Water Demand Forecasting

March 6, 2024 | Online

Click Here to register $895

If you are unable to attend at the scheduled date and time, we make recordings available to all registrants for three business days after the event

Water utilities face the challenge of accurately forecasting and planning for future water demand. Inaccurate demand projections can lead to inefficient water resource allocation, supply shortages, and compromised service delivery. Without robust demand planning strategies, utilities may struggle to meet the needs of growing populations, changing consumption patterns, and emerging challenges such as climate change and water scarcity.

The EUCI Water Demand Forecasting course offers insights and solutions to address the challenges associated with forecasting and planning for water demand. This course equips professionals with the knowledge, skills, and tools necessary to develop accurate and reliable demand projections. Participants will learn various demand forecasting methodologies, including statistical analysis, modeling techniques, and data-driven approaches such as:

  • Time series analysis
  • Regression analysis
  • Machine learning models

The course will also cover the challenges and limitations associated with water demand forecasting and provide participants with the skills needed to develop effective water demand management strategies.

Learning Outcomes

  • Utilize demand forecasting methodologies to generate accurate and reliable water demand projections
  • Assess challenges and limitations associated with water demand forecasting to ensure more precise and reliable forecasts
  • Align demand projections with resource availability to optimize operational efficiency, and mitigate the impacts of climate change and water scarcity
  • Leverage statistical analysis, modeling techniques, and data-driven approaches to improve forecasting outcomes and inform decision-making processes
  • Justify the importance of accurate water demand forecasting to ensure efficient resource allocation



9:00 a.m. – 4:00 p.m. Central Time

Introduction to Water Demand Forecasting

  • Overview of water demand forecasting
  • Key concepts and terminology
  • Short-, medium-, and long-term demand forecasts

Incorporating Water Demand Forecasts Throughout a Utility

  • Identifying internal customers
  • Time horizons for demand forecasts
    • Benefits and challenges from varying forecast horizons
    • Risk and uncertainty
    • Appropriate application of different forecasts throughout the organization
    • Scenario planning vs. stochastic forecasting

Demand Drivers for Water Use

  • Land use and customer class
  • Climate, weather, and landscape choices
  • Socioeconomic trends
  • Different drivers and opposite impacts dependent on time horizon

Challenges with Water Use Forecasting

  • Data availability and limitations
  • Technical expertise in statistical modeling
  • Seasonal variations and unpredictable weather patterns
  • Inability to accurately forecast water use drivers

Trend Analysis and Land-Based Modeling

  • Integration of GIS into long-term planning
  • GPCD and time trend analysis
  • Limitations and shortcomings

Econometric Modeling

  • Review of key concepts and methodology
  • Econometric forecasting for treatment plants and distribution system
  • Econometric forecasting for long term planning
  • Integration of econometric modeling with scenario planning
  • Limitations and shortcomings

Introduction to Machine Learning

  • Overview of fundamental concepts and terminology
  • Data preparation and model selection
  • Supervised learning algorithms
  • Deep learning and neural networks
  • Benefits and drawbacks of machine learning compared to econometric modeling

Modeling and Analysis of Water Demand Management Strategies

  • Non-structural solutions:
    • Conservation, drought restrictions, emergency demand management, and peak shaving
  • Modeling challenges
  • Benefits of implementation


Ryan Shepler, Lead Demand Planner, Denver Water

Ryan Shepler is a Lead Demand Planner at Denver Water.  At Denver Water, he conducts technical modeling and analysis of customer water use to inform decisions across the organization from financial forecasts to long-term planning decisions.  While at Denver Water, he has incorporated econometric forecasting into day-to-day operations and has led the implementation of demand management strategies that decrease the dependence of additional infrastructure.

Prior to Denver Water, he spent several years working for WestWater Research, a water resource economics consulting firm.  While there he improved an econometric forecasting model that estimated water rights prices, and developed a hydro-economic model that evaluated the costs and benefits of agricultural best management practices.