1. Enhanced demand forecasting and leakage detection utilising high-resolution loggers
Centre for Water Systems
University of Exeter
PhD Student: Paul Wills
Principal Supervisor: Fayyaz Memon
Second Supervisor: Dragan Savic
Industry Partner: South West Water

2. The overall aim is to develop improved demand forecasts and leakage detection using high resolution data. The key objectives include to:
Determine the best techniques for analysing this new high-resolution data
Understand the factors involved in demand/consumption and their magnitude
Predict demand/consumption levels based on given factor inputs (e.g. behaviour profiles, weather data, tourism data, seasonality, diurnal/nocturnal patterns)
Utilise the demand predictions to determine possible leakage
Compare leakage detection results with the night-flow analysis
Extrapolate consumption forecasting to areas without high-resolution loggers
Agglomerate forecasts to make predictions on a District-Metered-Area (DMA) level

3. The novelty in this project comes through using high-resolution loggers, particularly the pulse loggers (Figure 1).
“ By 2025, 1.8 billion people will be living in countries or regions with absolute water scarcity, and two-thirds of the world population could be under conditions of water stress. ” (UN-Water 2007)
Figure 1. Pulse data logger with 1L pulse resolution capability. (Ashridge Engineering 2017)

4. Figure 2. Spreadsheet of recorded pulse data

5. www.wisecdt.org Timeline:
Stage 1 – 4 months – Literature review, design, experimentation.
Publication 1 – Literature review
Stage 2 – 6 months – Initial demand model construction
Stage 3 – 2 months – Utilisation / testing of demand model with full datasets.
Stage 4 – 4 months – Refinement of demand model, increasing accuracy
Publication 2 – Demand modelling
Stage 5 – 6 months – Extension of model to predict leakage
Stage 6 – 2 months – Testing of extended model
Stage 7 – 2 months – Refinement of extended model, improving performance
Publication 3 – Leakage detection
Stage 8 – 4 months – Extrapolation – prediction for other types of meter
Publication 4 – Extrapolation performance
Stage 9 – 6 months Overlap / Extension / Writing up
Stage 10 – Thesis submission

6. www.wisecdt.org References:
Ashridge Engineering, (2017). Data-logger-2017 [ONLINE]. Available at: [Accessed 15 June 2017].
UN-Water (2007). Coping with Water Scarcity: Challenge of the Twenty-First Century. United Nations, New York.

7. For more information contact: pw375@exeter.ac.uk
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