[1] We present an unmixing method, based on genetic algorithm-soil-vegetationatmosphere-transfer modeling to extract subgrid information of soil and vegetation from remotely sensed soil moisture (downscaled; e.g., soil hydraulic properties, area fractions of soil-vegetation combinations, and unmixed soil moisture time series) that most land surface models use. The unmixing method was evaluated ...

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are nor...

This study reviews recent progress on soil moisture data assimilation. Data assimilation is a process of merging observations with a system dynamic model to provide an improved estimate of the states of the environment. The application of data assimilation in hydrology is relatively new, however, rapid progress has been made in the last decade or so with the available remotely sensed soil moist...

This is an update to the special section “Remote Sensing for Vadose Zone Hydrology—A Synthesis from the Vantage Point” [Vadose Zone Journal 12(3)]. Satellites (e.g., Soil Moisture Active Passive [SMAP] and Soil Moisture and Ocean Salinity [SMOS]) using passive microwave techniques, in particular at L-band frequency, have shown good promise for global mapping of near-surface (0–5-cm) soil moistu...

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Soil moisture satellite mission accuracy, repeat time and spatial resolution requirements are addressed through a numerical twin data assimilation study. Simulated soil moisture profile retrievals were made by assimilating near-surface soil moisture observations with various accuracy (0, 1, 2, 3, 4, 5 and 10%v/v standard deviation) repeat time (1, 2, 3, 5, 10, 15, 20 and 30 days), and spatial r...

[1] This study presents a systematic and integrated analysis of the sensitivity of the available satellite observations to in situ soil moisture measurements. Although none of these satellites is optimized for land surface characterization, before the launches of the SMOSand HYDROS-dedicated missions they are the only potential sources of global soil moisture measurements. The satellite observa...

Soil moisture is an important environmental variable in regulating energy fluxes and water infiltration near the soil surface. This makes it a significant parameter in meteorological and climate modelling applications. While ground measurement of soil moisture at a large spatial scale is cumbersome and time-consuming, remote sensing offers the advantage of frequent observations in time and spac...

Land surface models (LSM) are widely used as scientific and operational tools to simulate mass and energy fluxes within the soil vegetation atmosphere continuum for numerous applications in meteorology, hydrology or for geobiochemistry studies. A reliable parameterization of these models is important to improve the simulation skills. 5 Soil moisture is a key variable, linking the water and ener...

Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to 1) seasonality in the statistics of the atmospheric forcing, 2) the variation of evaporation with soil moisture, 3) the variation of runoff with soil moisture, and 4) correlation between the atmospheric forcing and antecedent soil moisture, as perhaps induc...