EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Testing statistical methods to predict pesticide drift deposition

Glenda Garcia-Santos, Michael Scheiber, and Juergen Pilz
Glenda Garcia-Santos et al.
  • Alpen-Adria-University Klagenfurt, Geography, Klagenfurt, Austria (

We studied the case of the Andean region in Colombia as example of non-mechanized small farming systems in which farmers use handheld sprayers to spray pesticides. This is the most common technique to spray pesticide in developing countries. To better understand the spatial distribution of airborne pesticide drift deposits on the soil surface using that spray technique, nine different spatial interpolation methods were tested using a surrogate tracer substance (Uranine) i.e. classical approaches like the linear interpolation and kriging, and some advanced methods like spatial vine copulas, the Karhunen-Loève expansion of the underlying random field, the integrated nested Laplace approximation and the Empirical Bayesian Kriging used in ArcMap (GIS). This study contributes to future studies on mass balance and risk assessment related to environmental drift pollution in developing countries.

How to cite: Garcia-Santos, G., Scheiber, M., and Pilz, J.: Testing statistical methods to predict pesticide drift deposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11014,, 2020


Display file