Correlation analysis between microbial fouling resistance, flow rate and water quality parameters

2021 ◽  
Author(s):  
Yilong Zhang ◽  
Pengyu Chen ◽  
Xia Li ◽  
Zhiming Xu
Keyword(s):  
Water Quality ◽  
Correlation Analysis ◽  
Flow Rate ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Fouling Resistance

Study on the Methods of Predicting the Fouling Characteristics of Plate Heat Exchanger Based on Water Quality Parameters

2013 ◽  
Vol 459 ◽  
pp. 153-158
Author(s):  
Xiao Qiang Wen
Keyword(s):  
Water Quality ◽  
Heat Exchanger ◽  
Experimental System ◽  
Quality Parameters ◽  
Plate Heat Exchanger ◽  
Water Quality Parameters ◽  
Fouling Resistance ◽  
Plate Heat ◽  
The Impact ◽  
Fouling Characteristics

Fouling characteristic of plate heat exchanger was studied through the experimental system, with the Songhua River water as working fluid. Several water quality parameters: pH value, conductivity, dissolved oxygen, turbidity, hardness, alkalinity, chloride ion, iron ion, chemical oxygen demand, total bacterial count, which had great influence on the formation of fouling, as well as running condition, fouling resistance and other parameters were measured through the experimental system built. A group of fouling data of the typical water quality was obtained. Two prediction models of fouling characteristics of the plate heat exchanger were built based on partial least squares algorithm (PLS) and support vector regression machine (SVR) with water quality parameters as independent variables and fouling resistance as dependent variable, and the impact of water quality parameter on predicting accuracy was analyzed. Research results showed that: the prediction accuracy of two methods could be controlled within 12.5% and meet the requirements of the project. Through the comparison of the prediction results, it was proved that the SVR method was better than the method of PLS. The impact of the water quality parameters on prediction model was discussed by the means of deleting the water quality parameters one by one.

scholarly journals Using multivariate statistical techniques to assess water quality of Nhu Y river in Thua Thien Hue province

2014 ◽  
Vol 17 (2) ◽  
pp. 50-60
Author(s):  
Ky Minh Nguyen ◽  
Lam Hoang Nguyen
Keyword(s):  
Water Quality ◽  
Correlation Analysis ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Variance ◽  
Quality Data ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

The aims of this research are to assess water quality by organic and nutrient matters and identifying the environmental pressures, examine the impact of the loads to Nhu Y River, Thua Thien-Hue Province. Five stations were sampled at Nhu Y River, the research had monitoring of water quality parameters such as Temperature (Temp), Dissolved Oxygen (DO), Biological Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Nitrate (NO3-) and Phosphate (PO43-). The research used multivariate statistical techniques such as correlation analysis, principal component analysis (PCA) and cluster analysis (CA) to assess water quality. The correlation analysis shown a strong positive correlation exists between water quality parameters such as TempDO and BOD5COD (p<0.01). The PCA technique was applied to water quality data sets, which was obtained from Nhu Y River and the results show that the indices which has changed water quality. The results of the PCA using a varimax rotation technique were illustrated with two principal components (PC) and accounts for 62.207% of the overall total variance. The first PC accounted for 40.873% of the total variance, which was loaded with Temp, DO, BOD5 and COD. The second PC consists of NO3- and PO43- which accounts for 21.334% of the total variance, it can be due to the discharge of agricultural activities. Similarly, the CA has identified two major clusters involving: BOD5, COD, Temp, DO (the first cluster) and NO3-, PO43- (the second cluster).

scholarly journals EFFECTIVENESS OF EMITTER FLUSHING USED FOR SUBSURFACE DRIP IRRIGATION SYSTEM

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Vinod Kumar Tripathi ◽  
Birendra Bharti ◽  
Pratibha Warwade ◽  
Sushil Kumar Shukla ◽  
Prabeer Kumar Parhi
Keyword(s):  
Water Quality ◽  
Flow Rate ◽  
Drip Irrigation ◽  
Irrigation System ◽  
Quality Parameters ◽  
Filtration Efficiency ◽  
Water Quality Parameters ◽  
Subsurface Drip Irrigation ◽  
Drip Irrigation System ◽  
Subsurface Drip

Filtration plays vital role to improve the efficacy and reduce the maintenance of drip irrigation systems. The experiment was conducted to evaluate drip irrigation filters (gravel, disk filter and their combination) for groundwater filtration. Water quality parameters responsible for emitter plugging, such as total solids, turbidity, Ca, Mg, CO3 and HCO3 were analyzed at the entry and exit points of filters. The filtration efficiency for water quality parameters was estimated with individual filters and in combination. Significant improvement was observed for turbidity, total solids, carbonate and bicarbonate. The filtration efficiency with combination filter was 14.3±8.8% for turbidity and 16.3±9.31% for bicarbonates. Gravel filter gave better results for filtration of bicarbonate in comparison to the disk filter. Emitters protected by the gravel media filter experienced the largest flow rate reductions but emitters protected by combination filters experienced least flow rate reduction. Backwashing of filters reduces the filtration efficiency and head loss. To reduce emitter plugging by removal of accumulated sediment, flushing of mains, submains and laterals are recommended. Higher improvement in uniformity coefficient was observed in subsurface drip after flushing operation. The results may be utilized in planning and design of subsurface drip irrigation system to diminish emitter clogging incidence.

