BISMImmediate response
What changes after an intervention?
Explore how chemical dosing or flushing affects sulfide formation and H₂S release.
BIOFILM-INITIATED SEWER PROCESS MODEL
Driven by biofilms
Predicting sewer
hydrogen sulfide
BISM couples wastewater quality, dynamic biofilms and gas exchange to predict where sulfide forms, how much accumulates, and how control measures perform over time.
BISM / THE COUPLED SYSTEM
WATER ↔ BIOFILM ↔ GAS
CONTROL OVER TIME
Beyond current concentrations: how long will control last?
Conventional water quality models often assume a stable biofilm. BISM tracks biofilm growth, detachment and recovery, and competition between sulfate-reducing bacteria (SRB) and heterotrophs, to assess how microbial dynamics affect long-term performance.
Biofilm recovery
When could the risk return?
Track microbial regrowth and competition as the biofilm recovers, and assess the potential for sulfide rebound.
Long-term operation
How should control be sustained?
Compare dosing and intervention scenarios over time to inform follow-up timing and operating strategies.
THE MODEL
A dynamic view of sewer processes
Three coupled submodels connect changing biofilms with wastewater quality and gas release.
Wastewater quality model
Track sulfide, sulfate, ammonium and organic matter along the flow path.
Processes in focusAlong-pipe transport · Component transformations · Dynamic concentrations
Dynamic biofilm model
Simulate microbial competition, biofilm growth, detachment and recovery.
Processes in focusLayered mass transfer · Microbial competition · Attachment and detachment
Gas exchange model
Connect H₂S release and oxygen reaeration with water and biofilm processes.
Processes in focusGas–liquid transfer · H₂S release · Oxygen reaeration
SCIENCE IN PRACTICE
From field validation to rapid prediction
Discover the engineering case and the next step toward fast, data-driven control.
HATS / HONG KONG
44 kmHATS network: stages 1 + 2ACase Studies
Explore how BISM reproduced sulfide dynamics in Hong Kong’s deep-tunnel sewer network and identified downstream formation hotspots.
Read the HATS case study ↗AI + BISM
BISM → SPMMechanistic modelling meets machine learningSwift Prediction Model
Learn how the Swift Prediction Model combines BISM-generated data with machine learning for fast H₂S prediction and control.
Discover AI + BISM ↗APPLICATIONS
A virtual testbed across the sewer lifecycle
Explore H₂S formation and release under daily variations and extreme events. Identify high-risk sections early and compare strategies to balance sewer safety and operating costs.
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Water quality fluctuations
Assess how changes in influent COD and sulfate concentrations affect sulfide formation potential.
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Flow variations
Analyze how hydraulic retention time (HRT) changes affect flow conditions and formation and emission risks.
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Seasonal temperatures
Quantify how winter–summer water temperature differences affect biofilm activity and biochemical reaction rates.
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Extreme weather
Explore how storm-driven dilution and dissolved oxygen inputs suppress H₂S formation.
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Chemical dosing
Compare short-term emergency and long-term control with nitrate, biocides and other chemicals to optimize dosing.
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Physical interventions
Assess the combined effects of hydraulic biofilm scouring and gas-phase ventilation on H₂S control.
Assessing hydrogen sulfide in your sewer network?
Discuss your research needs, engineering applications or control strategy assessment with the BISM team.