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| Created: | Jul 22, 2026 at 1:35 p.m. (UTC) | |
| Last updated: | Aug 18, 2026 at 7:02 a.m. (UTC) | |
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Abstract
Hydrologic systems are both complex and extremely heterogeneous in time and space. As hydrological models are simplified versions of reality, their predictions are by definition subject to uncertainty. The field of stochastic hydrology focuses on quantifying this uncertainty along with prediction. This course aims to present an overview of the field of stochastic hydrology at an introductory level. A wide range of topics and methods will be treated, while each topic and method is only treated at a basic level: descriptive statistics; probability and random variables; hydrological statistics and extremes; random functions; time series analysis; geostatistics; forward stochastic modeling; and state prediction and Kalman filtering. The course can be used for a 10-15-week course at third-year undergraduate or first-year graduate level.
The course consists of the following elements:
- PowerPoints (pptx or pdf) of the lectures.
- Auxiliary interactive material (.html- files and R-scripts) used as illustration.
- Exercises and answers. Exercises are both R-based (R scripts are added) as well as analytical hand calculations.
- The course guide of 2021, when the course was taught at Utrecht University for the last time.
- Associated with these lectures is an eBook, which can be downloaded from https://doi.org/10.48544/e4777242-d1df-47ce-8be5-288a60442def, but is also provided here.
Not uploaded here but on on Youtube: recorded lectures : https://www.youtube.com/channel/UCBPN92uUODh6QD1KqLNuuRQ
For questions: m.f.p.bierkens@uu.nl
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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