Parameterizing the modified water cloud model to improve soil moisture data retrieval using vegetation models

Kishan Singh Rawat; Sudhir Kumar Singh; Ram L. Ray; Szilárd Szabó; Sanjeev  Kumar

doi:10.15201/hungeobull.69.1.2

Kishan Singh Rawat Civil Engineering Department, Graphic Era (Deemed to be University), Dehradun, India https://orcid.org/0000-0001-5900-8195
Sudhir Kumar Singh K. Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, India https://orcid.org/0000-0001-8465-0649
Ram L. Ray College of Agriculture and Human Sciences, Prairie View A&M University, Prairie View, USA https://orcid.org/0000-0002-7833-9253
Szilárd Szabó Department of Physical Geography and Geoinformation Systems, University of Debrecen, Debrecen, Hungary https://orcid.org/0000-0002-2670-7384
Sanjeev Kumar Civil Engineering Department, Graphic Era (Deemed to be University), Dehradun, India https://orcid.org/0000-0003-3109-6423

DOI: https://doi.org/10.15201/hungeobull.69.1.2

Keywords: NDVI, EVI, SAR, Sentinel, WCM

Abstract

The objective was to parameterize a modified water cloud model using crop coefficients (A and B). These crop coefficients were derived from Landsat-8 and Sentinel-2 data. Whereas the coefficients C and D are of soil parameters. The water cloud model was modified using crop coefficients by minimizing the RMSE between observed VVσ⁰and Sentinel-1 based simulated VVσ⁰. The comparison with observed and simulated VV polarized σ⁰showed low RMSE (0.81 dB) and strong R²of 0.98 for NDVI-EVI combination. However, based on other possible combinations of vegetation indices VVσ⁰and simulated VVσ⁰do not show a good statistical agreement. It was observed that the errors in crop coefficients (A and B) are sensitive to errors in initial vegetation/canopy descriptor parameters.

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Parameterizing the modified water cloud model to improve soil moisture data retrieval using vegetation models

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