Coupling water and carbon processes to estimate field-scale maize evapotranspiration with Sentinel-2 data.

• A field-scale 10 m daily ET estimation model was developed with Sentinel-2 data. • The plant optimization theory was applied to the remote sensing-based ET model. • ET sensitivity towards warming and elevated CO2 concentration was analyzed based on the proposed model. • The remote sensing spatial scale effect on ET models was quantified. Crop evapotranspiration (ET) is an essential part of agricultural water consumption, and robust monitoring of remote sensing (RS)-based ET at the field scale improves agricultural water management against water shortages. In this study, we propose a high-resolution optical RS-driven daily ET estimation framework coupling water vaporization and carbon assimilation based on Sentinel-2 satellite data. To determine if the proposed framework is accurate compared with flux observations, three tower sites are chosen (Guantao and Huailai from the Haihe Basin; Daman from the Heihe Basin), with a total of four years of observations adopted for model validation. The correlation coefficient R ranges from 0.870 to 0.912, and the RMSE ranges from 0.89 to 1.21 mm/day. Sensitivity analyses indicate that ET is most sensitive to air temperature, followed by ambient CO 2 concentration and absorbed shortwave radiation, which provides indications into potential future farming strategies to confront global climate change. Finally, we discuss the scale effects on the proposed model at the field scale. Results from three sites show that for a larger area of interest (AOI) the impact of scales increases. This research provides insights into ET calculations across several spatial scales and application potential in precision agricultural water management. [ABSTRACT FROM AUTHOR]