Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques
Groundwater icings, typical features of permafrost hydrology, are indicative of hydrothermal interactions between surface and ground waters, and permafrost. Their main morphological parameters, i.e., icing area and volume, are generally estimated with low accuracy. Only scarce field observational da...
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ftdoajarticles:oai:doaj.org/article:ddba7dbb20134ecf97dfd44049191dde 2023-05-15T16:37:34+02:00 Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques Leonid Gagarin Qingbai Wu Andrey Melnikov Nataliya Volgusheva Nikita Tananaev Huijun Jin Ze Zhang Vladimir Zhizhin 2020-02-01T00:00:00Z https://doi.org/10.3390/rs12040692 https://doaj.org/article/ddba7dbb20134ecf97dfd44049191dde EN eng MDPI AG https://www.mdpi.com/2072-4292/12/4/692 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs12040692 https://doaj.org/article/ddba7dbb20134ecf97dfd44049191dde Remote Sensing, Vol 12, Iss 4, p 692 (2020) groundwater icing sub-permafrost groundwater supra-permafrost groundwater remote sensing uav-based photogrammetry sokolov equations of icing morphometry southern yakutia Science Q article 2020 ftdoajarticles https://doi.org/10.3390/rs12040692 2022-12-31T16:19:45Z Groundwater icings, typical features of permafrost hydrology, are indicative of hydrothermal interactions between surface and ground waters, and permafrost. Their main morphological parameters, i.e., icing area and volume, are generally estimated with low accuracy. Only scarce field observational data on icing volume and seasonal development exist to date. Our study evaluates and compares performance of several widely used techniques of icing morphometric estimation, based on field data, collected on a giant Icing #2 in the Samokit River basin, southern Yakutia. Groundwater icing area was estimated by: (a) staking, (b) unmanned aerial vehicle (UAV) surveys, and (c) satellite imagery analysis. Icing #2 area in late February was between 1.38·10 6 m 2 and 1.68·10 6 m 2 , icing volume, between 1.73·10 6 m 3 and 4.20·10 6 m 3 , depending on the technique used. Staking is the least accurate, but also the only direct technique, which is hence used as a baseline tool in our study. Staking-based assessment of icing morphometry is the most conservative, while UAV-based estimates of icing area are higher by 14% to 17%, and of icing volume, by 74% to 142%, compared to staking. The latter appears, in our case, to be the least accurate method, although a direct one. It requires a sufficient number of staking points and transects, which should be set up to represent all icing zones, i.e., channel branches and alluvial islands. Photogrammetry based on UAV surveys has numerous advantages, i.e., higher precision of a per pixel icing volume calculation, based on an ice-free valley bottom digital surface model (DSM), and potential reusability of a resulting DSM. However, positioning precision suffers from the overlay of multiple flyovers required because of battery replacements, and, in our case, an insufficient number of ground control points. Satellite imagery along with B.L. Sokolov’s empirical approach were used to estimate the annual maximum icing area and volume, and the empirical estimates tend to converge to satellite-based ... Article in Journal/Newspaper Ice permafrost Yakutia Directory of Open Access Journals: DOAJ Articles Remote Sensing 12 4 692 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
groundwater icing sub-permafrost groundwater supra-permafrost groundwater remote sensing uav-based photogrammetry sokolov equations of icing morphometry southern yakutia Science Q |
spellingShingle |
groundwater icing sub-permafrost groundwater supra-permafrost groundwater remote sensing uav-based photogrammetry sokolov equations of icing morphometry southern yakutia Science Q Leonid Gagarin Qingbai Wu Andrey Melnikov Nataliya Volgusheva Nikita Tananaev Huijun Jin Ze Zhang Vladimir Zhizhin Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
topic_facet |
groundwater icing sub-permafrost groundwater supra-permafrost groundwater remote sensing uav-based photogrammetry sokolov equations of icing morphometry southern yakutia Science Q |
description |
Groundwater icings, typical features of permafrost hydrology, are indicative of hydrothermal interactions between surface and ground waters, and permafrost. Their main morphological parameters, i.e., icing area and volume, are generally estimated with low accuracy. Only scarce field observational data on icing volume and seasonal development exist to date. Our study evaluates and compares performance of several widely used techniques of icing morphometric estimation, based on field data, collected on a giant Icing #2 in the Samokit River basin, southern Yakutia. Groundwater icing area was estimated by: (a) staking, (b) unmanned aerial vehicle (UAV) surveys, and (c) satellite imagery analysis. Icing #2 area in late February was between 1.38·10 6 m 2 and 1.68·10 6 m 2 , icing volume, between 1.73·10 6 m 3 and 4.20·10 6 m 3 , depending on the technique used. Staking is the least accurate, but also the only direct technique, which is hence used as a baseline tool in our study. Staking-based assessment of icing morphometry is the most conservative, while UAV-based estimates of icing area are higher by 14% to 17%, and of icing volume, by 74% to 142%, compared to staking. The latter appears, in our case, to be the least accurate method, although a direct one. It requires a sufficient number of staking points and transects, which should be set up to represent all icing zones, i.e., channel branches and alluvial islands. Photogrammetry based on UAV surveys has numerous advantages, i.e., higher precision of a per pixel icing volume calculation, based on an ice-free valley bottom digital surface model (DSM), and potential reusability of a resulting DSM. However, positioning precision suffers from the overlay of multiple flyovers required because of battery replacements, and, in our case, an insufficient number of ground control points. Satellite imagery along with B.L. Sokolov’s empirical approach were used to estimate the annual maximum icing area and volume, and the empirical estimates tend to converge to satellite-based ... |
format |
Article in Journal/Newspaper |
author |
Leonid Gagarin Qingbai Wu Andrey Melnikov Nataliya Volgusheva Nikita Tananaev Huijun Jin Ze Zhang Vladimir Zhizhin |
author_facet |
Leonid Gagarin Qingbai Wu Andrey Melnikov Nataliya Volgusheva Nikita Tananaev Huijun Jin Ze Zhang Vladimir Zhizhin |
author_sort |
Leonid Gagarin |
title |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
title_short |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
title_full |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
title_fullStr |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
title_full_unstemmed |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques |
title_sort |
morphometric analysis of groundwater icings: intercomparison of estimation techniques |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12040692 https://doaj.org/article/ddba7dbb20134ecf97dfd44049191dde |
genre |
Ice permafrost Yakutia |
genre_facet |
Ice permafrost Yakutia |
op_source |
Remote Sensing, Vol 12, Iss 4, p 692 (2020) |
op_relation |
https://www.mdpi.com/2072-4292/12/4/692 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs12040692 https://doaj.org/article/ddba7dbb20134ecf97dfd44049191dde |
op_doi |
https://doi.org/10.3390/rs12040692 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
4 |
container_start_page |
692 |
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1766027862885793792 |