Paper
7 October 2011 What perspective in remote sensing of soil moisture for hydrological applications by coarse-resolution sensors
Luca Brocca, Florisa Melone, Tommaso Moramarco, Wolfgang Wagner
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Abstract
Soil moisture is a key state variable in hydrology, it controls the proportion of rainfall that infiltrates, runoff and evaporates from the land. For hydrological applications, soil moisture monitoring at catchment scale is required and, for that, microwave remote sensing sensors might be used. However, due to their coarse-spatial resolution, the skepticism on the suitability to retrieve the soil moisture at catchment scale takes still place. This work attempts to bring out if coarse resolution sensors for soil moisture monitoring can have some perspectives for hydrological applications. Two soil moisture products derived from the Advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) are used for this purpose. The analysis is addressed by investigating: (i) the reliability of product data in the estimation of the wetness conditions of a catchment antecedent to rainfall events, and (ii) the benefit on runoff prediction if data are assimilated into a rainfall-runoff model. Rainfall-runoff observations are taken from several catchments in Italy and Luxembourg for testing. Results reveal that ASCAT and AMSR-E soil moisture products can be conveniently used to improve runoff prediction thus opening new important challenges and opportunities for the use of this new sources of data in the operational hydrology.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luca Brocca, Florisa Melone, Tommaso Moramarco, and Wolfgang Wagner "What perspective in remote sensing of soil moisture for hydrological applications by coarse-resolution sensors", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81740A (7 October 2011); https://doi.org/10.1117/12.898034
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Cited by 3 scholarly publications.
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KEYWORDS
Soil science

Data modeling

Satellites

Sensors

Floods

Calibration

Performance modeling

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