• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.94-94
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• 2020

최근 정부의 신북방정책 추진에 따라 수자원분야에서는 동북아지역 국제 공유하천을 중심의 물 정보 및 연구협력 기회 확보와 지정학적 특성을 고려한 지역 현안해결 중심의 연구가 재조명 되고 있다. 두만강은 이러한 동북아의 중심에 위치하고 있으며, 중국, 북한, 러이사의 국경을 따라 흐르며 지역 수자원의 대부분을 공급하는 국제하천이다. 또한, 지난 2018년 5월에는 하구유역이 람사르(Ramsar) 습지로 승인됨에 따라 철새 등을 포함한 생태가치의 중요성도 크게 증가하였다. 하지만 이 지역은 유역의 지정학적 민감성과 접근이 제한된 관측 정보들로 인해 그 수자원·환경 효용성을 정확하게 파악할 수 없을 뿐만 아니라, 최근 기후변화에 따른 영향으로 홍수, 가뭄 등의 수재해와 수질오염 등의 문제가 발생하고 있어 가용한 기술기반의 직·간접적 접근을 통한 장기수문 및 환경변화 등에 대한 분석과 관리방안 수립 등의 연구가 필요하다. 본 연구에서는 이러한 미계측 두만강 유역을 대상으로 우선, 가용한 위성자료 및 광역지표모형(MERRA-2) 기반 NASA POWER(Prediction of Worldwide Energy Resource) 수문기상 자료와 SWAT(Soil and Water Assessment Tool) 모형을 활용하여 장기 수문영향을 평가하고자 한다. SWAT 모형은 전 지구적으로 활용 가능한 격자 해상도 약 30m의 위성기반 수치표고모형(DEM), 광역 토양도, 지역 토지이용도 자료를 활용하여 두만강 유역을 전체 19개 소유역 및 18개 하도, 138개 HRUs의 수문분석 단위로 구축하였으며, 모의는 미국 NOAA NCDC(National Climate Data Center) 및 중국 CMDC(China Meteorological Data Service Center)의 주요 관측지점에서 선별한 총 13개소의 위치에 대해 재분석된 기후/기상자료들(NASA POWER 강수, 기온, 풍속, 상대습도 및 일사량)을 적용, 1990년에서 2019년까지의 30개년도 연속자료를 구축활용 하였다. 한편, 모형의 검·보정은 앞서 언급한 관측 자료의 부재로 과거 문헌 등을 통해 파악할 수 있는 연 단위 수자원 총량 등을 활용해 진행코자한다. 아울러, 향후는 최근 활용 가능한 장기 위성관측 강수량을 적용, 재분석 자료 결과와의 비교를 통해 상호 분석 오류를 줄여나갈 수 있을 것으로도 판단된다.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.1-16
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• 2007

The use of information on natural resources is indispensable to most agricultural activities to avoid disasters, to improve input efficiency, and to increase lam income. Most information is prepared and managed at a spatial scale called the "Hydrologic Unit" (HU), which means watershed or small river basin, because virtually every environmental problem can be handled best within a single HU. South Korea consists of 840 such watersheds and, while other watershed-specific information is routinely managed by government organizations, there are none responsible for agricultural weather and climate. A joint research team of Kyung Hee University and the Agriculture, forestry and Fisheries Information Service has begun a 4-year project funded by the Ministry of Agriculture and forestry to establish a watershed-specific agricultural weather information service based on "high definition" digital climate maps (HD-DCMs) utilizing the state of the art geospatial climatological technology. For example, a daily minimum temperature model simulating the thermodynamic nature of cold air with the aid of raster GIS and microwave temperature profiling will quantify effects of cold air drainage on local temperature. By using these techniques and 30-year (1971-2000) synoptic observations, gridded climate data including temperature, solar irradiance, and precipitation will be prepared for each watershed at a 30m spacing. Together with the climatological normals, there will be 3-hourly near-real time meterological mapping using the Korea Meteorological Administration's digital forecasting products which are prepared at a 5 km by 5 km resolution. Resulting HD-DCM database and operational technology will be transferred to local governments, and they will be responsible for routine operations and applications in their region. This paper describes the project in detail and demonstrates some of the interim results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Current Research on Agriculture and Life Sciences
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• v.3
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• pp.28-35
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• 1985

This work Was carried out to obtain the most suitable crop coefficient for the paddy rice growing in Taegu area. The result was due to the comparative measurements of evapotranspiration formula in terms of Blaney & Criddle and eight other formulas with those produced by experiment particularly in this area. The crop coefficient, evapotranspiration and transpiration ratio produced by this research are hopefully expected to be of service in the future calculation of evapotranspiration without repeating experiment respectively, whenever the water requirement of paddy rice is planned in Taegu and its vicinity. The accomplished results could be summarized as follows : The maximum amount of evapotranspiration was recorded in the early and middle parts of August. The average reading of evapotranspiration was 6.33mm/day throughout the growth. The evapotranspiration had a highly significant correlation with pan evaporation, solar radiation, sunshine hours and relative humidity of meteorological elements. K and Kc by the use of Blaney & Criddle formula calculated at 0.76 to 1.45 and 0.82 to 1.27, respectively. Its peak value appeared commonly in early August. The ratio of transpiration was 269.03.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.71-84
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• 2004

There is a growing demand for agrometeorological information that end-users can use and not just interesting information. lo achieve this, each region/community needs to develop and provide localized climate and weather information for growers. Additionally, provide tools to help local users interpret climate forecasts issued by the National Weather Service in the country. Real time information should be provided for farmers, including some basic data. An ideal agrometeorological information system includes several components: an efficient data measuring and collection system; a modern telecommunication system; a standard data management processing and analysis system; and an advanced technological information dissemination system. While it is conventional wisdom that, Internet is and will play a major role in the delivery and dissemination of agrometeorological information, there are large gaps between the "information rich" and the "information poor" countries. Rural communities represent the "last mile of connectivity". For some time to come, TV broadcast, radio, phone, newspaper and fax will be used in many countries for communication. The differences in achieving this among countries arise from the human and financial resources available to implement this information and the methods of information dissemination. These differences must be considered in designing any information dissemination system. Experience shows that easy across to information more tailored to user needs would substantially increase use of climate information. Opportunities remain unexplored for applications of geographical information systems and remote sensing in agro meteorology.e sensing in agro meteorology.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.