Shifting application dates on cereal reduces pesticide transfer via subsurface drainage based on water flow forecasts during autumn applications.

Background: Thanks to the changes in aquatic risk assessment within the marketing authorization (MA) process in France, the contamination of surface water through the subsurface drainage network is better accounted for. The measure adopted by risk regulations is to prohibit any use of selected pesticides on drained plots. Herbicide solutions on subsurface-drained plots are becoming scarce due to a limited number of innovations combined with the re-approvals process.

An indicator to assess risks on water and air of pesticide spraying in crop fields.

Stakeholders involved in actions to reduce the use and the impacts on the environment or human health of pesticides need operational tools to assess crop protection strategies in regard to these impacts. I-Phy3 brings together all improvements introduced since the first version of the indicator to better meet user's needs and requirements of integrating processes. I-Phy3 was deeply modified to ensure its predictive quality.

Modeling the risk of water pollution by pesticides from imbalanced data.

The pollution of ground and surface waters with pesticides is a serious ecological issue that requires adequate treatment. Most of the existing water pollution models are mechanistic mathematical models. While they have made a significant contribution to understanding the transfer processes, they face the problem of validation because of their complexity, the user subjectivity in their parameterization, and the lack of empirical data for validation.

Predictive quality of 26 pesticide risk indicators and one flow model: A multisite assessment for water contamination.

Stakeholders need operational tools to assess crop protection strategies in regard to environmental impact. The need to assess and report on the impacts of pesticide use on the environment has led to the development of numerous indicators. However, only a few studies have addressed the predictive quality of these indicators.