Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 5
Articles | Volume 26, issue 5
https://doi.org/10.5194/hess-26-1261-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-26-1261-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 5
Research article
 | 
09 Mar 2022
Research article |  | 09 Mar 2022

Probabilistic modelling of the inherent field-level pesticide pollution risk in a small drinking water catchment using spatial Bayesian belief networks

Mads Troldborg, Zisis Gagkas, Andy Vinten, Allan Lilly, and Miriam Glendell

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Short summary
Pesticides continue to pose a threat to surface water quality worldwide. Here, we present a spatial Bayesian belief network (BBN) for assessing inherent pesticide risk to water quality. The BBN was applied in a small catchment with limited data to simulate the risk of five pesticides and evaluate the likely effectiveness of mitigation measures. The probabilistic graphical model combines diverse data and explicitly accounts for uncertainties, which are often ignored in pesticide risk assessments.
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Special issue
Frontiers in the application of Bayesian approaches in water...