Phosphorus speciation in the Williams River, New South Wales: Eutrophication and a chemometric analysis of relationships with other water quality parameters

1995 ◽  
Vol 46 (7) ◽  
pp. 1055 ◽  
Author(s):  
AL Nolan ◽  
GA Lawrance ◽  
M Maeder
Keyword(s):  
Water Quality ◽  
Total Phosphorus ◽  
Algal Growth ◽  
Principal Component ◽  
River System ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Controlled Study ◽  
Data Set ◽  
Reactive Phosphorus

Phosphorus concentrations as both total phosphorus and partitioned (dissolved, 'bioavailable' and 'available-reactive') phosphorus have been determined in a quality-controlled study of the Williams River in the Hunter Valley, Australia, at Boags Hill during a five-month period. Complementary analyses of each sample for a range of standard water quality parameters were also obtained. Strong interrelationships between total phosphorus and partitioned phosphorus suggest that total phosphorus alone may be as adequate an indicator of potential algal growth as bioavailable phosphorus in this river system, an outcome supported by limited algal bioassay results. Principal component or factor analysis of the complete data set allowed qualitative insight into the relationship between the different concentrations (relevant cations and anions) and other measurements (colour (apparent), turbidity, etc.). Compounds from similar sources are clustered in the principal component plots. The samples taken over a specific time period have been analysed in a similar way, with clustering according to rainfall patterns being clearly indicated.

Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-Tongue

2017 ◽  
Vol 60 (4) ◽  
pp. 1037-1044
Author(s):  
Zhenbo Wei ◽  
Yu Zhao ◽  
Jun Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Pattern Recognition ◽  
Comprehensive Evaluation ◽  
Back Propagation ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Pattern Recognition Methods

Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. Keywords: Classify, E-tongue, Goldfish water, Prediction.

scholarly journals Economic evaluation of the impacts of water quality on fishery production in the Estuary Complex of Santos, São Vicente and Bertioga cities, in southeastern coast of Brazil

2020 ◽  
Vol 56 (1) ◽  
pp. 99-110
Author(s):  
Victor Carrozza Barcellini ◽  
Ângela Tavares Paes ◽  
Simone Georges El Khouri Miraglia
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Total Phosphorus ◽  
Linear Models ◽  
Quality Parameters ◽  
Sao Paulo ◽  
Water Quality Parameters ◽  
São Paulo ◽  
Fishing Activity ◽  
Monetary Loss

The present study proposes a diagnosis of water quality and fishery production in the Estuarine Complex of Santos, São Vicente, and Bertioga Cities as a requirement for economic valuation of water pollution impacts on fishing production. In the study period (2009–2014), three water quality parameters were identified (dissolved oxygen, total phosphorus, and nitrate), which occurred more frequently in non-conformity with Brazilian water standards, according to reports released by the Environmental Company of São Paulo State (Companhia Ambiental do Estado de São Paulo — CETESB). For data collection of fishery production, data from the monitoring of Institute of Fisheries of Santos City (Instituto de Pesca de Santos) were used, and 15 species were identified with higher occurrence in the study area. The relation between water quality parameters and fishery production was analyzed with mixed linear models, in which significant values for dissolved oxygen parameters, total phosphorus (positive relation), and nitrate (negative relation) were found. Environmental valuation considered only the direct use values (DUV) component of the valuation of fishery production variation in relation to water quality variation. For this purpose, the Marginal Productivity Method (MPM) of the dose-response function was used, which resulted in a range of monetary loss between US$ 24,760,550.22 and US$ 60,635,978.78. The obtained values represent only a portion of the valuation of economic and environmental loss in the fishing activity (part of DUV). Therefore, economic value calculated is conservative, and although it did not reached the total amount corresponding to all the impacts caused by poor water quality, given the limitations of methods and study period, the obtained values represent the minimum environmental monetary loss.

scholarly journals Assessment of the Ecological Health of Afrotropical Rivers Using Fish Assemblages: A Case Study of Selected Rivers in the Lake Victoria Basin, Kenya

