APEX 모형은 다양한 영농 활동의 토양과 물환경에 대한 영향을 필지 및 유역 규모로 평가하기 위해 개발된 모형이다. 최근 APEX의 주요 기작을 바탕으로 논에서의 수도작 운영에 따른 물수지, 양분 유출에 대한 모의가 가능하도록 한 APEX-Paddy가 고안된 바 있다. 본 연구에서는 익산 지역의 논 시험포 모니터링 자료를 이용하여 APEX-Paddy 모형의 적용성을 평가하고자 하였다. 2013년과 2014년의 논 유출량과 부하량 자료를 수집하고 자동보정 툴 APEX-CUTE 4.1과 추가적 수동보정을 통해 모형의 모의성능을 검토하고 한계점을 고찰하였다. 연구결과, 논의 물수지와 질소 배출부하량은 대체로 합리적인 수준의 모의성능을 보이는 한편 유사량과 인 배출부하량 모의에 있어 논의 담수상태 유사배출 기작에 대한 고려가 미흡하여 모의성능에 한계가 있는 것으로 분석되었으며 원인에 대해 고찰하였다. 더불어 자동보정 툴의 적용에 있어 매개변수 민감도를 바탕으로 한 수동보정 결과보다 정확도가 다소 떨어지는 경향을 보여 그 활용에 유의가 필요한 것으로 판단되었다.

The objective of this study was to assess the flood probability based on temporal distribution of forecasted-rainfall in Cheongmicheon watershed. In this study, 6-hr rainfalls were disaggregated into hourly rainfall using the Multiplicative Random Cascade (MRC) model, which is a stochastic rainfall time disaggregation model and it was repeated 100 times to make 100 rainfalls for each storm event. The watershed runoff was estimated using the Clark unit hydrograph method with disaggregated rainfall and watershed characteristics. Using the peak discharges of the simulated hydrographs, the probability distribution was determined and parameters were estimated. Using the parameters, the probability density function is shown and the flood probability is calculated by comparing with the design flood of Cheongmicheon watershed. The flood probability results differed for various values of rainfall and rainfall duration. In addition, the flood probability calculated in this study was compared with the actual flood damage in Cheongmicheon watershed (R² = 0.7). Further, this study results could be used for flood forecasting.

Although educational facilities are important considerations from a social equity standpoint, the educational environment generally found in rural areas has been continuously deteriorated due to numerous social problems following birth rate declines and school abolition numbers. The purpose of this study is to evaluate the commuting accessibility changed by the abolition of elementary schools. The village-level accessibility is assessed following physical accessibility criteria based on legally defined commuting distances. Moreover, this study shows the implications of commuting accessibility by school district zones through comparing the minimum commuting distances with real commuting distance. The target area is the Gangwon state, the coverage area in which for schools is the widest in South Korea (44.1 ㎢/school). We evaluated the commuting distances to the nearest elementary school for 992 rural villages and 74 urban villages. Of the 1,066 villages in urban and rural areas evaluated, most of the villages (about 77%) are exposed to commutes to elementary schools were the marginal distance is over 1,000 meters. The annual rate of increase of commuting distance for 1,066 villages in Gangwon state has steadily increased by 2.8%p since 2000, average commuting distance from 2.8 km to 3.6 km. By the designation of the school districts, elementary school students have to go to a faraway school located within administrative district, even though there is a school nearby. It is expected that the results of this study will be made use of as basic data for the establishment of policies such as a reasonable basis for closing schools measurements considering the locally unique environment.

The objective of this study was to assess the livestock nonpoint source pollutant impact on water quality in Namgang dam watershed using the HSPF (Hydrological Simulation Program-Fortran) model. The input data for the HSPF model was established using the landcover, digital elevation, and watershed and river maps. In order to apply the pollutant load to the HSPF model, the delivery load of the livestock nonpoint source in the Namgang dam watershed was calculated and used as a point pollutant input data for the HSPF model. The hydrologic and water quality parameters of HSPF model were calibrated and validated using the observed runoff data from 2007 to 2015 at Sancheong station. The R² (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. The simulation results for annual mean runoff showed that R² ranged 0.79~0.81, RMSE 1.91~2.73 mm/day, NSE 0.7~0.71 and RMAE 0.37~0.49 mm/day for daily runoff. The simulation results for annual mean BOD for RMSE ranged 0.99~1.13 mg/L and RMAE 0.49~0.55 mg/L, annual mean TN for RMSE ranged 1.65~1.72 mg/L and RMAE 0.55 mg/L, and annual mean TP for RMSE ranged 0.043~0.055 mg/L and RMAE 0.552~0.570 mg/L. As a result of livestock nonpoint pollutant loading simulation for each sub-watersehd using the HSPF model, the BOD ranged 16.6~163 kg/day, TN ranged 27.5~337 kg/day, TP ranged 1.22~14.1 kg/day.

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.

