Parameterizing the modified water cloud model to improve soil moisture data retrieval using vegetation models-Reference-Cited by-同舟云学术

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

Published:2020-04-02 Issue:1 Volume:69 Page:17-26
ISSN:2064-5031
Container-title:Hungarian Geographical Bulletin
language:
Short-container-title:HunGeoBull

Author:

Rawat Kishan Singh¹^ORCID,Singh Sudhir Kumar²^ORCID,Ray Ram L.³^ORCID,Szabó Szilárd⁴^ORCID,Kumar Sanjeev¹

Affiliation:

1. Civil Engineering Department, Graphic Era (Deemed to be University), Dehradun, India

2. K. Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, India

3. College of Agriculture and Human Sciences, Prairie View A&M University, Prairie View, USA

4. Department of Physical Geography and Geoinformation Systems, University of Debrecen, Debrecen, Hungary

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 VVσ0 and Sentinel-1 based simulated VVσ0. The comparison with observed and simulated VV polarized σ0 showed low RMSE (0.81 dB) and strong R2 of 0.98 for NDVI-EVI combination. However, based on other possible combinations of vegetation indices VVσ0 and simulated VVσ0 do 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.

Publisher

Research Centre for Astronomy and Earth Sciences

Subject

General Earth and Planetary Sciences,Geography, Planning and Development

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