scholarly journals Use of sodium chloride and zeolite during shipment of Ancistrus triradiatus under high temperature

2011 ◽  
Vol 9 (4) ◽  
pp. 909-914 ◽  
Author(s):  
Wilson F. Ramírez-Duarte ◽  
Carolina Pineda-Quiroga ◽  
Nhora Martínez ◽  
Pedro R. Eslava-Mocha
Keyword(s):  
Water Quality ◽  
High Temperature ◽  
Sodium Chloride ◽  
Dissolved Oxygen ◽  
High Temperatures ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
High Concentration ◽  
Before And After ◽  
Total Ammonia

The use of sodium chloride (0.5 g/L and 1 g/L) and zeolite (22.7 g/L) during shipment (48 h) of Ancistrus triradiatus at high temperatures (between 24.5 and 34ºC) were evaluated. Several water quality parameters (dissolved oxygen, pH, conductivity, and total ammonia) were measured before and after shipment. Glycemia was measured before shipment and at 24 and 48 h after shipment. After shipment, a resistance test was carried out in a high concentration of sodium chloride, and mortality was recorded after shipment, and 7 days post-shipment. While the two evaluated substances increased survival of A. triradiatus challenged by high temperatures during shipment, the best result was obtained with 1 g/L of sodium chloride.

scholarly journals Plankton and water quality variability in an estuary before and after the shrimp farming effluents: possible impacts and regeneration

2017 ◽  
Vol 65 (3) ◽  
pp. 495-508
Author(s):  
William Bauer ◽  
Paulo Cesar Abreu ◽  
Luis Henrique Poersch
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Pacific White Shrimp ◽  
Shrimp Farming ◽  
Water Quality Parameters ◽  
White Shrimp ◽  
Zooplankton Abundance ◽  
Patos Lagoon ◽  
Short Period ◽  
Before And After

Abstract Water quality, chlorophyll a, phytoplankton, proto and mezo-zooplankton abundance were spatiotemporally evaluated in an estuary receiving effluents from a Pacific white shrimp Litopenaeus vannamei farm in Patos Lagoon estuary, Southern Brazil. Samples were taken before (BD) and; 1 day (1 PD) 5 days (5 PD), 10 days (10 PD), 20 days (20 PD) and 30 days (30 PD) after the effluents discharge. Some water quality parameters were affected by the effluents discharge; however, these changes were restricted to a distance of 20 m from the effluent discharge channel for a period of 5 days. The microbial community was dominated by chlorophyceae, followed by diatoms, cyanobacteria and ciliates. There was an increase in the abundance of different groups on the 1 PD sampling compared to BD. The zooplankton abundance was low in practically all sites, except for 30 PD sampling. The meso-zooplanktonic organisms were represented by copepods, mostly Acartia tonsa. Despite some effects on water quality and phytoplankton and protozooplankton abundance until 5 PD sampling, these alterations dissipated in a short period of time. We conclude that the environment quickly assimilated the effluents discharge, and the water quality parameters remained within the limits stipulated by standard guidelines.

scholarly journals Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

scholarly journals Potensi budidaya ikan di Waduk Embung Klamalu Kabupaten Sorong Provinsi Papua Barat: Kajian kualitas fisika kimia air

2013 ◽  
Vol 1 (3) ◽  
Author(s):  
Agustina Frasawi ◽  
Robert J Rompas ◽  
Juliaan Ch. Watung
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Good Condition ◽  
Fish Farming ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Physical Chemical ◽  
Papua Barat

The objective of this research was to measure and analyze the water quality parameters including temperature, brightness, pH, dissolved oxygen, total alkalinity, carbon dioxide and BOD in reservoir Embung Klamalu Sorong regency, and to know the factors that affected the water quality of Embung Klamalu. Measurement of water quality parameters was done in situ for temperature, brightness, pH and in laboratory for dissolved oxygen, total alkalinity, carbon dioxide, and BOD. The results showed the temperature at the five observation stations ranged from 26.2 to 29.8 0C, brightness 38 to 46 cm, pH 7.20 to 8.48 mg /L, dissolved oxygen from 7.20 to 8.48 mg / L, alkalinity 100 to 150 mg /L, carbon dioxide from 25.90 to 28.95 mg / L, BOD from 0.20 to 0.38. Refers to the standards of water quality according to the PP. 82, 2001, it could be concluded that water physical-chemical qualities in fish farming locations in the Village Klamalu were still in good condition. Keywords: Water physical-chemical quality, aquaculture, waduk Embung Klamalu

scholarly journals Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yashon O. Ouma ◽  
Clinton O. Okuku ◽  
Evalyne N. Njau
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Dissolved Oxygen ◽  
Multiple Linear Regression ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Monitoring