To estimate the ventilation volume of mechanically ventilated swine farms, various regression models were applied, and errors were compared to select the regression model that can best simulate actual data. Linear regression, linear spline, polynomial regression (degrees 2 and 3), logistic curve, generalized additive model (GAM), and gompertz curve were compared. Overfitting models were excluded even when the error rate was small. The evaluation criteria were root mean square error (RMSE) and mean absolute percentage error (MAPE). The evaluation results indicated that degree 3 exhibited the lowest error rate; however, an overestimation contradiction was observed in a certain section. The logistic curve was the most stable and superior to all the models. In the estimation of ventilation volume by all of the models, the estimated ventilation volume of the logistic curve was the smallest except for the model with a large error rate and the overestimated model.

Enclosed pig house are creating an environment with high concentrations of gas and dust. Poor conditions in pig farms reduce pig weight and increase disease and accidents for livestock workers. In the pig house, the high concentration of harmful gas may cause asphyxiation accidents to workers and chronic respiratory disease by long-term exposure. As pig farm workers have been aging and feminized, the damage to the health of the harsh environment is getting serious, and real-time monitoring is needed to prevent the damage. However, most of the measuring devices related to humidity, harmful gas, and fine dust except temperature sensors are exposed to high concentrations of gas and dust inside pig house and are difficult to withstand for a long time. The purpose of this study is to develop an wearable based device to monitor the hazardous environment exposed to workers working in pig farms. Based on the field monitoring and previous researches, the measurement range and basic specifications of the equipment were selected, and wearable based device was designed in terms of utilization, economic efficiency, size and communication performance. Selected H₂S and NH₃ sensors showed the average error of 5.3% comparing to standard gas concentrations. The measured data can be used to manage the working environment according to the worker's location and to obtain basic data for work safety warning.

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

The purpose of this study is to develop a pipe type soil sampler that can easily collect soil cross section servey and soil samples to conduct ecological environment surveys while minimizing ecological disturbance in the area subject to soil survey. Furthermore, this study develop the exponential type estimation specific weight formula (ESWF) that uses pipe type soil sampler to easily carry out soil cross section survey and soil sample while estimating the specific weight of the area using water content and soil sample length variation ratio (SLVRs) and to obtain apparent specific gravity, hardness, and max. porosity which are used as growth of corps and ecological environment index. The calibration results of ESWF showed a high degree of significance, with NSE for actual specific weight (γ₀) and calibration estimation specific weight (γ_ec) 0.95, R² for 0.954, and RMSE for 0.051. The verification results of ESWF showed a high significance, with NSE for actual specific weight (γ₀) and verification estimation specific weight (γ_ev) 0.881, R² for 0.978, and RMSE for 0.055.

With the decrease of the agricultural population in Korea, the workers who is vulnerable to labor are increasing in agricultural industry because of aging, feminization of population. They are exposed in poor working environment with higher temperature and concentrations of dust, gas. Higher concentration of harmful gas and dust can cause chronic and acute disease to workers depending on exposure intensity and frequency. In order to improve the working environment in the livestock facilities, It is important to secure monitoring data of the thermal environment and the concentration of harmful gases and fine dust. Multi-point measurement was performed to analyze the regional environmental conditions in the pig rooms. When analyzing the working environment, video monitoring was conducted to analyze the concentration changes of ammonia, hydrogen sulfide and fine dust according to worker movement and work type. Ammonia and hydrogen sulfide monitoring result showed 1.5~2 times higher concentrations than other work when working in the pigs living zone, and 2~4 times higher than other work when working to increase the activity of pigs. In the case of fine dust, the result was 1.3 times higher than the worker's exposure standard in a specific work. The concentrations of gases and dusts from pig farms are not of concern for acute poisoning in normal work, but there is a risk of chronic respiratory disease if they are continuously exposed. Accordingly, there is a need for development of work environment monitoring device tailored to workers and preparation of alternatives.

The area of facility horticulture in Korea is increasing rapidly, the single-span pipe house which uses galvanized steel pipe as the main rafters occupies 78.7% of the facility area. Lightweight structures such as the single-span pipe house are vulnerable to meteorological disasters such as strong winds, economic losses of the state, local governments and farmers are continuing as construction does not meet the design standards. In order to minimize economic losses in the horticultural specialty facilities sector, the Rural Development Administration has been operating the horticultural disaster resilient standard for horticultural specialty facilities since April 2007. The only standard for the pipe connector is the disaster resilient standard, there is no standard for the uplift capacity of the house pipe foundation and the research on it is also insufficient. The purpose of this study is to investigate the characteristics of uplift capacity according to the foundation type, compaction ratio and embedded depth through soil box test. The results of the maximum uplift capacity according to the type, compaction ratio and embedded depth can be used as the basic data for the basic design of the pipe house conforming to the disaster resilient standard. Due to the limitation of soil box test, it may be different from the behavior of pipe house installed on site. In the future, the field test and the actual pipe house should be made and supplemented by comparing this result with the field test values.