Storm-driven versus nominal fouling regimes in UF pretreatment systems

ABSTRACT Storm events rapidly alter feedwater quality in ultrafiltration (UF) systems, yet their long-term impact on persistent membrane fouling remains debated. This study compares a turbidity-intensive storm period with a nominal operating period using high-resolution operational data from a full-scale UF–RO pretreatment system. A regime-based framework was employed to analyse fouling dynamics by integrating short-term turbidity variability and membrane resistance drift into a unified fouling state space. Unsupervised clustering and probabilistic modelling were used to identify distinct fouling regimes and quantify their temporal occupancy. Counterintuitively, although the storm period exhibited substantially higher turbidity variability, it spent a markedly smaller fraction of operating time in the high-fouling regime (approximately 41%) compared with the nominal period (approximately 47%). Consistently, the median positive resistance drift during storm conditions was lower (0.79 × 1013 m−1 h−1) than during baseline operation (1.17 × 1013 m−1 h−1). These results indicate that stormdriven fouling was predominantly transient and reversible (likely dominated by porous cake layer formation), whereas nominal operation showed a greater tendency towards persistent resistance accumulation (suggestive of pore blocking and strong adsorption). Overall, the findings suggest that acute storm events do not necessarily constitute the dominant long-term fouling risk in UF pretreatment. The proposed regime-based approach provides a physically interpretable framework for distinguishing transient disturbances from chronic fouling processes under dynamic operating conditions.

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Journal
Water Practice & Technology
Published
2026-09-28
DOI
https://doi.org/10.2166/wpt.2026.475
Primary Topic
Membrane Separation Technologies
Type
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Storm-driven versus nominal fouling regimes in UF pretreatment systems

Zhang Zhi
Water Practice & Technology
Membrane Separation Technologies
article

Storm-driven versus nominal fouling regimes in UF pretreatment systems

Zhang Zhi
article en

Abstract

ABSTRACT Storm events rapidly alter feedwater quality in ultrafiltration (UF) systems, yet their long-term impact on persistent membrane fouling remains debated. This study compares a turbidity-intensive storm period with a nominal operating period using high-resolution operational data from a full-scale UF–RO pretreatment system. A regime-based framework was employed to analyse fouling dynamics by integrating short-term turbidity variability and membrane resistance drift into a unified fouling state space. Unsupervised clustering and probabilistic modelling were used to identify distinct fouling regimes and quantify their temporal occupancy. Counterintuitively, although the storm period exhibited substantially higher turbidity variability, it spent a markedly smaller fraction of operating time in the high-fouling regime (approximately 41%) compared with the nominal period (approximately 47%). Consistently, the median positive resistance drift during storm conditions was lower (0.79 × 1013 m−1 h−1) than during baseline operation (1.17 × 1013 m−1 h−1). These results indicate that stormdriven fouling was predominantly transient and reversible (likely dominated by porous cake layer formation), whereas nominal operation showed a greater tendency towards persistent resistance accumulation (suggestive of pore blocking and strong adsorption). Overall, the findings suggest that acute storm events do not necessarily constitute the dominant long-term fouling risk in UF pretreatment. The proposed regime-based approach provides a physically interpretable framework for distinguishing transient disturbances from chronic fouling processes under dynamic operating conditions.

Water Practice & Technology
Durham University (GB)
Clean water and sanitation
Openalex Percentile: Top 21%
Membrane Separation Technologies
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Storm-driven versus nominal fouling regimes in UF pretreatment systems — Zhang Zhi · Water Practice & Technology (2026) | TGRS Research Map | TGRS