Soil Moisture Remote Sensing: State‐of‐the‐Science

Abstract

Core Ideas Satellites, particularly at L‐band frequency, can globally map near‐surface soil moisture. Near‐surface moisture is extended to the root zone using models and data assimilation. Validation uses core monitoring sites, monitoring networks, field campaigns, and multi‐satellite comparisons. Efforts are underway to associate soil moisture variability dynamics with land surface attributes. 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 moisture at a spatial resolution of 25 to 40 km and temporal resolution of 2 to 3 d. C‐ and X‐band soil moisture records date back to 1978, making available an invaluable data set for long‐term climate research. Near‐surface soil moisture is further extended to the root zone (top 1 m) using process‐based models and data assimilation schemes. Validation of remotely sensed soil moisture products has been ongoing using core monitoring sites, sparse monitoring networks, intensive field campaigns, as well as multi‐satellite comparison studies. To transfer empirical observations across space and time scales and to develop improved retrieval algorithms at various resolutions, several efforts are underway to associate soil moisture variability dynamics with land surface attributes in various energy‐ and water‐rich environments. We describe the most recent scientific and technological advances in soil moisture remote sensing. We anticipate that remotely sensed soil moisture will find many applications in vadose zone hydrology in the coming decades.

Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes

“…Accurate information about soil moisture temporal and spatial variation is therefore important for further application [2], e.g., for flood and drought forecasts [5,6], as well as for climate impact studies [7]. Coarse scale, but moderate temporal resolution global surface soil moisture can be obtained by satellite remote sensing, mostly by microwave sensors [8,9]. Currently several satellite missions provide global surface soil moisture products, such as: the Soil Moisture Active Passive (SMAP) [10], the Soil Moisture and Ocean However, the application of the CRNP method is hampered by its sensitivity to additional sources of hydrogen (e.g., above-and below-ground biomass, humidity of the lower atmosphere, However, the application of the CRNP method is hampered by its sensitivity to additional sources of hydrogen (e.g., above-and below-ground biomass, humidity of the lower atmosphere, lattice water of the soil minerals, organic matter and water in the litter layer, intercepted water in the canopy, and soil organic matter), e.g., Bogena et al [57], Franz et al [58], Heidbüchel et al [59].…”

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

“…Although recent decades have seen great advances in remote sensing applications for mapping surface soil moisture (Jackson, 1993;Njoku et al, 2003;Mohanty et al, 2017), most hydrological studies that make use of soil moisture data require integrated values over a certain soil depth (Brocca et al, 2017). Extrapolation of surface soil moisture from remote sensing techniques to depths beyond the sensor's capacity (up to 5 cm) is not a trivial task given the spatiotemporal variability of soil moisture.…”

Recent Advances in Soil Moisture Estimation from Remote Sensing

“…It plays important roles in various processes and feedback loops within the earth system [1][2][3][4]. Soil moisture can be measured by instruments in the field [5] or estimated by remote sensing techniques [1].…”