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.

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

Lacava T;Brocca L;Melone F;Moramarco T;Pergola N;
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.
2010
Istituto di Metodologie per l'Analisi Ambientale - IMAA
Istituto di Ricerca per la Protezione Idrogeologica - IRPI
SENSOR MICROWAVE IMAGER
ERS SCATTEROMETER
SURFACE WETNESS SATELLITE DATA
FLOOD SSM/I TIME ASSIMILATION RADIOMETER MISSION
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/145515
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