Validation of Soil Moisture in the Brazilian Semiarid, Using Smos Satellite Product And Simagri Model

Soil moisture constitutes one of the main factors for the study where there is a water deficit in the soil, mainly for semiarid regions. The semiarid region of Brazil, which extends from the northern of the Piaui State to the north of Minas Gerais, is a region vulnerable to drought. the accuracy of...

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Published inIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium pp. 84 - 87
Main Authors Rossato, L., Vall-Llossera, M., Camps, A., Portal, G., Sakuragi, J., Angelis, C. F., Zeri, M., Barbosa, H., Paredes, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2018
Subjects
Brazilian semiarid region
Data models
Estimation
Indexes
Mathematical model
Monitoring
SIMAGRI
SMOS
Soil moisture
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Summary:Soil moisture constitutes one of the main factors for the study where there is a water deficit in the soil, mainly for semiarid regions. The semiarid region of Brazil, which extends from the northern of the Piaui State to the north of Minas Gerais, is a region vulnerable to drought. the accuracy of soil moisture estimation is important for different studies. Thus, the aim of this work is to present the soil moisture derived from different methods: 1) Soil Moisture and Ocean Salinity (SMOS) satellite products generated at the Barcelona Expert Center (BEC) [2] and 2) System of Monitoring and Alert of Anomaly for Agriculture (SIMAGRI) model, at the semiarid region of Brazil. This region is selected because is a semiarid region recently affected by droughts and in situ measurements are available. Then it is very suitable for validation. In this paper an inter-comparison work with data recorded by that network, HR SM data from BEC and SIMAGRI model is presented. This study has been carried out from November, 2015 to June, 2016. We are going to present the statistical study, using correlation coefficient (R), Bias, and Root Mean Square Error (RMSE) as metrics. The results of this study will help to analyze environmental and economic impacts when droughts are detected in this area, which economy is mainly based on agriculture and to act for mitigating the negative consequences. Finally, it seems that the combination of satellite product and SIMAGRI model can be used as a valuable tool for monitoring and alert in case of dry and/or flooding episodes in different agricultural regions.
ISSN:2153-7003
DOI:10.1109/IGARSS.2018.8518430