• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.141-141
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• 2020

강원도는 산림 비중이 크고 급경사지가 많은 지형적 특성과 여름철 비교적 선선하고 강우량이 많은 기후적 특성 때문에 고랭지 농업이 활발히 이루어지고 있다. 하지만, 많은 부분을 차지하는 고랭지밭 면적 탓에 강우시에 토양침식과 비점오염물이 하천으로 유입되고 있다. 강원도 송천 상류에 위치한 도암호는 장기간 탁수를 저류하고 방류로 인한 해체 논란까지 일으키기도 했다. 이에 정부는 흙탕물 저감과 비점오염원 관리를 위한 국고보조사업과 다양한 환경 정책들을 시행중이다. 효율적이고 효과적인 수질 정책을 시행하고 분석하기 위해서는 장기간의 모니터링 자료를 이용한 통계적 분석을 활용하는 것이 중요하다. 수질 자료는 변동이 심하고, 비정규분포를 이루며 결측치와 검출한계 이하의 값들이 많아 비모수 통계 방법을 널리 사용되어 왔다. 그중에서도 계절적 특성을 갖는 수질자료의 장기경향분석에 적합한 Seasonal Mann-Kendall Test을 사용하여 남한강상류 유역의 수질 경향성을 분석하였으며, Sen's Slope를 구하여 수질 자료의 경향 크기를 구하였다. 하지만, Seasonal Mann-Kendall Test는 연구 기간동안의 경향성을 반영할 수 없다는 단점이 있기 때문에 LOWESS Test를 통해 장기간 수질 자료 사이의 경향성을 분석하였다. 이러한 수질자료의 경향 분석 결과는 유역 내 취약 지점을 확인할 수 있으며, 환경 정책의 효과를 평가하고 보완할 수 있는 자료로 이용될 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.333-333
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• 2022

본 연구는 저빈도·고강도의 확률강우량 산정을 위해, 대규모 기후 앙상블 모의실험 기반으로 생성된 d4PDF(Data for Policy Decision Making for Future Change)를 적용하는 것을 목적으로 수행되었다. 또한, d4PDF 를 이용하여 산정된 확률강우량과 관측자료 및 빈도해석을 통해서 산정된 확률강우량을 비교함으로써 빈도해석의 적용에 따라 발생하는 불확실성을 분석하였다. 이와 같은 연구는 용담댐에 위치한 금산, 임실, 전주, 장수 관측소를 대상으로 수행되었다. d4PDF 자료는 총 50 개의 앙상블로 구성되어 있으며, 하나의 앙상블은 60 년 동안의 기상자료를 제공하기 때문에 한 지점에서 3,000 개의 연 최대 일 강우량을 수집 및 활용하는 것이 가능했다. 이와 같은 d4PDF 의 특징을 토대로 본 연구는 빈도해석 방법을 적용하지 않고, 3000 개의 연 최대 일 강수량을 비모수적 접근법(Non-parametric approach)에 따라 규모별로 나열하여, 10 년부터 1000 년의 재현기간을 갖는 확률강우량을 산정했다. 그 후, 관측 자료와 Gumbel 및 GEV(General extreme value) 분포를 토대로 산정된 확률강우량과의 편차를 산정하였다. 그 결과, 재현기간과 관측 기간의 차이가 증가할수록 이 편차가 증가하였으며, 이 결과는 짧은 관측 기간과 빈도해석의 적용은 재현기간이 증가할수록 신뢰하기 어려운 확률강우량을 제시한다는 것을 의미한다. 반면에, d4PDF 는 대규모 표본을 이용함으로써 이와 같은 불확실성을 최소화시켜 합리적인 저빈도·고강도의 확률강우량을 제시하였다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.1
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• pp.42-54
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• 2016

