17 June 2026
Drought is no longer an exceptional phenomenon. Prolonged dry periods, irregular rainfall, and scarce water resources are posing growing challenges for agriculture and society. This is precisely where Drought Analytics comes in: the spin-off from Forschungszentrum Jülich helps farmers to assess the water requirements of their fields more accurately - using soil sensors, plant models, weather data, and an app that uses this information to generate specific, early recommendations for irrigation management.
The World Day to Combat Desertification and Drought serves as a reminder of the strong interconnection between healthy soils, water availability, and food security. For farmers, this raises a very practical question: when do plants really need water - and when do they not?
The answer often lies beneath the surface. It is not always immediately apparent whether plants have sufficient water. Drought Analytics makes this hidden information visible - and translates it into irrigation management recommendations.
Measuring water where plants need it
Drought Analytics was founded by David Mengen, Dr. Olga Dombrowski, and Dr. Felix Nieberding. The spin-off builds on research carried out at the Institute of Bio- and Geosciences - Agrosphere at Forschungszentrum Jülich, where researchers investigate how water, soil, plants, and the atmosphere interact - and how agriculture can better adapt to the consequences of climate change.
For David Mengen, the focus is on practical benefits: "The key information lies in the soil. The challenge is to process this information in such a way that farmers can use it to make the right decisions for their fields in their day-to-day work."
At the heart of the application is the combination of sensors in the field with a model that describes the physical processes taking place in the soil and within the plant. The sensors measure soil moisture directly in the plants' root zone, as a plant's water supply depends not only on how much rain falls, but also on how much water is actually stored in the soil and available to the roots. The model helps to interpret these measurements and use them to determine current water requirements.
"Drought stress often begins long before it becomes visible in the plant," says Dr. Felix Nieberding. "Our aim is to detect this point at an earlier stage."
The plant growth model is continuously calibrated against measurement data from the field. This creates what is known as a "digital twin" of the field: a computer-generated representation that reflects the current condition of the soil and the plants as accurately as possible. It is continuously updated with new data and linked to additional information: What crop is growing in the field? What stage of development is it at? What are the soil conditions? How will the weather develop over the coming days?
Based on this information, the application calculates when irrigation is advisable and how much water is required. "Farmers need specific guidance: when will the situation become critical, and what needs to be done now?" says Dr. Olga Dombrowski.
Turning data into action
In day-to-day farming, such recommendations can make all the difference. Farmers often have to decide under time pressure when to irrigate, which areas to prioritize, and how to manage limited water supplies. Measurement data from the soil, intelligently combined with model-based forecasts for the coming days, can help them not just respond on instinct or experience, but also weigh up their next steps more carefully.
This may mean scheduling irrigation earlier because signs of drought stress are emerging. However, it can also mean postponing planned irrigation because sufficient moisture is still present in the soil or rain is forecast. In both cases, the aim is the same: to ensure that plants receive sufficient water while avoiding unnecessary water use.
Drought Analytics therefore does not rely on irrigation based on the principle that "more is better", but instead on needs-based irrigation. The app is designed to help farmers combine their experience and knowledge of their own farms with up-to-date field measurements. This saves water, energy, and costs - while also helping to safeguard yields and quality.
Why it matters beyond agriculture
The benefits of such applications extend beyond individual farms. Agriculture must continue to produce food reliably, even under changing climatic conditions. At the same time, periods of drought place increasing pressure on regional water resources. As water becomes scarcer, good decision-making becomes more important. When should irrigation take place? How much water is needed? Where can water be saved without putting crops at risk?
Data-driven systems cannot make these decisions entirely on their own. They are no substitute for experience or knowledge of one's own field. But they can provide an additional basis for decision-making - particularly as weather and water availability become harder to predict.
Drought cannot be prevented. But it can be detected earlier. And, those who better understand what is happening beneath the surface can take more effective action - in the field, in water management, and in dealing with a resource that is becoming increasingly valuable.
