김준오 Juneoh Kim , 박정수 Jungsu Park

DOI:10.15681/KSWE.2023.39.1.1 Vol.39(No.1) 1-8, 2023

Monitoring and prediction of water quality are essential for effective river pollution prevention and water quality management. In this study, a multi-classification model was developed to predict chlorophyll-a (Chl-a) level in rivers. A model was developed using CatBoost, a novel ensemble machine learning algorithm. The model was developed using hourly field monitoring data collected from January 1 to December 31, 2015. For model development, chl-a was classified into class 1 (Chl-a≤10 ㎍/L), class 2 (10< Chl-a≤50 ㎍/L), and class 3 (Chl-a >50 ㎍/L), where the number of data used for the model training were 27,192, 11,031, and 511, respectively. The macro averages of precision, recall, and F1-score for the three classes were 0.58, 0.58, and 0.58, respectively, while the weighted averages were 0.89, 0.90, and 0.89, for precision, recall, and F1-score, respectively. The model showed relatively poor performance for class 3 where the number of observations was much smaller compared to the other two classes. The imbalance of data distribution among the three classes was resolved by using the synthetic minority over-sampling technique (SMOTE) algorithm, where the number of data used for model training was evenly distributed as 26,868 for each class. The model performance was improved with the macro averages of precision, rcall, and F1-score of the three classes as 0.58, 0.70, and 0.59, respectively, while the weighted averages were 0.88, 0.84, and 0.86 after SMOTE application.

Algal bloom, CatBoost, Ensemble Machine learning, SMOTE, Water quality prediction

서지유 Jiyu Seo , 이정훈 Jeonghoon Lee , 이호선 Hosun Lee , 김상단 Sangdan Kim

DOI:10.15681/KSWE.2023.39.1.9 Vol.39(No.1) 9-19, 2023

Drought is a natural disaster that can have serious social impacts. Drought's impact ranges from water supply for humans to ecosystems, but the impact of drought on river water quality requires careful investigation. In general, drought occurs meteorologically and is classified as agricultural drought, hydrological drought, and environmental drought. In this study, the BOD environmental drought is defined using the bivariate copula joint probability distribution model between the meteorological drought index and the river BOD, and based on this, the environmental drought condition index (EDCI-BOD) was proposed. The results of examining the proposed index using past precipitation and BOD observation data showed that EDCI-BOD expressed environmental drought well in terms of river BOD water quality. In addition, by classifying the calculated EDCI-BOD into four levels, namely, ‘attention’, ‘caution’, ‘alert’, and ‘seriousness’, a practical monitoring stage for environmental drought of BOD was constructed. We further estimated the sensitivity of the stream BOD to meteorological drought, and through this, we could identify the stream section in which the stream BOD responded relatively more sensitively to the occurrence of meteorological drought. The results of this study are expected to provide information necessary for river BOD management in the event of meteorological droughts.

BOD, Copula, Environmental Drought Index, Meteorological Drought

홍동균 Dong-gyun Hong , 박혜경 Hae-kyung Park , 김용진 Yong-jin Kim

DOI:10.15681/KSWE.2023.39.1.20 Vol.39(No.1) 20-29, 2023

This study analyzed the relationship between harmful cyanobacterial abundance and environmental factors in order to figure out the causes of the recent increase of cyanobacteria in Lake Dukdong from 2019 to 2021. Lake Dukdong, which is used as a drinking water source for Gyeongju City, has an algae alert system in place. Lake Dukdong has maintained good water quality, but algae alert level 1 (over 1,000 cells/mL) has been issued in recent years. As a result of Pearson correlation analysis (from May to Oct.), the cell density of Microcystis and Aphanizomenon, which form part of the most harmful cyanobacteria genus, were significantly positively correlated with the water temperature and water storage volume. T-test was performed to compare the data from 2016-2018 and 2019-2021 (from May to Oct.). The average density of harmful cyanobacteria cells increased about six-fold from 54 to 344 cells/mL. There were significant differences in water temperature, pH, total nitrogen (TN), total phosphorus (TP), TN/TP ratio, water storage volume, and cyanobacterial cell density. Water temperature increased from 19.2 to 22.8 ℃. TP concentration increased from 0.017 to 0.028 mg/L. The main cause of the recent increase of harmful cyanobacteria in Lake Dukdong is thought to be the increase in water temperature, TP concentration, and water storage volume from 2019 and 2021, resulting in more favorable conditions for cyanobacterial growth.

