EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

High resolution exposure modelling at landscape-level – on the development of a mechanistic drift module for SWAT+

Mike Fuchs1,2, Sebastian Gebler1, and Andreas Lorke2
Mike Fuchs et al.
  • 1BASF SE, Global Exposure Modelling Team, Germany
  • 2University of Koblenz-Landau, Institute for Environmental Sciences, Landau in der Pfalz

Modelling environmental concentrations of pesticides at landscape-level is of growing interest for pesticide registration and product stewardship, including higher-tier studies in risk assessment, mitigation measures, monitoring support and decision making. Typically, runoff, drainage, and leaching are taken into account, using different modelling concepts. However, the modelling of spray drift often is simplified or neglected in landscape-level models. For example, the Soil and Water Assessment Tool (SWAT) does not consider spray drift for pesticide transport simulation. Hence, external offline calculations of spray drift are necessary, with the pesticide masses added to the channel network via point sources. Although this is a pragmatic solution for including spray drift, future scientific questions in high spatial and temporal resolution require adequate integrated processes on landscape‑level. Hence, the goal of this project is to: (i) develop and validate a standalone spray drift model that can be used with other modelling approaches in a modular manner, and (ii) implement that model into SWAT+.

Our spray drift model consists of two parts. First, a mechanistic droplet model predicts the trajectories of individual droplets. Second, a 2D Gaussian diffusion model predicts longitudinal advection as well as vertical and lateral dispersion of droplets. This modelling approach allows for a reasonable tradeoff between accuracy and computational expenses. The following inputs are considered: (i) weather conditions, (ii) drop size distribution, (iii) physio‑chemical properties of the active ingredient, and (iv) operational characteristics (e.g., nozzle count, boom height and width, applied amounts and volumes, and forward driving speed).

It is planned to validate the model against an ensemble of computational fluid dynamics simulations. Additionally, the approach will be evaluated using high resolution SWAT+ models of medium sized agriculturally dominated catchments in Germany. We expect the implementation of spray drift to improve modelling performance for different research questions e.g., the sensitivity of aquatic pesticide concentrations on landscape-level regarding application timing.

How to cite: Fuchs, M., Gebler, S., and Lorke, A.: High resolution exposure modelling at landscape-level – on the development of a mechanistic drift module for SWAT+, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3887,, 2022.

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