Higher temporal evapotranspiration estimation with improved SEBS model from geostationary meteorological satellite...

Area of Science:

• Hydrology and Remote Sensing
• Environmental Science and Water Management

Background:

• Evapotranspiration (ET) is crucial for water resource management, especially in water-stressed regions like the Haihe River Basin.
• High-resolution ET data are vital for dynamic hydrological and land surface process modeling.

Purpose of the Study:

• To estimate 3-hourly and daily energy and water fluxes in the Haihe River Basin using geostationary satellite data and the SEBS model.
• To validate the model's performance and identify key factors influencing ET in the region.

Main Methods:

• Utilized geostationary satellite remote sensing data and in situ meteorological observations.
• Applied the Surface Energy Balance System (SEBS) model with a novel kB⁻¹ parameterization.
• Validated ET estimates against point-scale data from five observation flux towers.

Main Results:

• The SEBS model demonstrated good performance in estimating 3-hourly and daily ET (R² = 0.67, RMSE = 0.1 mm/h).
• Evapotranspiration was found to be strongly correlated with the Normalized Difference Vegetation Index (NDVI), with distinct response patterns at different NDVI levels.
• Factors influencing ET include land cover, surface properties, water availability, radiation, and atmospheric conditions.

Conclusions:

• The study provides reliable ET data for the Haihe River Basin, crucial for sustainable water resource management.
• Understanding ET dynamics and its correlation with NDVI enhances the comprehension of the basin's hydrologic cycle.
• The findings support improved water resource strategies in a region facing significant water challenges.