The case for automation and optimisation in wastewater modelling
Wastewater modelling sits at the centre of how UK water companies plan, invest and demonstrate compliance. The volume of work now required under AMP-8 and the expectations placed on modelling teams mean traditional modelling methods are under increasing strain. Automation and optimisation offer a practical path towards faster programme delivery, enhanced regulatory compliance and improved long-term network performance.
This article sets out the case for simulation automation and network optimisation, drawing on sector insights and the challenges informed by our collaboration with the technical teams responsible for wastewater modelling and planning.
Why existing methods are limiting progress
Technical directors, DWMP managers and senior modellers consistently report the same pattern: modelling programmes are growing faster than available modelling capacity. Consultancies and utilities companies alike are working with constrained teams, limited headcount growth and a reliance on manual processes that slow overall delivery.
Current wastewater modelling methods expose a number of limiting factors like manual calibration, repetitive verification steps, multi-tool data handling and labour-intensive scenario testing. Even minor tasks can consume hours of modeller time and introduce inconsistency and re-work.
Manual verification consumes human resources that could be better used for engineering analysis. These manual methods also often lead to inconsistent quality and governance. On top of this, disparate tools slow down DWMP cycles and spill-reduction planning. As a result, modellers spend more time on data processing than on solution development.
The role of automation in wastewater modelling
To address the challenges faced by wastewater modellers and DWMP managers, workflow automation improves delivery speed, consistency, and traceability across modelling programmes. By automating repetitive and time-consuming tasks, teams can focus on engineering analysis and interpretation of results rather than manual data handling. Key benefits of automation include:
- Automating DWMP model updates
- Automating the copying and transfer of data between software platforms
- Automating entire processes, including Excel spreadsheets, scripts (e.g., Python), models (e.g., InfoWorks ICM), and GIS platforms (e.g., QGIS)
- Automating any standard, repetitive task
- Testing the sensitivity of network design parameters to outcomes such as flooding and spills
Automation tools support the full modelling programme, enabling teams to increase throughput, reduce manual errors and improve governance without expanding headcount.
The parallel advantages of optimisation for wastewater planning
Drainage and Wastewater Management Planning has its own set of challenges, involving a delicate balance of hydraulic performance, environmental targets and capital cost. This is where optimisation complements automation by improving the quality of the engineering outcomes. Optimisation help modellers and planners explore a wider range of possible interventions and identify the combinations that deliver the best results:
- Broader exploration of viable design options
- Clearer comparisons between performance and cost
- Identification of intervention sets that reduce spills and flooding
- Stronger evidence for regulatory and investment decisions
- Improved testing of resilience under multiple future scenarios
Optimisation tools support these aims by evaluating many potential solutions systematically. Modellers can build workflows that can give you an optimised cost estimate for any level of service you wish to provide and can give you a different build-out pathways through multiple time horizons. This creates a more robust foundation for long-term planning, where decisions are justified with defensible evidence and tested under a range of conditions.
The impact on regulatory compliance and auditability
Regulators expect models that are reliable, consistent and supported by clear evidence. To support this, automation produces repeatable steps and complete records of every simulation to give teams a dependable audit trail for spill-reduction reporting, DWMP submissions, investment planning, etc.
These workflows strengthen model reliability by moving away from manual variation and improving the consistency of spill-prediction outputs. This creates clearer assurance that proposed solutions will perform as intended once delivered, supporting confidence that designs will work before they are fully built.
Optimisation adds further rigour by evaluating a wide range of intervention combinations and revealing which options provide the strongest balance of performance and cost. This gives decision-makers assurance that the full solution space has been explored and that investment is directed towards the most effective interventions to support the performance and longevity of the network infrastructure.
Advancing modelling capability for AMP-8 and beyond
Wastewater modelling now supports more planning horizons, larger DWMP portfolios and stricter AMP-8 performance obligations than before. Where manual methods struggle to meet this demand, automation can increase throughput and improve governance. At the same time, optimisation expands the range of solutions and strengthens the evidence behind investment decisions. Together, these methods create a clearer, faster and more reliable modelling process, a critical benefit for water companies and consultancies under AMP-8 and beyond.
STRIDE provides the tools and expertise to support this shift. Its proprietary API integrates with Siemens’ HEEDS platform to enable automated workflows that enhance existing InfoWorks ICM work, reduce operational friction, and comprehensively optimises project work to deliver transparent, audit-defensible evidence for planning and regulatory review.
STRIDE’s training and consultancy services help teams embed these approaches and build long-term capability, giving water companies and consultancies a practical route to more efficient and confident wastewater modelling.