Harmful cyanobacteria, Lake Dukdong, Water storage volume, Water temperature

이승원 Seung Won Lee , 서지훈 Jihoon Seo , 차성민 Sung Min Cha

DOI:10.15681/KSWE.2023.39.1.30 Vol.39(No.1) 30-37, 2023

This study aimed to evaluate the ability to reduce flood damage caused by abnormal rainfall events due to climate change by utilizing a blue-green roof (BGF), a type of rooftop greening technology. For two buildings with the same roof area, a BGF was installed in the experimental group, a general roof was configured in the control group, and rainfall runoff was compared. A total of 10 rainfall events were tested and analyzed by classifying them into three rainfall classes (less than 10 mm, less than 100 mm, and more than 100 mm). There was a reduction of 100% in the case of 10 mm or less of rainfall, 84. 7% in the case of 100 mm or less, and 39.8% in the case of 100 mm or more. Although this study showed that a BGF was effective in reducing rainfall runoff, additional experiments and analyses of various factors affecting rainfall runoff reduction are needed to generalize the results of the study. This research methodology may be used to develop a method for evaluating the resilience of a BGF to flood damage due to climate change.

Blue-Green Roof, Flood Damage Reduction, Green Infrastructure, Stormwater Runoff

강희만 Heeman Kang , 전지홍 Ji-hong Jeon

DOI:10.15681/KSWE.2023.39.1.38 Vol.39(No.1) 38-45, 2023

In this study, the removal efficiency of road sweeping and sand filter facility for removing total suspended solid (TSS) as nonpoint source pollution from expressway was evaluated for the last 10 years (2012~2021) using ROADMOD. ROADMOD is a screening level model and was calibrated for runoff rate and TSS loading both at the inlet, which is the loading from the drainage area, and the outlet, from the sand filter facility. The drainage area is 715 m² and the dimensions of sand filter facility are 1.5 m (wide) × 3.8 m (length) × 1.5 m (depth). The monitoring period for model calibration was the rainfall event during Aug. 31~ Sep. 1, 2021 and the amount of rainfall was 74.5 mm. As a result of calibration, the determination coefficients (R²) of the flow rate were 0.66 and 0.86, for the inlet and outlet, respectively, and those of TSS loading were 0.50 and 0.84, for the inlet and outlet, respectively. Considering that ROADMOD is a screening level model, the calibration results were reasonable to evaluate the best management practices (BMPs) on the expressway. Using ROADMOD simulation results for 2012~2021, the average yearly runoff rate from the expressway was 82% and removal efficiency was 9% for road sweeping, 35% for sand filter facility, and 39% for both road sweeping and sand filter facility.

Best management practices, BMPs, Expressway, Road-deposited sediment, SDR, Road sweeping, Sand filter facility

한지우 Jiwoo Han , 조용철 Yong-chul Cho , 이소영 Soyoung Lee , 김상훈 Sanghun Kim , 강태구 Taegu Kang

DOI:10.15681/KSWE.2023.39.1.46 Vol.39(No.1) 46-60, 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

Feature Importance, GRU, LSTM, Random Forest, Recurrent Neural Network, Water Quality

박수인 Suin Park , 전준범 Junbeom Jeon , 최민규 Minkyu Choi , 김성진 Sungjin Kim , 이상헌 Sanghun Lee , 이태호 Taeho Lee , 정상현 Sanghyun Jeong , 배효관 Hyokwan Bae

