• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.243-255
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• 2010

The spatial distribution of pan evaporation and pan evaporation trends have been studied. In this study, pan evaporation data from 1973 to 1990 for 56 climatological stations were analyzed. In addition to annual average daily pan evaporation, monthly average daily pan evaporation in April, July, October and January were analyzed, considering seasonal effect. The study results indicate that in case of annual average daily pan evaporation, 38 stations out of 56 stations show decreasing trend. In case of average daily pan evaporation in January, 33 stations show decreasing trend. In April, 38 stations show increasing trend. In July, 47 stations show decreasing trend. In October, 35 stations show increasing trend. Therefore, on the whole, pan evaporation tended to decrease in January, July, and annual basis. On the other hand, pan evaporation tended to increase in April and October. Furthermore, pan evaporation trend in each individual region shows also different trend even though the region is located nearby, indicating that there are geographical and topographical effects on pan evaporation trend. Pan evaporation data and climatic data from 1973 to 2006 for 11 climatological stations were used for trend analysis. Climatic variables such as temperature, relative humidity and wind speed show same or opposite trend direction compared with pan evaporation in annual or monthly basis. Annual and monthly solar radiation trends show the same direction compared with pan evaporation; however, annual and monthly precipitation trends show the opposite direction compared with pan evaporation.

• Horticultural Science & Technology
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• v.33 no.3
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• pp.349-355
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• 2015

Lisianthus (Eustoma grandiflorum) is relatively sensitive to temperature and light conditions. For year round production of good quality potted plants and energy saving, it is necessary to understand the growth and flowering response to the combined conditions of these environmental factors. This study was conducted to examine the growth and flowering responses to temperature, photoperiod, and light intensity during the post-seedling stage. 'El Paso Deep Blue' lisianthus plants with four true leaf pairs were grown in growth chambers maintained at average daily temperatures (ADT) of 14, 20, and $26^{\circ}C$ and provided with three photosynthetic photon fluxes [PPF; 100, 200, and $400{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$] for 8 (08:00-16:00) and 16 hours (08:00-24:00) by fluorescent and incandescent lamps, resulting in four daily light integrals (DLI): about 3, 6 (two photoperiods), 12 (two photoperiods), and $24mol{\cdot}m^{-2}{\cdot}d^{-1}$. After treatment for three weeks followed by growth for one week in a greenhouse of $20{\pm}3^{\circ}C$, growth and development were measured. Higher temperature, higher PPF, and longer photoperiod promoted plant growth and flowering; however the impacts of PPF and photoperiod were smaller than those of temperature. As ADT and DLI increased, the number of leaves, number of flowers, lateral shoot length, and shoot dry weight increased. An increase of about $1mol{\cdot}m^{-2}{\cdot}d^{-1}$ DLI could constitute an increase of 0.40 to $0.76^{\circ}C$ ADT depending on these crop characteristics when ADT and DLI are above $20^{\circ}C$ and $12mol{\cdot}m^{-2}{\cdot}d^{-1}$, respectively. Therefore, growers can select a regimen of heating or supplemental lighting without delaying harvesting time or decreasing crop quality.

• Journal of Soil and Groundwater Environment
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• v.16 no.5
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• pp.82-89
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• 2011

Understanding snowmelt movement to the watershed is crucial for both climate change and hydrological studies because the snowmelt is a significant component of groundwater and surface runoff in temperature area. In this work, a new energy balance budget algorithm has been developed for melting snow from a snowpack at the Central Sierra Snow Laboratory (CSSL) in California, US. Using two sets of experiments, artificial rain-on-snow experiments and observations of diel variations, carried out in the winter of 2002 and 2003, we investigate how to calculate the amount of snowmelt from the snowpack using radiation energy and air temperature. To address the effect of air temperature, we calculate the integrated daily solar radiation energy input, and the integrated discharge of snowmelt under the snowpack and the energy required to generate such an amount of meltwater. The difference between the two is the excess (or deficit) energy input and we compare this energy to the average daily temperature. The resulting empirical relationship is used to calculate the instantaneous snowmelt rate in the model used by Lee et al. (2008a; 2010), in addition to the net-short radiation. If for a given 10 minute interval, the energy obtained by the melt calculation is negative, then no melt is generated. The input energy from the sun is considered to be used to increase the temperature of the snowpack. Positive energy is used for melting snow for the 10-minute interval. Using this energy budget algorithm, we optimize the intrinsic permeability of the snowpack for the two sets of experiments using one-dimensional water percolation model, which are $52.5{\times}10^{-10}m^2$ and $75{\times}10^{-10}m^2$ for the artificial rain-on-snow experiments and observations of diel variation, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.73-79
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• 2019

Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.23-31
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• 2019

Crop response to weather and internal water pressure changes is more sensitive to crop water stress than soil water content. Recently, its implementation to optimal irrigation scheduling has been receiving much attention. This study was conducted to determine and compare the theoretical crop water stress index (CWSI) using meterological data and canopy temperature collected from three different irrigation treatments, which were Tr-1 plot (rainfed), Tr-2 plot (50% of daily evapotranspiration (ET) irrigated) and Tr-3 plot (75% of daily evapotranspiration (ET) irrigated). The readings of canopy temperature and CWSI were significantly different among irrigation treatment schemes. The average canopy temperatures and CWSIs of Tr-1 and Tr-3 plots were $34.6^{\circ}C$ and $32.6^{\circ}C$, 0.79 and 0.64, respectively. Solar radiation had the biggest correlation with CWSI (R=0.68) which was followed by wind speed, relative humidity and air temperature. Overall, the findings of this study indicated that canopy temperatures and CWSIs could be further used for irrigation scheduling for crop growth.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.333-340
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• 2005

