• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.513-521
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• 2019

With rapid climate change and increasing global warming, the distribution of evergreen broad-leaved trees (EBLTs) is gradually expanding to the inland regions of Korea. The aim of the present study was to analyze the survival rate of 148 EBLT plantations measuring 180 ha and to determine the optimal plantation size that would help in coping with climate change in the warm, temperate climate zone of the Korean peninsula. For enhancing the reliability of our estimated survival model, we selected a set of 11 control variables that may have also influenced the survival rates of the EBLTs in the 148 plantations. The results of partial correlation analysis showed that the survival rate of 67.0±26.9 of the EBLTs in the initial plantation year was primarily correlated with plantation type by the crown closure of the upper story of the forest, wind exposure, and precipitation. For predicting the probability of survival by quantification theory, 148 plots were surveyed and analyzed with 11 environmental site factors. Survival rate was in the order of plantation type by the crown closure of upper story of the forest, wind exposure, total cumulative precipitation for two weeks prior to planting, and slope stiffness in the descending order of score range in the estimated survival model for the EBLTs with the fact that survival rate increased with shade rate of upper story to some extent.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.348-356
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• 2016

Carbon dioxide ($CO_2$) gases concentration in atmosphere has been growing since preindustrial times. By sequestering a large amount of atmospheric carbon (C), terrestrial ecosystems are thought to offer a mitigation strategy for reducing global warming. Woody agro-ecosystems such as fruit tree are among the least quantified and most uncertain elements in the terrestrial carbon cycle. $CO_2$ and energy fluxes were measured by the eddy covariance method on a 15-year old apple orchard of South Korea in 2006. Environmental parameters (net radiation, precipitation, etc.) were measured along with fluxes. The results showed that during late June, the ability to sequestrate C was significant at an apple orchard ecosystem and it reached on the peak of $-6.5g\;C\;m^{-2}\;d^{-1}$. We found that in the apple orchard, the daily average of net ecosystem exchange of $CO_2$ (NEE) and cumulative NEE on a yearly basis were $-1.1g\;C\;m^{-2}$ and $-396.9g\;C\;m^{-2}$, respectively. These results reveal that there is high carbon sequestration in the apple orchard of South Korea, which is the same magnitude with repect to that of a natural forested ecosystem of the same biome rank (temperate-humid deciduous forest).

• Research in Plant Disease
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• v.24 no.3
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• pp.182-192
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• 2018

Since fire blight (Erwinia amylovora) firstly broke out at mid-Korea in 2015, it is necessary to investigate potential spread of the invasive pathogen. To speculate environmental factors of fireblight epidemic based on disease triangle, a fire blight predicting program, MARYBLYT, was run with the measured meteorological data in 2014-2017 and the projecting future data under RCP8.5 scenario for 2020-2100. After calculating blossom period of Singo pear from phenology, MARYBLYT was run for blossom blight during the blossom period. MARYBLYT warned "Infection" blossom blight in 2014-15 at Anseong and Cheonan as well as Pyungtak and Asan. In addition, it warned "Infection" in 2016-17 at Naju. More than 80% of Korean areas were covered "Infection" or "High", therefore Korea was suitable for fire blight recently. Blossom blight for 2020-2100 was predicted to be highly fluctuate depending on the year. For 80 years of the future, 20 years were serious with "Infection" covered more than 50% of areas in Korea, whereas 8 years were not serious covered less than 10%. By comparisons between 50% and 10% of the year, temperature and amount of precipitation were significantly different. The results of this study are informative for policy makers to manage the alien pathogen.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.221-221
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• 2019

기후변화로 인한 가뭄대비가 상시체제가 된 요즈음, 농업용수의 안정적인 공급을 위하여 가뭄 등의 비상시 지표수는 물론이고 지하수의 공급 가능량에 대해서도 국가적 관리가 필요한 실정이다. 지하수관리를 위해 국가 최상위 계획인'지하수관리기본계획(2012~2021)'이 수립되었고, 지하수의 장기적인 수량, 수질 관리를 위해 국가지하수관측망, 지역지하수관측망(보조지하수관측망), 수질측정망, 해수침투관측망 등 광역과 지역단위로 크게 나누어 지하수관측이 이루어지고 있다. 국가지하수관측망은 지하수법에 의거하여 전국의 주요지점(2016년 말 기준 412개소)에 관측소를 설치하여 수위 및 수질의 변동실태를 광역적으로 분석함이 목적이며, 보조지하수관측망은 국가지하수관측망과 연계하고 보완하기 위한 기능으로서, 지역별 주요 관측지점의 수위, 수질자료를 획득하며, 2018년 9월 현재 3,429개소가 설치되어있다. 본 연구에서는 지역지하수 관측망 중 경남밀양지역에 설치된 관측정 31개소에 대해 수위와 수질을 장기 분석하였다. 밀양지역의 보조지하수관측망 설치는 지하수관리계획의 하부계획인'경상남도 지하수관리계획(2015~2025)'에 의거 2012년에 6개소의 관측공이 설치를 시작으로, 2013년 7개소, 2014년 10개소, 2015년 8개소를 설치하여 총 31개소의 설치를 완료하였고, 2016년부터 2019년 현재까지 전체 관측정 31개소에 대하여 관측 운영 중이다. 본 연구에서는 2013년 1월~2019년 1월까지 지역의 누적강수량과 지하수위 및 수질변화를 관측하였다. 전 관측정에 대해 수위(GL.m), 수질(온도, EC)은 1시간 주기로 관측하였으며, 연 2회 생활용수 기준(19항목)의 수질검사를 실시하고, 지하수성분의 지질학적 기원분석을 위한 양음이온 분석을 연 1회 실시하였다. 관측정의 양수능력 변화관측을 위해 대수성 시험을 연 1회 실시하였고, 관측정의 특성상 장기간 미사용 관정이므로 최적의 상태유지를 위해 연1회 공내세척을 실시하였다. 또한, 관측정의 지형별 차이를 분석하기 위해 관측정의 설치위치를 산악, 강변, 기타 지역으로 구분하고, 각각의 대표관정에 대해 지형에 의한 서로 다른 영향을 분석하였고, 관측정의 심도별 변화를 알기위해 동일지역에 충적, 안반 관측정을 따로 설치하고 관측하여 지표수와 지하수의 심도별 영향의 차이를 분석하였다. 동일지역의 관측결과 평균 5m이하의 수위변화를 보이나, 5m 이상의 수위변동을 보이는 관측망은 15년 14개소 17년 19개소로 증가추세를 보이며, 이는 주로 밀집된 시설하우스 단지의 수막재배를 위한 겨울철 지하수 사용량 증가가 원인인 것으로 판단된다. 밀양지역은 강변지역에 밀집된 시설하우스단지의 동절기 수막재배를 위한 지하수 과다사용으로 수위급감 및 수량부족현상이 반복되고 있어, 예방과 대책강구를 위해 지표수의 함양과 지하수사용량의 상관관계 분석과 자료축적 및 추가연구를 위한 장기관측이 요구된다.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.3
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• pp.193-203
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• 2019