DOI:10.15681/KSWE.2023.39.1.61 Vol.39(No.1) 61-75, 2023

Denitrifying bacteria convert nitrate to nitrogen gas using an external carbon source as an electron donor. The external carbon source affects the denitrification performance and bacterial community structure. Although methanol is a cheap and effective external carbon source, the addition of diverse carbon sources may improve the total nitrogen removal rate and biomass characteristics, such as settleability. In this study, denitrifying reactions were performed using solely methanol and mixed carbon sources of methanol, glucose, and acetate in a sequencing batch reactor. The denitrifying reactor using methanol resulted in a total nitrogen removal rate of 0.39 ± 0.025 kg-N/㎥-day while the suspended biomass transformed into dark brown granules. Methyloversatilis discipulorum had the highest predominance at 43.84%. The individual denitrifying biomasses, which were separately enriched with methanol, glucose, and acetate, showed the same total nitrogen removal performance of 0.39 ± 0.016 kg-N/㎥-day. However, the addition of mixed carbon sources showed an improved total nitrogen removal rate of 0.42 ± 0.043 kg-N/㎥-day, with the domination of Candidatus Saccaribacteria at 25.61%. The denitrifying granules turned pale yellow color. Influent COD/NO₃ ^--N ratios of 3.5, 5, and 7.5 exhibited COD/NO₃ ^--N consumptions of 4.3 ± 0.4, 4.4 ± 0.8, and 5.2 ± 0.7, and the consistent predominance of Candidatus Saccharibacteria.

Bacterial community structure, Denitrification, Granule, Methanol, Mixed carbon sources, Settleability

최용주 Yongju Choi , 이우람 Wooram Lee

DOI:10.15681/KSWE.2023.39.1.76 Vol.39(No.1) 76-86, 2023

We are on the verge of paradigm shift for the design and operation of our urban water systems from treatment- and efficiency-based to recirculation- and sustainability-based. One of the most frequently suggested alternatives to embody this paradigm shift is to decentralize the currently highly centralized urban water infrastructure. However, claims for water infrastructure decentralization are often criticized due to poor economic feasibility, unstable performance, and unprofessional operation and maintenance. The current study critically reviews the literature to discuss the technical advancement needs to overcome such challenges. Firstly, decentralized water infrastructure was briefly defined and the rationale for the proposal of its introduction to the next-generation urban water systems was laid down. The main discussion focused on the following water technologies, which require special attention when working with decentralized water infrastructure: i) material collection, storage, and transport; ii) easily scalable water treatment; iii) sensor, information, and communications; and iv) system optimization. The principles, current development status, and challenges were discussed for each of the water technologies. The discussion on the water technologies has enabled the identification of future research needs for their application to the next-generation urban water systems which will be designed following decentralized water infrastructure. This paper will significantly improve the current understanding on water infrastructure decentralization and provides insight on future direction of water technology development.

Decentralization, Infrastructure, Sustainability, Urban water system, Water management

칸다따라니푸니디니샤 Kandaddara Badalge Nipuni Dineesha , 허진 Jin Hur , 이병준 Byung Joon Lee

DOI:10.15681/KSWE.2023.39.1.87 Vol.39(No.1) 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.

Fluorescence, Organic matter, Pollution, Watershed, Water quality

이재엽 Lee Jai-yeop , 이복진 Lee Bokjin , 제스민아터 Jesmin Akter , 안창혁 Ahn Chang Hyuk , 김일호 Kim Ilho

DOI:10.15681/KSWE.2023.39.1.102 Vol.39(No.1) 102-110, 2023

Wastewater Based Epidemiology (WBE) provides useful information not only on the use of illegal drugs in the community, but also on the presence of hygiene and health products and infectious pathogens in sewage facilities. As a consequence of the SARS-CoV-19 virus epidemic in 2019, monitoring the status of the infection is of utmost importance. SARS-CoV-19 was also detected in sewage, and the number and trend of infections in the community suggest that the application of the WBE system would be useful and appropriate. This study introduces a pre-treatment concentration method including viruses in sewage samples. A total of seven methods which were subdivided into methods for adsorption-extraction, ultra-filtration, PEG precipitation, and ultra-centrifugation, and the results for analyzing the recovery rates were included. Meanwhile, it is necessary to pay attention to rapid detection technologies which analyze infectious pathogens at the site of sewage facilities. These can include ELISA, FTIR, SERS, and biosensor based on the detection principle, and the characteristics, advantages, and disadvantages of each were summarized herein. If rapid detection technologies and accurate quantitative analyses are further developed, the use of sewage mechanics in response to pandemic viruses is expected to expand further.

Infectious pathogen, Pathogen Concentration, Rapid Forensic, SARS-CoV-19, Wastewater Based Epidemiology