Irrigation Amounts and Timing Retrieval through Data Assimilation of Surface Soil Moisture into the FAO-56 Approach in the South Mediterranean Region

Agricultural water use represents more than 70% of the world’s freshwater through irrigation inputs that are poorly known at field scale. Irrigation monitoring is thus an important issue for optimizing in particular with regards to scarcity semi-arid regions already facing. In this context, aim study develop and evaluate a new approach predict seasonal daily timing amounts The method based on surface soil moisture (SSM) data assimilated into simple land (FAO-56) model particle filter technique ensemble scenarios. implemented three steps. First, synthetic experiments designed assess impact frequency observation, errors SSM priori constraints scenarios different techniques (flooding drip). second step, evaluated using situ measurements revisit times (3, 6 12 days) mimic available product derived from remote sensing observation. Finally, estimates Sentinel-1 used. Data collected wheat fields grown Morocco, both flood drip addition rainfed used indirect evaluation performance. Using data, accurate results obtained. With observation every days time, retrieved R > 0.98, RMSE < 32 mm bias 2.5 mm. Likewise, good agreement observed scale as detected events have time difference actual shorter 4 days. Over irrigated fields, statistical metrics = 0.74, 24.8 2.3 cumulated over 15 When products 15-day slightly dropped 0.64, 28.7 1.9 amount retrievals close assimilating observations 0.99, 33.5 −18.8 among four seasons, only one false event was detected. This opens perspectives regional retrieval mapping irrigated/non areas.