• Title/Summary/Keyword: Water resource monitoring

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On-line identification of the toxicological substance in the water system using Baysian technique (베이지언 기법을 이용한 수계 내의 독성물질 판단)

  • Jung, Ha Kyu;Jung, Jong Hyuk;Lee, Hyun Wook;Kwon, Won Tae;Kim, Sang Gil;Jeon, Sook Lye
    • Journal of Korean Society of Water and Wastewater
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    • v.22 no.1
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    • pp.73-78
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    • 2008
  • Water resource can be examined using biological sensors. Algae has been one of the biological sensors used to evaluate and to monitor the water pollution. The monitoring system, however, has not been used to determine what kind of the toxicological substance is in the water. It needs additional expensive chemical test to figure out the cause of the water pollution. In this study, an endeavor is made to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve(FIC) from algae using monitoring system. Fundamental curves are obtained from the experiments with specified amount of toxicant. Baysian method is utilized to determine the unknown toxicant in the water by comparing it with the fundamental curves. The results shows that the proposed method works fairly well.

On-line identification of the toxicological substance in the water system using Baysian technique (베이지언 기법을 이용한 수계 내의 독성물질 판단)

  • Jung, Ha-Kyu;Jung, Jong-Hyuk;Lee, Hyun-Wook;Kwon, Won-Tae;Kim, Sang-Gil;Jeon, Sook-Lye
    • Proceedings of the KSME Conference
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    • 2007.05b
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    • pp.3122-3127
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    • 2007
  • Water resource can be examined using biological sensors. Algae has been one of the biological sensors used to evaluate and monitor the water pollution. The monitoring system, however, could determine whether the examined water was safe or not. It needs additional expensive chemical test to figure out the cause of the water pollution. In this study, an endeavor is given to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve(FIC) from algae using monitoring system. Fundamental curves are obtained from the experiments with specified amount of toxicant. Baysian method is utilized to determine the unknown toxicant in the water by comparing it with the fundamental curves. The results shows that the proposed method works fairly well.

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Strengthen the Construction of Water Resources Monitoring Ability, Support the Strictest System of Water Resources management

  • Jiang, Yun-Zhong;Yi, Wan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.27-33
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    • 2012
  • At present, the overall water resources monitoring ability in China is weak since there is an absence of a sound monitoring system and comprehensive monitoring information. In addition to the problem of weak management ability in monitoring, measurement and information, it can hardly meet the need of implementing the strictest management system of water resource and also restricts the practice of the system to some extent. The production states the necessity of further development of water resources monitoring ability and points out the concept of "One Country, One Account" for constructing water resources information. There is an analysis on the demand on further development of water resources monitoring ability and profound discussion about the strategies for supporting "three red-line" management.

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Optimum conditions for artificial neural networks to simulate indicator bacteria concentrations for river system (하천의 지표 미생물 모의를 위한 인공신경망 최적화)

  • Bae, Hun Kyun
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1053-1060
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    • 2021
  • Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

Inhibition of Microcystis aeruginosa by the Extracellular Substances from an Aeromonas sp.

  • Liu, Yu-Mei;Chen, Ming-Jun;Wang, Meng-Hui;Jia, Rui-Bao;Li, Li
    • Journal of Microbiology and Biotechnology
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    • v.23 no.9
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    • pp.1304-1307
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    • 2013
  • Growth of Microcystis aeruginosa could be inhibited significantly within 24 h by the extracellular substances prepared from Aeromonas sp. strain FM. During the treatment, the concentration of extracellular soluble carbohydrates increased significantly in algal culture. Morphological and ultrastructural changes in M. aeruginosa cells, including breakage of the cell surface, secretion of mucilage, and intracellular disorganization of thylakoids, were observed. HPLC-MS analysis showed that the extracellular substances of Aeromonas sp. strain FM were a mixture of free amino acids, tripeptides, and clavulanate. Among these, the algaelysis effects of lysine and clavulanate were confirmed.

Algicidal Activity of a Dibenzofuran-Degrader Rhodococcus sp.

