Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions
Hydrological models have been widely used to predict runoff in regions with observed discharge data, and regionalization methods have been extensively discussed for providing runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). Great progress has been achieved i...
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ftoslouniv:oai:www.duo.uio.no:10852/82159 2023-05-15T18:40:47+02:00 Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu 2020-12-28T15:51:03Z http://hdl.handle.net/10852/82159 http://urn.nb.no/URN:NBN:no-85077 https://doi.org/10.1016/j.jhydrol.2019.124357 EN eng NFR/274310 http://urn.nb.no/URN:NBN:no-85077 Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu . Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions. Journal of Hydrology. 2020, 582 http://hdl.handle.net/10852/82159 1863585 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Hydrology&rft.volume=582&rft.spage=&rft.date=2020 Journal of Hydrology 582 https://doi.org/10.1016/j.jhydrol.2019.124357 URN:NBN:no-85077 Fulltext https://www.duo.uio.no/bitstream/handle/10852/82159/2/HYDROL31529_R2_yang%2BXue.pdf Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/ CC-BY-NC-ND 0022-1694 Journal article Tidsskriftartikkel Peer reviewed AcceptedVersion 2020 ftoslouniv https://doi.org/10.1016/j.jhydrol.2019.124357 2021-11-17T23:32:19Z Hydrological models have been widely used to predict runoff in regions with observed discharge data, and regionalization methods have been extensively discussed for providing runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). Great progress has been achieved in the field of regionalization in previous studies, in which different hydrological models have been coupled with various regionalization methods. However, different conclusions have been drawn due to the use of different hydrological models, regionalization methods, and study regions. In this study, we assessed the performance of the five most widely used regionalization methods (spatial proximity with parameter averaging option (SP-par), spatial proximity with output averaging option (SP-out), physical similarity with parameter averaging option (Phy-par), physical similarity with output averaging option (Phy-out), and regression methods (PCR)) and four daily rainfall-runoff models (GR4J, WASMOD, HBV and XAJ, with 6, 8, 13, and 17 parameters, respectively) at the same time. Our aim was to evaluate how the performance of the regionalization methods depends on (a) the selection of hydrological models, (b) nonstationary climate conditions, and (c) different climatic regions. This investigation used data from 86 independent catchments evenly distributed throughout Norway, covering three different climate zones (oceanic, continental and polar tundra) according to the Köppen-Geiger classification. The results showed that (a) the SP-out and Phy-out methods performed better than the SP-par and Phy-par for all the hydrological models, and the regression method performed worst in most cases; (b) the difference between the parameter averaging option and the output averaging option is positively related to the number of hydrological model parameters, i.e. the greater the number of parameters, the larger the difference between the two options; (c) the XAJ model with the greatest number of parameters produced the best results in most cases, and models with fewer parameters tend to produce similar performance for the different regionalization methods; (d) models with more parameters displayed larger declines in performance than those with fewer parameters for nonstationary conditions; and (e) clear differences in the performance of the regionalization methods exist among the three climatic regions. This study provides insight into the relationship between the complexity of hydrological models and regionalization methods in cold and seasonally snow-covered regions. Article in Journal/Newspaper Tundra Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Geiger ENVELOPE(-62.900,-62.900,-64.300,-64.300) Norway Journal of Hydrology 582 124357 |
institution |
Open Polar |
collection |
Universitet i Oslo: Digitale utgivelser ved UiO (DUO) |
op_collection_id |
ftoslouniv |
language |
English |
description |
Hydrological models have been widely used to predict runoff in regions with observed discharge data, and regionalization methods have been extensively discussed for providing runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). Great progress has been achieved in the field of regionalization in previous studies, in which different hydrological models have been coupled with various regionalization methods. However, different conclusions have been drawn due to the use of different hydrological models, regionalization methods, and study regions. In this study, we assessed the performance of the five most widely used regionalization methods (spatial proximity with parameter averaging option (SP-par), spatial proximity with output averaging option (SP-out), physical similarity with parameter averaging option (Phy-par), physical similarity with output averaging option (Phy-out), and regression methods (PCR)) and four daily rainfall-runoff models (GR4J, WASMOD, HBV and XAJ, with 6, 8, 13, and 17 parameters, respectively) at the same time. Our aim was to evaluate how the performance of the regionalization methods depends on (a) the selection of hydrological models, (b) nonstationary climate conditions, and (c) different climatic regions. This investigation used data from 86 independent catchments evenly distributed throughout Norway, covering three different climate zones (oceanic, continental and polar tundra) according to the Köppen-Geiger classification. The results showed that (a) the SP-out and Phy-out methods performed better than the SP-par and Phy-par for all the hydrological models, and the regression method performed worst in most cases; (b) the difference between the parameter averaging option and the output averaging option is positively related to the number of hydrological model parameters, i.e. the greater the number of parameters, the larger the difference between the two options; (c) the XAJ model with the greatest number of parameters produced the best results in most cases, and models with fewer parameters tend to produce similar performance for the different regionalization methods; (d) models with more parameters displayed larger declines in performance than those with fewer parameters for nonstationary conditions; and (e) clear differences in the performance of the regionalization methods exist among the three climatic regions. This study provides insight into the relationship between the complexity of hydrological models and regionalization methods in cold and seasonally snow-covered regions. |
format |
Article in Journal/Newspaper |
author |
Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu |
spellingShingle |
Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
author_facet |
Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu |
author_sort |
Yang, Xue |
title |
Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
title_short |
Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
title_full |
Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
title_fullStr |
Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
title_full_unstemmed |
Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
title_sort |
dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions |
publishDate |
2020 |
url |
http://hdl.handle.net/10852/82159 http://urn.nb.no/URN:NBN:no-85077 https://doi.org/10.1016/j.jhydrol.2019.124357 |
long_lat |
ENVELOPE(-62.900,-62.900,-64.300,-64.300) |
geographic |
Geiger Norway |
geographic_facet |
Geiger Norway |
genre |
Tundra |
genre_facet |
Tundra |
op_source |
0022-1694 |
op_relation |
NFR/274310 http://urn.nb.no/URN:NBN:no-85077 Yang, Xue Magnusson, Jan Huang, Shaochun Beldring, Stein Xu, Chong-Yu . Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions. Journal of Hydrology. 2020, 582 http://hdl.handle.net/10852/82159 1863585 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Hydrology&rft.volume=582&rft.spage=&rft.date=2020 Journal of Hydrology 582 https://doi.org/10.1016/j.jhydrol.2019.124357 URN:NBN:no-85077 Fulltext https://www.duo.uio.no/bitstream/handle/10852/82159/2/HYDROL31529_R2_yang%2BXue.pdf |
op_rights |
Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/ |
op_rightsnorm |
CC-BY-NC-ND |
op_doi |
https://doi.org/10.1016/j.jhydrol.2019.124357 |
container_title |
Journal of Hydrology |
container_volume |
582 |
container_start_page |
124357 |
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1766230214384287744 |