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Soil moisture variations monitoring by AMSU-based soil wetness indices: A long-term inter-comparison with ground measurements

Articolo
Data di Pubblicazione:
2010
Abstract:
Soil moisture controls the partitioning of rainfall into runoff and infiltration and, consequently, the runoff generation. On the catchment scale its routine monitoring can be performed through remote sensing technologies. Within this framework, the purpose of this study is to investigate the potential of the Advanced Microwave Sounding Unit (AMSU), radiometer on board the NOAA (National Oceanic and Atmospheric Administration) satellites and operating since 1998, for the assessment of soil wetness conditions by comparing soil moisture data with both those measured in situ and provided by a continuous rainfall-runoff model applied to four catchments located in the Upper Tiber River (Central Italy). In particular, in order to perform a robust analysis an extensive and long-term period (nine years) of data was investigated. In detail, the Soil Wetness Variation Index, derived from the AMSU data modified in order to take account of the difference between the soil layer investigated by the satellite sensor and that used as a benchmark, was found to be correlated both with the in-situ and modeled soil moisture variations showing correlation coefficients in the range of 0.42-0.49 and 0.33-0.48, respectively. As far as the soil moisture temporal pattern is concerned, higher correlations were obtained (0.59-0.84 for the in-situ data and 0.82-0.87 for the modeled data set) partly due to the soil moisture seasonal pattem that enhances the correlation. Overall, the root mean square error was found to be less than 0.05 m(3)/m(3) for both the comparisons, thus assessing the potential of the AMSU sensor to quantitatively retrieve soil moisture temporal patterns. Moreover. the AMSU sensor can be considered as a useful tool to provide a reliable and frequently updated global soil moisture data set, considering its higher temporal resolution now available (about 4 passes per day) thanks to the presence of the sensor aboard different satellites.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
SENSOR MICROWAVE IMAGER; ERS SCATTEROMETER; SURFACE WETNESS SATELLITE DATA; FLOOD SSM/I TIME ASSIMILATION RADIOMETER MISSION
Elenco autori:
Tramutoli, Valerio; Calice, Giovanni; Moramarco, Tommaso; Pergola, Nicola; Lacava, Teodosio; Brocca, Luca; Melone, Florisa
Autori di Ateneo:
BROCCA LUCA
LACAVA TEODOSIO
MORAMARCO TOMMASO
PERGOLA NICOLA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/145515
Pubblicato in:
REMOTE SENSING OF ENVIRONMENT
Journal
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Dati Generali

URL

http://dx.doi.org/10.1016/j.rse.2010.05.008
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