Estimates of water volumes stored in the root-zone of vegetation are a key element controlling the hydrological response of a catchment. The moisture content of the root-zone regulates the partitioning between drainage and water fluxes and reliable estimates are, therefore, critical for predictions of runoff. Remotely-sensed soil moisture products are available globally, however, they are representative of the upper-most few centimeters of the soil. The Soil Water Index (SWI) features a single parameter, representing the characteristic time length T of temporal soil moisture variability, and enables to infer root-zone soil moisture from near-surface estimates. Climate and soil properties are typically assumed to influence estimates of T, however, no clear quantitative link has yet been established. In this study, we hypothesize that the optimal value for T can be linked to the seasonal signals of the interplay between precipitation (water supply) and evaporation (atmospheric water demand), and, thus, to catchment-scale vegetation-accessible water storage capacities in the unsaturated root-zone. We first identify the optimal values of T that provide an adequate match between estimated SWI from several satellite-based near-surface soil moisture products (derived from AMSR2, SMAP and Sentinel-1) and modeled time series of unsaturated root-zone soil moisture from a calibrated process-based model in 16 contrasting catchments of the Meuse river basin. We found that optimal values of T positively and strongly correlate to catchment-scale estimates of unsaturated root-zone capacities, estimated both as model calibration parameter and from a simple water-balance approach. This correlation provides evidence that the T value, used to infer root-zone soil moisture, reflects the vegetation-accessible water storage capacities in the unsaturated root-zone, that can be estimated from water-balance data.
|Number of pages||1|
|Publication status||Published - 2019|
|Event||AGU Fall Meeting 2019 - San Francisco, United States|
Duration: 9 Dec 2019 → 13 Dec 2019
|Conference||AGU Fall Meeting 2019|
|Period||9/12/19 → 13/12/19|