• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.437-446
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• 2022

In April 2020, the Korean government decided to operate the Hwacheon reservoir, a hydropower reservoir to supply water, and it is currently under pilot operation. Through the pilot operation, the Hwacheon reservoir is the first among the hydropower reservoirs in Korea to make a constant release for downstream water supply. In this study, the water supply capacity of the Hwacheon reservoir was estimated using the inflow data of the Hwacheon reservoir. A simulation model was developed to calculate the water supply that satisfies both the monthly water supply reliability of 95% and the annual water supply reliability of 95%. An optimization model was also developed to evaluate the water supply capacity of the Hwacheon reservoir. The inflow data used as input data for the model was modified in two ways in consideration of the impact of the Imnam reservoir. Calculating the water supply for the Hwacheon reservoir using the two modified inflows is as follows. The water supply that satisfies 95% of the monthly water supply reliability is 26.9 m³/sec and 24.1 m³/sec. And the water supply that satisfies 95% of the annual water supply reliability is 23.9 m³/sec and 22.2 m³/sec. Hwacheon reservoir has a maximum annual water supply of 777 MCM (Million Cubic Meter) without failure in the water supply. The Hwacheon reservoir can supply 704 MCM of water per year, considering the past monthly power generation and discharge patterns. If the Hwacheon reservoir performs a routine operation utilizing its water supply capacity, it can contribute to stabilizing the water supply during dry seasons in the Han River Basin.

• Journal of the Korean GEO-environmental Society
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• v.23 no.9
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• pp.33-40
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• 2022

Sedimentation and pH neutralization has been investigated as preteatment of acid contaminate water. The settling and neutralizing process derive more effective degradation efficiency as the pre-treatment process before the removal process of adsorption, volatile, biodegradation, or oxidation. Settling velocity, uniformity coefficient, coefficient of curvature, and grain size index can define in the sedimentation process for characteristics of the soil. The stainless steel sieve has been used to separate each particle size of the dry soil by assembling in order of 4, 10, 20, 40, 80, 100, and 200 mesh sizes. The soil from Gamcheon Port in Busan drops upper side of the sieve and shakes back and forth to separate each different size of the particle. The 1L of Imhoff cone and 200 mL of the mass cylinder were used as settling tanks to calculate settling velocity. Stokes' equation was used to figure out the average density of dry soil with a value from settling velocity. In the results, the average particle density and lowest settling velocity were 1.93 g/cm³ and 0.11 cm/s, respectively. These values can detect the range of settling points of sediment to prevent chemical accidents. In pH neutralization, the initial pH of 2, 3, 4, and 5 of nitric acid and sulfuric acid are used as an acid solution; 0.1, 0.01, and 0.001 M of sodium hydroxide and calcium hydroxide are used as a base solution. The main goal of this experiment is to figure out the volume percentage of the acid solution becomes pH 7. The concentration of 0.001 M of base solution exceeds all the conditions, 0.01 M exceeds partially, and 0.1 M does not exceed 5 v/v% except pH 2. Calcium hydroxide present less volume than sodium hydroxide at pH neutralization both sulfuric and nitric acid.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Korean Journal of Ecology and Environment
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• v.55 no.3
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• pp.185-200
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• 2022

The risk of various hazardous substances in aquatic environment comprises not only the concentration of substances in the environmental medium but also their accumulation in fish through complex food web and the health risks to humans through the fish. In Korea, the monitoring of residual toxicant in aquatic ecosystems began in 2016 following the enforcement of the Acts on registration and evaluation for the management of chemicals used in daily life (consumer chemical products), and attention has been paid to potentially hazardous substances attributed to them. Recently, studies have been carried out to investigate the distribution of these hazardous substances in the ecosystem and calculate their emission factors. These include the accumulation and transport of substances, such as detergents, dyes, fragrances, cosmetics, and disinfectants, within trophic levels. This study summarizes the results of recently published research on the inflow and distribution of hazardous substances from consumer chemical products to the aquatic environment and presents the scientific implication. Based on studies on aquatic environment monitoring techniques, this study suggests research directions for monitoring the residual concentration and distribution of harmful chemical substances in aquatic ecosystems. In particular, this study introduces the directions for research on trophic position analysis using compound specific isotope analysis and trophic magnification factors, which are needed to fulfill the contemporary requirements of selecting target fish based on the survey of major fish that inhabit domestic waters and assessment of associated health risk. In addition, this study provides suggestions for future biota monitoring and chemical research in Korea.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.41-48
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• 2023

