Performance evaluation of global hydrological models in six large Pan-Arctic watersheds
International audience Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model pe...
Published in: | Climatic Change |
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Main Authors: | , , , , , , , , , , , , , , |
Other Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2020
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Online Access: | https://hal.archives-ouvertes.fr/hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835/document https://hal.archives-ouvertes.fr/hal-03047835/file/G%C3%A4deke2020_Article_PerformanceEvaluationOfGlobalH.pdf https://doi.org/10.1007/s10584-020-02892-2 |
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openpolar |
institution |
Open Polar |
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Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
language |
English |
topic |
Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology |
spellingShingle |
Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology Gädeke, Anne Krysanova, Valentina Aryal, Aashutosh Chang, Jinfeng Grillakis, Manolis Hanasaki, Naota Koutroulis, Aristeidis Pokhrel, Yadu Satoh, Yusuke Schaphoff, Sibyll Müller Schmied, Hannes Stacke, Tobias Tang, Qiuhong Wada, Yoshihide Thonicke, Kirsten Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
topic_facet |
Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology |
description |
International audience Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. |
author2 |
Potsdam Institute for Climate Impact Research (PIK) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Technical University of Crete Chania National Institute for Environmental Studies (NIES) |
format |
Article in Journal/Newspaper |
author |
Gädeke, Anne Krysanova, Valentina Aryal, Aashutosh Chang, Jinfeng Grillakis, Manolis Hanasaki, Naota Koutroulis, Aristeidis Pokhrel, Yadu Satoh, Yusuke Schaphoff, Sibyll Müller Schmied, Hannes Stacke, Tobias Tang, Qiuhong Wada, Yoshihide Thonicke, Kirsten |
author_facet |
Gädeke, Anne Krysanova, Valentina Aryal, Aashutosh Chang, Jinfeng Grillakis, Manolis Hanasaki, Naota Koutroulis, Aristeidis Pokhrel, Yadu Satoh, Yusuke Schaphoff, Sibyll Müller Schmied, Hannes Stacke, Tobias Tang, Qiuhong Wada, Yoshihide Thonicke, Kirsten |
author_sort |
Gädeke, Anne |
title |
Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
title_short |
Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
title_full |
Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
title_fullStr |
Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
title_full_unstemmed |
Performance evaluation of global hydrological models in six large Pan-Arctic watersheds |
title_sort |
performance evaluation of global hydrological models in six large pan-arctic watersheds |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://hal.archives-ouvertes.fr/hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835/document https://hal.archives-ouvertes.fr/hal-03047835/file/G%C3%A4deke2020_Article_PerformanceEvaluationOfGlobalH.pdf https://doi.org/10.1007/s10584-020-02892-2 |
long_lat |
ENVELOPE(140.917,140.917,-66.742,-66.742) ENVELOPE(161.000,161.000,69.500,69.500) ENVELOPE(-135.000,-135.000,64.282,64.282) |
geographic |
Arctic Jules Kolyma Yukon Yukon Basin |
geographic_facet |
Arctic Jules Kolyma Yukon Yukon Basin |
genre |
Arctic Climate change permafrost Yukon Basin Yukon |
genre_facet |
Arctic Climate change permafrost Yukon Basin Yukon |
op_source |
ISSN: 0165-0009 EISSN: 1573-1480 Climatic Change https://hal.archives-ouvertes.fr/hal-03047835 Climatic Change, Springer Verlag, 2020, 163 (3), pp.1329-1351. ⟨10.1007/s10584-020-02892-2⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10584-020-02892-2 hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835/document https://hal.archives-ouvertes.fr/hal-03047835/file/G%C3%A4deke2020_Article_PerformanceEvaluationOfGlobalH.pdf doi:10.1007/s10584-020-02892-2 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1007/s10584-020-02892-2 |
container_title |
Climatic Change |
container_volume |
163 |
container_issue |
3 |
container_start_page |
1329 |
op_container_end_page |
1351 |
_version_ |
1766319470855323648 |
spelling |
ftunivnantes:oai:HAL:hal-03047835v1 2023-05-15T14:48:24+02:00 Performance evaluation of global hydrological models in six large Pan-Arctic watersheds Gädeke, Anne Krysanova, Valentina Aryal, Aashutosh Chang, Jinfeng Grillakis, Manolis Hanasaki, Naota Koutroulis, Aristeidis Pokhrel, Yadu Satoh, Yusuke Schaphoff, Sibyll Müller Schmied, Hannes Stacke, Tobias Tang, Qiuhong Wada, Yoshihide Thonicke, Kirsten Potsdam Institute for Climate Impact Research (PIK) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Technical University of Crete Chania National Institute for Environmental Studies (NIES) 2020 https://hal.archives-ouvertes.fr/hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835/document https://hal.archives-ouvertes.fr/hal-03047835/file/G%C3%A4deke2020_Article_PerformanceEvaluationOfGlobalH.pdf https://doi.org/10.1007/s10584-020-02892-2 en eng HAL CCSD Springer Verlag info:eu-repo/semantics/altIdentifier/doi/10.1007/s10584-020-02892-2 hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835 https://hal.archives-ouvertes.fr/hal-03047835/document https://hal.archives-ouvertes.fr/hal-03047835/file/G%C3%A4deke2020_Article_PerformanceEvaluationOfGlobalH.pdf doi:10.1007/s10584-020-02892-2 info:eu-repo/semantics/OpenAccess ISSN: 0165-0009 EISSN: 1573-1480 Climatic Change https://hal.archives-ouvertes.fr/hal-03047835 Climatic Change, Springer Verlag, 2020, 163 (3), pp.1329-1351. ⟨10.1007/s10584-020-02892-2⟩ Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology info:eu-repo/semantics/article Journal articles 2020 ftunivnantes https://doi.org/10.1007/s10584-020-02892-2 2022-10-18T23:30:00Z International audience Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. Article in Journal/Newspaper Arctic Climate change permafrost Yukon Basin Yukon Université de Nantes: HAL-UNIV-NANTES Arctic Jules ENVELOPE(140.917,140.917,-66.742,-66.742) Kolyma ENVELOPE(161.000,161.000,69.500,69.500) Yukon Yukon Basin ENVELOPE(-135.000,-135.000,64.282,64.282) Climatic Change 163 3 1329 1351 |