2021 ◽  
Vol 2 ◽  
Author(s):  
Alfred O. Achieng ◽  
Frank O. Masese ◽  
Tracey J. Coffey ◽  
Phillip O. Raburu ◽  
Simon W. Agembe ◽  
...  
Keyword(s):  
Water Quality ◽  
Fish Species ◽  
Fish Assemblages ◽  
Lake Victoria ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Lake Victoria Basin ◽  
Anthropogenic Pressures ◽  
Species Tolerance

Streams and rivers are globally threatened ecosystems because of increasing levels of exploitation, habitat degradation and other anthropogenic pressures. In the Lake Victoria Basin (LVB) in East Africa, these threats are mostly caused by unsustainable land use; however, the monitoring of ecological integrity of river systems has been hampered by a lack of locally developed indices. This study assessed the health of four rivers (Nzoia, Nyando, Sondu–Miriu and Mara) on the Kenyan side of the LVB using physicochemical water quality parameters and a fish-based index of biotic integrity (IBI). Fish tolerance ranking was derived from principal component analysis of water quality parameters, and the concept of niche breadth (NB). The relationship between fish species and water quality parameters was examined with canonical correspondence analysis, whereas community metrics and stressors were evaluated through Pearson network correlation analysis. Fish species richness, trophic structures, taxonomic composition and species tolerance were used to generate the metrics for fish-based IBI. NB showed that most of the fish species were moderately tolerant to poor water. Moderately tolerant and intolerant fish species were negatively correlated with a high level of organic loading in the Mara River. Fish-based IBI scores for the rivers ranged from 26 to 34, with Sondu–Miriu scoring the lowest. Our results show that the cumulative effect of stressors can adequately rank fish species tolerance according to the disturbance gradients and further develop regional metrics to assess river health. Despite the fact that fish communities are declining, continual management and enforcement of environmental regulations are important, with conservation and management of headwaters and low-order streams being essential while they are still species rich.

Assessment of Water Quality Parameters on Uzuncayır Dam Lake Using Principal Component and Cluster Analysis

2016 ◽  
Vol 16 (3) ◽  
Author(s):  
Banu KUTLU ◽  
Azime KÜÇÜKGÜL ◽  
Osman SERDAR ◽  
Rahmi AYDIN ◽  
Durali DANABAŞ
Keyword(s):  
Water Quality ◽  
Cluster Analysis ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
And Cluster Analysis

scholarly journals Integrated versus isolated scenario for prediction dissolved oxygen at progression of water quality monitoring stations

2011 ◽  
Vol 15 (8) ◽  
pp. 2693-2708 ◽  
Author(s):  
A. Najah ◽  
A. El-Shafie ◽  
O. A. Karim ◽  
O. Jaafar
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Prediction Model ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Effective Parameters ◽  
Data Set ◽  
Proposed Model ◽  
Input Parameters ◽  
Predicted Values

Abstract. This study examined the potential of Multi-layer Perceptron Neural Network (MLP-NN) in predicting dissolved oxygen (DO) at Johor River Basin. The river water quality parameters were monitored regularly each month at four different stations by the Department of Environment (DOE) over a period of ten years, i.e. from 1998 to 2007. The following five water quality parameters were selected for the proposed MLP-NN modelling, namely; temperature (Temp), water pH, electrical conductivity (COND), nitrate (NO3) and ammonical nitrogen (NH3-NL). In this study, two scenarios were introduced; the first scenario (Scenario 1) was to establish the prediction model for DO at each station based on five input parameters, while the second scenario (Scenario 2) was to establish the prediction model for DO based on the five input parameters and DO predicted at previous station (upstream). The model needs to verify when output results and the observed values are close enough to satisfy the verification criteria. Therefore, in order to investigate the efficiency of the proposed model, the verification of MLP-NN based on collection of field data within duration 2009–2010 is presented. To evaluate the effect of input parameters on the model, the sensitivity analysis was adopted. It was found that the most effective inputs were oxygen-containing (NO3) and oxygen demand (NH3-NL). On the other hand, Temp and pH were found to be the least effective parameters, whereas COND contributed the lowest to the proposed model. In addition, 17 neurons were selected as the best number of neurons in the hidden layer for the MLP-NN architecture. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Coefficient of Efficiency (CE), Mean Square Error (MSE) and Coefficient of Correlation (CC). A relatively low correlation between the observed and predicted values in the testing data set was obtained in Scenario 1. In contrast, high coefficients of correlation were obtained between the observed and predicted values for the test sets of 0.98, 0.96 and 0.97 for all stations after adopting Scenario 2. It appeared that the results for Scenario 2 were more adequate than Scenario 1, with a significant improvement for all stations ranging from 4 % to 8 %.

