GLEAM-HR: A 1-km terrestrial evaporation dataset with explicit representation of irrigation

Terrestrial evaporation (E) has traditionally been estimated either at coarse resolution over large domains or at high resolution over limited regions due to computational and storage constraints. Recent methodological and computational advances are bridging this gap, enabling regional- to global-scale E datasets at relatively high spatial resolutions for climate, water-management, and agricultural applications. Building on these developments and the fourth generation of the Global Land Evaporation Amsterdam Model (GLEAM4¹), we present GLEAM-HR, a 1-km E dataset for 2016–2023 covering Europe, Africa, and a portion of South America (Meteosat disk). GLEAM-HR combines precipitation from Multi-Source Weighted-Ensemble Precipitation (MSWEP) v2.8 with radiative forcing derived from merged Land Surface Analysis Satellite Application Facility (LSA SAF) and Moderate Resolution Imaging Spectroradiometer (MODIS) products.Algorithmic enhancements in GLEAM-HR enable a more realistic representation of fine-scale E dynamics, particularly in agricultural regions, and improve the characterisation of droughts and heatwaves. A key innovation is the explicit representation of irrigation through a four-step framework that (i) identifies irrigation timing and location at a daily scale, (ii) raises soil moisture to field capacity in irrigated grid cells, (iii) assimilates 1-km Sentinel-1² soil moisture observations, and (iv) estimates evaporative stress using an XGBoost-based model driven by vegetation and atmospheric stressors. Unlike other existing approaches, GLEAM-HR does not assume potential evaporation over irrigated croplands, but constrains E using multiple environmental stress factors.The resulting estimates show increases in annual evaporation of up to 450 mm yr⁻¹ over irrigated regions compared to simulations that neglect irrigation, with spatial patterns consistent with independent irrigation datasets. Evaluation against eddy-covariance measurements shows clear improvements at irrigated sites, with daily Kling–Gupta Efficiency (KGE) values of 0.20–0.40, while performance in non-irrigated regions ranges from 0.17 to 0.64. The dataset will be made publicly available through an interactive 3D data cube³ platform. Overall, GLEAM-HR provides a realistic high-resolution representation of irrigation effects on E, supporting applications in regional agricultural management and water-resource assessment. Future work includes global production of GLEAM-HR, development of a global 3D data cube, expansion of the record length, and propagation of algorithmic improvements to the next release of the long-term GLEAM climate record (0.1°) available via www.gleam.eu. ¹ Miralles, D.G., Bonte, O., Koppa, A., Baez-Villanueva, O.M., Tronquo, E., Zhong, F., Beck, H.E., Hulsman, P., Dorigo, W., Verhoest, N.E. and Haghdoost, S., 2025. GLEAM4: global land evaporation and soil moisture dataset at 0.1 resolution from 1980 to near present. Scientific data, 12(1), p.416² Fan, Dong; Zhao, Tianjie; Jiang, Xiaoguang; García-García, Almudena; Schmidt, Toni; Samaniego, Luis; Attinger, Sabine; Wu, Hua; Jiang, Yazhen; Shi, Jiancheng; Fan, Lei; Tang, Bo-Hui; Wagner, Wolfgang; Dorigo, Wouter; Gruber, Alexander; Mattia, Francesco; Balenzano, Anna; Brocca, Luca; Jagdhuber, Thomas; Wigneron, Jean-Pierre; Montzka, Carsten; Peng, Jian (2025): A Sentinel-1 SAR-based global 1-km resolution soil moisture data product: Algorithm and preliminary assessment. Remote Sensing of Environment, 318, 114579³ M. Söchting, M. D. Mahecha, D. Montero and G. Scheuermann, (2024): Lexcube: Interactive Visualization of Large Earth System Data Cubes. IEEE Computer Graphics and Applications, vol. 44, no. 1, pp. 25-37.