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Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry

Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays,...

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Autores principales: Wei, Haohan, He, Xiufeng, Feng, Yanming, Jin, Shuanggen, Shen, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891779/
https://www.ncbi.nlm.nih.gov/pubmed/31744110
http://dx.doi.org/10.3390/s19224994
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author Wei, Haohan
He, Xiufeng
Feng, Yanming
Jin, Shuanggen
Shen, Fei
author_facet Wei, Haohan
He, Xiufeng
Feng, Yanming
Jin, Shuanggen
Shen, Fei
author_sort Wei, Haohan
collection PubMed
description Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better.
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spelling pubmed-68917792019-12-12 Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry Wei, Haohan He, Xiufeng Feng, Yanming Jin, Shuanggen Shen, Fei Sensors (Basel) Article Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better. MDPI 2019-11-16 /pmc/articles/PMC6891779/ /pubmed/31744110 http://dx.doi.org/10.3390/s19224994 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wei, Haohan
He, Xiufeng
Feng, Yanming
Jin, Shuanggen
Shen, Fei
Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title_full Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title_fullStr Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title_full_unstemmed Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title_short Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry
title_sort snow depth estimation on slopes using gps-interferometric reflectometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891779/
https://www.ncbi.nlm.nih.gov/pubmed/31744110
http://dx.doi.org/10.3390/s19224994
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