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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Published in:Remote Sensing
Main Authors: Leonid Gagarin, Qingbai Wu, Andrey Melnikov, Nataliya Volgusheva, Nikita Tananaev, Huijun Jin, Ze Zhang, Vladimir Zhizhin
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Ice
Online Access:https://doi.org/10.3390/rs12040692
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/4/692/ 2023-08-20T04:07:08+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 agris 2020-02-20 application/pdf https://doi.org/10.3390/rs12040692 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs12040692 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 4; Pages: 692 groundwater icing sub-permafrost groundwater supra-permafrost groundwater remote sensing UAV-based photogrammetry Sokolov equations of icing morphometry Southern Yakutia Text 2020 ftmdpi https://doi.org/10.3390/rs12040692 2023-07-31T23:08:31Z 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 1.38·106 m2 and 1.68·106 m2, icing volume, between 1.73·106 m3 and 4.20·106 m3, 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 values. ... Text Ice permafrost Yakutia MDPI Open Access Publishing Remote Sensing 12 4 692
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic groundwater icing
sub-permafrost groundwater
supra-permafrost groundwater
remote sensing
UAV-based photogrammetry
Sokolov equations of icing morphometry
Southern Yakutia
spellingShingle groundwater icing
sub-permafrost groundwater
supra-permafrost groundwater
remote sensing
UAV-based photogrammetry
Sokolov equations of icing morphometry
Southern Yakutia
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
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 1.38·106 m2 and 1.68·106 m2, icing volume, between 1.73·106 m3 and 4.20·106 m3, 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 values. ...
format Text
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 Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12040692
op_coverage agris
genre Ice
permafrost
Yakutia
genre_facet Ice
permafrost
Yakutia
op_source Remote Sensing; Volume 12; Issue 4; Pages: 692
op_relation https://dx.doi.org/10.3390/rs12040692
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12040692
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