It is highly anticipated that warming temperature resulting from global climate change will affect the phenological pattern of kiwifruit, which has been commercially grown in Korea since the early 1980s. Here, we present the potential impacts of climate change on the variations of flowering day of a gold kiwifruit cultivar, Haegeum, in the Jeonnam Province, Korea. By running six global climate models (GCM), the results from this study emphasize the uncertainty in climate change scenarios. To predict the flowering day of kiwifruit, we obtained three parameters of the 'Chill-day' model for the simulation of Haegeum: $6.3^{\circ}C$ for the base temperature (Tb), 102.5 for chill requirement (Rc), and 575 for heat requirement (Rh). Two separate validations of the resulting 'Chill-day' model were conducted. First, direct comparisons were made between the observed flowering days collected from 25 kiwifruit orchards for two years (2014-15) and the simulated flowering days from the 'Chill-day' model using weather data from four weather stations near the 25 orchards. The estimation error between the observed and simulated flowering days was 5.2 days. Second, the model was simulated using temperature data extracted, for the 25 orchards, from a high-resolution digital temperature map, resulting in the error of 3.4 days. Using the RCP 4.5 and 8.5 climate change scenarios from six GCMs for the period of 2021-40, the future flowering days were simulated with the 'Chill-day' model. The predicted flowering days of Haegeum in Jeonnam were advanced more than 10 days compared to the present ones from multi-model ensemble, while some individual models resulted in quite different magnitudes of impacts, indicating the multi-model ensemble accounts for uncertainty better than individual climate models. In addition, the current flowering period of Haegeum in Jeonnam Province was predicted to expand northward, reaching over Jeonbuk and Chungnam Provinces. This preliminary result will provide a basis for the local impact assessment of climate change as more phenology models are developed for other fruit trees.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.678-688
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• 2021

This study was conducted to provide growth characteristics and stand information in preparation for natural regeneration method and silvicultural treatment of seed tree method in Korean red pine stands by using the field inventoried data 18 years after the seed tree regeneration method in 2001 and analyzing the stand and sapling characteristics. The study area was located in the Research Forest of Kangwon National University, Chuncheon-si, Gangwon-do. In November 2018, we collected tree measurement factors, such as diameter at breast height (DBH), height, crown class, stem quality, tree age, and annual height increment on the established plots. We calculated the basal area, volume, height-diameter ratio (HD ratio), and additional stand density variables such as the relative density and %stocking to analyze the managed stands. The number of mother trees was 58 trees/ha, with a 17.7% stocking level, whereas the number of saplings was 2,330 trees/ha, with a 79.0% stocking level. In germination, the age distribution of saplings ranged from 2001 to 2007, with most belonging to 15-16 years. The development condition of saplings was 10 cm in DBH and 8 m in height. DBH and height were higher as the crown class is more dominant, and this difference was statistically significant in the analysis of variance and Duncan's multiple comparison test (p<0.0001). HD ratio ranged mostly between 80% and 90%, and more than 95% of sapling stems were of high quality, with a straight, unbroken top, non-sweep, and non-diseased stem. On average, the annual height increment of saplings was 21.9 cm at 1 year, 43.3 cm at 5 years, 54.3 cm at 10 years, and 64.3 cm at 15 years. The overall height growth with age increased smoothly. According to the analysis of covariance, the annual height growth by crown class differed significantly. The regression analysis parameters revealed that annual height growth increased with age and dominant crown class.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1239-1247
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• 2009

Study the gene about economical characteristic of human disease or domestic animal is a matter of grave interest, preserve and elevation of gene of Korea cattle is key subject. Studies have been done on the gene of Korea cattle using EST based SNP map, but it is based on statistical model, therefore there are difference between real position and statistical position. These problems are solved using both EST_based SNP map and Gene on sequence by Lee et al. (2009b). We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, method is suggested E-MDR method using CART algorithm. Also we identified interaction effects of single nucleotide polymorphisms(SNPs) responsible for average daily gain(ADG) and marbling score(MS) using E-MDR method.

• Journal of Korean Society of Forest Science
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• v.69 no.1
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• pp.51-55
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• 1985

Pinus thunbergii ${\times}$ P. massoniana $F_1$ hybrids were made by pollinating 15 years old Japanese black pine (P. thunbergii) with Masson pine (P. massoniana) pollen, air-shipped from Taiwan. The crossability between two species were observed. Seedling height, morphological characteristics, and the composition of phenolic compounds of these hybrids and the open-pollinated progenies of P. thunbergii were investigated. The results of the observation were as follows; 1) Number of the hybrid seeds per cone was 2.3, while open-pollinated Japanese black pine produced 26 seeds per cone. 2) All hybrid seedlings outgrew P. thunbergii, averaging 151% of mean height of Japanese black pine seedlings. The growth of hybrids was much variable, ranging from 120% to 208% of mean height of the open-pollinated progenies of P. thunbergii. 3) With regard to needle characteristics, the hybrid needles were longer and softer than those of P. thunbergii. The color of hybrid needles showed yellowish green. The positions of resin ducts in P. thunbergii observed medial, while those of hybrids showed medial and external. 4) No large difference in phenolic compound composition between hybrid and P. thunbergii was found, but phenolic compound of unknown 4 and 6 were observed only in hybrid. Further intensive work is recommended in this area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.194-204
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• 2020

