• 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.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.801-813
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• 2023

Recently, as studies about Artificial Neural Network (ANN) are actively progressing, studies for predicting water quality of rivers using ANN are being conducted. However, it is difficult to analyze the operation process inside ANN, because ANN is form of Black-box. Although eXplainable Artificial Intelligence (XAI) is used to analyze the computational process of ANN, research using XAI technology in the field of water resources is insufficient. This study analyzed Multi Layer Perceptron (MLP) to predict Water Temperature (WT), Dissolved Oxygen (DO), hydrogen ion concentration (pH) and Chlorophyll-a (Chl-a) at the Dasan water quality observatory in the Nakdong river using Layer-wise Relevance Propagation (LRP) among XAI technologies. The MLP that learned water quality was analyzed using LRP to select the optimal input data to predict water quality, and the prediction results of the MLP learned using the optimal input data were analyzed. As a result of selecting the optimal input data using LRP, the prediction accuracy of MLP, which learned the input data except daily precipitation in the surrounding area, was the highest. Looking at the analysis of MLP's DO prediction results, it was analyzed that the pH and DO a had large influence at the highest point, and the effect of WT was large at the lowest point.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.247-261
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• 2018

The purpose of this study is to evaluate the groundwater level behavior of Geum river basin ($9,645.5km^2$) under future climate change scenario projection periods (2020s: 2010~2039, 2050s: 2040~2069, 2080s: 2070~2099) using SWAT (Soil and Water Assessment Tool). Before future evaluation, the SWAT was calibrated and validated using 11 years (2005~2015) daily multi-purpose dam inflow at 2 locations (DCD, YDD), ground water level data at 5 locations (JSJS, OCCS, BEMR, CASS, BYBY), and three years (2012~2015) daily multi-function weir inflow at 3 locations (SJW, GJW, BJW). For the two dam inflow and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.57~0.67 and 0.87~0.94, and the coefficient of determination ($R^2$) was 0.69~0.73 and 0.63~0.73 respectively. For the three weir inflow and storage, the NSE was 0.68~0.70 and 0.94~0.99, and the $R^2$ was 0.83~0.86 and 0.48~0.61 respectively. The average $R^2$ for groundwater level was from 0.53 to 0.61. Under the future temperature increase of $4.3^{\circ}C$ and precipitation increase of 6.9% in 2080s (2070~2099) based on the historical periods (1976~2005) from HadGEM3-RA RCP 8.5 scenario, the future groundwater level shows decrease of -13.0 cm, -5.0 cm, -9.0 cm at 3 upstream locations (JSJS, OCCS, BEMR) and increase of +3.0 cm, +1.0 cm at 2 downstream locations (CASS, BYBY) respectively. The future groundwater level was directly affected by the groundwater recharge by the future seasonal spatial variation of rainfall in the watershed.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.257-264
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• 1991

Korea has accomplished the afforestation of its forest land in the early 1980's. To meet the increasing demand for forest products and forest recreation, a development of scientific forest management system is needed as a whole. For this purpose the development of efficient forestfire management system is essential. In this context, the purpose of this study is to develop a theoretical foundation of forestfire danger rating system. In this study, it is hypothesized that the degree of forestfire risk is affected by Weather Factor and Man-Caused Risk Factor. (1) To accommodate the Weather Factor, a statistical model was estimated in which weather variables such as humidity, temperature, precipitation, wind velocity, duration of sunshine were included as independent variables and the probability of forestfire occurrence as dependent variable. (2) To account man-caused risk, historical data of forestfire occurrence was investigated. The contribution of man's activities make to risk was evaluated from three inputs. The first, potential risk class is a semipermanent number which ranks the man-caused fire potential of the individual protection unit relative to that of the other protection units. The second, the risk sources ratio, is that portion of the potential man-caused fire problem which can be charged to a specific cause. The third, daily activity level is that the fire control officer's estimate of how active each of these sources is, For each risk sources, evaluate its daily activity level ; the resulting number is the partial risk factor. Sum up the partial risk factors, one for each source, to get the unnormalized Man-Caused Risk. To make up the Man-Caused Risk, the partial risk factor and the unit's potential risk class were considered together. (3) At last, Fire occurrence index was formed fire danger rating estimation by the Weather Factors and the Man-Caused Risk Index were integrated to form the final Fire Occurrence Index.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.143-151
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• 2010

