Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan
“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in...
| Main Authors: | , , , , , , |
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| Format: | Article |
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Taylor & Francis
2016
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| Online Access: | https://eprints.nottingham.ac.uk/31975/ |
| _version_ | 1848794309281710080 |
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| author | Mount, Nick J. Maier, Holger R. Toth, Elena Elshorbagy, Amin Solomatine, Dimitri Chang, Fi-John Abrahart, R.J. |
| author_facet | Mount, Nick J. Maier, Holger R. Toth, Elena Elshorbagy, Amin Solomatine, Dimitri Chang, Fi-John Abrahart, R.J. |
| author_sort | Mount, Nick J. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | “Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focussed on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology present for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing; positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and / or data are available to inform the model development process. |
| first_indexed | 2025-11-14T19:14:09Z |
| format | Article |
| id | nottingham-31975 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:14:09Z |
| publishDate | 2016 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-319752020-05-04T20:05:34Z https://eprints.nottingham.ac.uk/31975/ Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan Mount, Nick J. Maier, Holger R. Toth, Elena Elshorbagy, Amin Solomatine, Dimitri Chang, Fi-John Abrahart, R.J. “Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focussed on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology present for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing; positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and / or data are available to inform the model development process. Taylor & Francis 2016 Article PeerReviewed Mount, Nick J., Maier, Holger R., Toth, Elena, Elshorbagy, Amin, Solomatine, Dimitri, Chang, Fi-John and Abrahart, R.J. (2016) Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan. Hydrological Sciences Journal . ISSN 2150-3435 (In Press) Data-driven; Hydrologic modelling; Socio-hydrology; Hypothesis; Conceptual modelling; Knowledge extraction |
| spellingShingle | Data-driven; Hydrologic modelling; Socio-hydrology; Hypothesis; Conceptual modelling; Knowledge extraction Mount, Nick J. Maier, Holger R. Toth, Elena Elshorbagy, Amin Solomatine, Dimitri Chang, Fi-John Abrahart, R.J. Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title | Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title_full | Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title_fullStr | Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title_full_unstemmed | Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title_short | Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan |
| title_sort | data-driven modelling approaches for socio-hydrology: opportunities and challenges within the panta rhei science plan |
| topic | Data-driven; Hydrologic modelling; Socio-hydrology; Hypothesis; Conceptual modelling; Knowledge extraction |
| url | https://eprints.nottingham.ac.uk/31975/ |