(Sediment) Accounting 101: An Example

Charles Podolak
Johns Hopkins University, Geography Environmental Engineering

Jon Major, Mackenzie Keith, Jim O'Connor, Rose Wallick
US Geological Survey

Author Profile

Shortcut URL: https://serc.carleton.edu/39732

Location

Continent: North America
Country: United States
State/Province:Oregon
City/Town: Sandy
UTM coordinates and datum: 10N 567913 5027715 (NAD83)

Setting

Climate Setting: Humid
Tectonic setting: Continental Arc
Type: Process, Computation











Description

I. Introduction

Rivers transport both water and sediment [rock fragments such as sand and gravel] from hillsides to the oceans. As sediment moves downstream it creates river bars, accumulates into floodplains, and often forms the bed of a river itself. One way to track the movement of sediment in a particular area is through a sediment budget. This is an expression of the conservation of mass for a reach [portion] of river, in which the difference between the sediment fluxes [rate of flow through a surface] into and out of the reach are balanced by a change in the mass of sediment stored within the reach. A sediment budget is not unlike a piggy bank--the change in value (storage) is determined by the difference between deposits (flux in) and withdrawals (flux out). An example of the application of a sediment budget comes from the 2007 removal of the Marmot Dam from the Sandy River, Oregon (described in the vignette titled An Example of One River's Response to a Large Dam Removal). The budget is presented here to provide a brief overview of the data collection and synthesis used in the construction of a sediment budget.

II. Changes in Storage

a. Remote Sensing

To calculate changes in sediment storage, measurements of topography were made at multiple points in time using several instruments. Airborne LiDAR [Light Detection And Ranging] is a method of collecting large amounts of topographic data from a landscape using a laser system. An airborne platform flies multiple 'swaths' across the area of interest from an altitude of several hundred meters. By using records of the aircraft's GPS [Global Positioning System] location, the angle of the laser, and the time for the laser pulses to return to the aircraft, a set of spatial coordinates for the surface of interest is generated. For the Sandy River, there were multiple pre- and post-dam-removal LiDAR flights flown from 10 km upstream to 48 km downstream of the dam, measuring at least 2 km on either side of the river (Figure 1 shows a portion of the data collected).

b. Ground Surveys

In order to measure bathymetry [underwater topography], two types of ground surveys with different methods of selecting points were made (Figure 2). The first type was a cross-section-based survey using fixed reference points, allowing comparisons from one survey to the next. Points were selected along each cross section so as to define the channel geometry. This type of survey resulted in an average point density of one point every 2.4 m for cross sections spaced an average of 13 m apart (on a river with a width of 20-40 m). The second type of survey involved tracing features of geomorphic significance such as tops of banks, channel thalweg [path of the deepest flow], and the water's edge. Cross section surveys were repeated annually from 2005 through 2009, while the topographic surveys were opportunistic and based on the occurrence of large storms and the low-water season.

c. Volume calculation

Spatial coordinates from LiDAR and ground surveys were interpolated to create digital elevation models [DEM]. Topography changes (height and volume differences) between surveys were identified by subtracting respective DEMs. A 5-km-long reach approximately centered on the dam site was mapped using a combination of ground surveys and LiDAR, then values of sediment erosion and deposition, reflecting the spatial and temporal changes in storage, were derived (Figure 1).

d. Grain Size

In addition to measuring channel shape, the channel-bed texture (or grain size distribution [GSD] of the bed material) was measured. Because different grain sizes (for example sand [0.0625-2 mm] and gravel [2-64 mm]) interact with the river bed differently, the budget accounted for various size classes separately. Two types of grain size measurements were made. First, facies [areas perceived to have the same GSD] on the bed surface were mapped, and a pebble count [size measurements of a random sample of grains from the surface] was conducted. Second, a bulk sample (Figure 3) involved excavating a pit, then sieving and weighing the excavated sediment (1500-2500 kg). The results (Figure 3c) show armoring [a surface layer coarser than the subsurface layer] and a pebble count (GSD by area) that differs slightly from the surface bulk sample (GSD by weight), both of which are typical findings when comparing GSD computed from bulk samples and pebble counts.

