• 한국태양에너지학회 논문집
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• 제24권2호
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• pp.83-88
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• 2004

Since the solar radiation is the main input for sizing any solar photovoltaic system, it will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 at 16 different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar photovoltaic system users as well as by research institutes From the results, we can conclude that 1) The yearly averaged horizontal global insolation of Korea was turned out $3.57kWh/m^2.day$ in the periods of $1982\sim2001$. 2) Horizontal global insolation of spring and summer was respectively 24 % and 21 % higher than the yearly average value, and that of fall and winter was respectively 12 % and 34 % lower than the yearly average value.

• 생태와환경
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• 제44권4호
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• pp.337-346
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• 2011

We investigated nutrient loading and trophic states in a coastal estuarine system in the Asan estuary by assessing phytoplankton biomass and using the trophic index (TRIX). The monthly and yearly nutrient loading (TN, TP) from freshwater discharge from the Asan and Sapgyo reservoirs into the estuary were estimated and analyzed with related factors. Monitoring data (physio-chemical and biological variables) collected at five estuary stations were used to assess trophic states. Descriptive statistics of total phytoplankton cells, chl a concentrations and primary productivity were also used to assess seasonal trophic status. N loading from freshwater ranged $1.0{\sim}1.3{\times}10^4$ ton yearly. The yearly P loading ranged between 350 and 400 ton during 2004~2006, increasing to 570 ton in 2007. Regression results suggest that DIN and DSi were correlated with freshwater discharge at the upper region. Based on phytoplankton biomass and total cell abundance, the trophic state of the estuary was found to be eutrophic during spring due to phytoplankton bloom. Primary productivity level was remarkably high, especially in summer coinciding with high nutrient loading. Pheopigments increased during warm seasons, i.e. summer and fall. Trophic index results indicate that the trophic state varied between mesotrophic and eutrophic in the estuary water body, especially in the upper region. The results suggest that phytoplankton production was regulated by nutrient loading from freshwater whereas biomass was affected by other properties than nutrient loading in the Asan Estuary ecosystem.

• 태양에너지
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• 제20권2호
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• pp.19-30
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• 2000

Since the solar radiation is the main input for sizing any solar system, it will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has began collecting horizontal global insolation data since May, 1982 at 16 different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar system users as well as by research institutes. From the results, we can conclude that 1) The yearly averaged horizontal global insolation of Korea was turned out $3,042kcal/m^2.day$ in the periods of $1982\sim1999$. 2) Horizontal global insolation of spring and summer were 24 % and 21 %, higher than the yearly average value, respectively, and for fall and winter, their values were 12 % and 34 % lower than the yearly average value, respectively.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2000년도 춘계임시총회 및 학술발표대회
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• pp.26-33
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• 2000

This study was conducted to investigate the relationships between yearly variations of elimatic elements and yearly variations of productivity in potato. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 9 years from 1987 to 1995. The meteorological data what gathered at the Goheung Weather Station for the same period of crop growing season were used to find out the relationships between climatic elements and crop productivity. Yearly variation of the daily minimum temperature in March and April were large with coefficients of variation (C.V.) of 126.0%, 368%, respectively, but the variation of the daily mean and maximum temperature in May and June were relative small. Stem length and number of stem show more C.V. of 9.3%, 14.3%, respectively, but the variation of the yield was relative small with 3.7%. Correlation coefficients between the amount of precipitation in April and yield, yield and daily mean temperature in June were negatively significant at the level of 5, 1 %, respectively. Correlation coefficients between the growth habits and yield are positively significant at the level of 5, 1 %, respectively. Simple linear regression equations by the least square method are estimated for stem length (Yl) and the precipitation in April(X) as Y,=82.47-0.11x (R2=0.3959), and for yield(Y2) and the precipitation in April(X) as Y,=2003.61-0.94X (R2=0.5418).

• Plant Resources
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• 제6권3호
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• pp.178-182
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• 2003

This study was conducted to investigate the relationship between yearly variations of climatic elements and yearly variations of productivity in perilla. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1991 to 2000. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly variation of the amount of precipitation in September was large with coefficients of variation(c. v.) of 11.1%, but the coefficient of variance(c. v.) in July and August were relative small with 1.8, 2.1%, respectively. Number of cluster per hill and weight of 1,000 grains were greatly with c. v. of 76.1, 79.3%, respectively, but the coefficients of variance(c. v.) of plant height and seed yield were more less with 9.58, 10.60%, respectively. Correlation coefficients between precipitation of September and seed yield were positively significant correlation at the level of 5.1%, respectively, but the duration of sunshine in September and seed yield were negatively significant at the level of 5.1%, respectively. Correlation coefficients of these, the plant height, number of branches per plant, cluster length, number of cluster per hill, weight of 1,000 grains and seed yield were positively significant at the level of 5.1% respectively.

• 조명전기설비학회논문지
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• 제22권12호
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• pp.10-19
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• 2008

광센서 조광제어시스템은 유용한 주광의 실내유입을 통하여 인공조명의 에너지를 절감하는 시스템이나, 쉐이팅시스템에 의한 주광유입의 차단으로 인하여 그 적용성은 미비하다. 따라서 광센서 조광제어시스템의 적용성 및 에너지 절감량 향상을 위해서는 자동롤러쉐이딩 시스템과의 통합은 필수적이다. 본 연구는 두 시스템을 통합한 주광이용 조광제어시스템의 적용성 향상을 위하여 시스템 적용 시 에너지 절감량을 예측할 수 있는 프로세스를 개발하고 이를 사례에 적용하였다. 개발된 프로세스는 주광이용 조광제어시스템의 초기투자비용 환수 및 시스템 적용을 위한 타당성 분석의 자료로 이용될 것이다.

• 한국농림기상학회지
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• 제18권3호
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• pp.109-119
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• 2016

본 연구는 우리나라의 대표 활엽수종 중의 하나인 신갈나무를 대상으로 기후변화에 의한 연도별 생장도일의 변화가 잠재분포 및 생장에 미치는 영향을 평가하기 위해 수행하였다. 이를 위해 신갈나무 분포 지역의 기후특성을 반영한 군집분석을 실시하였으며, 그 결과 7개의 기후군집으로 분류되었다. 각 군집에 포함된 시군에서 수집된 일평균기온 자료를 기반으로 1951년부터 2010년까지 60년 동안의 연도별 생장도일과 기온효과지수를 산출함으로써 시간 경과에 따른 신갈나무의 잠재분포 범위와 생장의 변화 추이를 평가하였다. 이와 함께 기후변화 시나리오 RCP 4.5와 RCP 8.5를 적용하여 2011년부터 2100년까지 연도별 생장도일과 온도효과지수를 산출하여, 기후변화에 의한 신갈나무의 잠재분포 범위와 생장의 변화를 예측하였다. 신갈나무가 현재 분포하고 있는 지역의 생장도일을 연도별로 산출하여 비교한 결과 위도와 해발고도가 낮은 지역은 시간이 경과함에 따라 신갈나무에 적합한 생육가능 범위를 벗어나는 것으로 분석되었다. 특히 기후변화 시나리오를 적용할 경우 지속적인 기온의 상승으로 인해 2050년 이후에는 잠재분포의 변화뿐만 아니라 생장에도 큰 지장을 주는 것으로 평가되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1207-1210
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• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the only historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1215-1218
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• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training data consist of the mixed data The mixed data involves the historic data and the generated data using PARMA (1,1). And, the testing data consist of the only historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1211-1214
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• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training data consist of the generated data using PARMA (1,1). And, the testing data consist of the historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.