Scaling, similarity, and the fourth paradigm for hydrology
Christa D. Peters-Lidard (NASA Goddard Space Flight Center)
Martyn Clark (University Corporation for Atmospheric Research)
Luis Samaniego (UZF - Helmholtz Centre for Environmental Research)
Niko E.C. Verhoest (Universiteit Gent)
Tim Van Emmerik (TU Delft - Civil Engineering & Geosciences)
Remko Uijlenhoet (Wageningen University & Research)
Kevin Achieng (University of Wyoming)
Trenton E. Franz (University of Nebraska-Lincoln)
Ross Woods (University of Bristol)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
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.
help_outline