Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/116557
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Type: Journal article
Title: Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan
Author: Mount, N.
Maier, H.
Toth, E.
Elshorbagy, A.
Solomatine, D.
Chang, F.
Abrahart, R.
Citation: Hydrological Sciences Journal, 2016; 61(7):1192-1208
Publisher: Taylor & Francis
Issue Date: 2016
ISSN: 0262-6667
2150-3435
Statement of
Responsibility: 
N.J. Mount, H.R. Maier, E. Toth, A. Elshorbagy, D. Solomatine, F.-J. Chang and R.J. Abrahart
Abstract: “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 focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents 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.
Keywords: Data-driven; hydrologic modelling; socio-hydrology; hypothesis; conceptual modelling; knowledge extraction
Rights: © 2016 IAHS
RMID: 0030046881
DOI: 10.1080/02626667.2016.1159683
Appears in Collections:Geology & Geophysics publications

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