A Machine Learning-Based Surrogate Model for Coupled Hydraulic and Water Quality Simulation in Water Distribution Networks

Ivo Daniel, Gopinathan R. Abhijith, Leonid Kadinski, Avi Ostfeld, Andrea Cominola

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ensuring consistent and high-level water quality is paramount for water utilities to meet health requirements and attain customer satisfaction. To this end, water utilities need to constantly surveil all relevant water quality parameters, for example, chlorine-concentration, as well as to optimally control dosage rates in their drinking water distribution systems (DWDSs). Simulation models coupling DWDS hydraulics and water quality have been well established and highly accurate. However, they are computationally very expensive such that optimization of control parameters may only be possible to a very limited extent. In this work, we are proposing the use of a lightweight, machine learning-based surrogate model for the coupled simulation of hydraulic and water quality parameters that may serve to reduce simulation times and render optimization of control parameters more efficient. The baseline model is system-specific and learns to predict the steady-state hydraulic and water quality state simultaneously based on common inputs to a DWDS model, that is, water demands and dosage rates at reservoir levels. Results indicate good prediction capabilities of the surrogate model with R2values greater than 0.98 as well as error rates below 0.01% for hydraulic parameters and below 1% for water quality parameters. Some slight spatial trends in the prediction error's variance are identified for hydraulics as well as for water quality parameters.

Original languageEnglish
Title of host publicationWorld Environmental and Water Resources Congress 2023
Subtitle of host publicationAdaptive Planning and Design in an Age of Risk and Uncertainty - Selected Papers from World Environmental and Water Resources Congress 2023
EditorsSajjad Ahmad, Regan Murray
Pages817-830
Number of pages14
ISBN (Electronic)9780784484852
DOIs
StatePublished - 2023
EventWorld Environmental and Water Resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty - Henderson, United States
Duration: 21 May 202325 May 2023

Publication series

NameWorld Environmental and Water Resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty - Selected Papers from World Environmental and Water Resources Congress 2023

Conference

ConferenceWorld Environmental and Water Resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty
Country/TerritoryUnited States
CityHenderson
Period21/05/2325/05/23

All Science Journal Classification (ASJC) codes

  • Water Science and Technology
  • Pollution
  • Management, Monitoring, Policy and Law
  • Environmental Engineering

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