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

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 www.wisecdt.org

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) www.wisecdt.org

Figure 2. Spreadsheet of recorded pulse data www.wisecdt.org

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 www.wisecdt.org

www.wisecdt.org References: Ashridge Engineering, (2017). Data-logger-2017 [ONLINE]. Available at: http://www.ash-eng.com/wp-content/uploads/2017/05/Data-logger-2017-140x124.png [Accessed 15 June 2017]. UN-Water (2007). Coping with Water Scarcity: Challenge of the Twenty-First Century. United Nations, New York. www.wisecdt.org

For more information contact: pw375@exeter.ac.uk Any questions? For more information contact: pw375@exeter.ac.uk www.wisecdt.org