Scaling, similarity, and the fourth paradigm for hydrology

Authors

Chirsta D. Peters-Lidard, NASA Goddard Space Flight CenterFollow
Martyn Clark, National Center for Atmospheric Research
Luis Samaniego, Environmental Research
Niko E. C. Verhoest, Ghent University
Tim van Emmerik, Delft University of Technology
Remko Uijlenhoet, Wageningen University
Kevin Achieng, University of Wyoming
Trenton E. Franz, University of Nebraska-LincolnFollow
Ross Woods, University of Bristol

Document Type

Article

Date of this Version

7-20-2017

Citation

Hydrol. Earth Syst. Sci., 21, 3701–3713, 2017 www.hydrol-earth-syst-sci.net/21/3701/2017/

Comments

Author(s) 2017

Abstract

In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm) and assert that it is time for hydrology to embrace a fourth paradigm of data intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing; describe a mutual information framework for testing these hypotheses; describe boundary condition, state, flux, and parameter data requirements across scales to support testing these hypotheses; and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.