• Korean Journal of Environment and Ecology
• /
• v.23 no.1
• /
• pp.50-55
• /
• 2009

To understand the status of the migrating Oriental Honey Buzzard(Pernis ptilorhynchus) in Korea, we carried out a preliminary study on the number and local movements of the Honey Buzzard from September 2005 to October 2007 at Hongdo Island, Jeonnam Province, Korea. A total of 702 Honey Buzzards in 2005, 404 individuals in 2006, and 659 individuals in 2007 were recorded during the fall migration season, but during the spring migration season only two and eight birds were observed in 2006 and 2007 respectively. The migrating Honey Buzzard showed peak numbers from 20 September to 5 October at the study site. According to observation of arrival time of538 Honey Buzzard in October 2007, a total of 2l6 birds(40.l %) were passing over Hongdo Island between 7:00 AM to 8:00 AM, rising skyward on columns of warm air. This suggests the use of thermal currents and avoidance of nocturnal movement for crossing water. They preferred moderate winds(<5 m/s in speed) from northwest, but the migrating number apparently decreased in case of strong winds (${\geqq}5 m/s$). This suggests that wind speed and direction are important environmental factors for migration of the Oriental Honey Buzzard. At present, it is unclear which breeding population(from north-eastern China or Japan) passes over Hongdo Island. Moreover, it is difficult to prove migration route and to understand migratory behaviors of the Oriental Honey Buzzard in Korea. To prove the breeding sites and routes of the migrants over the study site, we need more detailed and further studies such as satellite tracking researches.

• Journal of Korean Society of Forest Science
• /
• v.85 no.2
• /
• pp.210-224
• /
• 1996

The SLODSVAT consists of interrelated submodels that simulate : the transfer of radiation, water vapour, sensible heat, carbon dioxide and momentum in two canopy layers determined by environmental conditions and ecophysiological properties of the vegetation ; uptake and storage of water in the "root-stem-leaf" system of plants ; interception of rainfall by the canopy layers and infiltration and storage of rain water in the four soil layers. A comparison of the results of modeling experiments and field micro-climatic observations in a spruce forest(Picea abies [L].Karst) in the Soiling hills(Germany) shows, that the SLODSVAT can describe and simulate the short-term(diurnal) as well as the long-term(seasonal) variability of water vapour and sensible heat fluxes adequately to natural processes under different environmental conditions. It proves that it is possible to estimate and predict the transpiration and evapotranspiration rates for spruce forest ecosystems on the patch and landscape scales for one vegetation period, if certain meteorological, botanical and hydrological information for the structure of the atmospheric boundary layer, the canopy and the soil are available.

• Journal of Korea Water Resources Association
• /
• v.51 no.5
• /
• pp.425-438
• /
• 2018

Existing studies that analyze the causes and effects of water circulation use mostly rainfall - runoff models, which requires much effort in model development, calibration and verification. In this study, hydrological sensitivity analysis which can separate quantitatively the impacts by natural factors and anthropogenic factor was applied to the Hwacheon dam upper basin from 1967 to 2017. As a result of using various variable change point detection methods, 1999 was detected as a statistically significant change point. Especially, based on the hydrological sensitivity analysis using 5 Budyko based functions, it was estimated that the average inflow reduction amount by Imnam dam construction was $1.890\;billion\;m^3/year$. This results in this study was slightly larger than the those by existing researchers due to increase of rainfall and decrease of Hwacheon dam inflow. In future, it was suggested that effective water management measures were needed to resolve theses problems. Especially, it can be suggested that the monthly or seasonal analysis should be performed and also the prediction of discharge for future climate change should be considered to establish resonable measures.

