Understanding the impact of static and dynamic pressure on water main breaks in water distribution systems - QC-184

Preferred Disciplines: Spatial statistics (Post-Doc or PhD)
Project length: 12-18 months (3 units)
Approx. start date: March 2019
Location: Montreal, QC
No. of Positions: 1
Preferences: None
Company: CANN Forecast logiciel Inc

About Company:

CANN Forecast applies artificial intelligence to help municipalities make better shoreline and water treatment management decisions, helping our partners reduce operating costs and better understand their impact on the environment. CANN was founded by the winners of the 2016 AquaHacking challenge. After signing its first contract with the city of Montréal, CANN continues to refine its technology and deploys it throughout Québec and Ontario.

Summary of Project:

The InteliPipes tool, developed by Cann Forecast, enables water infrastructure managers to prioritize pipes that are the most vulnerable to breaks for proactive rehabilitation. The main benefit of using InteliPipes is the optimization of budgets regarding pipe replacements, by focusing on pipes in critical conditions and avoiding the replacement of pipes that can still last for many years. Correspondingly, this also decreases the occurrence of water main breaks, which are not only economically costly but socially and environmentally as well.

Water pressure is an important variable that can affect the breakage of pipes however this variable has not been included in the InteliPipes model because the effect of pressure is generally not well understood. The main objective of this project is to build a spatially explicit model of the impact of water pressure on pipe breaks in water distribution systems, using data derived from multiple municipalities across the country.

The intern will overview the integration of water pressure into the InteliPipes tool, supported by a GIS analyst, a programmer and a data scientist. 

Research Objectives/Sub-Objectives:

  1. Data organization and pre-processing
    1. Determine how to optimally divide the database into train, test and validate sets; the data is complex with multiple years and multiple municipalities (Supported by our data-scientist).
    2. Attribute a pressure value to each pipe using fire hydrant pressure data and a Digital Elevation Model (Supported by our GIS analyst).
  2. Model development:  spatial relationship between water pressure and breaks
    1. Identify potential spatial-modelling approaches
    2. Compare the performance of the different models
    3. Benchmark with the performance of InteliPipes
    4. Assess how the effect of pressure on water main breaks differ between cities 
  3. Reporting: Design a report template to communicate the main results to each participating municipalities

Methodology:

    • To be discussed with the researcher

    Expertise and Skills Needed:

    • Experience with statistical modelling
    • Intermediate to advanced skills in R

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects.
    2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Gabriel Garcia-Curiel
    Program: