Principles of Hydrologic Modelling

This course is offered twice per year and is available in both English and French.

Locations:

• University of Waterloo
• École de Technologie supérieure (ÉTS)

Delivery Schedule:

• Summer session
• Winter session

Detailed information regarding dates, registration, and fees is not yet available. Additional details will be posted on this page as they become available. For updates, please check back regularly.

Course Description

The CSHS Principles of Hydrologic Modelling course, offered annually since 2017, addresses the development of computational models of watershed hydrology in support of water resources management and scientific investigation. Participants learn from Canadian experts about a range of topics, including:

• The full model development and application cycle (pre-processing, understanding, and generating input forcing data)
• System discretization and algorithms for simulating hydrologic processes
• Parameter estimation
• Interpreting model output in the context of often significant system uncertainty.

The in-person course involves lectures and hands-on exercises. The course also includes practical applications of models to alpine, boreal forest, prairie, and agricultural settings in Canada.

Objectives of the course

Upon completion of this course, participants are able to:

• Understand the internal functioning of lumped and semi-distributed models of surface water hydrology, (principles of mass and energy balance, means of representing storage-flux relationships, algorithmic descriptions of critical hydrologic processes)
• Choose modelling approaches appropriate to the region being investigated, for supporting specific model goals, including water resource management decisions or scientific hypotheses
• Be able to intelligently apply concepts from the course to inform, build, and interpret hydrological models of watersheds.
• Be able to apply a number of standard and advanced software tools to manipulate and analyze hydrologic data, calibrate and evaluate models, and assess model uncertainty
• Have a greater appreciation of the difficulties inherent in prediction of hydrologic phenomena and the challenges specific to Canadian landscapes, their hydrological processes, and the availabiilty of data to describe them

Participants are exposed to a number of useful hydrological modelling software tools, including R, Ostrich, Raven, and GRASS GIS. Hydrologic modelling practitioners present both complex and simple modelling case studies demonstrating the challenges confronted in real-world modelling applications.

Audience

This course is intended for early career water resources professionals with some background in hydrology, undergraduate-level math/physics, and a competency with computer software.  In past offerings, this course could be taken by graduate students for credit or by practitioners.

All participants receive a certificate from the CSHS to recognize their participation in this course.

Course Content (Past Offerings)

• Module 1: Hydrologic Modelling Overview
  • the hydrological cycle as a mass balance problem – component models – integrated/differential models – conceptual vs. physically-based models – the modelling process – basic model numerics – the challenge of predictive modelling – upscaling – survey of commonly used Canadian models
• Module 2: Inputs & Data Preprocessing – Temporal
  • common forcing data – rain/snow partitioning – ET estimation – radiation/potential melt estimation – spatial Interpolation – dealing with missing data – generating future scenarios – time series basics – timestamp woes – Canadian forcing data – data issues – downscaling
• Module 3: Inputs & Data Preprocessing – Spatial
  • terrain and drainage analysis – subbasin & HRU delineation – contributing areas – system discretization – Canadian data resources overview – land use and soil data – spatial data issues – value of information – parameterization
• Module 4: Model Operation & Application – Single Basin
  • energy balances – snowmelt models – soil infiltration and redistribution models – Canadian hydrologic landscapes – hypothesis testing – case studies from industry
• Module 5: Model Operation & Application – Distributed Modelling
  • routing methods – overland flow and travel times – reservoirs, lakes, and managed systems – challenges in cold regions – flood prediction – climate change assessment
• Module 6: Model Calibration and Assessment
  • data and model uncertainty – model quality metrics – calibration targets – importance of validation – calibration algorithms – model evaluation – multioobjective optimization