• Journal of the Korean Geographical Society
• /
• v.51 no.5
• /
• pp.633-649
• /
• 2016

Exposure to high temperatures during the reproductive period of crops decreases their productivity. The Intergovernmental Panel on Climate Change's (IPCC) fifth Assessment Report predicts that the frequency of high temperatures will continue to increase in the future, resulting in significant impacts on the world's food supply. This study evaluate climate change-induced heat stress on four major agricultural crops (rice, maize, soybean, and wheat) at a global level, using the coupled atmosphere-ocean model of Hadley Centre Global Environmental Model version 2 (HadGEM2-AO) and FAO/IIASA Global Agro-Ecological Zone (GAEZ) model data. The maximum temperature rise ($1.8-3.5^{\circ}C$) during the thermal-sensitive period (TSP) from the baseline (1961-1990) to the future (2070-2090) is expected to be larger under a Representative Concentration Pathway (RCP) 8.5 climate scenario than under a RCP2.6 climate scenario, with substantial heat stress-related damage to productivity. In particular, heat stress is expected to cause severe damage to crop production regions located between 30 and $50^{\circ}N$ in the Northern Hemisphere. According to the RCP8.5 scenario, approximately 20% of the total cultivation area for all crops will experience unprecedented, extreme heat stress in the future. Adverse effects on the productivity of rice and soybean are expected to be particularly severe in North America. In Korea, grain demands are heavily dependent on imports, with the share of imports from the U.S. at a particularly high level today. Hence, it is necessary to conduct continuous prediction on food security level following the climate change, as well as to develop adaptation strategy and proper agricultural policy.

• Journal of Korea Water Resources Association
• /
• v.43 no.3
• /
• pp.309-323
• /
• 2010

As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

• Journal of Korea Water Resources Association
• /
• v.47 no.11
• /
• pp.1039-1050
• /
• 2014

The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

• Journal of Korea Water Resources Association
• /
• v.47 no.11
• /
• pp.1095-1105
• /
• 2014

A spatial downscaling method using the Support Vector Machine (SVM) Regression for 25 km Tropical Rainfall Measuring Mission (TRMM) Monthly precipitation is proposed. The nonlinear relationship among hydrometeorological variables and precipitation was effectively depicted by the SVM for predicting downscaled grid precipitation. The accuracy of spatially downscaled precipitation was estimated by comparing with rain gauge data from sixty-four stations and found to be improved than the original TRMM data in overall. Especially the positive bias of the original TRMM data was effectively removed after the downscaling procedure. The spatial distributions of 25 km and 1 km grid precipitation were generally similar, while the local spatial trend was better detected by 1 km grid precipitation. The downscaled grid data derived from the proposed method can be applied in hydrological modelling for higher accuracy and further be studied for developing optimized downscaling method incorporation other regression methods.

• Journal of Soil and Groundwater Environment
• /
• v.13 no.3
• /
• pp.27-36
• /
• 2008

This paper presents a comprehensive laboratory study that examines the effects of porosity, water content, density and grain size distribution on the thermal conductivity of soils which were sampled from 16 synoptic stations of Korea. The experimental results clearly demonstrate that porosity and water content are important parameters which strongly affect the thermal conductivity of soils. Soils with lower porosities and higher water contents have higher thermal conductivities. On the contrary, increase of the matrix density slightly increases the thermal conductivity, and grain size distribution hardly affects the thermal conductivity. Dry soils with the same porosity tend to have more scattered values of thermal conductivity than wet soils. Based on the experimental results, a multiple linear regression model and a nonlinear regression model, having two regression variables of porosity and water content, were presented to predict thermal conductivity. Both models show a high accuracy of prediction with $R^2$ values of 0.74 and 0.82, respectively. Thus, it is expected that the suggested empirical models can be used for predicting thermal conductivity of soils by measuring porosity and water content.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.13-13
• /
• 2023

