Long-Term Actual Evapotranspiration (ETa) Maps of Irrigated Croplands in the Amu Darya Basin (1987–2019)
Abstract
Overview This dataset contains annual actual evapotranspiration (ETa) estimates for irrigated croplands of the Amu Darya Basin from 1987 to 2019. ETa was derived at 30-m spatial resolution using Landsat Collection 2 imagery and the SSEBop FANO (v0.2.8) evapotranspiration model, implemented through the Google Earth Engine (GEE) Python API (Senay et al., 2013; Senay et al., 2022; Senay et al., 2023), using the open-source implementation provided by the OpenET GitHub repository (OpenET, 2024; https://github.com/Open-ET/openet-ssebop). Only irrigated areas were included, based on the Landsat-derived cropland maps from Rufin et al. (2022; dataset available at https://doi.org/10.5281/zenodo.6957723). The dataset provides annual cumulative ETa for the April–October growing season and supports analyses of long-term crop water use and irrigation dynamics in the Amu Darya Basin. A detailed description of the methods, processing steps, and interpretation is provided in the associated open-access research article published in Communications Earth & Environment (https://doi.org/10.1038/s43247-025-03142-y). Data description The ZIP archive contains one GeoTIFF file per year (1987-2019), each named ETa_YYYY.tif, representing April-October actual evapotranspiration (mm) for irrigated croplands. SSEBop ETa estimates were compared with Kc-based evapotranspiration (Allen et al., 2011) at five meteorological stations in Uzbekistan, showing consistent seasonal patterns and expected magnitudes. Full validation details are available in the associated research article. GeoTIFF specifications Unit: millimeters (mm) Spatial resolution: 30 m Projection: WGS84 (EPSG:4326) References: Allen, R. G., Pereira, L. S., Howell, T. A., & Jensen, M. E. (2011). Evapotranspiration information reporting: I. Factors governing measurement accuracy. Agricultural Water Management, 98(6), 899–920. https://doi.org/10.1016/j.agwat.2010.12.015 OpenET. (2024). openet-ssebop: SSEBop model with FANO implementation (Version 0.2.8) [Software]. GitHub. https://github.com/Open-ET/openet-ssebop. Accessed 17 April 2024. Rufin, P., Peña-Guerrero, M. D., Umirbekov, A., Wei, Y., & Müller, D. (2022). Post-Soviet changes in cropping practices in the irrigated drylands of the Aral Sea basin. Environmental Research Letters, 17, 095013. https://doi.org/10.1088/1748-9326/ac9aaf Rufin, P., Peña-Guerrero, M. D., Umirbekov, A., Wei, Y., & Müller, D. (2022). Landsat-based maps of cropping practices in the irrigated drylands of the Aral Sea Basin (1987–2019) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.6957723 Senay, G. B., Bohms, S., Singh, R. K., Gowda, P. H., Velpuri, N. M., Alemu, H., & Verdin, J. P. (2013).Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. Journal of the American Water Resources Association, 49(3), 577–591. https://doi.org/10.1111/jawr.12057 Senay, G. B., Kagone, S. H., Nieto, H., Schauer, M., Friedrichs, M., Velpuri, N. M., & Bohms, S. (2022).Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model. Remote Sensing of Environment, 275, 113011. https://doi.org/10.1016/j.rse.2022.113011 Senay, G. B., Kagone, S. H., Nieto, H., Friedrichs, M., Schauer, M., & Bohms, S. (2023).Improving the Operational Simplified Surface Energy Balance Evapotranspiration model using the Forcing and Normalizing Operation (FANO). Remote Sensing, 15(2), 260. https://doi.org/10.3390/rs15010260