Developing and testing a long-term soil moisture dataset at the catchment scale

• A procedure for developing a long-term soil moisture dataset was described.
• A soil moisture model was applied to distributed measurements in central Italy.
• The model reproduces the temporal and the spatial variability of observations.
• The modelled long-term soil moisture dataset was made freely available.

SummaryInferring long-term soil moisture time series with dense temporal resolution and representative of large areas is a challenging task. However, its accurate estimation over large areas might be essential for improving our knowledge of the mass and energy balance between the land surface and atmosphere, and also for many others practical applications. In this study, a long-term (1989–2011) simulated soil moisture dataset is developed by using 1-year in situ observations collected at 92 sites over an area of ∼400 km2 in central Italy. Specifically, a soil water balance model is calibrated for reproducing the soil moisture temporal variability at each site and, then, is tested for representing also the spatial variability of in situ measurements. The good temporal and spatial agreement between modelled and observed data gives confidence about the use of the modelled data in the study area for reconstructing a long-term soil moisture dataset with hourly temporal resolution (in accordance with the availability of hydrometeorological observations). The developed soil water balance model and procedure can be applied also in other climatic regions to obtain a similar dataset. Indeed, the obtained dataset and the model code are made freely available from the authors and can be used for hydrological and satellite soil moisture products validation studies.