To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid...To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis(PARAFAC), principal component analysis(PCA), and discriminant function analysis(DFA) with the trophic index(TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter(CDOM), fluorescence excitation–emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters(turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices(EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.展开更多
Among water blooms,cyanobacteria bloom occurs over the widest range and is much more harmful than other blooms.Its occurrence in inland water bodies is affected by many factors,such as meteorology,hydrology,and human ...Among water blooms,cyanobacteria bloom occurs over the widest range and is much more harmful than other blooms.Its occurrence in inland water bodies is affected by many factors,such as meteorology,hydrology,and human activities.Therefore,the study of the causes of cyanobacterial bloom has become a major focus of scholars.The China Knowledge Network Journal Database contains 143 papers from China and abroad from the years 2004 to 2019 that are relevant to the study of cyanobacteria bloom.We begin by analyzing keywords in these studies and creating a keyword distribution map which indicates the factors related to the blooms.Based on parameters such as the frequency of words appearing in the text,the full text of each of the 143 papers is analyzed to form a word cloud created by a program written in Python language.After irrelevant terms are eliminated,the word cloud map can reveal potential factors that were not identified by keywords alone.After completing this macro analysis,we examined approximately 100 related papers from the China Knowledge Network Journal Database and Web of Science Database published from 2014 to 2019.Finally,we summarize the main reasons for the outbreak of water blooms.The factors causing blooms can be divided into natural factors and human factors.Among the natural factors are illumination,water temperature and nutrient salt conditions.The human factors are generally related to large-scale water conservancy projects.This paper analyzes and summarizes these factors,and provides a reference to aid in the prevention and treatment of algal blooms.The information in the paper has a certain practical significance for the protection of water environments.展开更多
基金the National Natural Science Foundation of China (No. 41376106)the Shandong Provincial Natural Science Foundation of China (No. ZR2013DM017)
文摘To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis(PARAFAC), principal component analysis(PCA), and discriminant function analysis(DFA) with the trophic index(TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter(CDOM), fluorescence excitation–emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters(turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices(EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.
基金Development and Testing Project of Algal Bloom Remote Sensing Processing Module(2018-S018)。
文摘Among water blooms,cyanobacteria bloom occurs over the widest range and is much more harmful than other blooms.Its occurrence in inland water bodies is affected by many factors,such as meteorology,hydrology,and human activities.Therefore,the study of the causes of cyanobacterial bloom has become a major focus of scholars.The China Knowledge Network Journal Database contains 143 papers from China and abroad from the years 2004 to 2019 that are relevant to the study of cyanobacteria bloom.We begin by analyzing keywords in these studies and creating a keyword distribution map which indicates the factors related to the blooms.Based on parameters such as the frequency of words appearing in the text,the full text of each of the 143 papers is analyzed to form a word cloud created by a program written in Python language.After irrelevant terms are eliminated,the word cloud map can reveal potential factors that were not identified by keywords alone.After completing this macro analysis,we examined approximately 100 related papers from the China Knowledge Network Journal Database and Web of Science Database published from 2014 to 2019.Finally,we summarize the main reasons for the outbreak of water blooms.The factors causing blooms can be divided into natural factors and human factors.Among the natural factors are illumination,water temperature and nutrient salt conditions.The human factors are generally related to large-scale water conservancy projects.This paper analyzes and summarizes these factors,and provides a reference to aid in the prevention and treatment of algal blooms.The information in the paper has a certain practical significance for the protection of water environments.
