• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.302-311
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• 2018

BACKGROUND: Dithianon (75%) formulation were mixed and sprayed as closely as possible by normal practice on the ten farms located in the Mungeong of South Korea. Patches, cotton gloves, socks, masks, and XAD-2 resin were used for measurement of the potential exposure of dithianon on the applicators wearing standardized whole-body outer and inner dosimeter (WBD). This study has been carried out to determine the dermal and inhalation exposure to dithianon during preparation of spray suspension and application with a power sprayer on a apple orchard. METHODS AND RESULTS: A personal air monitor equipped with an air pump, IOM sampler and cassette, and glass fiber filter was used for inhalation exposure. The field studies were carried out in a apple orchard. The temperature and relative humidity were monitored with a thermometer and a hygrometer. Wind speed was measured using a pocket weather meter. All mean field fortification recoveries were between 85.1% and 99.1% in the level of 100 LOQ (limit of quantification), while the LOQ for dithianon was $0.05{\mu}g/mL$ using HPLC-DAD. The exposure to dithianon on arms of the mixer/loader (0.0794 mg) was higher than other body parts (head, hands, upper body, or legs). The exposure to dithianon on the applicator's legs (3.78 mg) was highest in the body parts. The dermal exposures for mixer/loader and applicator were 10 and 8.10 mg, respectively, from a grape orchard. The inhalation exposure during application was estimated as 0.151 mg, and the ratio of inhalation exposure was 11.2% of the dermal exposure (inner clothes). CONCLUSION: The dermal and inhalation exposure on the applicator appeared to be 4.203 mg - 25.064 mg and $0.529{\mu}g-116.241{\mu}g$, respectively. The total exposures on the agricultural applicators were at the level of 2.596 mg - 25.069 mg to dithianon during treatment for apple orchard. The TER showed 3.421 (>1) when AOEL of dithianon was used as a reference dose for the purpose of risk assessment of the mixing/loading and application.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.348-356
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• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Korean Journal of Environment and Ecology
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• v.35 no.6
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• pp.669-678
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• 2021

This study surveyed three land cover types in Chungju City in Chungcheongbuk Province to check the distribution of cultured bacteria in bio-aerosols according to land cover type. It was possible to compare and analyze the distribution of bacteria according to microclimatic changes at each measurement point by examining meteorological factors and bio-aerosols according to land cover. The microclimate temperature in each measurement point was 8.7℃ for the urban forest, 10.8℃ for the waterside green area, and 10.2℃ for the urban area, indicating the urban forest had the lowest temperature among the measurement points. The relative humanity was 61.8% fin the urban forest, 59.3% in the waterside green area, and 55.7% in the urban area, indicating that the urban forest was the most humid among the measurement points. The identified bacteria were found to be 43 genera and 99 species. In terms of species diversity of cultured bacteria, 22 genera were found in the waterside green area, 21 genera in the urban forest, and 17 genera in the urban area, 37 species were found in the waterside green area, 31 species in the urban area, and 31 species in the urban forest. Bacillus toyonensis and Pseudarthrobacter oxydan were the species present in all three types of measurement sites, and Herbiconiux flava was confirmed to inhabit green areas such as urban forests and waterside green areas. The analysis result of the bacterial concentration according to the microclimatic environment in each measurement point was 333 CFU/m³ in the urban forest, 287 CFU/m³, in the waterside green area, and 173 CFU/m³ in the downtown area. The relative humidity and wind speed were analyzed to show a similar trend as the concentration. This study is expected to provide basic data for healthy urban management and green area creation by identifying the distribution of cultured bacteria in bio-aerosols according to land cover type and comparing and analyzing the traits of bio-aerosol in each measurement point.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.356-365
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• 2022