디지털 기술은 오늘날 플랫폼과 디지털 트윈의 기술도입을 통해 현실 세계를 네트워크와 가상세계와의 연결이 통합되어진 가상 현실 세계의 입문 도약이다. 현실에서 가상현실의 사이의 디지털 전환(digital transformation)에는 디지털 기술과 솔루션을 비즈니스의 모든 영역에 통합하는 것이 포함된다. 이러한 디지털 전환의 핵심은 데이터에 관한 것이며, 데이터를 활용하여 가치를 창출하고 고객경험과 비즈니스 영역을 극대화하는 방식을 제공한다. 최적의 데이터를 제공하기 위한 플랫폼과 가상 현실세계 구현을 위한 디지털 트윈의 상호연계 관한 기본 개념은 데이터 수집, 데이터 분석, 데이터 시각화 및 데이터 보고와 같은 데이터 비즈니스이다. 현장 데이터는 디지털 양식을 통해 수집, 기록, 저장된다. 현장 IoT 기반 데이터(사진 및 비디오 매체 등)는 지속적으로 수집되고 종종 다른 데이터베이스에 저장되지만 지리 공간적 위치에 연결되지 않는다. 모든 디지털 발전을 조화시키고 지하수 데이터에서 더 빠른 이해를 도출하기 위해서는 디지털 트윈이 시작되어야 한다. 단일 지하수플랫폼에서 현장 조건을 시각화하고 실시간 데이터를 스트리밍하며, 과거 3D 데이터와 상호작용하여지질 또는 지화학 데이터를 선택적 사용을 위해 지하수 플랫폼과 디지털 트윈이 연계되어야 한다. 데이터를 디지털 정보모델과 연결하면 디지털 트윈에 생명을 불어넣을 수 있지만 디지털 트윈의 가치를 극대화하려면 여전히 데이터 플랫폼 서비스와 전달 방식을 선택해야 한다. 지하수 플랫폼동시성을 갖는 디지털 트윈은 정적 및 동적 데이터를 저장하는 데이터베이스 또는 크라우드 서비스에서 데이터를 가져오는 API(애플리케이션 프로그래밍 인터레이스), 디지털 트윈을 위한 호스팅 공간, 디지털 대상을 구축하는 소프트웨어, 구성 요소 간 읽기/쓰기를 위한 스크립트, chatGPT 및 API를 활용할 수 있다. 이를 통해 수집된 데이터의 실시간 양방향 통신기술인 지하수 플랫폼 기술을 활용하여 디지털 트윈을 적용하고 완성할 수 있고, 이를 지하수 분야에도 그대로 적용할 수 있다. 지하수 분야의 디지털 트윈 기술의 근간은 지하수 모니터링을 위한 관측장치와 이를 활용한 지하수 플랫폼의 구축 및 양방향 자료전송을 통한 분석 및 예측기술이다. 특히 낙동강과 같이 유역면적이 넓고 유역 내 지자체가 많아 이해관계가 다양하며, 가뭄과 홍수/태풍 등 기후위기에 따른 극한 기상이변가 자주 발생하고, 또한 보 및 하굿둑 개방 등 정부정책 이행에 따른 민원이 다수 발생하는 지역의 경우 하천과 유역에 대한 지하수 플랫폼과 디지털 트윈의 동시성 기술적용 시 지하수 데이터에 대한 고려가 반드시 수반되어야 한다.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.6
• /
• pp.91-98
• /
• 2023

The amount of power generation of a solar plant has a high correlation with weather conditions, geographical conditions, and the installation conditions of solar panels. Previous studies have found the elements which impacts the amount of power generation. Some of them found the optimal conditions for solar panels to generate the maximum amount of power. Considering the realistic constraints when installing a solar power plant, it is very difficult to satisfy the conditions for the maximum power generation. Therefore, it is necessary to know how sensitive the solar power generation amount is to factors affecting the power generation amount, so that plant owners can predict the amount of solar power generation when examining the installation of a solar power plant. In this study, we propose a polynomial regression analysis method to analyze the relationship between solar power plant's power generation and related factors such as weather, location, and installation conditions. Analysis data were collected from 10 solar power plants installed and operated in Daegu and Gyeongbuk. As a result of the analysis, it was found that the amount of power generation was affected by panel type, amount of insolation and shade. In addition, the power generation was affected by interaction of the installation angle and direction of the panel.