• Economic and Environmental Geology
• /
• v.37 no.6 s.169
• /
• pp.631-645
• /
• 2004

This study assesses groundwater vulnerability to contaminants in industrial and residential/commercial areas of the city of Changwon, using DRASTIC technique and groundwater data. The DRASTIC technique was originally applied to situations in which the contamination sources are at the ground surface, and the contaminants flow into the groundwater with infiltration of rainfall. Mostly the industrial area has higher DRASTIC indices than the residential/commercial area. However, a part of the residential/commercial area having much groundwater production and great drawdown is more contaminated in groundwater than other industrial and the residential/commercial areas even if it has lowest DRASTIC indices in the study area. It indicates that groundwater contamination in urban areas can be closely related to excessive pumping resulting in a lowering of the water level. The correlation coefficient between minimum DRASTIC indices and the degree of poor water quality for 10 districts is as low as 0.40. On the other hand, the correlation coefficients between minimum DRASTIC indices and the groundwater discharge rate, and between minimum DRASTIC indices and well distribution density per unit area are 0.70 and 0.87, respectively. Thus, to evaluate the potential of groundwater contamination in urban areas, it is necessary to consider other human-made factors such as groundwater withdrawal rate and well distribution density per unit area as well as the existing seven DRASTIC factors.

• Journal of Korean Society of Water and Wastewater
• /
• v.36 no.4
• /
• pp.239-248
• /
• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

• Journal of Korean Society on Water Environment
• /
• v.22 no.5
• /
• pp.757-767
• /
• 2006

Biological assessments are the primary tool for evaluating the biological condition of a water body and makes it possible to understand accumulative and long-term effect of stressors. They also provide reliable biological information for which disturbed systems are to be restored. Sustainable water environment is not enough with attaining only the clean water, but it should sustain healthy and diverse aquatic life. Aquatic organisms are affected by various factors, including not only water quality but also habitat condition and stressors, and thus good condition of both physical and chemical water quality is prerequisite for sustaining healthy organisms. Therefore, biological assessment, along with other physical and chemical assessments, are crucial for evaluating the health of a water body. Overall, sustainability of water environment demands the attainment and maintenance of ecological integrity, which is resulted from the combination of physical, chemical and biological integrity. The biological criteria will play very important role in the water resource management and policy issues, and thus bioassessment program should be fully implemented and supported eventually by the law. To keep ecosystem health of water environment safely from the toxic pollutants and other stressors, the following suggestions need to be considered in environmental quality standards in Korea. For the first step, the biological indicators need to be introduced in evaluating river quality condition; they provide a qualitative description of biological condition of water body. Secondly, the biological water quality standards using biotic indices should be developed and implemented under the consideration of characteristics of Korean river systems. Lastly, the ecological status classification regime (ESCR) should be developed and introduced; it could be used in quality assessment of the water environment in general. In developing ESCR, integration of physico-chemical, biological, and habitat parameters should be taken into account.

• Journal of Ginseng Research
• /
• v.5 no.2
• /
• pp.108-113
• /
• 1981

Major quality indices for deterioration of red ginseng including oxidation of lipids and change of brown color intensity were periodically investicated during storage of Red Ginseng under various water activity conditions at 3$0^{\circ}C$. The results obtained were summarized as follows. 1. The monolayer moisture contents were 3.25% and 6.3% for red ginseng and red ginseng powder, respectively, and the corresponding water activities were 0.14 and 0.16, respectively. 2. Oxidation of lipids as measured by TBA value increased with an increase in relative humidity and storage period 3. Under storage conditions above 42% R H., brown color intensity also increased in similar fashion to that of oxidation of lipids as relative humidity and storage Period increased 4. It was concluded from above results that water activity of Red Ginseng should be kept less than 0.57 so that red ginseng could Preserve stable qualify.

• Journal of environmental and Sanitary engineering
• /
• v.16 no.3
• /
• pp.62-71
• /
• 2001

The present study was performed to examine the community structure of benthic macroinvertebrates in the provincial park of Mt. Daedun and its nearby region. Sampling was conducted two times in May.June and October.November, 2000. Main two areas are Mt. Anpyong (470.0m) and Mt. Daedun (877.0m) area. Total taxa of benthic macroinvertebrates were 111 species, 47 families, 15 orders, 6 classes in 4 phyla. Aquatic insects were composed of 29 species in ephemeroptera, 10 species in odonata, 7 species in plecoptera, 2 species in hemiptera, 2 species in megaloptera, 23 species trichuptera, 6 species in coleoptera and 17 species in diptera. Other non-insects were composed of 1 species in platyhelminthes, 8 species in gastropoda, 2 species in oligochaeta, 3 species in hirudinea and 1 species in crustacea. Ephemeroptera, trichoptera and plecoptera as indicators in clean water were very abundantly. Occurrence species at each surrey area was 77 species at Mt. Anpyong area and 89 species at Mt. Daedun area, respectively. Mean values of species diversity indices were 3.04 and 2.69, respectively. According to the saprobic system based on the species diversity indices of benthic macroinvertebrates, Mt. Anpyong region are determined as polysaprobic area or ${\beta}-mesosaprobic$ area and Mt. Daedun region are determined as polysaprobic area, $\beta-mesosaprobic$ area or ${\alpha}-mesosaprobic$ area.

