Surface Soil Moisture Data Assimilation in AquaCrop: Overcoming Limited Vertical Coupling with an Exponential Filter

Root-zone soil moisture (RZSM) critically controls crop development, yet satellite missions observe only near-surface soil moisture, which poses challenges for its incorporation into crop models. In AquaCrop, the soil water module exhibits limited vertical coupling between computational soil compartments due to the abrupt effects of wilting point and field capacity thresholds, restricting the downward propagation of surface information. To address this limitation, an exponential filtering approach can be used to transform surface soil moisture into temporally smoothed estimates that are more representative of deeper soil layers. We assess the assimilation of SMAP Level-2 surface soil moisture into AquaCrop over European croplands (2015–2023, 0.1° resolution) with the aim of improving RZSM under these structural constraints. We compare direct assimilation of SMAP retrievals with assimilation of exponentially filtered datasets representing effective target depths of 30, 60, and 100 cm, using seasonally varying CDF matching within an ensemble Kalman filter.

The assimilation consistently improves topsoil (0–30 cm) moisture, but gains in subsoil (30–100 cm) moisture are strongly affected by the weak internal vertical coupling of the soil water balance. Specifically, while the direct assimilation of surface observations has limited impact below 30 cm, that of filtered products leads to improvements in RZSM. The best performance is obtained for a 60 cm target depth, with widespread increases in correlation against in situ observations. The impact of improved soil moisture is also evaluated for canopy cover and biomass using satellite-based reference data. Vegetation improvements remain weak and inconsistent, influenced by several factors including biases in the reference data and limitations in soil–plant coupling, for example, due to the use of a generic crop parameterization that is not spatially explicitly calibrated. Our results highlight the value of exponential filtering for soil moisture assimilation in weakly coupled crop models and point to joint soil moisture–vegetation assimilation as a promising pathway for further improvements.