scholarly journals Statistical Assessment of Water Quality Parameters for Pollution Source Identification in Sukhnag Stream: An Inflow Stream of Lake Wular (Ramsar Site), Kashmir Himalaya

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Salim Aijaz Bhat ◽  
Gowhar Meraj ◽  
Sayar Yaseen ◽  
Ashok K. Pandit
Keyword(s):  
Water Quality ◽  
Cluster Analysis ◽  
Principal Component ◽  
Pollution Source ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Accumulation Factor ◽  
Kashmir Himalaya ◽  
And Cluster Analysis ◽  
Maximum Similarity

The precursors of deterioration of immaculate Kashmir Himalaya water bodies are apparent. This study statistically analyzes the deteriorating water quality of the Sukhnag stream, one of the major inflow stream of Lake Wular. Statistical techniques, such as principal component analysis (PCA), regression analysis, and cluster analysis, were applied to 26 water quality parameters. PCA identified a reduced number of mean 2 varifactors, indicating that 96% of temporal and spatial changes affect the water quality in this stream. First factor from factor analysis explained 66% of the total variance between velocity, total-P, NO3–N, Ca2+, Na+, TS, TSS, and TDS. Bray-Curtis cluster analysis showed a similarity of 96% between sites IV and V and 94% between sites II and III. The dendrogram of seasonal similarity showed a maximum similarity of 97% between spring and autumn and 82% between winter and summer clusters. For nitrate, nitrite, and chloride, the trend in accumulation factor (AF) showed that the downstream concentrations were about 2.0, 2.0, and 2.9, times respectively, greater than upstream concentrations.

scholarly journals EVALUATING SURFACE WATER QUALITY AND WATER MONITORING PARAMETERS IN THE TIEN RIVER, VIETNAMESE MEKONG DELTA

2021 ◽  
Vol 83 (3) ◽  
pp. 29-36
Author(s):  
Thanh Giao Nguyen ◽  
Vo Quang Minh
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring Program ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Monitoring ◽  
Water Quality Parameters

The study aimed to evaluate the surface water quality of the Tien River and identify water quality parameters to be monitored using the water quality monitoring data in the period of 2011 - 2019. The water samples were collected at five locations from Tan Chau to Cho Moi districts, An Giang province for three times per year (i.e., in March, June, and September). Water quality parameters included temperature (oC), pH, dissolved oxygen (DO), total suspended solids (TSS), nitrate (NO3--N), orthophosphate (PO43--P), biological oxygen demand (BOD), and coliforms. These parameter results were compared with the national technical regulation on surface water quality QCVN 08-MT: 2015/BTNMT, column A1. Principal component analysis (PCA) was used to identify the sources of pollution and the main factors affecting water quality. The results of this study showed that DO concentration was lower and TSS, BOD, PO43--P, coliforms concentrations in the Tien river exceeded QCVN 08-MT: 2015/BTNMT, column A1. pH, temperature, and NO3--N values were in accordance with the permitted regulation. The water monitoring parameters were seasonally fluctuated. DO, BOD, TSS, and coliforms concentrations were higher in the rainy season whereas NO3--N and PO43--P were higher in the dry season. The PCA results illustrated that pH, TSS, DO, BOD, PO43--P and coliforms should be included in the monitoring program. Other indicators such as temperature and NO3--N could be considered excluded from the program to save costs. 

