Analysis and prediction of eutrophication for advanced warning of the water quality concerns in Gaoyou Lake

2019 ◽  
Vol 20 (1) ◽  
pp. 186-196
Author(s):  
Lei Zhang ◽  
Yu Cheng ◽  
Yulong Niu ◽  
Jiahu Jiang
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Principal Component ◽  
Scientific Basis ◽  
Contribution Rate ◽  
Increasing Trend ◽  
Trophic Level Index

Abstract This paper used the trophic level index (TLI) method combined with the relevant data from 2014 to 2017 to evaluate the water quality of Gaoyou Lake. Meanwhile, based on principal component analysis (PCA) and multiple linear regression (MLR) models on chlorophyll a (Chla), this research developed predictions and an early warning scheme for eutrophication in Gaoyou Lake. The results showed the following: 1. The TLI of Gaoyou Lake showed a significant increasing trend, and the lake was in the state of light to moderate eutrophy. 2. According to the PCA eigenvalues that were greater than 1, principal components (PCs) with a cumulative contribution rate of 76.04% were obtained, and a linear model was further obtained: CChla = 6.146 + 1.209 (Score 1) + 0.583 (Score 2) + 1.095 (Score 3). 3. The credibility of the early warning system reached 75%, which met the requirements of this study. This study provides a scientific basis for the control of eutrophication and improvement of water quality.

New Design for Water Quality Early Warning System

2012 ◽  
pp. 681-685
Author(s):  
Tian Jing ◽  
Zheng Shuyin ◽  
Zhang Guangxin ◽  
Hou Dibo ◽  
Huang Pingjie ◽  
...  
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System

scholarly journals Early Warning System and Monitoring of River Water Quality Based on Internet of Things

2021 ◽  
Vol 3 (1) ◽  
pp. 42-58
Author(s):  
Vito Hafizh Cahaya Putra ◽  
Mokhamad Hendayu ◽  
Purnomo Yustianto
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
River Water ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
River Water Quality ◽  
The Internet ◽  
Acceptance Test ◽  
Average Value

River conditions in Bandung City are currently in critical condition. This study aims to create an early warning system and monitoring of river water quality based on the Internet of Things in the hope that early warnings sent through the telegram application belonging to the Bandung City DLHK officer and the Twitter social media website, can inform the Bandung City DLHK officer that a river is in a polluted condition and the officer can immediately go to the location of river water to carry out mitigation, and give warnings to the community. The research method used using the waterfall method which consists of: needs analysis, system design, implementation, testing, and maintenance with sequential implementation. Data collection methods were carried out in several ways, namely: interviews, giving questionnaires, and literature studies used in this study sourced from books, journals, seminar presentations, and the internet as references in the research conducted. Based on the research that has been carried out, the following test results are obtained: black box testing is carried out in accordance with those contained in the test plan with the results of each test having valid results. The results obtained from the user acceptance test which are calculated using the Likert scale have an average value of 86.94% which fall into the category of strongly agree, and there are three guidelines which are a follow-up to the output of the early warning system that can be carried out either by the Environmental Service. and Cleanliness (DLHK) of Bandung City and the community.

Research and Application of Real-Time Remote Monitoring and Early Warning System of Source Water Quality

2013 ◽  
Vol 779-780 ◽  
pp. 1408-1413
Author(s):  
Shu Yuan Li ◽  
Jian Hua Tao ◽  
Lei Yu
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Early Warning ◽  
Remote Monitoring ◽  
Early Warning System ◽  
Warning System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
The Real ◽  
Monitoring And Early Warning

Drinking water sources play an important role in assurance of life safety, normal production and social stability. In this paper, a real-time remote water quality monitoring and early warning system has been developed. The paper concentrates on the system architecture and key techniques of the real-time water quality monitoring and early warning. The implementation of the system by advanced water quality sensor techniques, wireless transmission, databases and water quality modeling is retraced in detail. It can be applied to the real-time remote monitoring of water quality and decision support for water pollution incidents.

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