• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.181-189
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• 2023

Hydrogen has gained attention as an environmentally friendly energy source among various renewable options, however, its application in agriculture remains limited. This study aims to apply the hydrogen fuel cell triple heat-combining system, originally not designed for greenhouses, to greenhouses in order to save energy and reduce greenhouse gas emissions. This system can produce heating, cooling, and electricity from hydrogen while recovering waste heat. To implement a hydrogen fuel cell triple heat-combining system in a greenhouse, it is crucial to evaluate the greenhouse's heating and cooling load. Accurate analysis of these loads requires considering factors such as greenhouse configuration, existing heating and cooling systems, and specific crop types being cultivated. Consequently, this study aimed to estimate the cooling and heating load using building energy simulation (BES). This study collected and analyzed meteorological data from 2012 to 2021 for semi-enclosed greenhouses cultivating tomatoes in Jeonju City. The covering material and framework were modeled based on the greenhouse design, and crop energy and soil energy were taken into account. To verify the effectiveness of the building energy simulation, we conducted analyses with and without crops, as well as static and dynamic energy analyses. Furthermore, we calculated the average maximum heating capacity of 449,578 kJ·h^-1 and the average cooling capacity of 431,187 kJ·h^-1 from the monthly maximum cooling and heating load analyses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.177-185
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• 2008

Accurate monitoring of snow cover is a key component for studying climate and global as well as for daily weather forecasting and snowmelt runoff modelling. The few observed data related to snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) were built for 7 major watersheds in South Korea. The decrease pattern of SCA for time (day) was expressed as exponentially decay function, and the determination coefficient was ranged from 0.46 to 0.88. The SCA decreased 70% to 100% from the maximum SCA when 10 days passed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.41-53
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• 2008

Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.513-521
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• 2008

The objective of this study is the evaluation of the impact on the construction condition due to historical observation data and IPCC SRES A2 climate change scenario. For this purpose, daily precipitation and daily mean temperature data which have been observed over the past 30 years by Korea Meteorological Administration are collected and applied. Also, A2 scenarios during 2011~2040 and 2051~2080 are used for this analysis. According to the results of trend analyses on annual precipitation and annual mean temperature, they are on the increase mostly. The available working day and the day occurred an extreme event are used as correlation indices between climate factor and construction condition. For the past observation data, linear regression and Mann-Kendall test are used to analyze the trend on the correlation index. As a result, both working day and extreme event occurrence day are increased. Likewise, for the future, variation analysis showed the similar result to that of the past and the occurrence frequency of extreme events is increased obviously. Therefore, we can project to increase flood damage potential on the construction site by climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.495-504
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• 2008

Evapotranspiration (ET) is an important state variable while simulating daily streamflow in hydrological models. In the estimation of ET, for example, when using FAO Penman Monteith equation, the LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAI from MODIS satellite data is available, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. Four years (2001-2004) of MODIS LAI was prepared for the evaluation of Penman Monteith ET in the continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungju watershed ($6661.3km^2$) located in the upstream of Han river basin. For four years (2001-2004) dam inflow data and meteorological data, the model was calibrated and verified using MODIS LAI data. The average Nash-Sutcliffe model efficiency was 0.66. The 4 years watershed average Penman Monteith ETs of deciduous, coniferous, and mixed forest were 639.1, 422.4, and 631.6 mm for average MODIS LAI values of 3.64, 3.50, and 3.63 respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.23-33
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• 2009

Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.116-124
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• 2023

As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.

• Journal of Marine Bioscience and Biotechnology
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• v.16 no.1
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• pp.63-86
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• 2024

This study analyzed the distribution, diversity, and density variation of algal clusters in a freshwater reservoir from an oceanic island and a traditional inland water system to gain insights on future marine freshwater resource management. In the Paldang water system (Han River), despite the upstream Paldang Dam and the downstream Jamsil underwater reservoir being in the same meteorological zone, their algae density patterns varied inversely. The distinct algal cluster structure (diversity/dominance) of Paldang was altered in the downstream reservoir, suggesting that physical devices aid algae management in traditional water systems. In contrast, 24 out of 35 genera (63.2%) identified in the Jeolgol Reservoir (Baeknyeong Island) were unique, lacking regulatory mechanisms, and existing in a complex ecotone. The desmid Chlorophyceae Cosmarium, adapted to higher photosynthetic stress and low temperatures, dominated in January (38.04%) and August (86.45%) during the periods of extreme photosynthetic stress. Jeolgol's annual algal cluster structure (H' 2.097; D 0.259; S' 35) demonstrated higher stability than Paldang (H' 1.125; D 0.448; S' 13) and the Jamsil underwater reservoir (H' 1.078; D 0.469; S' 12), maintaining an H' above 1.5 even during midwinters. No evidence of TN/TP inflow from surrounding soils was observed, even during torrential rainfalls, with phosphorus being the limiting factor for algal growth. TOC, BOD, chlorophyll-a, and turbidity peaked during Cosmarium bloom. Future climate change is expected to cause fluctuations in algal clusters and related water quality factors. The complex transitional nature of the Jeolgol Reservoir, its algal diversity, and the interspecies interactions contribute to the high stability of its algal community.

• Atmosphere
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• v.34 no.3
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• pp.283-304
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• 2024

This study analyzed the variability and correlation between ground-level air pollutant concentrations and the atmospheric mixing layer height using data from four types of air pollutants (PM_2.5, PM₁₀, NO₂, and O₃) collected at AirKorea monitoring stations nationwide over a five-year period (2018~2022), and aerosol backscatter data observed by the Vaisala CL31 to derive atmospheric mixing layer heights. The five-year trends and variability of ground-level air pollutant concentrations under seasonal and hourly conditions were examined, as well as the seasonal distribution and diurnal variation of the atmospheric mixing layer height. Five correlation coefficient methodologies were applied to analyze the correlations between ground-level air pollutants and atmospheric mixing layer height under various seasonal and hourly conditions, confirming the dilution effect of the atmospheric mixing layer height. The results showed that PM_2.5, PM₁₀, and NO₂ generally had negative correlations with the atmospheric mixing layer height, while O₃ showed a strong positive correlation up to an altitude of 1,200~1,500 meters, and a negative correlation beyond that altitude. It was also shown that a single high concentration event (e.g., PM₁₀) can alter the overall correlation. The correlation can also vary depending on the characteristics of the correlation coefficient methodology, highlighting the importance of applying the appropriate methodology for each case during the analysis process.