Estimation of Crops’ Water Consumption by Remote Sensing: SEBAL Model Calculations Versus Ground Observation in the Irrigated Area of Lakhmass (Siliana, Northern Tunisia)

Belhaj Kilani, Amani [UCL] S. Khlifi Vanclooster, Marnik [UCL]

Agriculture remains a crucial sector in the Tunisian economy and is facing considerable hydric constraints due to climate change that needs to be addressed by appropriate irrigation water management. Assessing irrigation water requirements for the public irrigated areas (PIA) is therefore one of the priorities in supporting irrigation water management. In the present study, water consumption and requirements for the PIA of Lakhmass in Tunisia are assessed using remote sensing technology. PIA scale ET is estimated through the implementation of the Surface Energy Balance Algorithm for Land (SEBAL), within the Google Earth Engine (GEE) platform, by combining ERA5-land meteorological reanalysis data with visible, near-infrared, and thermal imagery satellites from high-resolution (10 m) Sentinel 2 images. The remote sensing data were combined with the seasonal supplied water to the PIA Lakhmass, collected at plot level. This study was conducted over five agricultural campaigns from 2016-2017 to 2020-2021. The results indicate that ET decreases in winter to be lower than 20 mm/month and increases in spring, 20 and 50 mm/month. During summer, it exceeds more than 70 mm/month. Furthermore, the results of the method were satisfactory, relevant, and encouraging, which could allow the monitoring of overconsumption with the identification of areas where there have been water losses. The seasonal ET was compared with water allocations which will allow calibrating the estimation of derived estimated from the SEBAL model. KEYWORDS: Evapotranspiration, Irrigation, Water use, Remote sensing, GEE, SEBAL.