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A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin
This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distribu...
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Published in: | Hydrology and earth system sciences 2017-09, Vol.21 (9), p.4825-4839 |
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description | This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. The main outcome of this study consists in a new generalizable methodology for implementing a distributed hydrologic model with a high computation cost in an efficient and reliable manner, over a large area with ungauged portions, using global calibration |
doi_str_mv | 10.5194/hess-21-4825-2017 |
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More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. The main outcome of this study consists in a new generalizable methodology for implementing a distributed hydrologic model with a high computation cost in an efficient and reliable manner, over a large area with ungauged portions, using global calibration and a unit hydrograph to replace the routing component.</description><identifier>ISSN: 1607-7938</identifier><identifier>ISSN: 1027-5606</identifier><identifier>EISSN: 1607-7938</identifier><identifier>DOI: 10.5194/hess-21-4825-2017</identifier><language>eng</language><publisher>Katlenburg-Lindau: Copernicus GmbH</publisher><subject>Algorithms ; Atmospheric models ; Basins ; Basins (Geology) ; Calibration ; Climate change ; Climate models ; Computation ; Computational efficiency ; Computer simulation ; Creeks & streams ; Environment models ; Finite element method ; Hydrologic cycle ; Hydrologic models ; Hydrology ; Lake basins ; Lakes ; Mathematical models ; Modelling ; Natural history ; Objective function ; Parameter identification ; Parameter robustness ; Precipitation ; Predictions ; River basins ; Rivers ; Runoff ; Simulation ; Snow ; Soil ; Stream discharge ; Stream flow ; Streamflow ; Unit hydrographs ; Vegetation ; Weather forecasting</subject><ispartof>Hydrology and earth system sciences, 2017-09, Vol.21 (9), p.4825-4839</ispartof><rights>COPYRIGHT 2017 Copernicus GmbH</rights><rights>Copyright Copernicus GmbH 2017</rights><rights>2017. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c511t-584653b8dcc6caad6eae3b8570c238e6c6f94df77f33a86663f3d091485191cc3</citedby><cites>FETCH-LOGICAL-c511t-584653b8dcc6caad6eae3b8570c238e6c6f94df77f33a86663f3d091485191cc3</cites><orcidid>0000-0002-9787-9124 ; 0000-0003-4568-4883</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2414398688/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2414398688?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2102,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Gaborit, Ãtienne</creatorcontrib><creatorcontrib>Fortin, Vincent</creatorcontrib><creatorcontrib>Xu, Xiaoyong</creatorcontrib><creatorcontrib>Seglenieks, Frank</creatorcontrib><creatorcontrib>Tolson, Bryan</creatorcontrib><creatorcontrib>Fry, Lauren M</creatorcontrib><creatorcontrib>Hunter, Tim</creatorcontrib><creatorcontrib>Anctil, François</creatorcontrib><creatorcontrib>Gronewold, Andrew D</creatorcontrib><title>A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin</title><title>Hydrology and earth system sciences</title><description>This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. 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D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin</atitle><jtitle>Hydrology and earth system sciences</jtitle><date>2017-09-28</date><risdate>2017</risdate><volume>21</volume><issue>9</issue><spage>4825</spage><epage>4839</epage><pages>4825-4839</pages><issn>1607-7938</issn><issn>1027-5606</issn><eissn>1607-7938</eissn><abstract>This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. The main outcome of this study consists in a new generalizable methodology for implementing a distributed hydrologic model with a high computation cost in an efficient and reliable manner, over a large area with ungauged portions, using global calibration and a unit hydrograph to replace the routing component.</abstract><cop>Katlenburg-Lindau</cop><pub>Copernicus GmbH</pub><doi>10.5194/hess-21-4825-2017</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-9787-9124</orcidid><orcidid>https://orcid.org/0000-0003-4568-4883</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Atmospheric models Basins Basins (Geology) Calibration Climate change Climate models Computation Computational efficiency Computer simulation Creeks & streams Environment models Finite element method Hydrologic cycle Hydrologic models Hydrology Lake basins Lakes Mathematical models Modelling Natural history Objective function Parameter identification Parameter robustness Precipitation Predictions River basins Rivers Runoff Simulation Snow Soil Stream discharge Stream flow Streamflow Unit hydrographs Vegetation Weather forecasting |
title | A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T08%3A23%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20hydrological%20prediction%20system%20based%20on%20the%20SVS%20land-surface%20scheme:%20efficient%20calibration%20of%20GEM-Hydro%20for%20streamflow%20simulation%20over%20the%20Lake%20Ontario%20basin&rft.jtitle=Hydrology%20and%20earth%20system%20sciences&rft.au=Gaborit,%20%C3%83%C2%89tienne&rft.date=2017-09-28&rft.volume=21&rft.issue=9&rft.spage=4825&rft.epage=4839&rft.pages=4825-4839&rft.issn=1607-7938&rft.eissn=1607-7938&rft_id=info:doi/10.5194/hess-21-4825-2017&rft_dat=%3Cgale_doaj_%3EA507097703%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c511t-584653b8dcc6caad6eae3b8570c238e6c6f94df77f33a86663f3d091485191cc3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1943493764&rft_id=info:pmid/&rft_galeid=A507097703&rfr_iscdi=true |