Abstract
Accurate information about soil moisture content (SMC) in mountain catchments is of great importance in hydrological
applications, agriculture and climate change impact analysis. In the last two decades microwave remote sensing sensors
such as Synthetic Aperture Radar (SAR) have been deeply exploited for surface SMC estimation. However, obtaining
reliable predictions of fine-scale spatial and temporal patterns of SMC in mountain areas is still challenging due to the
extreme variability in topography, soil and vegetation properties. In this contribution we analyze the spatial and temporal
dynamic of surface SMC of alpine meadows and pastures with different techniques: (I) a network of fixed stations; (II)
field campaigns with mobile ground sensors; (III) SMC retrieval from RADARSAT2 SAR images; (IV) simulations
using the GEOtop 2.0 hydrological model. The strength and the weaknesses of the different estimation techniques are
evaluated and the physical controls of the observed SMC patterns are analyzed. Results show that SAR SMC estimation
corresponds well to the spatial ground surveys, but shows different patterns with respect to the model, especially for
irrigated meadows. In fact, SAR patterns reflect vegetation, soil type and topography. Model output is in agreement with
fixed stations observations, but it shows less spatial variability compared to SAR. Differences are likely due to the
difficulties to know with sufficient spatial detail model parameters and irrigation amount. Therefore, results suggest that
SAR products have a good ability to reproduce small-scale SMC patterns in mountain regions, thus complementing the
ability of the hydrological model to predict temporal variations of SMC.
