August 24 – College of Agriculture and Human Science’s Research Scientist and Associate Professor Ram Ray Ph.D., developed an integrated approach using Water Cloud Model combined with satellite data to improve soil moisture measurements at the farm scale. Ray and colleagues, Kishan S. Rawat, Ph.D., Sudhir K Singh, Ph.D., and Szilard Szabo, Ph.D., modified the Water Cloud Model using Normalized Difference Vegetation Index (NDVI) obtained from Sentinel-2 and Landsat-8 satellites. They applied this modified WCM at the winter wheat crop field to estimate soil moisture. This study investigated the use of NDVI as vegetation descriptors in the WCM with an assumption of constant surface roughness over the crop in the growing period. This method will help manage water resources better and precisely estimate irrigation water requirements at the range of scales. Their findings have made significant contributions to the soil and plant science, agricultural water resources management, hydrologic modeling, and remote sensing.

Abstract

Soil moisture is essential for water resources management, yet accurate information of soil moisture has been a challenge. The major goal was to parametrize the Modified Water Cloud Model (MWCM). The Sentinel-1A data of the winter wheat crop was collected for two weeks. Concurrently, in-situ soil moisture data was collected using Time Domain Reflectometer (TDR). A parametric scheme was used for the retrieval of the VV polarization of Sentinel-1A. The effect of NDVI as a vegetation descriptors (V1 and V2) on total VV backscatter (s0) was analyzed. The calibration showed NDVI has the potential to influence Water Cloud Model (WCM) and vegetation descriptors; hence it is recommended to calibrate the MWCM. The coefficient of determination (R2=0.83) showed a good agreement between observed and estimated soil moisture. Therefore, this approach helps improve soil moisture prediction and can be applied to determine soil moisture more accurately for winter crops, grasses, and pasture lands.

To read the entire article  research, please visit:

HTML Version: https://www.tandfonline.com/doi/full/10.1080/10106049.2020.1783579

PDF Version: https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1783579

Dr. Ram Ray

Ram L. Ray, Ph.D., P.E.
Associate Professor
Raray@pvamu.edu
(936) 261-5094