In order to better quantify the contribution from nonroad sources to emission inventories, it is important to understand not only the emissions rates of these engines but also activity patterns that can be used to accurately portray their in-use operation. To date, however, very little information is available on the actual activity patterns of nonroad equipment. In this study, a total of 18 pieces of nonroad equipment were instrumented with collected data including intake manifold air pressure (MAP), exhaust temperature and, on a subset of vehicles, engine rpm and throttle position. The equipment included backhoes, compactors, dozers, motor graders, loaders and scrappers used in applications such as landfilling, street maintenance and general roadwork. The activity patterns varied considerably depending on the type of equipment and the application. Daily equipment operating time ranged from less than 30 minutes to more than 8 hours, with landfill equipment having the highest daily use. The number of engine starts per day ranged from 3-11 lover the fleet with an average of 5 starts per day. The average percent idle time for the fleet was approximately $25\%$ with a range from 11 to $65\%$ for individual pieces of equipment. Duty cycles based on exhaust temperature/throttle position profiles were also developed for two graders and one dozer.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.372-372
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• 2021

The agriculture sector plays a vital role in the economy of Pakistan by contributing about 20% of the GDP and 42% of the labor force. Rivers from the top of Himalayas are the major water resources for this agriculture sector. Recent reports have found that Pakistan is one of the most vulnerable country to climate change that can cause water scarcity which is a big challenge to the communities. Previous studies have investigated the impact of climate change on the trend of streamflow, but the understanding of seasonal change in the regional hydrologic regimes remained limited. Therefore, a better understanding of the seasonal hydrologic change will help cope with the future water scarcity issue. In this study, we used the daily stream flow data for four major river basins of Pakistan (Chenab, Indus, Jhelum and Kabul) over 1962 - 2019. Utilizing these daily river discharge data, we calculated the winter-spring center time and the summer-autumn center times. In this study Winter-spring center time (WSCT) is defined as the day of the calendar year during which half of the total six months (Jan-Jun) discharge volume was exceeded. Results show that the four river basins experienced a statistically significant decreasing trend of WSCT, that is the center time keeps coming earlier compared to the past. We further used the Climate Research Unit (CRU) climate data comprising of the average temperature and precipitation for the four basins and found that the increasing average temperature value causes the early melting of the snow covers and glaciers that resulted in the decreasing of 1^st center time value by 4 to 8 days. The findings of this study informs an alarming situation for the agriculture sector specifically.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.142-151
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• 2017

Spontaneous intracerebral hemorrhage (sICH) has a high mortality rate. Research has demonstrated that sICH occurrence is related to weather conditions; therefore, this study used the decision tree method to explore the impact of climatic risk factors on sICH at different ages. The Taiwan National Health Insurance Research Database (NHIRD) and other open-access data were used in this study. The inclusion criterion was a first-attack sICH. The decision tree algorithm and random forest were implemented in R programming language. We defined a high risk of sICH as more than the average number of cases daily, and the younger, middle-aged and older groups were calculated as having 0.77, 2.26 and 2.60 cases per day, respectively. In total, 22,684 sICH cases were included in this study; 3,102 patients were younger (<44 years, younger group), 9,089 were middle-aged (45-64 years, middle group), and 10,457 were older (>65 years, older group). The risk of sICH in the younger group was not correlated with temperature, wind speed or humidity. The middle group had two decision nodes: a higher risk if the maximum temperature was >$19^{\circ}C$ (probability = 63.7%), and if the maximum temperature was <$19^{\circ}C$ in addition to a wind speed <2.788 (m/s) (probability = 60.9%). The older group had a higher risk if the average temperature was >$23.933^{\circ}C$ (probability = 60.7%). This study demonstrated that the sICH incidence in the younger patients was not significantly correlated with weather factors; that in the middle-aged sICH patients was highly-correlated with the apparent temperature; and that in the older sICH patients was highly-correlated with the mean ambient temperature. "Warm" cold ambient temperatures resulted in a higher risk of sICH, especially in the older patients.

• Korean journal of food and cookery science
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• v.14 no.4
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• pp.367-374
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• 1998

The purpose of this study was to evaluate the microbiological quality of, and to assure the hygienic safety of, the kimbap production in the university foodservice facilities in accordance with the HACCP (Hazard Analysis Critical Control Point) Program. The time-temperature relationship and the microbiological quality (specifically, total plate count and coliform bacteria count) were assessed to find the critical control point (CCP) during each of the production phases. The average of the daily longest duration time of the kimbap at the facilities was 23.4 hours in summer, while 29.6 hours in winter. In the purchasing phase of the raw materials, the microbiological quality of laver, fish paste, carrot and cucumber in summer was not at an acceptable level according to the standard set by the Natick research center, especially the number of TPC and the coliform level of laver was higher than the threshold level. In the refrigerator storage phase, the temperature of the carrot was 7.4$^{\circ}C$. This temperature is far exceeding the standard so that the microbiological counts was increased by the 2 log cycle during the average storage time of 17 hours or more. In the preparation phase, the temperature of the blanching is too low compared to the standard. In the holding phase before serving, its time-temperature relationship was out of the FDA food code standard both in winter and summer. In the sewing phase, the number of microbiological count was higher than the threshold level in summer while that in winter was up to standard. According to the Harrigan and McCance standard, the number of microbiological count of the utensils was higher than the threshold level in summer while that in winter was up to standard.