scholarly journals Assessment of Water Quality for Aquaculture in Hau River, Mekong Delta, Vietnam Using Multivariate Statistical Analysis

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3307
Author(s):  
Fridah Gacheri Mutea ◽  
Howard Kasigwa Nelson ◽  
Hoa Van Au ◽  
Truong Giang Huynh ◽  
Ut Ngoc Vu
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Soluble Solids ◽  
Accumulation Factor ◽  
Multivariate Statistical ◽  
Aquaculture Production

The deterioration signs of water quality in the Hau River are apparent. The present study analyzed the surface water quality of the Hau River using multivariate statistical techniques, including principal component analysis (PCA) and Cluster Analysis (CA). Eleven water quality parameters were analyzed at 19 different sites in An Giang and Can Tho Provinces for 12 months from January to December 2019. The findings show high levels of Biological Oxygen Demand (BOD), Total Soluble Solids (TSS), and total coliform, all year round. The PCA revealed that all the water quality parameters influenced the water quality of the Hau River, hence the relevance for water sample scrutiny. The dendrogram of similarity between sampling sites showed a maximum similarity of 95.6%. The Accumulation Factor (AF) trend showed that the concentrations/values of TSS, BOD, and phosphate (PO43−) in the downstream were 1.29, 1.53, and 1.52 times, respectively, greater than the upstream levels. Despite most of the parameters analyzed supporting aquaculture production, caution is needed in the regulation of pollution point sources to undertake sustainable aquaculture production.

scholarly journals Phycocyanin as a proxy for algal blooms in surface waters: case study of Ukerewe Island, Tanzania

2019 ◽  
Vol 14 (1) ◽  
pp. 229-239 ◽  
Author(s):  
Geofrey J. Mchau ◽  
Edna Makule ◽  
Revocatus Machunda ◽  
Yun Yun Gong ◽  
Martin Kimanya
Keyword(s):  
Water Quality ◽  
Redox Potential ◽  
Algal Blooms ◽  
Nitrate Nitrogen ◽  
Quality Parameters ◽  
Water Sources ◽  
Water Quality Parameters ◽  
Total Chlorophyll ◽  
Nitrite Nitrogen ◽  
Reactive Phosphorus

Abstract Knowledge of the parameters that contribute to water body eutrophication is essential for proper monitoring and management of water quality for human consumption. This study assessed water quality parameters in relation to phycocyanin (PC) as a proxy indicator for harmful algal blooms (HABs). Samples were collected from 23 water sources – lakes, wells, springs and boreholes – in selected villages, for six months. Parameters measured included temperature, pH, redox potential, dissolved oxygen, electrical conductivity, total dissolved solids, nitrate nitrogen, nitrite nitrogen, phosphorus, reactive phosphate and total chlorophyll, which were related to (PC) occurrence. The PC concentration detected in Lake Victoria ranged from 5 to 58.4 μg/l above the WHO alert level and exceeded that in other water sources by almost 30 μg/l (P < 0.001). Univariate relationship between water quality parameters and PC indicates association with temperature, redox potential, total chlorophyll, nitrate nitrogen, nitrite nitrogen, phosphate and reactive phosphorus (P < 0.001). The multivariate model indicates that redox potential, nitrate nitrogen and phosphorus are significant statistically (P < 0.05). A predictive model indicates that nitrate nitrogen and reactive phosphorus contribute significantly to PC occurrence whereby unit (1 mg/l) increases in these parameters increase PC by 9.55 and 4.38 μg/l (P < 0.05) respectively. This study demonstrates that water quality parameters can be used to predict increases in PC and hence as a proxy for HABs. It remains important to be able to classify algal blooms, to understand which species are present and their potential cyanotoxin production.

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