The aim of this study was to analyze the relationship between rice yield and climate elements in Daegu (southern plain area) and Andong (inland mountainous area) regions. Over the past 20 years, rice yield has increased in both regions. The rice yield of middle and mid-late maturing cultivars in the recent 5 years increased by about 10% and 18%, respectively, compared to that produced in the early 2000s in the Daegu region. In the Andong region, the rice yield of mid-late maturing rice cultivars in the recent 5 years was higher by about 7% than that of the early 2000s. The number of panicles per hill and grain ripening rate significantly affected rice yield in mid-late maturing cultivars. In addition, the grain weight and grain ripening rate significantly affected rice production in middle maturing cultivars grown in the Daegu region. With regard to the middle maturing cultivars, the relationship between grain weight and rice yield had a positive significant correlation in both regions. To understand the effect of climate factors on rice yield, the milled rice yield of several rice cultivars produced over the past 20 years (1999-2018) at both locations, Daegu and Andong, were evaluated. The rice yields increased owing to long sunshine duration during the grain filling stage in the Daegu region. In Andong, rising maximum temperature during the vegetative stage increased rice yield of early and mid-late maturing cultivars. Long sunshine hours increased yield of mid-late maturing cultivars in both regions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.405-412
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• 2022

This paper studies the method of estimating power loss and classifying the factors for improving the power generation efficiency through O&M. It is installed under various climatic conditions worldwide, operational and maintenance technologies suitable for the characteristics of the installation location are required. Existing studies related to solar power generation efficiency have been actively quantifying the impact on short-term losses by environmental factors such as high temperature, dust accumulation, precipitation, humidity, and wind speed, but analysis of the overall impact from a long-term operation perspective is limited. In this study, the potential for efficiency improvement was analyzed by re-establishing a loss classification system according to the power flow of solar power to derive a comprehensive efficiency model for long-term operation and estimating power loss through a case study for each region where climate conditions are classified. As a result of the analysis, the average annual potential for improving soiling loss was 26.9%, Death Valley 7.2%, and Seoul 3.8%. Aging losses was 6.6% in the 20th year as a cumulative. The average annual potential due to temperature loss was 2.9 % for Doha, 1.9% for Death Valley, and 0.2% for Seoul.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.1-10
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• 2023

This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982-2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0-6 years) and number of cutting (NC, 2nd-5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.404-414
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• 2023

In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1125-1134
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• 2023

Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.

• Korean Journal of Environment and Ecology
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• v.36 no.2
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• pp.139-149
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• 2022

This study aimed to prepare basic data for protecting the habitat of Fairy Pitta Pitta nympha and coping with climate change by detecting songs with bio-acoustic recording technology and identifying phenological characteristics in protected areas in Korea. The study sites were 36 protected areas nationwide. Data were collected between January and December 2019, and the analysis period was from May 1 to August 31, 2019. The main results are described as follows. Firstly, songs were detected in 22 out of 36 study sites. Frequency analysis results of songs show that high frequency was observed in southern inland, including Jeju island, and the area with the highest latitude was Seoraksan National Park. Secondly, the first song was observed in Hallyeohaesang National Park Geumsan on May 14, 2019, and the last song was observed in Ungok wetland in Gochang on August 6, 2019. Thirdly, circadian rhythm analysis results of songs show that the frequency rapidly increased at five o'clock in the morning, peaked at six o'clock, and then decreased afterward. Fourthly, seasonal cycle analysis results of songs show that they were observed from May 14, 2019 to August 6, and the day with the highest accumulated frequency of songs was June 3, 2019 (Julian date: 154). The average temperature of the day the songs were detected was 17.4℃, the average precipitation was 0.02mm, and the average humidity was 82.6%. Fifthly, a correlation analysis result between Fairy Pitta's songs and meteorological factors shows that temperature indicated a negative correlation with Fairy Pitta's songs (p<0.001), but precipitation (p=0.053) and humidity (p=0.077) did not indicate a statistical significance (df=471). This study is significant in that it confirmed the distribution of Fairy Pitta's songs using bio-acoustic recording technology in protected areas nationwide and identified their ecological characteristics by precisely analyzing the relationship between the song period and meteorological factors.