Correlation Analysis between Primary Productivity Factors and Water Environment Factors

2013 ◽  
Vol 448-453 ◽  
pp. 902-907
Author(s):  
Shih Chieh Chen ◽  
Chao Cheng Chung ◽  
Wen Liang Lai ◽  
Chung Yi Chung ◽  
Hwa Sheng Gau ◽  
...  
Keyword(s):  
Water Quality ◽  
Correlation Analysis ◽  
Chlorophyll A ◽  
Primary Productivity ◽  
Explanatory Power ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Canonical Variables ◽  
The Relationship

In this study, we use canonical correlation analysis to interpret the relationship between water quality parameters (T, Alk, Cl, EC, TN, TP, UV-254, pH, HPC, DO) and primary productivity parameters (algae and chlorophyll-a). In these two sets of constructed canonical variables, the water quality parameters can account for 39.25% of the total variance of primary productivity. The majority of the explanatory power is from the first set of canonical variables, which has a correlation coefficient of 0.84. The main factors that control chlorophyll-a are HPC, Alk, T, TN, and pH.

Correlation Analysis of the Seasonality of Adenovirus Gene Detection and Water Quality Parameters Based on Yearly Monitoring

2011 ◽  
Vol 3 (2) ◽  
pp. 101-107 ◽  
Author(s):  
Hugo D. Silva ◽  
Sônia F. O. Santos ◽  
Aliny P. Lima ◽  
Elisângela P. Silveira-Lacerda ◽  
Carlos E. Anunciação ◽  
...  
Keyword(s):  
Water Quality ◽  
Correlation Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Gene Detection

scholarly journals Management of Arfak Rainbow Fish Based on Bioecologycal Aspect (Case in Some River in Manokwari)

2018 ◽  
pp. 119
Author(s):  
Mariance Y. Kaliele ◽  
Roni Bawole ◽  
Irma E Kawulur
Keyword(s):  
Water Quality ◽  
Chemical Oxygen Demand ◽  
Flow Rate ◽  
Field Observation ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Fish Sample

The aim of this research is to study the bioecological aspect of Arfak Rainbowfish, distribution long-wieght frequency and management of endemic arfak rainbow fish in Manokwari. This study conducted for five months from 7 September 2015 to 9 Januari 2016. Fish sample were collected from Prafi river, Nimbai river and Aimasi river and brought to fisheries laboratory. The method of this research is descriptive methode with field observation. The result of water quality parameters are temperature average 30.01oC±1,06oC, flow rate is slow 0.92±0,12, the pH 7,80±0,12, oxygen solute 5,38±0,24, average biological oxygen demand for Prafi river 4 mg/L, Nimbai river 3.1 mg/L, Aimasi river 5.2 mg/L and chemical oxygen demand for Prafi river 8.3 mg/L, Nimbai river 14.2 mg/L dan Aimasi river 7.4 mg/L. Long-weight relation shows that the growth is alometric negative (b<3). The management that could be done is reboisation and management of catching that should not be done at the time fish is mature or ready to mate.

scholarly journals Impact of Precipitation and Flow Rate Changes on the Water Quality of a Coastal River

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hassan Pourfallah Koushali ◽  
Reza Mastouri ◽  
Mohammad Reza Khaledian
Keyword(s):  
Water Quality ◽  
River Water ◽  
Flow Rate ◽  
River Flow ◽  
Quality Parameters ◽  
River Water Quality ◽  
Water Quality Parameters ◽  
Box Plots ◽  
Coastal River

This paper aims to investigate the effects of natural variables, including precipitation and flow rate, on the quality of the Zarjoub River in Guilan province, Iran. The new hydrological insight in this study is a lack of national research focused on the dual effects of rainfall and flow rate on river water quality in coastal areas along the Anzali Wetland. To investigate the effect of precipitation and flow rate on river water quality, nine water quality variables were monitored during the 10-year period. In this article, (a) the existence of trends and the best fitted models of water quality parameters and the discharge and precipitation were analysed using statistical techniques and (b) the relationships between concentration of constituents with the discharge and precipitation on the up-stream and middle station were also examined. Box plots, for explaining the distribution of a data collection, were used. The results showed the existence of trend of water quality parameters with river flow and rainfall. As presented in Section 3, with increasing precipitation and flow rate, concentration of all constituents, except pH and SO₄2, decreased. On the contrary, the maximum amount of water quality elements was observed in low precipitations; therefore, the maximum concentration occurred in less than 15 mm precipitation. Simple regression was used to evaluate the discharge concentration and precipitation concentration. According to the correlation coefficient (r), the relationship between concentration and precipitation is weaker than (0.238) discharge concentration (0.699). The results further showed climate change and river water quality to be related.

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