Improving reference crop evapotranspiration estimation using Solar-Induced chlorophyll fluorescence

Area of Science:

• Hydrology
• Remote Sensing
• Agronomy

Background:

• Accurate reference crop evapotranspiration (ET₀) estimation is vital for water resource management and crop water needs.
• Traditional ET₀ models often suffer from incomplete meteorological data.
• Sun-induced chlorophyll fluorescence (SIF) offers a promising alternative for ET₀ estimation.

Purpose of the Study:

• To develop an improved SIF-based model for ET₀ estimation that accounts for environmental variables.
• To enhance the accuracy and spatiotemporal resolution of ET₀ estimates.
• To provide a novel methodology for precise ET₀ estimation in arid and semi-arid regions.

Main Methods:

• Incorporated the basal crop coefficient (Kcb) into the ET₀_SIF model to create a hybrid model (RET₀_SIF).
• Integrated the RET₀_SIF model with satellite observations and reanalysis data for high-resolution ET₀ estimation (RET₀_SIFd).
• Validated the model against 22 monitoring stations and compared it with the Penman-Monteith (ET₀PM) method.

Main Results:

• The RET₀_SIF model significantly improved ET₀ estimation accuracy and captured seasonal variations.
• RET₀_SIF demonstrated superior performance over conventional models with minimal bias compared to ET₀PM.
• RET₀_SIFd revealed a west-to-east decreasing spatial pattern and a positive temporal trend in ET₀.

Conclusions:

• The hybrid SIF-based model (RET₀_SIF) offers a more accurate approach to ET₀ estimation.
• This methodology effectively addresses the limitations of existing models by incorporating environmental factors.
• The high-resolution ET₀ estimates provide valuable insights for water management in arid and semi-arid environments.