• 한국수자원학회논문집
• /
• 제42권10호
• /
• pp.877-889
• /
• 2009

본 연구에서는 SWAT(Soil and Water Assessment Tool) 모형을 이용하여 미래 기후변화가 충주댐 유역(6,585.1 km$^2$)의 하천수질에 미치는 영향을 분석하고자 하였다. 미래 기상자료는 IPCC에서 제공하는 A2, A1B, B1 배출시나리오를 포함하는 ECHAM5-OM 모형의 결과를 과거 30년(1977-2006, baseline period) 기후자료를 바탕으로 편이보정(bias correction)과 Change Factor Method로 Downscaling 하였다. 6년(1998-2003) 동안의 일별 유출량 및 월별 수질(SS, T-N, T-P) 자료를 이용하여 모형의 보정 및 검증을 실시한 후, Downscaling된 ECHAM5-OM의 A2, A1B, B1 시나리오에 대해 2020s, 2050s, 2080s로 대별되는 미래의 수문학적 거동 변화 및 하천수질 변화를 전망하였다.

• 한국재난관리표준학회지
• /
• 제2권3호
• /
• pp.61-66
• /
• 2009

과거 우리나라의 재난관리는 재해가 발생한 후 이에 대한 복구를 수행하는 사후복구에 중심을 두었다고 볼 수 있으나, 현재는 과거와 같은 사후복구가 아닌 재해발생을 미리 예측하고 이에 대한 정보를 일반인에게 전파하여 재해발생에 따른 피해를 최소화 하는 재난관리시스템 구축에 중점을 두고 있다. 그리고 최근에 전 세계적으로 발생되고 있는 재난은 과거에 비해 그 규모나 피해 정도가 대형화되고 있는데 이는 산업발달과 인구의 증가 등에 따른 기후변화가 주된 원인으로 작용하고 있기 때문이다. 본 연구를 통해 기후변화 적응을 중심으로한 국제기구 및 유럽 방재선진국의 재난관리 사례를 분석, 국내 실정에 적합한 미래 재난관리 표준시스템 구축을 위한 방안과 대안을 기술하고자 한다.

• 대한원격탐사학회지
• /
• 제24권1호
• /
• pp.45-55
• /
• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• 대기
• /
• 제32권4호
• /
• pp.395-409
• /
• 2022

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

• 대기
• /
• 제33권4호
• /
• pp.423-440
• /
• 2023

The updated version of Global Ocean Data Assimilation and Prediction System (GODAPS) in the NIMS/KMA (National Institute of Meteorological Sciences/Korea Meteorological Administration), which has been in operation since December 2021, is being introduced. This technical note on GODAPS2 describes main progress and updates to the previous version of GODAPS, a software tool for the operating system, and its improvements. GODAPS2 is based on Forecasting Ocean Assimilation Model (FOAM) vn14.1, instead of previous version, FOAM vn13. The southern limit of the model domain has been extended from 77°S to 85°S, allowing the modelling of the circulation under ice shelves in Antarctica. The adoption of non-linear free surface and variable volume layers, the update of vertical mixing parameterization, and the adjustment of isopycnal diffusion coefficient for the ocean model decrease the model biases. For the sea-ice model, four vertical ice layers and an additional snow layer on top of the ice layers are being used instead of previous single ice and snow layers. The changes for data assimilation include the updated treatment for background error covariance, a newly added bias scheme combined with observation bias, the application of a new bias correction for sea level anomaly, an extension of the assimilation window from 1 day to 2 days, and separate assimilations for ocean and sea-ice. For comparison, we present the difference between GODAPS and GODAPS2. The verification results show that GODAPS2 yields an overall improved simulation compared to GODAPS.

• 한국농공학회논문집
• /
• 제65권1호
• /
• pp.15-26
• /
• 2023

This study aimed to evaluate the performance of water level classification from CCTV images in agricultural facilities such as reservoirs. Recently, the CCTV system, widely used for facility monitor or disaster detection, can automatically detect and identify people and objects from the images by developing new technologies such as a deep learning system. Accordingly, we applied the ResNet-50 deep learning system based on Convolutional Neural Network and analyzed the water level of the agricultural reservoir from CCTV images obtained from TOMS (Total Operation Management System) of the Korea Rural Community Corporation. As a result, the accuracy of water level detection was improved by excluding night and rainfall CCTV images and applying measures. For example, the error rate significantly decreased from 24.39 % to 1.43 % in the Bakseok reservoir. We believe that the utilization of CCTVs should be further improved when calculating the amount of water supply and establishing a supply plan according to the integrated water management policy.

