Why manual modelling methods fall short in wastewater planning under AMP-8
The AMP-8 cycle places sustained pressure on water companies and consultancies to deliver faster, justify investment decisions clearly and meet stricter environmental targets. Wastewater planning sits at the centre of this challenge. It requires experienced modellers to assess complex networks and produce evidence that satisfies regulatory scrutiny.
Many organisations still rely on manual modelling approaches. These methods have supported the industry for years, but they introduce structural limitations that restrict delivery speed and constrain the ability to respond to AMP-8 requirements.
The scale of the modelling challenge
Wastewater planning for solution development involves a large number of interacting design parameters. Pipe upgrades, pump upgrades, flow controls, real-time control strategies, SuDS, storage, rainfall conditions, population growth and network constraints all shape system performance and affect how intervention options perform in combination. Each potential intervention can affect multiple parts of the system, and combinations of interventions behave differently depending on how they interact.
In practical terms, this creates a vast design space. Even a modest set of upgrade options can produce thousands or millions of possible combinations. In large catchments, the number of viable permutations becomes far greater.
Manual modelling approaches explore only a small portion of this space. Engineers select a subset of options, adjust parameters and run simulations sequentially. This process depends on experience and intuition to guide which scenarios are tested.
Limited exploration leads to constrained outcomes
When only a small number of scenarios can be tested, and there is no clear indication whether there is a better performing design possible if more effort is spent. Water modellers can identify a potential improvement, but manual methods usually produce one candidate solution at a time. That solution then needs to be costed, reviewed and tested by wider project teams, and it is often passed back for further design iterations. This has direct implications for wastewater planning under AMP-8:
- Investment decisions are based upon limited choice
- Better performing, more sustainable, less costly solutions may remain undiscovered
- There is no clear benchmark for optimal performance
Time constraints further add to this limitation. Large-scale simulations, particularly those involving long-duration rainfall or Event Duration Monitoring (EDM) data, require significant computational effort. As deadlines approach, teams need to prioritise a limited set of scenarios, reducing the breadth of analysis This approach introduces uncertainty into both engineering and commercial decision-making.
Iterative workflows slow delivery
Manual modelling methods are inherently iterative. Engineers adjust parameters, run simulations, review outputs and then repeat the process. Calibration and verification activities follow a similar pattern, usually requiring detailed review of time-series data and multiple rounds of adjustment.
These processes are valuable, but they are also time-intensive. In many cases, calibration or verification for a single catchment can take weeks or months, particularly when long-duration datasets are involved. AMP-8 increases the volume of work across multiple fronts:
- Greater focus on CSO spill performance
- Ongoing DWMP updates and scenario testing
- Increased expectations around model accuracy and auditability
The cumulative effect is a workload that grows faster than available modelling capacity. Manual workflows make it difficult to scale delivery in line with these demands.
Data volume exceeds practical analysis capacity
Modern wastewater modelling generates large volumes of data. Long-duration simulations can produce outputs covering multiple years, across numerous nodes and assets.
Manual methods reduce this data to summary metrics or isolated events, as it is not practical to interrogate every output in detail. This limits the depth of insight that can be extracted from each simulation.
As a result, important patterns or interactions may remain hidden, and decisions are made using a simplified view of system behaviour.
Fragmented tools and processes reduce consistency
Wastewater modelling environments typically combine multiple tools and data sources. Engineers work across hydraulic models, GIS platforms, spreadsheets and custom scripts. Each component may follow different conventions, assumptions and workflows.
Manual coordination is required to align these elements. This introduces variability between projects and teams, particularly when processes are adapted locally or developed independently.
Inconsistent practices create challenges for:
- Auditability and regulatory reporting
- Reproducibility of results
- Knowledge transfer between teams
Under AMP-8, where decisions must be supported by clear and defensible evidence, consistency becomes a critical requirement.
A need for systematic exploration and automation
The challenges outlined above are structural. They arise from the limitations of manual exploration and fragmented systems. A different approach focuses on systematic exploration of the design space, supported by automation and data-driven optimisation.
Optimisation technology enables engineers to evaluate large numbers of design permutations efficiently. Algorithms analyse relationships between inputs and outputs, guiding the search towards high-performing solutions across multiple objectives such as cost, performance, and environmental impact.
This approach produces a set of optimal solutions that define the achievable trade-offs within a given problem. Engineers and decision-makers can then select options based on clear evidence, with visibility of how each choice performs relative to alternatives. Automation also integrates tools and reduces repetitive manual effort. This supports faster delivery, improved consistency and more robust audit trails.
Enabling better capital decisions in wastewater planning
Manual modelling methods continue to support wastewater planning, but they limit the ability to explore complex systems at the scale required by AMP-8. Restricted scenario testing, iterative workflows, and fragmented processes reduce delivery speed, constrain insight, and make it difficult to demonstrate that selected solutions represent the best use of investment.
A systematic approach based on automation and optimisation expands what teams can achieve within the same timeframes. Large design spaces can be explored efficiently, relationships between inputs and outcomes become clearer, and decision-makers gain visibility of cost-performance trade-offs across a full range of viable options.
STRIDE applies this approach through HEEDS, combining optimisation technology with deep domain expertise in water and wastewater modelling. Workflows are configured around real project constraints, integrate with existing tools such as InfoWorks ICM, and produce structured, auditable outputs aligned with regulatory expectations. This enables teams to evaluate more options, reach decisions faster, and support capital investment with clear, defensible evidence.
