Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed
Hydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Glob...
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ftcopernicus:oai:publications.copernicus.org:hess66873 2023-05-15T14:52:58+02:00 Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed Casson, David R. Werner, Micha Weerts, Albrecht Solomatine, Dimitri 2018-11-30 info:eu-repo/semantics/application/pdf https://doi.org/10.5194/hess-22-4685-2018 https://www.hydrol-earth-syst-sci.net/22/4685/2018/ eng eng info:eu-repo/grantAgreement/EC/FP7/603608 doi:10.5194/hess-22-4685-2018 https://www.hydrol-earth-syst-sci.net/22/4685/2018/ info:eu-repo/semantics/openAccess eISSN: 1607-7938 info:eu-repo/semantics/Text 2018 ftcopernicus https://doi.org/10.5194/hess-22-4685-2018 2019-12-24T09:49:56Z Hydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded meteorological and SWE data may be well suited to improve hydrological assessment and snowpack simulation. To investigate representation of hydrological processes and SWE for application in hydropower operations, global re-analysis datasets covering 1979–2014 from the European Union FP7 eartH2Observe project are applied to global and local conceptual hydrological models. The recently developed Multi-Source Weighted-Ensemble Precipitation (MSWEP) and the WATCH Forcing Data applied to ERA-Interim data (WFDEI) are used to simulate snowpack accumulation, spring snowmelt volume and annual streamflow. The GlobSnow-2 SWE product funded by the European Space Agency with daily coverage from 1979 to 2014 is evaluated against in situ SWE measurement over the local watershed. Results demonstrate the successful application of global datasets for streamflow prediction, snowpack accumulation and snowmelt timing in a snowmelt-driven sub-Arctic watershed. The study was unable to demonstrate statistically significant correlations ( p < 0.05 ) among the measured snowpack, global hydrological model and GlobSnow-2 SWE compared to snowmelt runoff volume or peak discharge. The GlobSnow-2 product is found to under-predict late-season snowpacks over the study area and shows a premature decline of SWE prior to the true onset of the snowmelt. Of the datasets tested, the MSWEP precipitation results in annual SWE estimates that are better predictors of snowmelt volume and peak discharge than the WFDEI or GlobSnow-2. This study demonstrates the operational and scientific utility of the global re-analysis datasets in the sub-Arctic, although knowledge gaps remain in global satellite-based datasets for snowpack representation, for example the relationship between passive-microwave-measured SWE to snowmelt runoff volume. Other/Unknown Material Arctic Copernicus Publications: E-Journals Arctic Hydrology and Earth System Sciences 22 9 4685 4697 |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
language |
English |
description |
Hydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded meteorological and SWE data may be well suited to improve hydrological assessment and snowpack simulation. To investigate representation of hydrological processes and SWE for application in hydropower operations, global re-analysis datasets covering 1979–2014 from the European Union FP7 eartH2Observe project are applied to global and local conceptual hydrological models. The recently developed Multi-Source Weighted-Ensemble Precipitation (MSWEP) and the WATCH Forcing Data applied to ERA-Interim data (WFDEI) are used to simulate snowpack accumulation, spring snowmelt volume and annual streamflow. The GlobSnow-2 SWE product funded by the European Space Agency with daily coverage from 1979 to 2014 is evaluated against in situ SWE measurement over the local watershed. Results demonstrate the successful application of global datasets for streamflow prediction, snowpack accumulation and snowmelt timing in a snowmelt-driven sub-Arctic watershed. The study was unable to demonstrate statistically significant correlations ( p < 0.05 ) among the measured snowpack, global hydrological model and GlobSnow-2 SWE compared to snowmelt runoff volume or peak discharge. The GlobSnow-2 product is found to under-predict late-season snowpacks over the study area and shows a premature decline of SWE prior to the true onset of the snowmelt. Of the datasets tested, the MSWEP precipitation results in annual SWE estimates that are better predictors of snowmelt volume and peak discharge than the WFDEI or GlobSnow-2. This study demonstrates the operational and scientific utility of the global re-analysis datasets in the sub-Arctic, although knowledge gaps remain in global satellite-based datasets for snowpack representation, for example the relationship between passive-microwave-measured SWE to snowmelt runoff volume. |
format |
Other/Unknown Material |
author |
Casson, David R. Werner, Micha Weerts, Albrecht Solomatine, Dimitri |
spellingShingle |
Casson, David R. Werner, Micha Weerts, Albrecht Solomatine, Dimitri Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
author_facet |
Casson, David R. Werner, Micha Weerts, Albrecht Solomatine, Dimitri |
author_sort |
Casson, David R. |
title |
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
title_short |
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
title_full |
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
title_fullStr |
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
title_full_unstemmed |
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed |
title_sort |
global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-arctic watershed |
publishDate |
2018 |
url |
https://doi.org/10.5194/hess-22-4685-2018 https://www.hydrol-earth-syst-sci.net/22/4685/2018/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
eISSN: 1607-7938 |
op_relation |
info:eu-repo/grantAgreement/EC/FP7/603608 doi:10.5194/hess-22-4685-2018 https://www.hydrol-earth-syst-sci.net/22/4685/2018/ |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/hess-22-4685-2018 |
container_title |
Hydrology and Earth System Sciences |
container_volume |
22 |
container_issue |
9 |
container_start_page |
4685 |
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4697 |
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