• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.393-402
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• 2023

Drought, which has been increasing in frequency and magnitude due to recent abnormal weather events, poses severe challenges in various sectors. To address this issue, it is important to develop technologies for drought monitoring, forecasting, and response in order to implement effective measures and safeguard the ecological health of aquatic systems during water scarcity caused by drought. This study aimed to predict water quality fluctuations during drought periods by integrating the watershed model HSPF and the water quality model QUAL-MEV. The researchers examined the SPI and RCP 4.5 scenarios, and analyzed water quality changes based on flow rates by simulating them using the HSPF and QUAL-MEV models. The study found a strong correlation between water flow and water quality during the low flow. However, the relationship between precipitation and water quality was deemed insignificant. Moreover, the flow rate and SPI6 exhibited different trends. It was observed that the relationship with the mid- to long-term drought index was not significant when predicting changes in water quality influenced by drought. Therefore, to accurately assess the impact of drought on water quality, it is necessary to employ a short-term drought index and develop an evaluation method that considers fluctuations in flow.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.27-40
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• 2006

Damage of cut-and-cover tunnel lining can be attributed to physical and mechanical factors. Physical factors include material property, reinforcement corrosion, etc. while mechanical factors include underground water pressure, vehicle loads, etc. This study is limited to the modeling of rigid circular cut and cover tunnel constructed at a depth of $1.0{\sim}1.5D$ in loose sandy ground and subjected to a vibration frequency of 100 Hz. In this study, only damages due to mechanical factors in the form of additional loads were considered. Among the different types of additional, excessive earth pressure acting on the cut-and-cover tunnel lining is considered as one of the major factors that induce deformation and damage of tunnels after the construction is completed. Excessive earth pressure may be attributed to insufficient compaction, consolidation due to self-weight of backfill soil, precipitation and vibration caused by traffic. Laboratory tunnel model tests were performed in order to determine the earth pressure acting on the tunnel lining and to investigate the applicability of existing earth pressure formulas. Based on the difference in the monitored and computed earth pressure, a factor of safety was recommended. Soil deformation mechanism around the tunnel was also presented using the picture analysis method.

• Journal of Environmental Health Sciences
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• v.50 no.3
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• pp.181-190
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• 2024

Background: Air pollutants have been reported to have harmful effects on human health. Busan is a vulnerable area in terms of air quality due to the installation of various industrial complexes, particularly the port industry. However there is limited research data on the ambient air quality of residential areas near ports and industrial complexes. Objectives: This study aimed to determine the quarterly levels of air pollutants near industrial complexes and ports and to identify trends and characteristics of air pollutant exceedances. Methods: Air measurements were conducted quarterly. The measured air pollutants included O₃, SO₂, CO, NO₂, PM₁₀, and PM_2.5. PM₁₀ and PM_2.5 were measured using BAM-1020 equipment, while O₃, SO₂, CO, and NO₂ were measured using AP-370 Series equipment. The quarterly concentration levels of air pollutants were determined, and the influence of precipitation and commuting hours on fine particulate matter was examined. Analysis of variance (ANOVA) was conducted to determine if there was significance between the concentrations of fine particulate matter during commuting hours and non-commuting hours. Results: The concentrations of air pollutants were generally higher in the first and second quarters. Furthermore, the concentrations of PM₁₀ and PM_2.5 tended to decrease continuously following consecutive rainfall, with concentrations at the end of rainfall periods lower than those observed at the beginning. The frequency of exceeding average concentrations of PM₁₀ and PM_2.5 was higher on weekdays. Moreover, the average concentrations of PM₁₀ and PM_2.5 during weekday commuting hours were higher compared to non-commuting hours. Conclusions: The concentrations of air pollutants in the survey area were found to be higher than the overall average in Busan. Based on this study, continuous air quality monitoring is necessary for residential areas near industrial complexes and ports. For further research, health biomonitoring of residents in these areas should be conducted to assess their exposure levels.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.39-47
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• 2009

The importance of securing water resources and their efficient management has attracted more attention recently due to water deficit. In water budget analysis, however, evapotranspiration(${\lambda}E$) has been approximated as the residual in the water balance equation or estimated from empirical equations and assumptions. To minimize the uncertainties in these estimates, it is necessary to directly measure ${\lambda}E$. In this study, using the eddy covariance technique, we have measured ${\lambda}E$ in a mixed forest in the Seolmacheon catchment in Korea from September 2007 to December 2008. During the growing season(May-July), ${\lambda}E$ in this mixed forest averaged about $2.2\;mm\;d^{-1}$, whereas it was on average $0.5\;mm\;d^{-1}$ during the non-growing season in winter. The annual total ${\lambda}E$ in 2008 was $581\;mm\;y^{-1}$, which is about 1/3 of the annual precipitation of 1997 mm. Despite the differences in the amount and frequency of precipitation, the accumulated ${\lambda}E$ during the overlapping period(i.e., September to December) for 2007 and 2008 was both ${\sim}110$ mm, showing virtually no difference. The omega factor, which is a measure of decoupling between forest and the atmosphere, was on average 0.5, indicating that the contributions of equilibrium ${\lambda}E$ and imposed ${\lambda}E$ to the total ${\lambda}E$ were about the same. The results suggest that ${\lambda}E$ in this mixed forest was controlled by various factors such as net radiation, vapor pressure deficit, and canopy conductance. In this study, based on the direct measurements of ${\lambda}E$, we have quantified the relative contribution of ${\lambda}E$ in the water balance of a mixed forest in the Seolmacheon catchment. In combination with runoff data, the information on ${\lambda}E$ would greatly enhance the reliability of water budget analysis in this catchment.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.264-272
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• 2013

