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Article

Estimation of Snow Depth in the Hindu Kush Himalayas of Afghanistan during Peak Winter and Early Melt Season

1
Department of Environment Bio-Production Engineering, Tokyo University of Agriculture, Tokyo 156-8502, Japan
2
Faculty of Engineering Geology and Mines, Jowzjan University, Jowzjan 1901, Afghanistan
3
National Centre for Geodesy, Indian Institute of Technology Kanpur, Kanpur 208016, India
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(17), 2788; https://doi.org/10.3390/rs12172788
Received: 9 July 2020 / Revised: 21 August 2020 / Accepted: 24 August 2020 / Published: 27 August 2020
(This article belongs to the Special Issue Recent Advances in Cryospheric Sciences)
The Pamir ranges of the Hindu Kush regions in Afghanistan play a substantial role in regulating the water resources for the Middle Eastern countries. Particularly, the snowmelt runoff in the Khanabad watershed is one of the critical drivers for the Amu River, since it is a primary source of available water in several Middle Eastern countries in the off monsoon season. The purpose of this study is to devise strategies based on active microwave remote sensing for the monitoring of snow depth during the winter and the melt season. For the estimation of snow depth, we utilized a multi-temporal C-band (5.405 GHz) Sentinel-1 dual polarimetric synthetic aperture radar (SAR) with a differential interferometric SAR (DInSAR)-based framework. In the proposed approach, the estimated snowpack displacements in the vertical transmit-vertical receive (VV) and vertical transmit-horizonal receive (VH) channels were improved by incorporating modeled information of snow permittivity, and the scale was enhanced by utilizing snow depth information from the available ground stations. Two seasonal datasets were considered for the experiments corresponding to peak winter season (February 2019) and early melt season (March 2019). The results were validated with the available nearest field measurements. A good correlation determined by the coefficient of determination of 0.82 and 0.57, with root mean square errors of 2.33 and 1.44 m, for the peak winter and the early melt season, respectively, was observed between the snow depth estimates and the field measurements. Further, the snow depth estimates from the proposed approach were observed to be significantly better than the DInSAR displacements based on the correlation with respect to the field measurements. View Full-Text
Keywords: DInSAR; dual polarimetric SAR; Sentinel-1; snow depth; snow permittivity DInSAR; dual polarimetric SAR; Sentinel-1; snow depth; snow permittivity
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MDPI and ACS Style

Mahmoodzada, A.B.; Varade, D.; Shimada, S. Estimation of Snow Depth in the Hindu Kush Himalayas of Afghanistan during Peak Winter and Early Melt Season. Remote Sens. 2020, 12, 2788. https://doi.org/10.3390/rs12172788

AMA Style

Mahmoodzada AB, Varade D, Shimada S. Estimation of Snow Depth in the Hindu Kush Himalayas of Afghanistan during Peak Winter and Early Melt Season. Remote Sensing. 2020; 12(17):2788. https://doi.org/10.3390/rs12172788

Chicago/Turabian Style

Mahmoodzada, Abdul B., Divyesh Varade, and Sawahiko Shimada. 2020. "Estimation of Snow Depth in the Hindu Kush Himalayas of Afghanistan during Peak Winter and Early Melt Season" Remote Sensing 12, no. 17: 2788. https://doi.org/10.3390/rs12172788

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