Cultivar parameters, which are key inputs to a crop growth model, have been estimated using observation data in good quality. Observation data with high quality often require considerable labor and cost, which makes it challenging to gather a large quantity of data for calibration of cultivar parameters. Alternatively, data in sufficient quantity can be collected from the reports on the evaluation of cultivars by region although these data are of questionable quality. The objective of our study was to assess the quality of crop and management data available from the reports on the regional adaptation trials for rice cultivars. We also aimed to propose the measures for improvement of the data quality, which would aid reliable estimation of cultivar parameters. DatasetRanker, which is the tool designed for quantitative assessment of the data for parameter calibration, was used to evaluate the quality of the data available from the regional adaptation trials. It was found that these data for rice cultivars were classified into the Silver class, which could be used for validation or calibration of key cultivar parameters. However, those regional adaptation trial data would fall short of the quality for model improvement. Additional information on management, e.g., harvest and irrigation management, can increase the quantitative quality by 10% with the minimum effort and cost. The quality of the data can also be improved through measurements of initial conditions for crop growth simulations such as soil moisture and nutrients. In addition, crop model improvement can be facilitated using crop growth data in time series, which merits further studies on development of approaches for non-destructive methods to monitor the crop growth.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.66-76
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• 2019

Recently, natural disasters such as floods and droughts are frequently occurred due to climate change and the damage is also increasing. Wetland is known to play an important role in reducing and minimizing the damage. In particular, water level variability needs to be analyzed in order to understand the various functions of wetland as well as the reduction of damage caused by natural disaster. Therefore, in this study, we fitted water level series of Upo wetland in Changnyeong, Gyeongnam province to a proper time series model and residual test was performed to confirm the appropriateness of the model. In other words, ARIMA model was constructed and its residual tests were performed using existing nonparametric statistics, BDS statistic, and Close Returns Histogram(CRH). The results of residual tests were compared and especially, we showed the applicability of CRH to analyze the residuals of time series model. As a result, CRH produced not only accurate randomness test result, but also produced result in a simple calculation process compared to the other methods. Therefore, we have shown that CRH and BDS statistic can be effective tools for analyzing residual in time series model.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.97-105
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• 2005

In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.

• Journal of Animal Science and Technology
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• v.54 no.4
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• pp.275-282
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• 2012

The data including milk yields, fat and protein percent for 628,395 heads collected by National Agricultural Cooperative Federation, 15 type traits and final score for 62,262 heads collected by Korea Animal Improvement Association, which were born in 1998 to 2004, and net profits calculated from milk price and raising expenses of individuals were used to estimate genetic parameters. The highest positive genetic correlation, 0.81, was shown between body depth (BD) and loin strength (SR). Genetic correlations between body depth (BD) and udder depth (UD), front teat placement (TP) and front teat length (TL) were -0.23, which were lowest among the linear type traits. Furthermore, medium level of negative genetic correlations were shown the milk yield with milk contents rate traits. Mostly low level of positive genetic correlations were shown between the milk traits and linear score traits except milk yield and stature. Most of the genetic correlations of between the linear score traits and net profit were low level of positive or negative genetic correlations. Among the genetic correlations, body depth (BD), angularity (DF) and rear attachment width (UW), and final score (FS) with net profit were high as 0.17, 0.17, 0.18 and 0.18, respectively. Finally all of the genetic correlations between net profit and milk traits were positive and higher than the linear traits with positive genetic correlations. The results of this study suggest that net profit has been related with the linear traits, such as body depth (BD), angularity (DF) and rear attachment width (UW) traits, and furthermore, milk traits including yield and contents rates influence positively and greatly on net profit.