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17 May 2022 Correlation analysis and modeling based on water quality data of Shuimentang Reservoir
Haiyan Wang, Qingshan Xu, Shizhuang Weng, Ren Cai, Shouguo Zheng
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Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 1225941 (2022) https://doi.org/10.1117/12.2638958
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 2022, Kunming, China
Abstract
In order to improve and protect the water quality of Shuimentang Reservoir, the six relevant indexes of 12 sampling sites were measured, the spatial distribution characteristics of each index were analyzed, the correlation among each index was discussed, and the regression model was established for some indexes with strong correlation. Through the water quality detection and correlation analysis of Shuimentang Reservoir, Hydrogen Potential (pH) and Electrical Conductivity (EC) are significantly negatively correlated, Suspended Solids (SS) and Particulate Organic Matter (POM) are significantly positively correlated, and the correlation coefficients are -0.883 and 0.860, respectively. Based on the correlation analysis results, the "pH-EC" and "SS-POM" linear regression models were further constructed, and R-Square, Mean Square Regression and Sum of Squares of Error were 0.78, 1.20, 0.34 and 0.74, 32.83, 11.57, respectively. The two models have good fitting results, and pH and SS concentrations in Shuimengtang Reservoir water body were predicted by EC and POM concentrations, which reduces the number of water quality testing indicators and the testing cost.
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Haiyan Wang, Qingshan Xu, Shizhuang Weng, Ren Cai, and Shouguo Zheng "Correlation analysis and modeling based on water quality data of Shuimentang Reservoir", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 1225941 (17 May 2022); https://doi.org/10.1117/12.2638958
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KEYWORDS
Data modeling
Analytical research
MATLAB
Error analysis
Hypoxia
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