Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling

Simple linear regression models have been widely employed in the analysis of suspended-sediment concentration (SSC) time series from glacierized catchments, although they have many limitations. This paper builds regression models which address these shortcomings and permit inferences concerning the...

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Main Author: Richard Hodgkins
Format: Other Non-Article Part of Journal/Newspaper
Language:unknown
Published: 1999
Subjects:
Online Access:https://figshare.com/articles/journal_contribution/Controls_on_suspended-sediment_transfer_at_a_High-Arctic_glacier_determined_from_statistical_modelling/9485660
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spelling ftloughboroughun:oai:figshare.com:article/9485660 2023-05-15T15:00:44+02:00 Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling Richard Hodgkins 1999-01-01T00:00:00Z https://figshare.com/articles/journal_contribution/Controls_on_suspended-sediment_transfer_at_a_High-Arctic_glacier_determined_from_statistical_modelling/9485660 unknown 2134/3334 https://figshare.com/articles/journal_contribution/Controls_on_suspended-sediment_transfer_at_a_High-Arctic_glacier_determined_from_statistical_modelling/9485660 CC BY-NC-ND 4.0 CC-BY-NC-ND Geology Earth Sciences not elsewhere classified Suspended sediment Arctic Regression Time series Hysteresis Autocorrelation Text Journal contribution 1999 ftloughboroughun 2022-01-01T20:50:56Z Simple linear regression models have been widely employed in the analysis of suspended-sediment concentration (SSC) time series from glacierized catchments, although they have many limitations. This paper builds regression models which address these shortcomings and permit inferences concerning the controls on suspended-sediment transfer from a glacier at 788N in the Svalvard archipelago. A bivariate regression model, deterministically predicting SSC from discharge alone, explained less than 15 per cent of the variance in SSC. A multivariate model, incorporating additional potentially explanatory variables, offered little improvement. Diurnal hysteresis in the data gives rise to quasi-autocorrelation in the residual series from regression models. This was effectively removed by incorporating dummy diurnal variables into the multivariate model. The presence of a first-order autoregressive, stochastic process gives rise to true autocorrelation in the residual series from regression models. This was accommodated by incorporating an ARIMA (1,0,0) term into a multivariate autoregression model. The model-building process yielded a systematic progression in the explanation of variance in SSC, stripping away pattern in the autocorrelation function of the residual series; mean model error was reduced from 54 per cent to 6 per cent. The dependence of SSC on the magnitude of discharge is weak and highly variable, whereas the dependence of current SSC on recent values of SSC, revealed through the stochastic term, is an order of magnitude greater and relatively constant during the melt season. The dominant control on SSC throughout the melt season is therefore short-term sediment availability. The simple and largely unchanging stochastic process generally responsible for generating the observed SSC series implies a simple and unchanging glacier drainage system. Other Non-Article Part of Journal/Newspaper Arctic Loughborough University: Figshare Arctic
institution Open Polar
collection Loughborough University: Figshare
op_collection_id ftloughboroughun
language unknown
topic Geology
Earth Sciences not elsewhere classified
Suspended sediment
Arctic
Regression
Time series
Hysteresis
Autocorrelation
spellingShingle Geology
Earth Sciences not elsewhere classified
Suspended sediment
Arctic
Regression
Time series
Hysteresis
Autocorrelation
Richard Hodgkins
Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
topic_facet Geology
Earth Sciences not elsewhere classified
Suspended sediment
Arctic
Regression
Time series
Hysteresis
Autocorrelation
description Simple linear regression models have been widely employed in the analysis of suspended-sediment concentration (SSC) time series from glacierized catchments, although they have many limitations. This paper builds regression models which address these shortcomings and permit inferences concerning the controls on suspended-sediment transfer from a glacier at 788N in the Svalvard archipelago. A bivariate regression model, deterministically predicting SSC from discharge alone, explained less than 15 per cent of the variance in SSC. A multivariate model, incorporating additional potentially explanatory variables, offered little improvement. Diurnal hysteresis in the data gives rise to quasi-autocorrelation in the residual series from regression models. This was effectively removed by incorporating dummy diurnal variables into the multivariate model. The presence of a first-order autoregressive, stochastic process gives rise to true autocorrelation in the residual series from regression models. This was accommodated by incorporating an ARIMA (1,0,0) term into a multivariate autoregression model. The model-building process yielded a systematic progression in the explanation of variance in SSC, stripping away pattern in the autocorrelation function of the residual series; mean model error was reduced from 54 per cent to 6 per cent. The dependence of SSC on the magnitude of discharge is weak and highly variable, whereas the dependence of current SSC on recent values of SSC, revealed through the stochastic term, is an order of magnitude greater and relatively constant during the melt season. The dominant control on SSC throughout the melt season is therefore short-term sediment availability. The simple and largely unchanging stochastic process generally responsible for generating the observed SSC series implies a simple and unchanging glacier drainage system.
format Other Non-Article Part of Journal/Newspaper
author Richard Hodgkins
author_facet Richard Hodgkins
author_sort Richard Hodgkins
title Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
title_short Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
title_full Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
title_fullStr Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
title_full_unstemmed Controls on suspended-sediment transfer at a High-Arctic glacier, determined from statistical modelling
title_sort controls on suspended-sediment transfer at a high-arctic glacier, determined from statistical modelling
publishDate 1999
url https://figshare.com/articles/journal_contribution/Controls_on_suspended-sediment_transfer_at_a_High-Arctic_glacier_determined_from_statistical_modelling/9485660
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation 2134/3334
https://figshare.com/articles/journal_contribution/Controls_on_suspended-sediment_transfer_at_a_High-Arctic_glacier_determined_from_statistical_modelling/9485660
op_rights CC BY-NC-ND 4.0
op_rightsnorm CC-BY-NC-ND
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