Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland

ABSTRACT Forecasting of glacier mass balance is important for optimal management of hydrological resources, especially where glacial meltwater constitutes a significant portion of stream flow, as is the case for many rivers in Iceland. In this study, a method was developed and applied to forecast th...

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Published in:Journal of Glaciology
Main Authors: EYTHORSSON, DARRI, GARDARSSON, SIGURDUR M., GUNNARSSON, ANDRI, HRAFNKELSSON, BIRGIR
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2018
Subjects:
Online Access:http://dx.doi.org/10.1017/jog.2018.22
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143018000229
id crcambridgeupr:10.1017/jog.2018.22
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spelling crcambridgeupr:10.1017/jog.2018.22 2024-03-03T08:44:37+00:00 Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland EYTHORSSON, DARRI GARDARSSON, SIGURDUR M. GUNNARSSON, ANDRI HRAFNKELSSON, BIRGIR 2018 http://dx.doi.org/10.1017/jog.2018.22 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143018000229 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology volume 64, issue 244, page 311-320 ISSN 0022-1430 1727-5652 Earth-Surface Processes journal-article 2018 crcambridgeupr https://doi.org/10.1017/jog.2018.22 2024-02-08T08:35:03Z ABSTRACT Forecasting of glacier mass balance is important for optimal management of hydrological resources, especially where glacial meltwater constitutes a significant portion of stream flow, as is the case for many rivers in Iceland. In this study, a method was developed and applied to forecast the summer mass balance of Brúarjökull glacier in southeast Iceland. In the present study, many variables measured in the basin were evaluated, including glaciological snow accumulation data, various climate indices and meteorological measurements including temperature, humidity and radiation. The most relevant single predictor variables were selected using correlation analysis. The selected variables were used to define a set of potential multivariate linear regression models that were optimized by selecting an ensemble of plausible models showing good fit to calibration data. A mass-balance estimate was calculated as a uniform average across ensemble predictions. The method was evaluated using fivefold cross-validation and the statistical metrics Nash–Sutcliffe efficiency, the ratio of the root mean square error to the std dev. and percent bias. The results showed that the model produces satisfactory predictions when forced with initial condition data available at the beginning of the summer melt season, between 15 June and 1 July, whereas less reliable predictions are produced for longer lead times. Article in Journal/Newspaper glacier Iceland Journal of Glaciology Cambridge University Press Nash ENVELOPE(-62.350,-62.350,-74.233,-74.233) Sutcliffe ENVELOPE(-81.383,-81.383,50.683,50.683) Brúarjökull ENVELOPE(-16.157,-16.157,64.682,64.682) Journal of Glaciology 64 244 311 320
institution Open Polar
collection Cambridge University Press
op_collection_id crcambridgeupr
language English
topic Earth-Surface Processes
spellingShingle Earth-Surface Processes
EYTHORSSON, DARRI
GARDARSSON, SIGURDUR M.
GUNNARSSON, ANDRI
HRAFNKELSSON, BIRGIR
Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
topic_facet Earth-Surface Processes
description ABSTRACT Forecasting of glacier mass balance is important for optimal management of hydrological resources, especially where glacial meltwater constitutes a significant portion of stream flow, as is the case for many rivers in Iceland. In this study, a method was developed and applied to forecast the summer mass balance of Brúarjökull glacier in southeast Iceland. In the present study, many variables measured in the basin were evaluated, including glaciological snow accumulation data, various climate indices and meteorological measurements including temperature, humidity and radiation. The most relevant single predictor variables were selected using correlation analysis. The selected variables were used to define a set of potential multivariate linear regression models that were optimized by selecting an ensemble of plausible models showing good fit to calibration data. A mass-balance estimate was calculated as a uniform average across ensemble predictions. The method was evaluated using fivefold cross-validation and the statistical metrics Nash–Sutcliffe efficiency, the ratio of the root mean square error to the std dev. and percent bias. The results showed that the model produces satisfactory predictions when forced with initial condition data available at the beginning of the summer melt season, between 15 June and 1 July, whereas less reliable predictions are produced for longer lead times.
format Article in Journal/Newspaper
author EYTHORSSON, DARRI
GARDARSSON, SIGURDUR M.
GUNNARSSON, ANDRI
HRAFNKELSSON, BIRGIR
author_facet EYTHORSSON, DARRI
GARDARSSON, SIGURDUR M.
GUNNARSSON, ANDRI
HRAFNKELSSON, BIRGIR
author_sort EYTHORSSON, DARRI
title Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
title_short Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
title_full Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
title_fullStr Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
title_full_unstemmed Statistical summer mass-balance forecast model with application to Brúarjökull glacier, South East Iceland
title_sort statistical summer mass-balance forecast model with application to brúarjökull glacier, south east iceland
publisher Cambridge University Press (CUP)
publishDate 2018
url http://dx.doi.org/10.1017/jog.2018.22
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143018000229
long_lat ENVELOPE(-62.350,-62.350,-74.233,-74.233)
ENVELOPE(-81.383,-81.383,50.683,50.683)
ENVELOPE(-16.157,-16.157,64.682,64.682)
geographic Nash
Sutcliffe
Brúarjökull
geographic_facet Nash
Sutcliffe
Brúarjökull
genre glacier
Iceland
Journal of Glaciology
genre_facet glacier
Iceland
Journal of Glaciology
op_source Journal of Glaciology
volume 64, issue 244, page 311-320
ISSN 0022-1430 1727-5652
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1017/jog.2018.22
container_title Journal of Glaciology
container_volume 64
container_issue 244
container_start_page 311
op_container_end_page 320
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