This dataset was used to run the remote sensing-based two-source energy balance (TSEB) model to estimate evapotranspiration and related crop stress indicators using high-resolution imagery from unmanned aerial vehicles (UAVs) over a a vineyard experimental site in Madrid, Spain ('El Socorro', Belmonte de Tajo, Madrid, Spain). The dataset includes an example script to run the python implementation of TSEB (pyTSEB, https://github.com/hectornieto/pyTSEB) forced with UAV imagery and meteorological data acquired over the study site. The model outputs are also provided for the different TSEB version (TSEB-PT and TSEB-2T). These results are associated with the manuscript titled 'Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics' published in Irrigation Science.

All the inputs and outputs of the two-source energy balance (TSEB) model are in the 'inputs' and 'outputs folder. Another readme file explicitely describes this data. Also described below: ## inputs ### meteo A csv file with meterological and EC measurements during UAV overpass time. ### UAV UAV imagery are stored in seperate folders for each date (in YYYYMMDD). Each input is available over the study site at 2m spatial resolution. ## outputs The model outputs are available for both TSEB-PT and TSEB-2T versions using pyTSEB (https://github.com/hectornieto/pyTSEB). In each folder, both Main ('Main') and ancillary ('Anc') output data is made available.

The experiment was undertaken under the Digital Agriculture Technologies for Irrigation efficiency (DATI) project (2020-2024) funded by the Spanish Ministry of Science and Innovation (AEI/10.13039/501100011033) and the PRIMA EU program. It additionally received support from the EO4WUE research project (TED2021-129814B-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. We also would like to thank Dr. Bill Kustas and USDA for helping with research infrastructure and scientific support.

Peer reviewed