Climate changes have caused not only changes in the frequency and intensity of extreme climate events, but also temperature and precipitation. The damages on agricultural production system will be increased by heavy rainfall and snow. In this study we assessed vulnerability of crop cultivation facility and animal husbandry facility by heavy rain in 232 agricultural districts. The climate data of 2000 years were used for vulnerability analysis on present status and the data derived from A1B scenario were used for the assessment in the years of 2020, 2050 and 2100, respectively. Vulnerability of local districts was evaluated by three indices such as climate exposure, sensitivity and adaptive capacity, and each index was determined from selected alternative variables. Collected data were normalized and then multiplied by weight value that was elicited in delphi investigation. Jeonla-do and Gangwon-do showed higher climate exposures than the other provinces. The higher sensitivity to abnormal weather was observed from the regions that have large-scale cultivation facility complex compared to the other regions and vulnerability to abnormal weather also was higher at these provinces. In the projected estimation based on the SRES A1B, the vulnerability of controlled agricultural facility in Korea totally increased, especially was dramatic between 2000's and 2020 year.

• Journal of Korean Society of Forest Science
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• v.76 no.1
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• pp.11-16
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• 1987

With the purpose of pursuing the increase and decrease of chlorophyll a and chlorophyll b caused by application of the simulated acid rain treatment on Pinus koraiensis seedlings and Ligustrum obtusifolium cuttings, the experimental design of randomized block arrangement with three replications was implemented in the experimental field of Yesan National Agricultural Junior College, during the growing season of 1985. Pinus koraiensis seeds stratified in cool and moist condition were sown on pots, and in case of Ligustrum obtusifolium, C1/1 cuttings were potted for experimental use in the early spring. The regime of artificial acid rain, based upon precipitation frequency and density, was simulated from the learning of climatological data averaged from 30 years records. The spray of acid water containing pH values of 4.0 and 2.0 was initiated from the 1st of May and ended on the 31st of August. As control, ground water was also treated at the same time. To analyse the chlorophyll content, those leaves looking representative and unaffected by other harmful agents were sampled on the 18th of September, and UV-visible spectrophotometer was used. With decrease in pH values of acid rain, the content of chlorophyll a and chlorophyll b decreased in both species. The decrease in chlorophyll a could be confirmed through statistical significance, but not in chlorophyll b. And when we discussed the chlorophyll decrease index which was explained in detail in the paper, an attention might be given to similarly decreasing values in both chlorophyll a and chlorophyll b, according as pH levels of acid rain decreased. The ratios of chlorophyll a to chlorophyll b in both species were not affected by different pH leaves of acid rain.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.779-797
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• 2016

A calibrated hydrological model is a useful tool for quantifying the impacts of the climate variations and land use/land cover changes on sediment load, water quality and runoff. In the rainy season each year, the Xe Bang Fai river basin is provisionally flooded because of typhoons, the frequency and intensity of which are sensitive to ongoing climate change. Severe heavy rainfall has continuously occurred in this basin area, often causing severe floods at downstream of the Xe Bang Fai river basin. The main purpose of this study is to investigate the climate change impact on river discharge using a Soil and Water Assessment Tool (SWAT) model based on future climate change scenarios. In this study, the simulation of hydrological river discharge is used by SWAT model, covering a total area of $10,064km^2$ in the central part of country. The hydrological model (baseline) is calibrated and validated for two periods: 2001-2005 and 2006-2010, respectively. The monthly simulation outcomes during the calibration and validation model are good results with $R^2$ > 0.9 and ENS > 0.9. Because of ongoing climate change, three climate models (IPSL CM5A-MR 2030, GISS E2-R-CC 2030 and GFDL CM3 2030) indicate that the rainfall in this area is likely to increase up to 10% during the summer monsoon season in the near future, year 2030. As a result of these precipitation increases, the SWAT model predicts rainy season (Jul-Aug-Sep) river discharge at the Xebangfai@bridge station will be about $800m^3/s$ larger than the present. This calibrated model is expected to contribute for preventing flood disaster risk and sustainable development of Laos