Research Assistant Professor
Global Water Futures
Hydrology Research Group
Dept. Civil and Environmental Engineering
University of Waterloo
Phone:+1 (519) 888-4567 ext. 30016
Address:200 University Ave West
Waterloo, ON N2L 3G1


Model Variable Augmentation MVA
Model Variable Augmentation (MVA) is a method to determine the quality of Sensitivity Analysis results without the necessity of further model runs. The methods is proven to outperform bootstrapping for small sample sizes. The method has been published:
      J Mai & BA Tolson ( 2019).
Model Variable Augmentation (MVA) for diagnostic assessment of sensitivity analysis results.
Water Resources Research, 55, 2631– 2651.
The source code of MVA and a step-by-step tutorial can be found on GitHub and its associated Wiki.
Efficient Elementary Effects EEE
The Efficient Elementary Effects (EEE) method is a sequential screening approach based on the Morris method that fully automatically distinguishs informative parameters from noninformative ones using a minimal number of model runs. The method has been published:
      M Cuntz & J Mai et al. (2015).
Computationally inexpensive identification of noninformative model parameters by sequential screening.
Water Resources Research, 51, 6417- 6441.
The source code of EEE and several examples showing how the method works step-by-step can be found on GitHub and its associated Wiki.
Environmental models and Bayesian inference
This is the slides and exercise material used for the "Environmental models and Bayesian inference" course at the University of Waterloo (Juliane Mai, Dmitri Kavetski).
  1. Day: Basics of Modeling
    • Principles of environmental modeling (DK: slides)
    • Sensitivity analysis (JM: slides)
    • Optimization methods (JM: slides)
    • Exercises in Sensitivity analysis (JM: description and material)
  2. Day: Bayesian Methods
    • Bayesian methods: Intro (DK: slides)
    • Bayesian methods: Time series models (DK: slides)
    • Bayesian methods: Prediction and diagnostics (DK: slides)
    • Exercises in Bayesian methods (DK: description and material)
  3. Day: Applications and Research Topics
    • MCMC methods (DK: slides)
    • Applications in hydrological modeling (JM: slides)
    • Improving the inference (DK: slides)
    • Exercises in MCMC methods (DK: description and material)
Model calibration using OSTRICH software package
This is the course material usually used for the calibration part of the "Principles of Hydrologic Modeling" course at the University of Waterloo (James Craig, Bryan Tolson, Juliane Mai).
There are four exercise practice sheets available:
  1. DDS (single objective) in sequential mode (description)
  2. PADDS (multiple objectives) in sequential mode (description)
  3. DDS (single objective) in parallel mode (description)
  4. PADDS (multiple objectives) in parallel mode (description)
The full course material including documentation for RAVEN and OSTRICH and all executables and model setups can be also downloaded (.zip).
The slides of the crash course are available for download as well (.pdf).
Introduction to LaTeX
This is the course material for the "Introduction to LaTeX" course at the University of Waterloo (Juliane Mai).
Prior to the course the participants are asked to install LaTeX on their computer following the instructions (pdf). The instructions will refer to a few installation packages for the different operating systems. They can be downloaded here:
LaTeX templates
Over the years I have prepared several templates in LaTeX for creating posters, text documents and presentations. The first set was developed during my time at the Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany. When I started at the University of Waterloo, Canada (UWaterloo) in 2016, I ported all templates to their style and color scheme.
All templates are under a GNU Lesser General Public License.