DÜNGEcht combines remote sensing, a scientific cropping systems model, and weather forecasts into a practical tool, developed together with farmers from Brandenburg.
With around 500 mm of rainfall per year, Brandenburg is one of the driest regions in Germany, and almost two-thirds of its farmland consists of sandy, low-water-retention soils. This makes drought the most significant yield-limiting factor for arable farming in the region.
Farmers have to plan the timing and amount of their nitrogen fertilisation without knowing how much rain will fall in the coming weeks. Too little fertiliser costs yield; too much costs money and harms the environment through leaching.
Remote-sensing-based approaches, such as satellite imagery, already help adapt nitrogen application to spatial differences within a field. What these approaches can’t yet do: account for the uncertainty of future weather.
DÜNGEcht combines three data sources into a single tool:
The result: farmers receive projections of expected yield ranges and nitrogen losses for their planned fertilisation strategy, along with concrete recommendations on the timing and amount of the next application, tailored to their individual risk preference.
The project is structured into six work packages. Central to it is an iterative co-design process: the app is developed together with the participating farms and continuously improved based on their feedback, from an initial concept to a field-tested final product by the end of 2028.
Identifies the desired features and specifications of the tool together with farmers and advisors.
Development of the hybrid model combining remote sensing, cropping systems model, and weather forecast.
Translating the scientific tool into a user-friendly app with an intuitive interface.
Alpha and beta tests with project farmers and a broader group of regional farms.
Collection, linking, and responsible management of all required data.
Coordination across all work packages, reporting, and public outreach.