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From end-use characterization to decentralized reuse design: Closing the data-to-system gap.
1Water Environment Technology, Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, SE-41296, Sweden.
Water Research
|July 7, 2026
Summary
Decentralized water reuse risk models use outdated exposure data. Smart meter data reveals higher toilet flushes and shorter showers, impacting microbial risk assessment accuracy for safer water reuse systems.
Area of Science:
- Environmental Engineering
- Microbiology
- Risk Assessment
Background:
- Decentralized water reuse systems are growing, but lack empirical data for design and risk assessment.
- Existing quantitative microbial risk assessment (QMRA) frameworks use assumed, not measured, exposure parameters.
- High-resolution smart metering data for fixture-level water demand is underutilized in reuse practice.
Purpose of the Study:
- To evaluate if empirical end-use data from smart meters supports current QMRA exposure parameters for non-potable water reuse.
- To bridge the gap between residential water use characterization, decentralized reuse system design, and QMRA.
Main Methods:
- Systematic comparison of QMRA exposure assumptions against smart meter measurements for toilet flushing and showering.
- Sensitivity analysis to determine the impact of using measured versus assumed exposure parameters on infection probabilities.
- Review of current regulatory frameworks for water reuse standards.
Main Results:
- Assumed toilet flush frequency (5.0/person/day) is lower than smart meter estimates (5.0-6.4/person/day), potentially underestimating enteric exposure.
- Assumed shower durations (15 min) significantly exceed measured means (7.8 min), possibly overestimating inhalation risk.
- Accidental ingestion volume during toilet flushing, a key QMRA parameter, remains empirically unmeasured.
Conclusions:
- Current QMRA exposure parameters for water reuse are not fully supported by empirical data, necessitating updated risk assessments.
- Regulatory frameworks lack requirements for empirically grounded exposure parameters.
- An integrated framework linking smart meter data to system design and risk assessment is proposed, highlighting needs for ingestion measurements.
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