Hydraulic backwashing decision method based on fouling index trend analysis in full-scale ultrafiltration systems

ABSTRACT In full-scale ultrafiltration (UF) systems, timely hydraulic backwashing is essential for maintaining filtration efficiency and membrane service life. Conventional fixed-interval hydraulic backwashing strategies cannot account for cycle-to-cycle variations in membrane fouling, which may lead to premature or delayed intervention. To address this problem, this study proposes a trend fouling index (TFI)-based hydraulic backwashing decision method for full-scale UF operation. A resistance-in-series-derived fouling index model was first established, and each production cycle was divided into fast and stable water production stages. The trend feature of TFI during the stable stage was then extracted to formulate a slope-based hydraulic backwashing criterion. The proposed method was validated in a full-scale water treatment plant and compared with the conventional fixed-interval strategy. The results show that the proposed strategy could adaptively adjust the filtration duration according to the fouling condition of different production cycles. The fouling trend analysis and transmembrane pressure distribution further confirmed that the additional fouling caused by the extended filtration period remained within the range of physically removable contamination. In addition, the analysis of different initial pressure definitions for TFI calculation provides a reference for long-term operational assessment and maintenance of full-scale UF systems.

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Publication Details

Journal
AQUA - Water Infrastructure Ecosystems and Society
Published
2026-09-07
DOI
https://doi.org/10.2166/aqua.2026.133
Primary Topic
Membrane Separation Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Hydraulic backwashing decision method based on fouling index trend analysis in full-scale ultrafiltration systems

Wei Guo, Ranran Liu, Ning Zhang, Biao Wang et al.
AQUA - Water Infrastructure Ecosystems and Society
Membrane Separation Technologies
article

Hydraulic backwashing decision method based on fouling index trend analysis in full-scale ultrafiltration systems

Wei Guo, Ranran Liu, Ning Zhang, Biao Wang, Yao Wu, Yugai Zhang
article en

Abstract

ABSTRACT In full-scale ultrafiltration (UF) systems, timely hydraulic backwashing is essential for maintaining filtration efficiency and membrane service life. Conventional fixed-interval hydraulic backwashing strategies cannot account for cycle-to-cycle variations in membrane fouling, which may lead to premature or delayed intervention. To address this problem, this study proposes a trend fouling index (TFI)-based hydraulic backwashing decision method for full-scale UF operation. A resistance-in-series-derived fouling index model was first established, and each production cycle was divided into fast and stable water production stages. The trend feature of TFI during the stable stage was then extracted to formulate a slope-based hydraulic backwashing criterion. The proposed method was validated in a full-scale water treatment plant and compared with the conventional fixed-interval strategy. The results show that the proposed strategy could adaptively adjust the filtration duration according to the fouling condition of different production cycles. The fouling trend analysis and transmembrane pressure distribution further confirmed that the additional fouling caused by the extended filtration period remained within the range of physically removable contamination. In addition, the analysis of different initial pressure definitions for TFI calculation provides a reference for long-term operational assessment and maintenance of full-scale UF systems.

AQUA - Water Infrastructure Ecosystems and Society
Jiangsu University of Technology (CN), Suzhou Electrical Apparatus Science Academy (CN)
Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions
Clean water and sanitation
Openalex Percentile: Top 21%
Membrane Separation Technologies
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