Comparisons to ground-based surface soil moisture estimates are necessary to evaluate the capability of remote sensors to determine soil moisture and its spatiotemporal variability. Soil moisture can be especially variable in regions of complex terrain which exhibit large variations in vegetation, soil properties and hydrologic conditions. The objective of this study is to evaluate the spatiote...

High-altitude and alpine areas are predicted to experience rapid and substantial increases in future temperature, which may have serious impacts on soil carbon, nutrient and soil fauna. Here we report the impact of 20 years of experimental warming on soil properties and soil mites in three contrasting plant communities in alpine/subarctic Sweden. Long-term warming decreased juvenile oribatid mi...

The combined effect of soil moisture in unsaturated soil layers and pore-water pressure in saturated soil layers is critical to predict landslides. An improved infinite slope stability model, that directly includes unsaturated zone soil moisture and groundwater, is derived and used to analyze the factor of safety’s sensitivity to unsaturated zone soil moisture. This sensitivity, the change in t...

The capability of active microwave remote sensing to measure soil moisture was validated via the use of GIS techniques incorporating soil landscape unit assessment and terrain wetness. The work was carried out over an 80 km region in the Mount lofty Ranges in South Australia. Search for atypically wet sites (ie. wet areas in a dry landscape, which were non-irrigated) was completed using analysi...

A key state variable in land surface–atmosphere interactions is soil moisture, which affects surface energy fluxes, runoff and the radiation balance. Soil moisture modelling relies on parameter estimates that are inadequately measured at the necessarily fine model scales. Hence, model soil moisture estimates are imperfect and often drift away from reality through simulation time. Because of its...

Current models for seasonal climate prediction are limited due to poor initialization of the land surface soil moisture states. Passive microwave remote sensing provides quantitative information on soil moisture in a thin near-surface soil layer at large scale. This information can be integrated with a land surface process model through data assimilation to give better prediction of the near su...

Satellite remote sensing observations have the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from microwave remote sensing techniques are typically complex due to inherent difficulty in characterizing the interactions among land surface parameters that contribute to the retrieval process. Therefore, adequate physical mathe...

Three independent surface soil moisture datasets for the period 1979–87 are compared: 1) global retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), 2) global soil moisture derived from observed meteorological forcing using the NASA Catchment Land Surface Model, and 3) ground-based measurements in Eurasia and North America from the Global Soil Moisture Data Bank. Time-average ...

[1] Climate model prediction skill is currently limited in response to poor land surface soil moisture state initialization. However, initial soil moisture state prediction skill can potentially be enhanced by the assimilation of remotely sensed near-surface soil moisture data in off-line simulation. This study is one of the first to evaluate such potential using actual remote sensing data toge...