• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.501-511
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• 2014

The effects of initial conditions and input values of the rainfall-runoff model were studied in the applications of a lumped concept model for flood event data extension. For the initial conditions of the rainfall-runoff model, baseflow effects and spatial distributions of saturation points ($R_{sa}$) for the storage function methods (SFM) were analyzed. In addition, researches on the effects of rainfall data conditions as input values for the rainfall-runoff model were performed. The Chungju Dam watershed was selected and divided into 3 catchments including smaller size of 22 sub-catchments. The observed discharge and inflow amounts at Yeongwol 1, Chungju Dam, and Yeongwol 2 water level stations were individually operated as criteria for flood data extension in 30 flood events from 1993 to 2009. Direct and base flow were distinguished from a stream flow. In order to test capability of flood data extension, obtained base flow was applied to the rainfall-runoff model for three water level stations. When base flow was adopted in the model, the Nash-Sutcliffe Efficiency(NSE) was increased. The numbers of over satisfaction for model performance (>0.5) were increased over 10%. Saturation points ($R_{sa}$) which strongly influence the runoff amount when rainfall starts were optimized based on the runoff amount at three water level stations. The sizes of saturation points for three locations were similar which means saturation point size is not depending on the runoff amount. The effects of rainfall information for flood runoff were tested at 2002ev1 and 2008ev1. When increased the amount of rainfall information, the runoff simulations were closer to the simulations with full of rainfall information. However, the size of improvement was not substantial on rainfall-runoff simulations in terms of the size of total amount of rainfall.

• Journal of Mushroom
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• v.19 no.3
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• pp.210-215
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• 2021

For sterilization of microorganisms of the Listeria genus contaminating enoki mushroom, pilot mushroom grower equipped with air sterilization devices were developed. Sterilization experiments were performed using physical and chemical treatments. Internal temperature and humidity were controlled, maintaining 6.62℃±0.30 in the upper shelves, 6.46℃±0.24 in the middle shelves, and 6.48℃±0.25 in the lower shelves. Humidities were 79.97%±4.42, 79.43%±4.06, and 79.94±4.30%, respectively, with a temperature setting of 6.5℃, and a relative humidity of 75%. A suitable enoki mushroom cultivation stage for air sterilizer application was during the growth stage, with temperature in the 6.5~8.5℃ range, and humidity of 70~80%. At these same internal conditions, the ozone concentration in the mushroom cultivator was found to be 160 ppb during ion-cluster generator operation. After physical sterilization, the Listeria innocua survival rate was 0.1 to 0.9% using ion cluster sterilization, and 9.3 to 10.6% using UV air sterilization. The Listeria innocua survival rates on different materials were 9.3~10.6% on the metal specimen, and 9.9~16.2% on the plastic wrapper. The survival rate was particularly high on the rough side of the plastic wrapper. Ion cluster air sterilization is a labor-saving and effective method for suppressing the occurrence of Listeria bacteria on mushroom growers walls and shelves. For the plastic wrapper, chemical sterilization is more effective than physical sterilization.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.