The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system

Li, Huiping; Zhou, Baiqin; Xu, Xiaoyan; Huo, Ranran; Zhou, Ting; Dong, Xiaochen; Ye, Cheng; Li, Tian; Xie, Li; Pang, Weihai

doi:10.1016/j.envres.2024.118474

Cited by 3 publications

(2 citation statements)

References 43 publications

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“…This result is consistent with previous studies. 36,37 Similarly, DOC (2.0%) and pH (0.3%) were negatively correlated with THMs, but their effects were not as signicant as residual chlorine. The impact of water quality parameters on THMs varied across different sections of the water supply pipeline; for instance, pH, DOC, SUVA, and UV 254 displayed a negative association with THMs in WDS, whereas turbidity (the explain value only reached 0.1%) exhibited a positive correlation with THMs (Table 3).…”

Section: Proposed Model At the Junction Of Dual-source Dwdsmentioning

confidence: 99%

Analysis of the seasonal water quality variation at the hydraulic junction of a dual-source water distribution system

Dong,

Huang,

Wang

et al. 2024

RSC Adv.

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Section: Proposed Model At the Junction Of Dual-source Dwdsmentioning

confidence: 99%

Analysis of the seasonal water quality variation at the hydraulic junction of a dual-source water distribution system

Dong,

Huang,

Wang

et al. 2024

RSC Adv.

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“…Furthermore, the range of SHAP values in the GBDT-based SHAP plot is much larger than that in the SVM-based and DT-based SHAP plot. Previous studies [80,81] also acquired further explanations to avoid the disadvantages of the "black box" of ML models. This may be one of the reasons why the GBDT-based model is more accurate that the other models in this study.…”

Section: Sensitivity Analysis Of Fluorescent Componentsmentioning

confidence: 99%

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Zhang,

Guo,

Luo

et al. 2024

Water

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The rapid identification of the amount and characteristics of chemical oxygen demand (COD) in influent water is critical to the operation of wastewater treatment plants (WWTPs), especially for WWTPs in the face of influent water with a low carbon/nitrogen (C/N) ratio. Given that, this study carried out batch kinetic experiments for soluble chemical oxygen demand (SCOD) and nitrogen degradation for three WWTPs and established machine learning (ML) models for the accurate prediction of the variation in SCOD. The results indicate that four different kinds of components were identified via parallel factor (PARAFAC) analysis. C1 (Ex/Em = 235 nm and 275/348 nm, tryptophan-like substances/soluble microbial by-products) contributes to the majority of internal carbon sources for endogenous denitrification, whereas C4 (230 nm and 275/350 nm, tyrosine-like substances) is crucial for readily biodegradable SCOD composition according to the machine learning (ML) models. Furthermore, the gradient boosting decision tree (GBDT) algorithm achieved higher interpretability and generalizability in describing the relationship between SCOD and carbon source components, with an R2 reaching 0.772. A Shapley additive explanations (SHAP) analysis of GBDT models further validated the above result. Undoubtedly, this study provided novel insights into utilizing ML models to predict SCOD through the measurements of the excitation–emission matrix (EEM) in specific Ex and Em positions. The results could help us to identify the degradation and transformation relationship between different kinds of carbon sources and nitrogen species in the wastewater treatment process, and thus provide a novel guidance for the optimized operation of WWTPs.

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Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling

Balakrishnan,

Preetam Raj,

Somasekar

et al. 2024

Remote Sens Earth Syst Sci

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The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system

Cited by 3 publications

References 43 publications

Analysis of the seasonal water quality variation at the hydraulic junction of a dual-source water distribution system

Analysis of the seasonal water quality variation at the hydraulic junction of a dual-source water distribution system

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling

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