This study was conducted to confirm the possibility of a new carbon stock in the Sejong National Arboretum, a major urban greenspace in Sejong-si. This study involved field and ground surveys of 1,336 trees, including 794 Pinus densiflora trees with a diameter at breast height (DBH) of above 5.5cm, which are the most planted in the Sejong National Arboretum, Chionanthus retusus 154 trees planted, Metasequoia glyptostroboides 216 trees, and Aesculus turbinata 172 trees as street trees. Measurements were performed from April to November. Based on the results of the survey, the carbon storage and annual carbon stock were calculated using the annual carbon stock estimation equation used in the forest carbon offset projects. As a result of comparing the carbon stock of the 12cm diameter class, which is the most distributed of four major trees, it was found in the order of C. retusus (0.0136tC/tree), P. densiflora (0.0126tC/tree), M. glyptostroboides (0.0092tC/tree), and A. turbinata (0.0076tC/tree). In addition, the field survey measurement data compared with terrestrial LiDAR measurement data for 20 trees showed a difference of 10.0cm in tree height and 1.7cm in diameter at breast height (p<0.05). In the future, additional carbon stock and annual uptake of other species planted in the arboretum are expected to promote the carbon uptake effect of the arboretum and contribute to the achievement of the national NDC. In the long term, it is also necessary to develop the carbon uptake factor of trees and shrubs mainly used to calculate the exact carbon uptake amount of trees mainly used in urban forests and gardens.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.31-61
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• 2000

Introduction. Despite the fact that half of premature deaths are caused by unhealthy lifestyles such as smoking tobacco, sedentary lifestyle, alcohol and drug abuse and poor nutrition, there are no theoretical models which accurately explain these health promotion related behaviors. This study tests a new model of health behavior called the Model of Health Promotion Behavior. This model draws on elements and frameworks suggested by the Health Belief Model, Social Cognitive Theory, the Theory of Planned Action and the Health Promotion Model. This model is intended as a general model of behavior but this first test of the model uses amount of exercise as the outcome behavior. Design. This study utilized a cross sectional mail-out, mail-back survey design to determine the elements within the model that best explained intentions to exercise and those that best explained amount of exercise. A follow-up questionnaire was mailed to all respondents to the first questionnaire about 10 months after the initial survey. A pretest was conducted to refine the questionnaire and a pilot study to test the protocols and assumptions used to calculate the required sample size. Sample. The sample was drawn from 2000 eligible participants at two blue collar (utility company and part of a hospital) and two white collar (bank and pharmaceutical) companies located in Southeastern Michigan. Both white collar site had employee fitness centers and all four sites offered health promotion programs. In the first survey, 982 responses were received (49.1％) after two mailings to non-respondents and one additional mailing to secure answers to missing data, with 845 usable cases for the analyzing current intentions and 918 usable cases for the explaining of amount of current exercise analysis. In the follow-up survey, questionnaires were mailed to the 982 employees who responded to the initial survey. After one follow-up mailing to non-respondents, and one mailing to secure answers to missing data, 697 (71.0％) responses were received, with 627 (63.8％) usable cases to predict intentions and 673 (68.5％) usable cases to predict amount of exercise. Measures. The questionnaire in the initial survey had 15 scales and 134 items; these scales measured each of the variables in the model. Thirteen of the scales were drawn from the literature, all had Cronbach's alpha scores above .74 and all but three had scores above .80. The questionnaire in the second mailing had only 10 items, and measured only outcome variables. Analysis. The analysis included calculation of scale scores, Cronbach's alpha, zero order correlations, and factor analysis, ordinary least square analysis, hierarchical tests of interaction terms and path analysis, and comparisons of results based on a random split of the data and splits based on gender and employer site. The power of the regression analysis was .99 at the .01 significance level for the model as a whole. Results. Self efficacy and Non-Health Benefits emerged as the most powerful predictors of Intentions to exercise, together explaining approximately 19％ of the variance in future Intentions. Intentions, and the interaction of Intentions with Barriers, with Support of Friends, and with Self Efficacy were the most consistent predictors of amount of future exercise, together explaining 38％ of the variance. With the inclusion of Prior Exercise History the model explained 52％ of the variance in amount of exercise 10 months later. There were very few differences in the variables that emerged as important predictors of intentions or exercise in the different employer sites or between males and females. Discussion. This new model is viable in predicting intentions to exercise and amount of exercise, both in absolute terms and when compared to existing models.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.363-370
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• 2023

Various earth observation satellites need to provide accurate and high-quality data after launch. To maintain and enhance the quality of satellite data, it is crucial to employ a cross-calibration process that accounts for differences in sensor characteristics, such as the spectral band adjustment factor (SBAF). In this study, we utilized Landsat-8 and Sentinel-2A satellite imagery collected from desert sites in Libya4, Algeria3, and Mauritania2 among pseudo-invariant calibration sites to calculate and apply SBAF, thereby compensating the uncertainties arising from variations in bandwidths. We quantitatively compared the reflectance differences based on the similarity of bandwidths, including Blue, Green, Red, and both the near-infrared (NIR) narrow, and NIR bands of Sentinel-2A. Following the application of SBAF, significant results with reflectance differences of approximately 1% or less were observed for all bands except NIR. In the case of the Sentinel-2A NIR band, it exhibited a significantly larger bandwidth difference compared to the NIR narrow band. However, after applying SBAF, the reflectance difference fell within the acceptable error range (5%) of 1-2%. It indicates that SBAF can be applied even when there is a substantial difference in the bandwidths of the two sensors, particularly in situations where satellite utilization is limited. Therefore, it was determined that SBAF could be applied even when the bandwidth difference between the two sensors is large in a situation where satellite utilization is limited. It is expected to be helpful in research utilizing the quality and continuity of satellite data.