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. The agrivoltaic systems are expected to reduce the incident solar radiation, the consequent surface cooling effect, and evapotranspiration, and bring additional income to farms through solar power generation by combining crops with solar photovoltaics. In this study, to evaluate if agrivoltaic systems are suitable for viticulture, we investigated the microclimatic change, the growth of vines and the characteristics of grape grown under solar panels set by planting lines compared with ones in open vineyards. There was high reduction of wind speed during over-wintering season, and low soil temperature under solar panel compared to those in the open field. There was not significant difference in total carbohydrates and bud burst in bearing mother branches between plots. Despite high content of chlorophyll in vines grown under panels, there is no significant difference in shoot growth of vines, berry weight, cluster weight, total soluble solid content and acidity of berries, and anthocyanin content of berry skins in harvested grapes in vineyards under panels and open vineyards. It was observed that harvesting season was delayed by 7-10 days due to late skin coloration in grapes grown in vineyards under panels compared to ones grown in open vineyards. The results from this study would be used as data required in development of viticulture system under panel in the future and further study for evaluating the influence of agrivoltaic system on production of crops including grapes.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.1-22
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• 2022

The modification effects of street trees on outdoor thermal comfort in summertime according to tree planting types and road direction were analyzed using a computer simulation program, ENVI-met. With trees, the air temperature and wind speed decreased, and the relative humidity increased. In the case of mean radiant temperature (T_mrt) and human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI), there was a decrease during the daytime. The greatest change among the meteorological factors by trees happened in Tmrt, and PET and UTCI showed similar patterns with T_mrt·The most effective tree planting type on thermal comfort modification was low tree height, wide tree crown, high leaf area index, and narrow planting interval (LWDN). T_mrt, PET and UTCI showed a large difference depending on shadow patterns of buildings and trees according to solar altitude and azimuth angles, and building locations. When the building shade areas increased, the thermal modification effect by trees decreased. In particular, results on the east and west sidewalks showed a large deviation over time. When applying the LWDN, the northwest, west and southwest sidewalks showed a significant reduction of 8.6-12.3℃ PET and 4.2-4.5℃ UTCI at 10:00, and the northeast, east and southeast sidewalks showed 8.1-11.8℃ PET and 4.4-5.0℃ UTCI at 16:00. On the other hand, when the least effective type (high tree height, narrow tree crown, low leaf area index, and wide planting interval) was applied, the maximum reduction was up to 1.8℃ PET and 0.9℃ UTCI on the eastern sidewalks, and up to 3.0℃ PET and 0.9℃ UTCI on the western ones. In addition, the difference in modification effects on T_mrt, PET and UTCI between the tree planting types was not significant when the tree effects were reduced by the effects of buildings. These results can be used as basic data to make the most appropriate street tree planting model for thermal comfort improvement in urban areas in summer.

• Korean Journal of Plant Resources
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• v.36 no.1
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• pp.1-14
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• 2023

This study measured the antioxidant activity and phytochemical content of 192 Boehmeria nivea var. tenacissima (Gaudich.) Miq. collected from six regions in order to identify the possibility of its industrial application. Two antioxidant activity assay (DPPH radical scavenging activity and ABTS radical scavenging activity) and two phytochemical content assay (total polyphenol content (TPC) and total flavonoid content (TFC)) of 192 samples were analyzed. The results showed that the DPPH radical scavenging activity of 192 samples was ranged from 0.02 to 1.35 mgAAE/g, and among them, the samples collected from Goheung (0.53 ± 0.37) and Ulleungdo (0.52 ± 0.28) showed the highest activity. The ABTS radical scavenging activity was showed the ranged from 0.07 to 1.81 mgAAE/g, and the samples collected at Ulleungdo (0.47 ± 0.36) showed the highest activity. The total polyphenol content of 192 samples was 18.6 to 234.8 ugGAE/g, and the samples collected at Mokpo (93.4 ± 34.7) and Jindo (90.4 ± 24.5) showed the highest content. The total flavonoid content was 0.10 to 1.22 mgQE/g and the samples collected at Ulleungdo (0.49 ± 0.31) showed the highest content. In the correlation analysis, there was no significant relationship between the environmental conditions and the antioxidant activity. The total polyphenol content showed a positive correlation with daily temperature difference, and negative correlation with average wind speed and average humidity, and total flavonoid content showed negative correlations with the average temperature, maximum temperature, and minimum temperature. This result can be used as a basic data establish the cultivation conditions of B. nivea var. tenacissima (Gaudich.) Miq. as a functional raw material to increase the usefulness of B. nivea var. tenacissima (Gaudich.) Miq..