• Journal of Korean Society on Water Environment
• /
• v.39 no.1
• /
• pp.87-101
• /
• 2023

The constituents of a watershed control a wide range of ecosystem processes, such as, carbon sequestration, nutrient retention, and biodiversity preservation. Maintenance of a healthy watershed is advantageous to humans in many direct and indirect ways. Dissolved organic matter fluorescence analysis is one of the most commonly utilized parameters for water quality measurement, pollution source tracking, and determination of the ecological state of a watershed. Throughout the recent decades, the advancement in data processing, instrumentation, and methods has resulted in many improvements in the area of watershed study with fluorescence analysis. The current trend of coupling advanced instrumentations and new comparative parameters, such as, microplastics of different types, antibiotics, and specific bacterial contaminants have been reported in watershed studies. However, conventional methodologies for obtaining fluorescence excitation emission matrices and for calculating the fluorescence and spectral indices are preferred to advanced methods, due to their easiness and simple data collection. This review aims to gain a general understanding of the use of dissolved organic matter fluorescence analysis for diagnosis and source identification of watershed pollutions, by focusing on how the studies have utilized fluorescence analysis to improve existing knowledge and techniques in recent years.

• Proceedings of the Korean Society of Applied Entomolohy Conference
• /
• 2002.11a
• /
• pp.68-68
• /
• 2002

• Journal of Environmental Impact Assessment
• /
• v.7 no.2
• /
• pp.103-112
• /
• 1998

Nature-friendly river project has became common practice in Japan. In order to make it available for the conservation and rehabilitation of desirable water environment, water criteria for water environmental assessment must be established. Especially, the criteria estimating the effects on ecosystem in and around river should be constructed. In this paper, classification method for water quality has been developed using biological indices and applied to observed data in Honmyo River, Nagasaki, Japan. Modified PI method (BI') has been suggested and those of three most abundant species resulted effective estimate for an overall water quality with comparatively simple procedure. Extensive database management code was prepared for the comprehensive ecological monitoring of river basin, which includes various biota. That system enables easy access of all the ecological data for a dissemination of a sound and sustainable water environment. The result of this study could improve knowledge base, serve making consensus for citizens, and help river management plans. In Japan, citizen's realization and action are the most critical factor for nature-friendly river restoration project.

• Journal of Gastric Cancer
• /
• v.17 no.4
• /
• pp.342-353
• /
• 2017

Purpose: This study evaluated the changes in nutritional status based on quality of life (QoL) item-level analysis to determine whether individual QoL responses might facilitate personal clinical impact. Materials and Methods: This study retrospectively evaluated QoL data obtained by the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Core 30 (QLQ-C30) and Quality of Life Questionnaire-Stomach (QLQ-STO22) as well as metabolic-nutritional data obtained by bioelectrical impedance analysis and blood tests. Patients were assessed preoperatively and at the 5-year follow-up. QoL was analyzed at the level of the constituent items. The patients were categorized into vulnerable and non-vulnerable QoL groups for each scale based on their responses to the QoL items and changes in the metabolic-nutritional indices were compared. Results: Multiple shortcomings in the metabolic-nutritional indices were observed in the vulnerable groups for nausea/vomiting (waist-hip ratio, degree of obesity), dyspnea (hemoglobin, iron), constipation (body fat mass, percent body fat), dysphagia (body fat mass, percent body fat), reflux (body weight, hemoglobin), dry mouth (percent body fat, waist-hip ratio), and taste (body weight, total body water, soft lean mass, body fat mass). The shortcomings in a single index were observed in the vulnerable groups for emotional functioning and pain (EORTC QLQ-C30) and for eating restrictions (EORTC QLQ-STO22). Conclusions: Long-term postoperative QoL deterioration in emotional functioning, nausea/vomiting, pain, dyspnea, constipation, dysphagia, reflux, eating restrictions, dry mouth, and taste were associated with nutritional shortcomings. QoL item-level analysis, instead of scale-level analysis, may help to facilitate personalized treatment for individual QoL respondents.

• Journal of Korea Water Resources Association
• /
• v.57 no.2
• /
• pp.73-85
• /
• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.