III. Sediment Fluxes

The other part of the budget is the measurement of fluxes in and out of the reach. The bed of the Sandy River is composed primarily of sand and gravel. Bed material moves down the river both as suspended load [carried in suspension throughout the water column] and bedload [moving in near-continuous contact with the bed surface]. On the Sandy River, the high-discharge flows that move most of the bedload occur throughout the winter. Samples were taken during most of the high-flow events for the first two winters following the dam removal at multiple locations along the river (Figure 4) which allowed measurements of sediment moving into and out of the dam area. At each site, suspended sediment and bedload samples were collected concurrently with measurements of water discharge to produce paired values of sediment flux and water discharge. A regression curve was fit to the discharge / sediment transport relationship (Figure 4D) at each site. This regression relationship [rating curve] was used with a continuous record of water discharge at each site to calculate the annual sediment load at each site.

IV. Putting it all Together--A Balancing Act

A sediment budget for one reach encompassing Marmot Dam shows the increase in sediment flux due to the dam removal and the deposition of the sediment downstream of the dam (Figure 5). The sediment budget approach together with the monitoring data proved to be an effective way to measure the fate of the sediment released by the Marmot Dam removal. This study serves as just one example of how various field data can be combined with the simple concept of mass continuity to construct a sediment budget of a particular river reach.

Associated References

  • Diplas, P., Kuhnle, R., Gray, J., Glysson, D., and Edwards, T., 2008, in Garcia, M.H., ed., Sedimentation Engineering--Processes, Measurements, Modeling, and Practice.American Society of Civil Engineers Manuals and Reports on Engineering Practice no. 110, p. 995-1020.
  • Edwards, T.K., and Glysson, G.D., 1999. Field Methods for Measurement of Fluvial Sediment, Techniques of Water-Resource Investigation, USGS Report number 03-C2. available online at: http://pubs.er.usgs.gov/usgspubs/twri/twri03C2
  • Graham Matthews and Associates (GMA), 2008, Sandy River Sediment Transport Monitoring Project, WY 2008 Annual Report, prepared for Sandy River Basin Watershed Council. available online at: http://www/jhu.edu/marmot
  • Harrelson, C.C., Rawlins, C.L., and Potyondy, J.P., Stream Channel Reference Sites: An Illustrated Guide to Field Technique. available online at: http://www.stream.fs.fed.us/publications/documentsStream.html
  • Kondolf, G.M., Lisle, T.E., and Wolman, M.G., 2003. Bed Sediment Measurement, in Tools in Fluvial Geomorphology, edited by G. Kondolf and H. Piégay, pp. 347-395, John Wiley & Sons, Hoboken, NJ, USA.
  • Major, J.J., O'Connor, J.E., Grant. G.E., Spicer, K.R., Bragg, H.M., Rhode, A., Tanner, D.Q., Anderson, C.W., Wallick, J.R., 2008, Initial fluvial response to the removal of Oregon's Marmot Dam: EOS, Transactions American Geophysical Union, v. 89, no. 27, p. 241-242. available online at: http://www.agu.org/pubs/crossref/2008/2008EO270001.shtml
  • Notebaert, B., Verstraeten, G., Govers, G., and Poesen, J., 2009, Qualitative and Quantitative Applications of LiDAR Imagery in Fluvial Geomorphology, Earth Surface Processes and Landforms, v. 34, p. 217-231.
  • Wolman, M.G, 1954. A Method of Sampling Coarse River-Bed Material, Transactions, American GeophysicalUnion, v. 35, no. 6, p. 951-956.
  • Wooland, J.W., and Colby, J.D., 2002. Spatial Characterization, Resolution, and Volumetric Change of Coastal Dunes using airborne LIDAR: Cape Hatteras, North Carolina, Geomorphology, v 48, p. 269-287.
  • Young, A.P., and Ashford, S.A., 2006. Application of Airborne LIDAR to Seacliff Volumetric Change and Beach-Sediment Budget Contributions, Journal of Coastal Research, v. 22, no. 2, p. 307-318.
Marmot Dam Websites:
  • Johns Hopkins University/National Center for Earth-surface Dynamics: http://www.jhu.edu/marmot/
  • US Geological Survey: http://or.water.usgs.gov/projs_dir/marmot/index.html