Evapotranspiration in Semi-Arid Climate: Remote Sensing vs. Soil Water Simulation

Area of Science:

• Hydrology
• Agricultural Science
• Remote Sensing

Background:

• Accurate crop evapotranspiration (ETa) estimation is crucial for water resource management.
• Remote sensing and surface energy balance (SEB) models offer a way to assess ETa using biophysical variables.

Purpose of the Study:

• To compare ETa estimations from the simplified surface energy balance index (S-SEBI) using Landsat 8 data with HYDRUS-1D simulations.
• To evaluate the performance of S-SEBI for rainfed and irrigated crops in a semi-arid environment.

Main Methods:

• Utilized Landsat 8 optical and thermal infrared bands for S-SEBI model calculations.
• Employed HYDRUS-1D model with in-situ measurements of soil water content and pore electrical conductivity.
• Conducted real-time measurements in barley and potato fields in Tunisia.

Main Results:

• S-SEBI ETa estimations showed good correlation with HYDRUS-1D (R² of 0.86 for barley, 0.70 for potato).
• S-SEBI performed better for rainfed barley (RMSE 0.35-0.46 mm·d⁻¹) than for irrigated potato (RMSE 1.5-1.9 mm·d⁻¹).
• HYDRUS-1D proved effective for modeling water and salt movement in the root zone.

Conclusions:

• The S-SEBI model, driven by Landsat 8 data, provides a reliable method for estimating crop evapotranspiration.
• Model performance is influenced by available energy and soil flux (G0) estimations.
• S-SEBI shows potential for water management applications in semi-arid agricultural systems.