The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. The empirical, conceptual, and physical distributed models for the simulation of hydrological interactions may not adequately represent the nonlinear dynamics in the process of water quality prediction, especially in watersheds with scarce water quality monitoring networks. To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. To understand the influence of the contributing factors to the DO variations, the model considered the inputs from the available water quality parameters (WQPs) including discharge, electrical conductivity (EC), pH, turbidity, temperature, total phosphates (TPs), and total nitrates (TNs) as the basin land-use and land-cover (LULC) percentages. The performance of the FNN model is compared with the multiple linear regression (MLR) model. For both FNN and MLR models, the use of the eight water quality parameters yielded the best DO prediction results with respective Pearson correlation coefficient R values of 0.8546 and 0.6199. In the model optimization, EC, TP, TN, pH, and temperature were most significant contributing water quality parameters with 85.5% in DO prediction. For both models, LULC gave the best results with successful prediction of DO at nearly 98% degree of accuracy, with the combination of LULC and the water quality parameters presenting the same degree of accuracy for both FNN and MLR models.

scholarly journals Can Decomposition Approaches Always Enhance Soft Computing Models? Predicting the Dissolved Oxygen Concentration in the St. Johns River, Florida

2019 ◽  
Vol 9 (12) ◽  
pp. 2534 ◽  
Author(s):  
Mohammad Zounemat-Kermani ◽  
Youngmin Seo ◽  
Sungwon Kim ◽  
Mohammad Ali Ghorbani ◽  
Saeed Samadianfard ◽  
...  
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Soft Computing ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Performance Criteria ◽  
Input Combination ◽  
Do Concentration ◽  
Computing Models

This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron (MLP) neural network and cascade correlation neural network (CCNN), were proposed for estimating the DO concentration in the St. Johns River, Florida, USA. The DO concentration and water quality parameters (e.g., chloride (Cl), nitrogen oxides (NOx), total dissolved solid (TDS), potential of hydrogen (pH), and water temperature (WT)) were used for developing the standalone models by defining six combinations of input parameters. Results were evaluated using five performance criteria metrics. Overall results revealed that the CCNN model with input combination III (CCNN-III) provided the most accurate predictions of DO concentration values (root mean square error (RMSE) = 1.261 mg/L, Nash-Sutcliffe coefficient (NSE) = 0.736, Willmott’s index of agreement (WI) = 0.919, R2 = 0.801, and mean absolute error (MAE) = 0.989 mg/L) for the standalone model category. In the second stage, two decomposition approaches, including discrete wavelet transform (DWT) and variational mode decomposition (VMD), were employed to improve the accuracy of DO concentration using the MLP and CCNN models with input combination III (e.g., DWT-MLP-III, DWT-CCNN-III, VMD-MLP-III, and VMD-CCNN-III). From the results, the DWT-MLP-III and VMD-MLP-III models provided better accuracy than the standalone models (e.g., MLP-III and CCNN-III). Comparison of the best hybrid soft computing models showed that the VMD-MLP-III model with 4 intrinsic mode functions (IMFs) and 10 quadratic penalty factor (VMD-MLP-III (K = 4 and α = 10)) model yielded slightly better performance than the DWT-MLP-III with Daubechies-6 (D6) and Symmlet-6 (S6) (DWT-MLP-III (D6 and S6)) models. Unfortunately, the DWT-CCNN-III and VMD-CCNN-III models did not improve the performance of the CCNN-III model. It was found that the CCNN-III model cannot be used to apply the hybrid soft computing modeling for prediction of the DO concentration. Graphical comparisons (e.g., Taylor diagram and violin plot) were also utilized to examine the similarity between the observed and predicted DO concentration values. The DWT-MLP-III and VMD-MLP-III models can be an alternative tool for accurate prediction of the DO concentration values.