The impact of climate change on rice plants in Gangwon province was examined by comparing the climatic conditions during the recent 10 years (2000~2009) with those of normal (1971~2000) years, and by evaluating the rice plant responses. The daily mean air temperature increased by $0.5^{\circ}C$ while the daily range decreased by $0.1^{\circ}C$ as compared with the normal years. During the main rice growing period in field (from June to September) precipitation increased from 900 to 1,051mm and sunshine hours decreased from 704 to 619 hours. The respiration consumption effect during the rice growing period increased by 0.07 as a result of increased air temperature and reduced sunshine hours. The optimum heading date (determined by the mean air temperature for 40 days after the heading) was delayed in Chuncheon, Hongcheon, Wonju, and Gangneung compared with the normal. The maximum climatic yield potential based on mean temperature and sunshine hours for 40 days after the rice heading decreased by 94 kg/10a mainly due to the decrease in sunshine. The mean air temperature for 40 days after the rice heading from 1999 to 2009 in Chuncheon, Cheorwon, and Gangneung was generally above $22^{\circ}C$ implying that yield and quality of rice can be reduced. Therefore, it is necessary to delay the heading date by planting mid- to late-maturing varieties or by changing the transplanting date in order to produce high quality rice and to maintain rice productivity. In addition, it is also important to develop or select cultivars suitable to changing climate for each region in Gangwon province.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.188-194
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• 2007

The relationships between pine mushroom emergence and meteorological factors were analyzed with three years (from 2003 to 2005) of measurement data at Yangyang site, in order to evaluate the effect of micrometeorological environment on pine mushroom production. fine mushroom was daily monitored and collected in the survey area during the its producing period (approximately one month). Pine mushroom production was highest in 2005 with the meteorological conditions of high temperature and frequent rainfalls in October. The production was lowest in 2004 due to dry conditions from mid September to late October, The meterological factors related to humidity (i.e., relative humidity, soil water content, and precipitation) were better correlated than those related to temperature (i.e., air and soil temperature, soil heat flux and solar radiation) with pine mushroom production. However, all of the correlation coefficients were statistically insignificant with values ranging from 0.15 to 0.46. Such poor correlations may be attributed to various other environmental conditions (e.g., topography, soil, vegetation, other fungi, the relationship between pine mushroom and pine forest) affecting pine mushroom production. We found that a mycelium requires a stimulation of low temperature (of three-day moving average) below $19.5^{\circ}C$, in order to farm a mushroom primordium which grows to pine mushroom after 16 days from the stimulation. We also found that the pine mushroom production ended when the soil temperature (of three-day moving average) fell below $14.0^{\circ}C$.

• Korean Journal of Environmental Agriculture
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• v.24 no.2
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• pp.77-82
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• 2005

This study was conducted to identify the characteristics of non-point pollutants discharge in a small agricultural watershed during farming season. for this purpose, the Neoungchon watershed in Goesangun was selected as a typical agricultural area. Runoff and water quality data in the stream, the domestic sewage and the precipitation of the watershed were analyzed periodically from June 1 to November 6 in 2004 and pollutant loads were estimated. As a result the mean concentrations of BOD, SS, TN and TP in the stream were 3.0, 76.7, 8.7, 0.16 mg/L in rainy season and 2.4, 10.0, 3.5, 0.11 mg/L in dry season respectively. Daily discharge of non-point pollutant occurred above of 95% in rainy period. Measured pollutant loads in the watershed were $26.63kg/km^2/day$ of T-N and $0.62kg/km^2/day$ of T-P, within the range of other research results. Effluent loads based on guideline of total pollutant to stream management of MOE (Ministry of Environment) were less than delivery loads since the guideline could not reflect the agricultural practices, geomorphic and meteorological characteristics in an agricultural watershed.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.2
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• pp.89-100
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• 1999