  • Wang, Meng-Hui;Peng, Peng;Liu, Yu-Mei;Jia, Rui-Bao;Li, Li
    • Journal of Microbiology and Biotechnology
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    • v.23 no.2
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    • pp.260-266
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    • 2013
  • Rhodococcus sp. strain p52, a previously isolated dibenzofuran degrader, could effectively inhibit the growth of cyanobacteria, including species of Microcystis, Anabaena, and Nodularia. When strain p52 was inoculated at the concentration of $7.7{\times}10^7$ CFU/ml, 93.5% of exponentially growing Microcystis aeruginosa ($7.3{\times}10^6$ cells/ml initially) was inhibited after 4 day. The threshold concentration for its algicidal activity against M. aeruginosa was $7.7{\times}10^6$ CFU/ml. Strain p52 exerted algicidal effect by synthesizing extracellular substances, which were identified as trans-3-indoleacrylic acid, DL-pipecolic acid, and L-pyroglutamic acid. The effective concentrations of trans-3-indoleacrylic acid and DL-pipecolic acid against M. aeruginosa were tested to be 0.5 mg/l and 5 mg/l, respectively.

Implementations of Remote Sensing, GIS, and GPS for Water Resources and Water Quality Monitoring

  • Wu, Mu-Lin;Chen, Chiou-Hsiung;Liu, Shiu-Feng;Wey, Jiun-Sheng
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1191-1193
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    • 2003
  • Water quantity and quality monitoring at Taipei Watershed Management Bureau (WRATB) is not only a daily business but also a long term job. WRATB is responsible for providing high quality drinking water to about four millions population in Taipei. The quality of drinking water provided by WRATB is among one of the best in Taiwan. The total area is 717 square kilometers. The water resource pollution is usually divided into two categories, point source pollution and nonpoint source pollution. Garbage disposal is the most important component of the point source pollution, especially those by tourist during holidays and weekends. Pesticide pollution, fertilizer pollution, and natural pollution are the major contributions for nonpoint source pollution. The objective of this paper is to implement remote sensing, geographic information systems, and global positioning systems to monitor water quantity and water quality at WRATB. There are 12 water quality monitoring stations and four water gauge stations at WRATB. The coordinates of the 16 stations were determined by GPS devices and created into the base maps. MapObjects and visual BASIC were implemented to create application modules for water quality and quantity monitoring. Water quality of the two major watersheds at WRATB was put on Internet for public review monthly. The GIS software, ArcIMS, can put location maps and attributes of all 16 stations on Internet for general public review and technical implementations at WRATB. Inquiry and statistic charts automatic manipulations for the past 18 years are also available. Garbage disposal by community and tourist were also managed by GIS and GPS. The storage, collection, and transportation of garbage were reviewed by ArcMap file format. All garbage cart and garbage can at WRATB can be displayed on the base maps. Garbage disposal by tourist during holidays and weekends can be managed by a PDA with a GPS device and a digital camera. Man power allocation for tourist garbage disposal management can be done in an integration of GIS and GPS. Monitoring of water quality and quantity at WRATB can be done on Internet and by a PDA.

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Spatial Distribution Mapping of Cyanobacteria in Daecheong Reservoir Using the Satellite Imagery (위성영상을 이용한 대청호 남조류의 공간 분포 맵핑)

  • Back, Shin Cheol;Park, Jin Ki;Park, Jong Hwa
    • Journal of The Korean Society of Agricultural Engineers
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    • v.58 no.2
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    • pp.53-63
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    • 2016
  • Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

Short-range sensing for fruit tree water stress detection and monitoring in orchards: a review

  • Sumaiya Islam;Md Nasim Reza;Shahriar Ahmed;Md Shaha Nur Kabir;Sun-Ok Chung;Heetae Kim
    • Korean Journal of Agricultural Science
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    • v.50 no.4
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    • pp.883-902
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    • 2023
  • Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

Design of In-situ Self-diagnosable Smart Controller for Integrated Algae Monitoring System

  • Lee, Sung Hwa;Mariappan, Vinayagam;Won, Dong Chan;Shin, Jaekwon;Yang, Seungyoun
    • International Journal of Advanced Culture Technology
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    • v.5 no.1
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    • pp.64-69
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    • 2017
  • The rapid growth of algae occurs can induce the algae bloom when nutrients are supplied from anthropogenic sources such as fertilizer, animal waste or sewage in runoff the water currents or upwelling naturally. The algae blooms creates the human health problem in the environment as well as in the water resource managers including hypoxic dead zones and harmful toxins and pose challenges to water treatment systems. The algal blooms in the source water in water treatment systems affects the drinking water taste & odor while clogging or damaging filtration systems and putting a strain on the systems designed to remove algal toxins from the source water. This paper propose the emerging In-Situ self-diagnosable smart algae sensing device with wireless connectivity for smart remote monitoring and control. In this research, we developed the In-Site Algae diagnosable sensing device with wireless sensor network (WSN) connectivity with Optical Biological Sensor and environmental sensor to monitor the water treatment systems. The proposed system emulated in real-time on the water treatment plant and functional evaluation parameters are presented as part of the conceptual proof to the proposed research.