• 한국지리정보학회지
• /
• 제14권3호
• /
• pp.36-51
• /
• 2011

본 연구의 목적은 지리정보를 활용하여 기후변화에 따른 지하수 함양량 산정 모델 개발 및 검증을 수행하는 것이다. 이를 위하여 기후변화에 따른 지하수 함양량 변화를 산정하는 방법론을 제시하였고, 지리정보시스템을 활용하여 연구지역의 시기별 미래 지하수 함양량을 추정하였다. 연구지역은 낙동강 본류를 포함하는 낙동강 유역을 선정하였다. 최종 연구결과는 미래 기후변화에 따른 시기별 강우량, 함양률, 함양량을 추정하였다. 함양량 및 함양률은 기후변화에 따른 강우량의 변화와 함께 변화하는 추세를 나타내고 있는 것으로 파악되었다. 본 연구에서는 지리정보를 활용하여 기존에 기후변화와 지하수 함양량의 불명확한 관계를 정량적으로 분석하였으며, 미래 기후변화 예측 결과를 반영한 연구지역 내 지하수 함양률 변화를 시-공간적으로 산정하였다. 또한 유역내 기저유출량과 비교 분석을 통하여 검증하였다. 앞으로 연계모델의 고도화 방안 및 현장조사가 추가 된다면 보다 정량적으로 기후변화와 지하수 함양량의 상관관계를 파악 할 수 있으며, 향후 본 연구는 수자원으로 이용이 증가되는 지하수의 전반적인 관리 및 효율적인 운영 체제 구축을 위한 한 축을 차지 할 수 있다는 점에서 중요성이 있다고 하겠다.

• 대한안전경영과학회지
• /
• 제8권6호
• /
• pp.1-11
• /
• 2006

Since Zohar(1980) emphasized the influence of social, organizational, and psychological context in occupational safety and health study, the research in this area tends to be emphasizing the influences of personal and physical interaction. With this research trend, this paper is to examine the relationship between safety climate model and safety accident, and the interactional or moderating effect of personal and physical factor on the above relationship. Author conducted a survey to 292 manufacturing workers in construction industry, and the chief results of statistical analysis are as follows 1) management involvement, safety education, precaution activities, and safety system have negative effects on safety accident, 2) a-type personality has interactional effect on safety accident with communication, precaution activities, and safety system. 3) physical job load has interactional effect on safety accident with precaution activities, and safety system.

• 대한안전경영과학회지
• /
• 제6권4호
• /
• pp.11-24
• /
• 2004

Recently occupational safety and health literatures begin to emphasize the influence of social, organizational or psychological context. Based on this research trend, this paper tried to review the relationship between safety climates and safety compliance. Based on the responses from 385 manufacturing workers, this paper reviewed the relationships among safety climates, safety motivation, and safety compliance. The results of statistical analysis showed that all safety climate factors(management involvement, leadership, safety training, precaution activities, safety system) have affirmative effects on safety motivation and safety compliance. Also, safety motivation appeared to have mediating effects on the relationship between 5 safety climate factors and safety compliance. Especially it appeared to have full mediating effects on the relationship between safety training/ safety system and safety compliance.

• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 2006년도 추계공동학술대회
• /
• pp.151-160
• /
• 2006

Since Zohar(1980) emphasized the influence of social, organizational, and psychological context in occupational safety and health study, the research in this area tends to be emphasizing the influences of personal and physical interaction. With this research trend, this paper is to examine the relationship between safety climate model and safety accident, and the interactional or moderating effect of personal and physical factor on the above relationship. Author conducted a survey to 292 manufacturing workers in construction industry, and the chief results of statistical analysis are as follows : 1) management involvement, safety education, precaution activities, and safety system have negative effects on safety accident, 2) a-type personality has interactional effect on safety accident with communication, precaution activities, and safety system. 3) physical job load has interactional effect on safety accident with precaution activities, and safety system.