Long-term weather forecast app to help farmers with climate adaptation

09-11 | |
Waterapps uses meteorological weather data integrated with the indigenous knowledge of the farmers. - Photo: Canva
Waterapps uses meteorological weather data integrated with the indigenous knowledge of the farmers. - Photo: Canva

Waterapps is a long-term weather forecast app developed by Wageningen University & Research (WUR), which is to help farmers adapt to rapidly changing circumstances.

Waterapps was developed by Fulco Ludwig, a Water and Climate Change professor at the Wageningen Institute for Environment and Climate Research (WIMEK). The app is used by, among others, farmers in Bangladesh and Ghana. Climate change has made extreme weather more frequent in these countries: heavy rainfall and long periods of drought. As farmers choose their moments of sowing or fertilising based on the weather, climate change and its consequences are disastrous for them.

Farmers require long-term weather forecast

According to Fulco Ludwig weather forecasts in these countries focus on the short term, while farmers require a long-term weather forecast, so they can sow when rainy days are ahead. Manure or pesticides must be applied during a dry spell. Ludwig says Waterapps is able to offer a long-term weather forecast. “The sooner they know what lies ahead, the better they are able to prepare.”

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Waterapps uses meteorological weather data integrated with the indigenous knowledge of the farmers, such as presence of certain insects and bird behaviour. Certain cloud formations and changes in atmospheric pressure are indicators of changes in the weather, as are the appearance of the sun and moon. Ludwig says he found this difficult to believe at first. “But we were able to find a scientific explanation for some of the indicators. Including such elements in the weather forecast gave the farmers more confidence in the app.”

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Training through local weather schools

Farmers also receive training to use the app, through local weather schools. “Farmers must learn how to make decisions based on the information and must understand the uncertainties. The app for farmers in Bangladesh worked with percentages, which proved too complicated for the farmers as they found it difficult to translate the data into actions. So, we provided training and translated the dependability into colour codes,” Ludwig says.

According to Ludwig the goal is for the local administrations and businesses to ultimately take over and enhance the app and training programmes.

Claver
Hugo Claver Web editor for Future Farming



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