SMAP (Soil Moisture Active Passive) Handbook: Mapping Soil Moisture and Freeze/Thaw from Space

Soil moisture is a primary state variable of hydrology and the water cycle over land. In diverse Earth and environmental science disciplines, this state variable is either an initial condition or a boundary condition of relevant hydrologic models. Applications such as weather forecasting, skillful modeling and forecast of climate variability and change, agricultural productivity, water resources management, drought prediction,  flood area mapping, and ecosystem health monitoring all require information on the status of soil moisture.

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The NOAA Hydrometeorology Testbed Soil Moisture Observing Networks: Design, Instrumentation, and Preliminary Results

The NOAA Hydrometeorology Testbed (HMT) program has deployed soil moisture observing networks in the watersheds of the Russian River and the North Fork (NF) of the American River in northern California, and the San Pedro River in southeastern Arizona. These networks were designed to serve the combined needs of the hydrological, meteorological, agricultural, and climatological communities for observations of soil moisture on time scales that range from minutes to decades.

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McMaster Mesonet soil moisture dataset: Description and spatio-temporal variability analysis

This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR) probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution.

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