Estimation of Crops Water Consumption by Remote Sensing: SEBAL Model Calculations Versus Ground Observation In The Irrigated Area of Lakhmess (Siliana, Northern Tunisia)

Tunisian agriculture remains a crucial component of the country’s economic development and faces considerable constraints related to increasing water demand and reducing water resources’ availability. Improving the assessment of irrigation water use is a prerequisite for sustainable water management. The present study aims to evaluate the quality of water consumption estimates in the Public Irrigated Area of Lakhmess using open-source data. High-resolution (10 m) Sentinel 2 images, combined with ERA5-land meterological data, were used to assess monthly and seasonal actual evapotranspiration (ET) and water use through the implementation of the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine (GEE) environment. The calculated water uses were combined with the seasonal supplied water to the PIA Lakhmess, collected at plot level.

This study was conducted over eight agricultural campaigns from 2015-2016 to 2022-2023. The method is validated for three sectors Sidi Jaber, Gantra and Gabel, comparing the seasonal water use estimates to water meter observations. Correlation analysis between estimated water use from open-access data and  in-situ measurement yielded correlation coefficients of 0.76, 0.75 and 0.73, with corresponding RMSE values of 0.461, 0.425, and 0,391 mm/day, respectively. In addition, SEBAL-derived evapotranspiration estimates were evaluated through comparison with reference evapotranspiration computed using the FAO-56 Penman-Monteith, resulting in an R²  of 0,68 and an RMSE of 0.315 mm/day. Overall, the methods were deemed satisfactory, as they facilitated the monitoring of excessive water usage by identifying areas where water losses occurred.

Key words: Evapotranspiration, Irrigation, water use, Remote sensing, GEE, SEBAL.