In arid areas where water resources are limited, crop irrigation often already exceeds 80% of overall water use. However, food production will have to increase by 60% to feed an estimated world population of 9 billion in 2050, while climate change is likely to reduce the available resource. Precise irrigation management reduces agricultural water consumption without affecting yields. The synergy between satellite data, meteorological measurements and forecasts now offers efficient and inexpensive solutions to farmers.
For the past 15 years, the team of LMI TREMA have been studying the water consumption of the main crops in the Tensift region (Marrakech) and have developed methods to take advantage of satellite imagery, including the use of new data that is offered free of charge by the ESA COPERNICUS program (High Resolution and hight revisit time Images). The SAT-IRR online tool provides real-time irrigation recommendations specific to each plot. For this, the farmer enters via a simple web interface some informations about his plot (delimitation, species, water intake past …) and the system provides forecasted date and amount for the next irrigation. The complex part of recovery and processing of satellite and meteorological information is completely transparent to the user. This tool is potentially deployable all over the globe.
Main actions within the Chaams project (WP6) will be: (1) to strenghen the tool by constraining the soil water budget using disagregated surface soil moisture product derived from microwave remote sensing (WP4); (2) to promote the use of the Sat-Irr application towards individual farmer or farmer association involved on the four catchment of the project through training sessions and real-conditions experiments. We also aim to study how these end-users will be able to appropriate this new information.
Web site: Sat-Irr application
Development: M. Le Page
Document: Le Page, M., Toumi, J., Khabba, S., Hagolle, O., Tavernier, A., Kharrou, M., Er-Raki, S., Huc, M., Kasbani, M., Moutamanni, A., Yousfi, M., Jarlan, L., 2014. A Life-Size and Near Real-Time Test of Irrigation Scheduling with a Sentinel-2 Like Time Series (SPOT4-Take5) in Morocco. Remote Sens. 6, 11182–11203.