Remote sensing and global databases for soil moisture estimation at different depths in the Pernambuco state, Northeast Brazil
نویسندگان
چکیده
ABSTRACT The present study aimed to apply and assess an exponential filter that calculates the root-zone soil moisture using surface data from ocean salinity (SMOS) satellite, as well simulated in land-surface models global databases. water index (obtained after application of filter) land (GLDAS-CLSM, GLDAS-Noah, ERA5-Land) databases were compared with situ evaluate their efficiency estimating content at different depths. Surface measurements SMOS satellite allowed estimation depths 20 40 cm by applying filter. At both depths, significantly improved measured satellite. GLDAS-Noah model had best root mean square error values, whilst GLDAS-CLSM ERA5-Land overestimated moisture. Nevertheless, seasonal variation was represented all models.
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ژورنال
عنوان ژورنال: Revista Brasileira de Recursos Hídricos
سال: 2022
ISSN: ['1414-381X', '2318-0331']
DOI: https://doi.org/10.1590/2318-0331.272220220016