My research involves environmental fluid mechanics and transport theory applied to problems in geomorphology and hydrology, and the intersection of these fields with ecology. This work combines theoretical, experimental, computational and field-based components aimed at understanding the dynamics of Earth surface systems spanning human to geomorphic time scales. I have taught courses in geology, hydrology and geomorphology, transport processes in Earth and environmental systems, fluid dynamics, and probability and statistics. I view the wonderful process of deep intellectual discovery in simple terms: Thoughtful collaborations with intellectual co-conspirators are essential in moving science forward. But great, lasting ideas often are crazy ideas, and these crazy ideas mostly come from quirky thinking of individuals.
The languages of mathematics and physics are key elements of how I do science. Here are two lessons I have learned:
Mathematics is the purest imaginable friend. It is inveterately demanding, compelling, nuanced and tantalizing. It has everlasting beauty and elegance. It never lies… and it never changes its mind. If you listen carefully, it reveals truth you have not imagined.
Physics, on the other hand, is your undeniably cool, scary-smart brother or sister or crazy uncle who dares you to do crazy stuff… just because it is crazy… as measured by uncrazy undaring standards. Physics lies… and plays games with your head. Physics purposefully leads you down rabbit holes. But when you get it right and it stops lying and works, physics is as beautiful as mathematics.
Our current research is centered on theoretical, experimental and field-based studies of the probabilistic physics of sediment particle motions. It is aimed at clarifying our understanding of the transport and dispersal of sediment and sediment-borne substances in rivers and on hillslopes. In addition to its interesting technical aspects, this work has an important philosophical basis.
Namely, in learning how to describe the behavior of mechanical systems, mostly we are initially exposed to deterministic examples. We study Newton’s laws as these pertain to simple particle systems, and then move on to the behavior of solids and fluids treated as continuous materials. The formalism is unambiguous, and describing the behavior of a well constrained system is in principle straightforward. Indeed, much (although not all) of the legacy of geophysics resides in the determinism of continuum mechanics. Perhaps it is therefore natural that we might envision that a mechanistic description of the behavior of a system implies that such a description ought to be, or perhaps only can be, a deterministic one. Such a perception represents a lost opportunity. The most elegant counterpoint example is the field of classical statistical mechanics — devoted specifically to the probabilistic (i.e., non-deterministic) treatment of the behavior of gas particle systems in order to justify the principles of thermodynamics — yet which is no less mechanical in its conceptualization of this behavior than, say, the application of Newton’s laws to the behavior of a deterministic system consisting of the interactions of a few billiard balls or the players of the solar system, or involving the motion of a Newtonian fluid subject to specific initial and boundary conditions.
Once steeped in the language of mechanics, we understandably take comfort in mechanistic descriptions of system behavior. Specifically, we invest trust in the underlying foundation, and implied rigor, provided by classical mechanics. This is a good thing. But given the complexity and the uncertainty in describing the behavior of sediment systems, here it is essential to consider the idea that the concepts and language of probability are well suited to the problem of describing this behavior — precisely because of the complexity and uncertainty involved — relaxing our expectations that a deterministic-like relationship exists between, say, the flux of bed-load sediment and the fluid stress imposed on the streambed, or the flux of sediment on a hillslope and the local land-surface slope. This idea of leaning on probability to describe the behavior of sediment systems is not as straightforward as describing the behavior of idealized gas particle systems. Nonetheless, the objective is the same: to be mechanistic, yet probabilistic. These world views are entirely compatible.
Within this context, we currently are pursuing work on probabilistic descriptions of bed-load sediment transport within turbulent shear flows. This is mostly centered on detailed experimental measurements of particle motions using high-speed imaging, and PIV measurements of near-bed fluid motions. Our efforts are aimed at probabilistic formulations of transport, including descriptions of particle diffusion (or ‘dispersion’), appealing to methods and techniques of classical statistical mechanics. We also are focusing on the problem of describing effects of patchy, intermittent particle motions that are mostly rarefied — conditions that are at odds with continuum based formulations of transport.
In addition, we are pursuing work on probabilistic formulations of sediment transport on hillslopes. This involves both experiments and field-based measurements to inform theory and computational models of hillslope evolution. In addition to analysis of archived DEM data and descriptions of sediment behavior on a laboratory scale “hillslope,” we are pursuing field-based studies of long hillslopes in the southern Appalachian Mountains, and age-dated glacial moraines on the east side of the Sierra Nevada Mountains. Our efforts are aimed at clarifying the significance of local versus nonlocal sediment transport in steepland topography, including how these styles of transport influence the behavior of two-dimensional topography.
Tyler Doane (Ph.D.) Earth and Environmental Sciences
Eli Schwat (B.A.) Earth and Environmental Sciences
Selected Publications (*Denotes Student Author)
Furbish, D. J., J. J. Roering, P. Almond, and T. H. Doane* (2018), Soil particle
transport and mixing near a hillslope crest: 1. Particle ages and residence
times, Journal of Geophysical Research – Earth Surface. (in press)
Furbish, D. J., J. J. Roering, A. K. Zebert, P. Almond, T. H. Doane*, and R.
Schumer (2018), Soil particle transport and mixing near a hillslope crest: 2.
Cosmogenic nuclide and optically stimulated luminescence tracers, Journal
of Geophysical Research – Earth Surface. (in press)
*Doane, T. H., D. J. Furbish, J. J. Roering, R. Schumer, and D. J. Morgan (2018),
Nonlocal sediment transport on steep lateral moraines, eastern Sierra Nevada,
California, USA, Journal of Geophysical Research – Earth Surface, 123, 187-208, doi: 10.1002/2017JF004325.
Furbish, D. J., S. L. Fathel*, and M. W. Schmeeckle (2017), Particle motions and bed load theory: The entrainment forms of the flux and the Exner equation, in Tsutsumi, D. and Laronne, J. B. (eds.), Gravel-bed Rivers: Processes and Disasters, Wiley-Blackwell, ISBN: 978-1-118-97140-6.
Schumer, R., A. Taloni, and D. J. Furbish (2017), Theory connecting non-local sediment transport, earth surface roughness, and the Sadler effect, Geophysical Research Letters, doi.
Furbish, D. J., S. L. Fathel*, M. W. Schmeeckle, D. J. Jerolmack, and R. Schumer (2016), The elements and richness of particle diffusion during sediment transport at small timescales, Earth Surface Processes and Landforms, doi: 10.1002/esp.4084.
Grieve, S. W. D., S. M. Mudd, D. T. Milodowski, F. J. Clubb, and D. J. Furbish (2016), How does grid-resolution modulate the topographic expression of geomorphic processes?, Earth Surface Dynamics, doi:10.5194/esurf-4-627-2016.
*Fathel, S. L., D. J. Furbish, and M. W. Schmeeckle (2016), Parsing anomalous versus normal diffusive behavior of bed load sediment particles, Earth Surface Processes and Landforms, doi: 10.1002/esp.3994.
Furbish, D. J., M. W. Schmeeckle, R. Schumer, and S. L. Fathel* (2016), Probability distributions of bed-load particle velocities, accelerations, hop distances and travel times informed by Jaynes’s principle of maximum entropy, Journal of Geophysical Research – Earth Surface, doi: 10.1002/2016JF003833.