Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This sit...
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ftdoajarticles:oai:doaj.org/article:a26564b3cd894ab99ac346e5a52a7145 2023-05-15T14:50:08+02:00 Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time Sina Muster William J. Riley Kurt Roth Moritz Langer Fabio Cresto Aleina Charles D. Koven Stephan Lange Annett Bartsch Guido Grosse Cathy J. Wilson Benjamin M. Jones Julia Boike 2019-01-01T00:00:00Z https://doi.org/10.3389/feart.2019.00005 https://doaj.org/article/a26564b3cd894ab99ac346e5a52a7145 EN eng Frontiers Media S.A. https://www.frontiersin.org/article/10.3389/feart.2019.00005/full https://doaj.org/toc/2296-6463 2296-6463 doi:10.3389/feart.2019.00005 https://doaj.org/article/a26564b3cd894ab99ac346e5a52a7145 Frontiers in Earth Science, Vol 7 (2019) permafrost hydrology waterbodies size distribution thermokarst statistical moments Science Q article 2019 ftdoajarticles https://doi.org/10.3389/feart.2019.00005 2022-12-31T12:25:35Z Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km2 (100 m2) to 1 km2. We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the ... Article in Journal/Newspaper Arctic permafrost Thermokarst Directory of Open Access Journals: DOAJ Articles Arctic Frontiers in Earth Science 7 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
permafrost hydrology waterbodies size distribution thermokarst statistical moments Science Q |
spellingShingle |
permafrost hydrology waterbodies size distribution thermokarst statistical moments Science Q Sina Muster William J. Riley Kurt Roth Moritz Langer Fabio Cresto Aleina Charles D. Koven Stephan Lange Annett Bartsch Guido Grosse Cathy J. Wilson Benjamin M. Jones Julia Boike Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
topic_facet |
permafrost hydrology waterbodies size distribution thermokarst statistical moments Science Q |
description |
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km2 (100 m2) to 1 km2. We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the ... |
format |
Article in Journal/Newspaper |
author |
Sina Muster William J. Riley Kurt Roth Moritz Langer Fabio Cresto Aleina Charles D. Koven Stephan Lange Annett Bartsch Guido Grosse Cathy J. Wilson Benjamin M. Jones Julia Boike |
author_facet |
Sina Muster William J. Riley Kurt Roth Moritz Langer Fabio Cresto Aleina Charles D. Koven Stephan Lange Annett Bartsch Guido Grosse Cathy J. Wilson Benjamin M. Jones Julia Boike |
author_sort |
Sina Muster |
title |
Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
title_short |
Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
title_full |
Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
title_fullStr |
Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
title_full_unstemmed |
Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time |
title_sort |
size distributions of arctic waterbodies reveal consistent relations in their statistical moments in space and time |
publisher |
Frontiers Media S.A. |
publishDate |
2019 |
url |
https://doi.org/10.3389/feart.2019.00005 https://doaj.org/article/a26564b3cd894ab99ac346e5a52a7145 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic permafrost Thermokarst |
genre_facet |
Arctic permafrost Thermokarst |
op_source |
Frontiers in Earth Science, Vol 7 (2019) |
op_relation |
https://www.frontiersin.org/article/10.3389/feart.2019.00005/full https://doaj.org/toc/2296-6463 2296-6463 doi:10.3389/feart.2019.00005 https://doaj.org/article/a26564b3cd894ab99ac346e5a52a7145 |
op_doi |
https://doi.org/10.3389/feart.2019.00005 |
container_title |
Frontiers in Earth Science |
container_volume |
7 |
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1766321201177690112 |