Proceedings of the U.S. Geological Survey (USGS) Sediment Workshop, February 4-7, 1997

PREDICTING DEPOSITION AND EROSION RATES IN MARINE ENVIRONMENTS

By Rubin, D.M.,
U.S. Geological Survey,
345 Middlefield Rd. MS 999,
Menlo Park, CA 94025

Predicting the rate of deposition and erosion is perhaps the most important practical application of our knowledge of sediment transport. Because deposition and erosion are calculated from gradients in the transport vector, even crude predictions of deposition and erosion require extremely precise quantification of sediment transport into and out of an area. Most work on sediment transport has been conducted in rivers or in laboratory simulations of fluvial flows. The problem is considerably more complicated in marine environments because flow varies in both strength and direction (in response to waves, tides, and storms), grain size varies regionally, and biologic organisms influence sediment cohesiveness and bed roughness. Virtually all existing predictive models of sediment transport are too poor to allow the gradient in transport to be quantified even crudely. The USGS could perform an essential national service by improving the capability to predict rates of sediment transport, deposition, and erosion. Several USGS projects working on specific aspects of marine sediment transport, but a more widespread approach could be expected to make a more rapid advance toward solving this critical problem.

A straightforward approach to the problem of quantifying transport rates is to make simultaneous field measurements of flow conditions and sediment transport. Such data can be used to learn relations between flow and sediment response and can be used to evaluate predictive sediment transport models. This approach has been applied in the field in estuarine, nearshore, shelf, and slope environments (Dingler, 1993; Cacchione et al., 1994, 1995; Jaffe and Rubin, 1996; Noble et al., 1996).

The same approach can be used in laboratory studies utilizing wave tanks to simulate marine flows. The advantage of the lab studies is that more sophisticated instruments such as laser-doppler velocimetry can be used to make high-frequency turbulence measurements. The importance of turbulence in influencing the transport rate has been demonstrated by Nelson et al. (1995a, 1995b).

Although the sediment transport rate is controlled by flow, the relation is often extremely difficult to discern in unsteady flows. Jaffe and Rubin (1996) used nonlinear statistical tools developed by NASA-funded research on sediment bedforms (Rubin, 1992) to quantify the relations between wave-generated flows and sediment transport in the surf zone. Although the correlation between the instantaneous flow velocity and sediment concentration was zero, the nonlinear statistical techniques were able to document a nonlinear relation between sequences of flow velocities and the resulting sediment concentration (Figure 1).

A side benefit of the ability to predict transport rates will be the ability to predict pollutant transport, as is required for major research efforts such as the EPA-funded study of the Palos Verde shelf (Sherwood et al., 1996).

The same relations that can be used to predict regional deposition and erosion can be used locally on bedform surfaces to quantify bedform formation, orientation, and migration (McLean et al., 1996). Because of this similarity, transport models can be tested using sediment bedforms, where the gradient in transport is locally great. Increasing our knowledge of the relation between flow and transport also enables more precise computation of bedform morphology, which will increase the accuracy with which sediment bedforms and sedimentary structures can used as sediment transport and flow indicators (Rubin, 1987; Rubin and Hunter, 1987; Rubin and Ikeda, 1990).

figure 1
Figure 1. Results of input-output modeling of suspended sediment concentration in the surf zone (from Jaffe and Rubin, 1996). Concentration does not mimic the flow, but nevertheless can be predicted from the flow. The best predictions employ nonlinear models using 3.0 seconds of velocity data. The correlation coefficient between predicted and observed concentration is 0.6. For comparison, the correlation between simultaneous values of flow velocity and concentration is zero.

REFERENCES

Cacchione, D.A., Drake, D.E., Ferreira, J.T., and Tate, G.B., 1994, Bottom stress estimates and sand transport on northern California inner continental shelf: Continental Shelf Research, v. 14, p. 1273-1289.

Cacchione, D.A., Drake, D.E., Kayen, R.W., Sternberg, R.W., Kineke, G.C., and Tate, G.B., 1995, Measurements in the bottom boundary layer on the Amazon subaqueous delta: Marine Geology, v. 125, 235-257.

Dingler, 1993, Short-term water and suspended-sediment flucutations in a Louisiana marsh: Coastal Zone 93, p. 220-229.

Jaffe, B.E., and Rubin, D.M., 1996, Using nonlinear forecasting to learn the magnitude and phasing of time-varying sediment suspension in the surf zone: Journal of Geophysical Research Oceans, v. 101, p. 14283-14,296.

McLean, S.R., Nelson, J.M., and Shreve, R.L., 1996, Chapter 10: Flow-sediment interactions in separating flows over bedforms, in Coherent Flow Structures in Open Channels, Wiley, Chichester, 733 p.

Nelson, J.M., Shreve, R.L., Fredsoe, J., Sumer, B.M., and Lodahl, C., 1995b, Bedload transport in oscillatory flow, Eos Transactions, American Geophysical Union, v. 76, p. 263.

Nelson, J.M., Shreve, R.L., McLean, S.R., and Drake, T.G., 1995a, Role of near-bed turbulence structure in bed load transport and bed form mechanics: Water Resources Research, v. 31, p. 2071-2086.

Noble, M. A., K. Kinoshita, L. Rosenfeld. C. Piliskan, F. Schwing, S. Eittreim, 1996, Currents and sediment movement in Monterey Canyon: Sixth annual Monterey Bay Research Symposium, Sanctuary Currents 96, pg 29.

Rubin, D.M., 1987, Cross-bedding, Bedforms, and Paleocurrents: Concepts in Sedimentology and Paleontology, v. 1, SEPM, Tulsa, 187 p.

Rubin, D.M., 1992, Use of forecasting signatures to help distinguish periodicity, randomness, and chaos in ripples and other spatial patterns: Chaos, v. 2, p. 525-535.

Rubin, D.M., and Hunter, R.E., 1987, Bedform alignment in directionally varying flows: Science, v. 237, p. 276-278.

Rubin, D.M., and Ikeda, Hiroshi, 1990, Flume experiments on the alignment of transverse, oblique, and longitudinal dunes in directionally varying flows: Sedimentology, v. 37, p. 673-684.

Sherwood, C.R., Wiberg, P.L., Wheatcroft, R. A., and D. E. Drake, 1996, Long-term fate of waste in an urban coastal ocean: Calculations of DDE concentration in effluent-affected sediment off the Palos Verdes Peninsula: EOS, Transactions, v. 76, no. 3.

AUTOBIOGRAPHY

David M. Rubin is a U.S. Geological Survey sedimentologist in Menlo Park, CA. His research has focused on sediment transport and bedforms. He has worked on dunes in Australia and China, sandstones in the western U.S., and marine sediments in San Francisco Bay, offshore California, Alaska, Tonga, and Western Samoa. He has taught graduate sedimentology courses at Stanford University and UC Santa Cruz. Rubin shares an NSF grant on sediment transport with Jon Nelson (WRD Denver) and Ron Shreve (UCLA), and his work on nonlinear forecasting was supported by a NASA Grant for "Basic Research and Analysis of a Highly Innovative Nature". His contributions in the USGS have been recognized with a G.K. Gilbert Fellowship, the Pacific Marine Geology Best Paper Award, and the Department of Interior Superior Service Award.

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