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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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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1774715042816589824 |