The Crop Generator: Implementing crop rotations to effectively advance eco-hydrological modelling

Related GLP Member: Diana Sietz


  • Eco-hydrological models mainly neglect crop rotations due to a lack of well-resolved multi-year crop cover data.
  • We designed the Crop Generator to reproduce crop rotations at regional scale emphasising their stochastic characteristics.
  • Emulating farmers' crop rotation decisions, the Crop Generator reproduces regional cropping patterns well.
  • Implementation of crop rotations influences outputs of an eco-hydrological model, as illustrated by higher daily discharge.
  • Crop Generator enables more realistic projections for the future and scenario impact analysis.



Crop rotations considerably affect the hydrological regime of river basins used for agricultural production and are key for sustainable land and water management. However, eco-hydrological modelling usually neglects crop rotations.


In this paper, we present a Crop Generator to reproduce the stochastic characteristics of crop rotations at regional scale.


The Crop Generator emulates farmers’ decision making on crop rotation planning. We combined the Crop Generator with the eco-hydrological Soil and Water Integrated Model to show the hydrological relevance of considering crop rotations in a study region in central Europe including the Elbe River basin.


A spatial validation showed that the Crop Generator reproduced the given cropping patterns well. Higher daily discharge, runoff and groundwater seepage and lower evapotranspiration were simulated based on crop rotations compared with a simplified representation of cropping patterns. The Crop Generator is a solution to simulate more realistic cropping patterns in large-scale eco-hydrological modelling. It closes the gap between aggregated agricultural statistics and the requirement of representing crop rotations in a realistic way in eco-hydrological modelling.


The Crop Generator enables smart projections of future adjustments in crop rotations in view of climate and socio-economic changes as a basis for improving eco-hydrological projections and designing more sustainable agricultural systems.