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 Stress response in transport of juvenile cobia Rachycentron canadum using the anesthetic benzocaine

2017 ◽  
Vol 44 (3) ◽  
pp. 638-642
Author(s):  
Janaína S. Pedron ◽  
Denise S. Miron ◽  
Ricardo V. Rodrigues ◽  
Marcelo H. Okamoto ◽  
Marcelo B. Tesser ◽  
...  
Keyword(s):  
Water Quality ◽  
Blood Glucose ◽  
Stress Response ◽  
Stocking Density ◽  
Ammonia Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Blood Samples ◽  
Total Ammonia Nitrogen ◽  
Total Ammonia

This experiment evaluated the efficacy of benzocaine to reduce stress response during transport of juvenile cobia. Fish (30 g) were packed in bags and transported for 8 h (stocking density = 10 g L-1). Three concentrations of benzocaine were evaluated: 0, 2, and 6 mg L-1. Blood samples were taken for glucose and hematocrit before transportation, and then at 0, 2, 24, and 48 h after. Water quality parameters were verified. No mortality was observed. Total ammonia nitrogen was higher (2.46 mg L-1) and pH was lower (6.92) at 2 mg benzocaine L-1. There was an increase in blood glucose for all treatments on arrival, and it was higher for those exposed to benzocaine at 6 mg L-1, although at 48 h they were all similar. The hematocrit did not differ among treatments. The results suggest: 1) the density 10 g L-1 is considered safe for juvenile cobia transport; 2) benzocaine did not mitigate stress response on cobia during transport, therefore its use is not recommended for this purpose.

Effects of Two Types of Landfills on River Water Quality and Endocrine Disruptor Concentrations Before and After Rainfall in a Subtropical Climate

2009 ◽  
Vol 44 (4) ◽  
pp. 355-363 ◽  
Author(s):  
Chia-Wei Lin ◽  
Mei-Hui Li
Keyword(s):  
Water Quality ◽  
River Water ◽  
Quality Parameters ◽  
River Water Quality ◽  
Water Quality Parameters ◽  
Sanitary Landfill ◽  
Garbage Dump ◽  
Before And After ◽  
Dilution Effects

Abstract One closed uncontrolled landfill, the Neihu garbage dump, and one active controlled landfill, the Sanzhuku sanitary landfill, were selected for investigation of their leachate characteristics and effects on adjacent river water quality before and after rainfall in northern Taiwan. A total of seven samplings were made during February and June 2007, with four samplings done after individual rainfall events on study sites. Water quality of runoff samples collected from the Sanzhuku sanitary landfill showed less pollution than the water quality of leachates collected from the Neihu garbage dump; however, some water quality levels of leachate samples collected from the Neihu garbage dump were relatively high, such as ammonia nitrogen (NH3-N), orthophosphate (PO43-) and biochemical oxygen demand (BOD5). At the uncontrolled dump, rainfall lead to dilution effects on river water NH3-N and PO43- concentrations, but not other water quality parameters. In contrast, the concentrations of bisphenol A (BPA) and nonylphenol were increased in both types of landfills after rainfall in the present study. Dilution effects of rainfall on most water quality parameters and toxicity tests were observed in the Neihu garbage dump leachates after rainfall, but not for the Sanzhuku Landfill runoff. The highest concentration of BPA measured in this study was 25.8 μg L-1 in the Sanzhuku sanitary landfill runoff after the heaviest rainfall event, during which 236 mm of rainfall accumulated over four days. The results of this study suggest that both uncontrolled and controlled landfill leachates can be an important potential pollution source of BPA to adjacent water bodies.

scholarly journals Recirculation anaesthesia for laboratory fish

1987 ◽  
Vol 21 (3) ◽  
pp. 210-215 ◽  
Author(s):  
L. A. Brown
Keyword(s):  
Water Quality ◽  
Surgical Procedures ◽  
Ictalurus Punctatus ◽  
Channel Catfish ◽  
Ammonia Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Ammonia Nitrogen ◽  
Total Ammonia

An economic reliable long-term recirculation anaesthesia system for laboratory fish is described. Anaesthesia of channel catfish ( Ictalurus punctatus Rafinesque) was induced within 60 s and was maintained for up to 40 min using tricaine methanesulphonate; recovery occurred within 30-60 s. Various surgical procedures were performed on the fish. No deaths were recorded. All water-quality parameters tested over 19 days use of the system remained stable except for total ammonia nitrogen and, by calculation, un-ionized ammonia which increased to a maximum of 0·23 mg/1.

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 %.

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