han Stream were considered in the reaching time, and the sub-basin was separated to calculate the flood discharge, which resulted in an error rate of –8.77 to 8.71%, showing a large improvement of 7.31 - 28.79% from the existing method. The flood hydrograph also showed a similar tendency.

In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean PM10 concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.

Arctic sea ice as an indicator of climate change plays an important role in controlling global climate system. Thus, accurate observation and prediction of Sea Ice Concentration (SIC) is essential for understanding global climate change. In this study, we aim to improve the prediction accuracy of SIC by using machine learning and Regional Climate Model (RCM) data for a more robust method and a higher spatial resolution. Using the CORDEX RCM and NASA SIC data between January 1981 and December 2015, we developed three statistical models using Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Deep Neural Network (DNN) which can deal with the non-linearity problem, respectively. The DNN model showed the best performance among the three models with the significant correlation between the predictive and observed SIC (r=0.811, p-value < 0.01)and the Root Mean Square Error (RMSE) of 0.258. With deeper considerations of the polar fronts and the characteristics of ocean current and tide, the DNN model can be applied for near future prediction of Arctic sea ice changes.

This study analyzes relationship between land cover change and local climate data of 46 weather stations in South Korea from the 1980s to 2000s. The used area shows proportional relationships to mean daily min. temperature and mean temperature, and a reverse relationship is found between the used area and relative humidity. However, the forest indicates reverse relationships to mean daily min. temperature and mean temperature. The agricultural land causes to increase in relative humidity and decrease in mean wind speed, while the water increases mean daily min. temperature, daily min. temperature and mean temperature as well as mean wind speed. The urbanization type (used area + barren) shows high correlations with temperature and humidity. The suburbanization type (agricultural land + forest + grass + wetland) has high correlations with temperature and wind speed. High correlations are also found between the waterfront type (wetland + water), and temperature and wind speed. It can be concluded that change in land cover around weather station obviously influences on climate data of the weather station and it is also expected that reliability and homogeneity of climate data from a weather station can be enhanced by this study.

최근 국지성 집중호우 및 급격한 기상변화로 인해 돌발홍수와 같은 기상재해의 발생빈도가 증가함에 따라 고해상도의 기상레이더 강수자료를 사용한 수공학 분야의 연구가 활발하게 진행되고 있다. 기상레이더 강수자료를 활용하는 목적은 기상레이더 강수자료가 제공하는 공간분포를 최대한 활용하는데 있다. 본 연구에서는 고해상도 기상레이더 강수자료의 공간적 특성을 유지하면서 지상 강수자료의 양적특성을 극대화할 수 있는 조건부 합성기법을 보간법에 따라 분석 하였다. 기상레이더 강수자료와 지상 강수자료를 조건부 합성하기 위하여 Kriging, 역거리 가중법 및 Spline 보간법을 적용하였다. 조건부 합성결과는 지상 강수패턴을 현실성 있게 재현하였으며 추가적으로 보간법에 적용되지 않은 강수자료와 모형검증을 수행한 결과 조건부 합성을 통하여 생산된 공간적 강수정보의 수문학적 활용이 가능할 것으로 판단된다.

Phosphorus (P) is an essential and major nutrient for both plants and animals. However, anthropogenic P in the environment may cause severe problems such as the deterioration of water quality. Therefore, it is essential for the Korean government to manage P in the agricultural sector. The annual P budget for Korea was 46 kg P ha-1 in 2013, placing Korea in second among Organication for Economic Co-operation and Development (OECD) countries. P surplus and deficiency in agricultural lands can be estimated according to the P budget, which is one of the OECD agri-environment indicators. In the P budget, it is important to ensure consistency in the input-output data sources, in order to apply national and regional policies for the environmentally sound management of agricultural P. This study examines the impacts on the input-output data sources in the regional P budget in Korea. P budgets were between 99-145 kg-P/ha, depending on different data sources. We suggest two recommended data combinations (DC 1 and DC 2) for reliability of the data. P budgets calculated using DC 1 and DC 2 were 128 kg-P/ha and 97 kg-P/ha, respectively. According to the results, one of the core factors affecting P budgets was crop production. In this study, DC 2 was recommended rather than DC 1 in order to consider the cultivated areas for various crops. It is also necessary to analyze the sensitivity of the coefficients used in P budget in the future.