Calibration of a SVAT Model in the Central Zone of Mexico with In-Situ Data over a Corn Field Region

Integrate information of soil moisture obtained through available satellite observations with low implementation cost can help to guarantee food security and sovereignty in Mexican production. With few reliable databases of the behavior of soil moisture during the growth of corn and other crops, the validation of satellite retrievals with Mexican field campaigns it is necessary. In this study, we present the calibration of a SVAT-LSP model during a complete growing season over a corn region in Central Mexico. In-situ soil moisture values and SVAT-LSP estimates of soil moisture were also compared with the SMAP L2SM product. The calibration of the SVAT-LSP model was carried out using the Monte Carlo methodology. The surface soil moisture from the calibrated SVAT-LSP model show an RMSE of 0.0258 m
³
/m
³
when compared with in-situ values. In contrast, an RMSE of 0.1331 m
³
/m
³
was obtained between in-situ values and SMAP L2SM retrievals.