Gururaj, P.Umesh, P.Shetty, A.2026-02-042022Geocarto International, 2022, 37, 25, pp. 10301-1031910106049https://doi.org/10.1080/10106049.2022.2032398https://idr.nitk.ac.in/handle/123456789/22839The goal of this study is to evaluate the efficiency of surface soil moisture models based on L-band SAR data at two different crop stages in typical Indian agricultural plots. Agricultural fields examined include paddy, tomato, sugarcane, at two distinct crop stages, and a reference fallow field. Among the evaluated models, X-Bragg model underestimates soil moisture in all agricultural fields, whereas the Oh 2004 model fits into three agricultural plots for two crop stages without any necessity of auxiliary field information. All models underperformed in the case of sugarcane at the grand growth stage. Although WCM gave best result, it came at the cost of field data utilized to calibrate model parameters. Overall, the Oh 2004 model outperforms other models across crop types and growth stages. To the best of our knowledge, this is the only study that deals with soil moisture estimations at the plot scale across different crops. © 2022 Informa UK Limited, trading as Taylor & Francis Group.agricultural soilbackscattercrop plantgrowthmapping methodsoil moisturesynthetic aperture radar