Programme
17:00 – 17:30 | Arrival and networking (light refreshments served)
17:30 – 17:40
Welcome and Introduction from Chair
17:40 – 19:00
Finalists presentations
Georgia Wade | Graduate Water Quality Consultant | Stantec
Future-Proofing Water Quality: A Multi-Scenario Framework for DWMP Climate Resilience
For a client’s DWMP, I developed a framework to assess future water quality pressures by combining nutrient modelling, thermal risk analysis, and climate-driven hydrological changes.
For phosphorus modelling, I used the EA-approved SAGIS/SIMCAT tools alongside UKCEH flow-change factors, to map future hydrological conditions for 2035, 2045 and 2055. The adjusted flow states were incorporated to represent how climate alters dilution and phosphorus pathways. I mapped each scenario in ArcGIS and wrote Python script to classify the waterbodies’ ecological status, which therefore provided a clear evidence base to set future permit requirements.
Alongside this, I designed a temperature risk methodology using multiyear effluent and river datasets, applying 98th percentile analysis and a climate uplift derived from the EA Chief Scientist’s river temperature projections (~0.6 °C per decade). This highlighted future thermal hotspots, where ecological headroom may narrow, specifically at salmonid sites. These workflows provide a repeatable, climate aware decision platform supporting no deterioration, targeting Good Status, and strengthening AMP8/9 catchment planning.
Rebecca Lee | Flood Risk Analyst | JBA Consulting
Challenging Conventional Practice: Evaluating Innovative Approaches to Modelling Flood Risk and Peatland Restoration in Actively Managed, Lowland Catchments such as Gordano, North Somerset
The water sector is under pressure to extract greater value from limited funding. This growing demand for efficiency, alongside lessons learned from previous projects, sparked a study for North Somerset Council, appraising innovative approaches to modelling actively managed, lowland catchments, with penned water levels. It aims to identify where traditional methods can be tailored to achieve cost, data, and carbon efficiencies while maintaining high quality.
I trialled nine methodologies spanning two EA benchmarked software, evaluating four themes: software and model build/complexity, data inputs such as LiDAR and survey, bridge/culvert structure representation, and flow application. I assessed each methodology against industry good practice, alongside their financial implications including model build and survey costs, and associated carbon impacts. I produced thorough documentation, including a ‘Suitability Table’ designed to guide future funding bids, tender and scope development, and methodology selection.
Outputs are already guiding the client’s review of planning-application models and methods, as well as targeting future spend proportionality. It has been shared with national and local EA teams, supporting more efficient, evidence-based spending.
Jo Schoenberg | Assistant Urban Drainage Modeller | Stantec
Harnessing the power of automation to facilitate catchment-scale solution engineering optimisation
The wastewater industry is facing increasing social, regulatory and operational pressures at a time when skilled resource is finite. Technological advances in automation and optimisation offer a clear opportunity to improve efficiency, increase output, and enable a more integrated catchment scale approach to solution engineering.
In collaboration with a technical partner, I co-developed a bespoke HEEDS workflow to deliver catchment-scale opportunity identification studies, finding the optimal balance between spill frequency reduction and adequate Level of Service.
The workflow utilises HEEDS’ capabilities to generate and evaluate thousands of design options. By learning from successive iterations, the optimiser converges towards the Pareto front. Results demonstrate significant potential for catchment wide spill reduction with maintaining Level of Service standards.
In one catchment, looking at seven CSOs, a thousand design iterations were simulated, a task estimated to require over two years of fulltime manual modelling to the same level of detail. This automation approach was completed in approximately three weeks, with the optimisation itself running over a single weekend. This work provides a clear proof of concept for how optimiser-led, automated workflows can transform how we undertake solution engineering at scale.
Q&A of finalists
19:00
Winner announced
19:15 | Close