Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications
Study region: Lake Hume in Australia and Harsha Lake in USA. Study focus: Large-scale hydrological models (LSHMs), though important for both scientific and societal reasons, require the representation of many unknown features that influence river system response. However, current model identificatio...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Journal of Hydrology: Regional Studies |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825002150 |
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| author | Ilias G. Pechlivanidis Jude Lubega Musuuza |
| author_facet | Ilias G. Pechlivanidis Jude Lubega Musuuza |
| author_sort | Ilias G. Pechlivanidis |
| collection | DOAJ |
| description | Study region: Lake Hume in Australia and Harsha Lake in USA. Study focus: Large-scale hydrological models (LSHMs), though important for both scientific and societal reasons, require the representation of many unknown features that influence river system response. However, current model identification practices in catchment modelling cannot lead to robust LSHMs for local decision-making. To address this, it is necessary to customise the models by integrating local data and knowledge from various sources (e.g. in-situ and earth observations) and fluxes. We present a framework to customize LSHMs for impactful local applications and showcase this using the global WWH hydrological model as the reference LSHM. New hydrological insights: We present significant improvements in modelling streamflow and actual and potential evapotranspiration, following WWH refinements to include local lakes and reservoir management. Local streamflow measurements and earth observations from NASA MODIS evapotranspiration products were used to re-calibrate the locally adapted model, leading to spatial consistency in performance. Combining multiple variables and metrics during model identification improved streamflow performance and robustness, with combination sets reducing variability and enhancing representation of diverse hydrological processes, highlighting the need for tailored metric and variable selection. This underpins the importance of including informative data in customized multi-objective modelling chains. Finally, incorporating reservoir management improved simulation of a regulated system, with local insights informing reservoir parameterization in LSHMs and bridging the gap to global-scale applications. |
| format | Article |
| id | doaj-art-0275a4d19ba9425a929f2cf4c32e016d |
| institution | OA Journals |
| issn | 2214-5818 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-0275a4d19ba9425a929f2cf4c32e016d2025-08-20T01:55:31ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-06-015910239010.1016/j.ejrh.2025.102390Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applicationsIlias G. Pechlivanidis0Jude Lubega Musuuza1Corresponding author.; Swedish Meteorological and Hydrological Institute, Norrköping, SwedenSwedish Meteorological and Hydrological Institute, Norrköping, SwedenStudy region: Lake Hume in Australia and Harsha Lake in USA. Study focus: Large-scale hydrological models (LSHMs), though important for both scientific and societal reasons, require the representation of many unknown features that influence river system response. However, current model identification practices in catchment modelling cannot lead to robust LSHMs for local decision-making. To address this, it is necessary to customise the models by integrating local data and knowledge from various sources (e.g. in-situ and earth observations) and fluxes. We present a framework to customize LSHMs for impactful local applications and showcase this using the global WWH hydrological model as the reference LSHM. New hydrological insights: We present significant improvements in modelling streamflow and actual and potential evapotranspiration, following WWH refinements to include local lakes and reservoir management. Local streamflow measurements and earth observations from NASA MODIS evapotranspiration products were used to re-calibrate the locally adapted model, leading to spatial consistency in performance. Combining multiple variables and metrics during model identification improved streamflow performance and robustness, with combination sets reducing variability and enhancing representation of diverse hydrological processes, highlighting the need for tailored metric and variable selection. This underpins the importance of including informative data in customized multi-objective modelling chains. Finally, incorporating reservoir management improved simulation of a regulated system, with local insights informing reservoir parameterization in LSHMs and bridging the gap to global-scale applications.http://www.sciencedirect.com/science/article/pii/S2214581825002150Large-scale hydrological modellingHydrological model customizationLocal applicationsWater resources managementLocal data and knowledge |
| spellingShingle | Ilias G. Pechlivanidis Jude Lubega Musuuza Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications Journal of Hydrology: Regional Studies Large-scale hydrological modelling Hydrological model customization Local applications Water resources management Local data and knowledge |
| title | Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications |
| title_full | Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications |
| title_fullStr | Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications |
| title_full_unstemmed | Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications |
| title_short | Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications |
| title_sort | customizing large scale hydrological models harnessing the open data realm for impactful local applications |
| topic | Large-scale hydrological modelling Hydrological model customization Local applications Water resources management Local data and knowledge |
| url | http://www.sciencedirect.com/science/article/pii/S2214581825002150 |
| work_keys_str_mv | AT iliasgpechlivanidis customizinglargescalehydrologicalmodelsharnessingtheopendatarealmforimpactfullocalapplications AT judelubegamusuuza customizinglargescalehydrologicalmodelsharnessingtheopendatarealmforimpactfullocalapplications |