Wellington Water – Transforming How a Region Understands Its Stormwater Network

Digital Innovations

By 2021, Wellington Water Ltd (WWL) had developed 35 stormwater models covering the Wellington region.
The models were a significant technical asset whose value was constrained by how they could be accessed and used.
Awa Environmental enabled WWL to develop and implement standardised System Performance Analysis (SPA) across all models.
This involved replacing reactive, issue-specific analysis done solely by the modelling team with a consistent, region-wide approach accessible to the whole organisation.
Starting with a pilot and expanding to all models, Awa automated processing workflows and made outputs available to all relevant WWL staff via an interactive ArcGIS web map – all within budget and on schedule.

Before SPA was enabled, WWL had no standardised way to analyse or present stormwater model results.
When a flooding issue was reported – for example, a customer’s property was repeatedly inundated – a modeller would investigate that specific location.
Investigation approaches varied between individuals and frequently focused on the immediate problem or project.
This predominantly reactive, issue-specific approach meant that adjacent impacts and broader patterns, such as which catchments posed the greatest risk, which infrastructure was most constrained, or how one problem related to others across the town, city, or region, were rarely examined.
Comparing results across projects was difficult because the underlying analysis was often done differently.
Non-modellers across the organisation – including engineers, operations staff, and planners – had limited ability to access model insights directly.
Every query required modeller time, creating a bottleneck as demand grew and pulling technical experts away from higher-value work.

Awa began with a pilot study using a single model, working with WWL’s modelling team to define outputs that would be useful to a non-modeller audience.
Three core SPA output types were developed:
- Floodplain Issues – flooding depth, extent, and velocity and number of affected properties across a range of storm sizes
- Network Capacity Analysis – flows through the stormwater network and potential system constraints and sources of flooding
- Model Data Confidence – a single, easily interpretable quality score consolidating data from dozens of underlying fields.
Critically, all outputs were standardised and quantified to enable direct comparison between catchments – something WWL had not been able to do before.
A flooding hotspot in one suburb could now be meaningfully compared to others across the region, supporting prioritisation and investment decisions at scale.

Following the successful pilot, Awa rolled out the SPA methodology across all 35 models.
Throughout the expansion, Awa workshopped outputs with non-modellers to refine thresholds and incorporate additional use cases.
The Operations team, for example, needed to identify frequently surcharging manholes, which is a public safety and infrastructure risk.
Awa developed specific SPA criteria to address this, further broadening the methodology’s utility across the organisation.

Awa replaced manual processing with an automated Feature Manipulation Engine (FME) workflow, reducing cost, delivery time, and the potential for human error.
Outputs were migrated from static report maps to a self-service ArcGIS Online web map, giving all relevant WWL staff direct, interactive access to SPA results across the entire region.
The web map is designed for non-modellers, using consistent, simplified symbology: pipes are colour-coded by capacity, data confidence is shown as a single score, and all outputs are spatially explorable across Floodplain Issues, Network Capacity Analysis, and Model Data Confidence layers.
A WWL engineer investigating a reported flood can now – without engaging the modelling team:
- Check the property in question
- See surrounding impacts
- Identify where capacity constraints originate
- Assess data confidence
- Understand whether the issue is isolated or part of a broader pattern across the catchment.

WWL now has a consistent, region-wide picture of stormwater system performance that did not exist previously.
The SPA web map – drawing on all 35 models – enables staff across the organisation to explore flooding risks, network constraints, and data confidence at any scale, from a single property to the entire Wellington region.
By enabling non-modellers to answer their own questions directly, the SPA has significantly reduced demand on WWL’s modelling team.
This has freed up those technical experts to focus more on proactive model management, complex assessments, client council requirements, and community consultation.
Standardised outputs mean decisions across the region are now grounded in comparable, consistently produced evidence.
The lessons from this project have been applied to further work for WWL, extending the use of FME automation and ArcGIS Online to new programmes of work by Awa.