Potential evaporation (PET) is a core input to hydrological modelling, yet it is rarely measured directly. Practitioners instead rely on meteorological data such as temperature, radiation, wind and humidity to estimate PET using empirical and physically based methods. Understanding these approaches is essential for reliable water resource assessments.

In this hands‑on course, participants learn how to estimate PET using the open‑source Python package PyET. Participants explore temperature‑based methods such as Hamon and Hargreaves, then move into more data‑rich approaches including Penman–Monteith and FAO‑56. Each method is introduced in context so participants can see how data availability and site conditions influence the choice of PET estimator.

Working in a Jupyter notebook with example meteorological datasets, participants run multiple PET methods, compare outputs and interpret differences between approaches. By the end of the course, participants will be confident applying PET estimation techniques to their own catchments and integrating results into hydrological modelling workflows.

https://awschool.com.au/training/pyet-essentials/