Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland

The benefits of fractional snow cover area, as an additional dataset for calibration, were evaluated for an Icelandic catchment with a low degree of glaciation and limited data. For this purpose, a Hydrological Projections for the Environment (HYPE) model was calibrated for the Geithellnaá catchment...

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Published in:Water
Main Authors: Julia de Niet, David Christian Finger, Arvid Bring, David Egilson, David Gustafsson, Zahra Kalantari
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/w12040975
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spelling ftmdpi:oai:mdpi.com:/2073-4441/12/4/975/ 2023-08-20T04:04:40+02:00 Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland Julia de Niet David Christian Finger Arvid Bring David Egilson David Gustafsson Zahra Kalantari agris 2020-03-30 application/pdf https://doi.org/10.3390/w12040975 EN eng Multidisciplinary Digital Publishing Institute Water Resources Management, Policy and Governance https://dx.doi.org/10.3390/w12040975 https://creativecommons.org/licenses/by/4.0/ Water; Volume 12; Issue 4; Pages: 975 glaciated-catchment modeling conceptual hydrological model multi-dataset calibration Hydrological Predictions for the Environment Geithellnaá Iceland Text 2020 ftmdpi https://doi.org/10.3390/w12040975 2023-07-31T23:18:23Z The benefits of fractional snow cover area, as an additional dataset for calibration, were evaluated for an Icelandic catchment with a low degree of glaciation and limited data. For this purpose, a Hydrological Projections for the Environment (HYPE) model was calibrated for the Geithellnaá catchment in south-east Iceland using daily discharge (Q) data and satellite-retrieved MODIS snow cover (SC) images, in a multi-dataset calibration (MDC) approach. By comparing model results using only daily discharge data with results obtained using both datasets, the value of SC data for model calibration was identified. Including SC data improved the performance of daily discharge simulations by 7% and fractional snow cover area simulations by 11%, compared with using only the daily discharge dataset (SDC). These results indicate that MDC improves the overall performance of the HYPE model, confirming previous findings. Therefore, MDC could improve discharge simulations in areas with extra sources of uncertainty, such as glaciers and snow cover. Since the change in fractional snow cover area was more accurate when MDC was applied, it can be concluded that MDC would also provide more realistic projections when calibrated parameter sets are extrapolated to different situations. Text Arctic Iceland MDPI Open Access Publishing Arctic Water 12 4 975
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic glaciated-catchment modeling
conceptual hydrological model
multi-dataset calibration
Hydrological Predictions for the Environment
Geithellnaá
Iceland
spellingShingle glaciated-catchment modeling
conceptual hydrological model
multi-dataset calibration
Hydrological Predictions for the Environment
Geithellnaá
Iceland
Julia de Niet
David Christian Finger
Arvid Bring
David Egilson
David Gustafsson
Zahra Kalantari
Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
topic_facet glaciated-catchment modeling
conceptual hydrological model
multi-dataset calibration
Hydrological Predictions for the Environment
Geithellnaá
Iceland
description The benefits of fractional snow cover area, as an additional dataset for calibration, were evaluated for an Icelandic catchment with a low degree of glaciation and limited data. For this purpose, a Hydrological Projections for the Environment (HYPE) model was calibrated for the Geithellnaá catchment in south-east Iceland using daily discharge (Q) data and satellite-retrieved MODIS snow cover (SC) images, in a multi-dataset calibration (MDC) approach. By comparing model results using only daily discharge data with results obtained using both datasets, the value of SC data for model calibration was identified. Including SC data improved the performance of daily discharge simulations by 7% and fractional snow cover area simulations by 11%, compared with using only the daily discharge dataset (SDC). These results indicate that MDC improves the overall performance of the HYPE model, confirming previous findings. Therefore, MDC could improve discharge simulations in areas with extra sources of uncertainty, such as glaciers and snow cover. Since the change in fractional snow cover area was more accurate when MDC was applied, it can be concluded that MDC would also provide more realistic projections when calibrated parameter sets are extrapolated to different situations.
format Text
author Julia de Niet
David Christian Finger
Arvid Bring
David Egilson
David Gustafsson
Zahra Kalantari
author_facet Julia de Niet
David Christian Finger
Arvid Bring
David Egilson
David Gustafsson
Zahra Kalantari
author_sort Julia de Niet
title Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
title_short Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
title_full Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
title_fullStr Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
title_full_unstemmed Benefits of Combining Satellite-Derived Snow Cover Data and Discharge Data to Calibrate a Glaciated Catchment in Sub-Arctic Iceland
title_sort benefits of combining satellite-derived snow cover data and discharge data to calibrate a glaciated catchment in sub-arctic iceland
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/w12040975
op_coverage agris
geographic Arctic
geographic_facet Arctic
genre Arctic
Iceland
genre_facet Arctic
Iceland
op_source Water; Volume 12; Issue 4; Pages: 975
op_relation Water Resources Management, Policy and Governance
https://dx.doi.org/10.3390/w12040975
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/w12040975
container_title Water
container_volume 12
container_issue 4
container_start_page 975
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