Satellite-based Irrigation Water Use Estimates at 1km Spatial resolution over Europe

The datasets consist of high-resolution (1 km) Irrigation Water Use (IWU) estimates over Europe obtained from remote sensing observations. They rely on the SM-Inversion (Soil-Moisture-Inversion) approach. Two versions are provided: v1.0 and v1.1. They differ in terms of input data used; in both versions, satellite soil moisture from Sentinel-1 retrievals as delivered by the operational Copernicus Land Monitoring Services are considered. Both datasets rely on precipitation from the European ReAnalysis v5 - Land (ERA5-Land). The difference between v1.0 and v1.1 lies in the source for potential evaporation data; in fact, while v1.0 relies on ERA5-Land, v1.1 exploits outputs from the Global Land Evaporation Amsterdam Model (GLEAM) v4.2b. In both cases, all the input datasets have been resampled to the 1 km grid of Sentinel-1 soil moisture, which has been adopted as the target grid. As a result of the different inputs used, the two datasets cover different time periods, i.e., 2016-September 2025 and 2016-2024 in case of v1.0 and v1.1, respectively. Both datasets are provided with 14-day temporal aggregation. v1.0 data can be operationally extended as it relies on operational data. The datasets are an outcome of the European Space Agency (ESA) Irrigation-EU project. Details on the products development as well as on their technical validation can be found in: Dari, J., Baljeet Singh, Y.K., Ntokas, K., Fomferra, N., Brandt, G., Morbidelli, R., Saltalippi, C., Flammini, A., Leopardi, F., Rahmati, M., Filippucci, P., Camici, S., Fernández-Prieto, D., Volden, E., Brocca, L., 2026. Two satellite-based irrigation water use datasets at 1 km spatial resolution over Europe. In preparation. Acknowledgements: ESA Irrigation-EU project (CCN to ESA Contract 4000129870/20/I-NB, Irrigation+). Technical Section: The datasets can be accessed by downloading the archives directly from Zenodo or through Python and Jupyter notebooks using the xcube-zenodo plugin (https://github.com/xcube-dev/xcube-zenodo). Consider the code examples. The plugin adds a Zenodo data store to xcube and allows compressed Zarr datasets from a specific Zenodo record to be preloaded. For example, a data cube can be opened using the following code: from xcube.core.store import new_data_store store = new_data_store("zenodo", root=" 21473561" ) # The root is the zenodo DOI data_ids = store.list_data_ids() print(data_ids) # This will print all the the data_ids of the 4 datasets provided. cube = store.open_data( "iwu_temporal_v1.1.zarr.zip" ) # Open any of those datasets lazily print(cube) The spatially chunked archive is generally the preferred option for producing maps, extracting large spatial subsets, or analysing individual time steps. The temporally chunked archive is more appropriate for extracting complete time series at individual points or over small spatial areas.