The rain water samples were collected at Chunchon and Seoul by using wet only automatic sampler from January 1996 through 1997. The daily base rain water samples collected over than 95% rainy events components, $SO_4^{-2}$, $NO_3^-$, $CI^-$, NH_4^+$, $Ca^{2+}$, $Mg^{2+}$, $Na^+$, and $K^+$, by ion chromatography. In 1996, about 77% of sampled rain water showed below pH 5.6 and the 60% of rain water was lower than pH 5.0. The volume weighted average pH was 4.7 at all sites. In 1997, the volume weighted average pH was 4.6 and 4.9 at Seoul and Chunchon, respectively. Among the rain water samples,, 87% and 55% fo samples showed below than pH 5.6 and 5.0, respectively. The pH value of Chunchon was significantly (p＜0.05) lower than Seoul at the rain samples for less than 20mm rainfall. However conductivity of the rain samples were 20.9$\mu$S/cm for 1996 and 27.7$\mu$S/cm for 1997 at Seoul, and 19.1$\mu$S/cm for 1996 and 14.1$\mu$S/cm for 1997 at Chunchon. $H_2SO_4$ and $HNO_3$ contributed 65.9% and 29.6% of free acidity at Seoul, respectively. The ratio of [$NO_3^-$]/[nss-$SO_4^{-2}$] were 0.43 at Seoul and 0.51 at Chunchon for rain samples for less than 20mm rainfall. The annual wet deposition of $CI^-$, $NO_3^-$, $SO_4^{-2}$, $H^+$M, $Na^+$, NH_4^+$, $K^+$, $Mg^{2+}$, and $Ca^{2+}$, respectively, 568.8kg/$ extrm{km}^2$, 1489.3kg/$\textrm{km}^2$, 3184.8kg/$\textrm{km}^2$, 20.9kg/$\textrm{km}^2$, 249.4kg/$\textrm{km}^2$, 1091.2kg/$\textrm{km}^2$, 189.8kg/ $\textrm{km}^2$, 90.2kg/$\textrm{km}^2$ and 702.4kg/$\textrm{km}^2$ at Seoul for 1996; 656.4kg/$\textrm{km}^2$, 2029.7kg/$\textrm{km}^2$, 3280.7kg/$\textrm{km}^2$, 27.2kg /$\textrm{km}^2$, 229.4kg/$\textrm{km}^2$, 1063.9kg/$\textrm{km}^2$, 106.9kg/$\textrm{km}^2$, 78.2kg/$\textrm{km}^2$, 645.3kg/$\textrm{km}^2$ at Seoul for 1997; 116.9kg/ $\textrm{km}^2$, 983.3kg/$\textrm{km}^2$, 1797.0kg/$\textrm{km}^2$, 21.4kg/$\textrm{km}^2$, 83.2kg/$\textrm{km}^2$, 648.1kg/$\textrm{km}^2$, 78.0kg/$\textrm{km}^2$, 22.2kg/$\textrm{km}^2$, 368.8kg/$\textrm{km}^2$ at chunchon for 1996; 100.2kg/$\textrm{km}^2$, 1077.6kg/$\textrm{km}^2$, 1754.0kg/$\textrm{km}^2$, 13.4kg/$\textrm{km}^2$, 146.0kg/$\textrm{km}^2$, 602.3kg/$\textrm{km}^2$, 88.8kg/$\textrm{km}^2$, 16.2kg/$\textrm{km}^2$ and 206.8kg/$\textrm{km}^2$ at chunchon for 1997.