High-resolution irrigation estimates for maize across Europe from ensemble AquaCrop simulations

Irrigation plays a key role in the terrestrial water cycle and agricultural production, yet it remains one of the most uncertain components of large-scale water use estimates. In recent years, several irrigation datasets based on modeling approaches and remote sensing have been developed. While these products have improved the spatial and temporal characterization of irrigation water use, they often lack an explicit quantification of uncertainty, limiting their applicability for hydrological and land surface modeling, as well as data assimilation.

This study presents high-resolution irrigation estimates for maize across Europe using ensemble simulations with the crop model AquaCrop (version 7.2) coupled to NASA’s Land Information System. Simulations are run for the period 2010-2020 at a 0.05° lat–lon resolution over European regions with irrigated maize, assuming sprinkler irrigation. The ensemble mean crop and irrigation estimates are evaluated against ground-truth and satellite observations. At the field scale, simulated irrigation amounts are compared against reported irrigation data over maize fields in the Lot and Tarn departments in southern France for the period 2016–2019. At the continental scale, simulated vegetation dynamics are evaluated using the Copernicus Land Monitoring Service fraction of canopy cover (FCOVER) product across Europe.

To explicitly represent uncertainty, ensembles are generated by perturbing meteorological forcings and a key irrigation parameter, specifically the root-zone soil moisture threshold that triggers irrigation events. Multiple ensemble configurations are tested to account for uncertainties related to irrigation management practices and meteorology. In a first experiment, shortwave radiation and precipitation are perturbed. In a second experiment, this configuration is extended by additionally perturbing air temperature, leading to a larger spread in vegetation development since crop growth stages are defined by accumulated heat units (growing degree days). In a final experiment, the ensemble is further expanded by perturbing the irrigation threshold, resulting in an increased spread in simulated irrigation amounts. An ensemble verification against field-level irrigation observations is performed to assess the ensemble uncertainty, providing a basis for future data assimilation applications.