Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations

Abstract. The current intensive use of agricultural land is affecting the quality and contributes to climate change. Feeding world's growing population under changing climatic conditions demands a global transition more sustainable systems. This requires efficient models data monitor cultivation practices at field scale. study outlines spatially distributed version field-scale crop model AquaCrop 6.1 simulate biomass production soil moisture variability over Europe relatively fine resolution 30 arcsec (∼1 km). A highly parallel processing system implemented run regionally with meteorological input from Modern-Era Retrospective analysis for Research Applications 2 (MERRA-2), textural information Harmonized World Soil Database 1.2 (HWSDv1.2), generic information. setup chosen as baseline future satellite-based assimilation system. relative temporal in daily evaluated Copernicus Global Land Service dry matter productivity (CGLS-DMP) data. Surface compared against NASA Moisture Active–Passive surface (SMAP-SSM) retrievals, (CGLS-SSM) product derived Sentinel-1, situ International Network (ISMN). Over central Europe, regional able capture both moisture, spatial mean correlation 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), 0.52 (CGLS-SSM). higher performance when evaluating SMAP-SSM Sentinel-1 CGLS-SSM largely due lower satellite retrievals vegetation. further captures short-term inter-annual variability, anomaly 0.46 correlations 0.65 0.50 moisture. It shown that characteristics irrigated areas influence performance. Overall, adequately simulates provides suitable subsequent assimilation.