August 01, 2019
Riverbed Sediment Types are Key for Understanding Biogeochemical Processes in Watersheds
The use of riverine facies enables more accurate modeling of hydrologic exchange flows and biogeochemical processes.
Scientists produced a map that identifies different classes of sediments that compose the riverbed along the Hanford Reach of the Columbia River. These sediment classes, called facies, have distinct textures that play important roles in surface water/groundwater exchanges and biogeochemical activity.
The riverbed sediments along the Hanford Reach of the Columbia River are strongly heterogeneous, making it challenging to incorporate their complexity in predictive models. This research categorized the sediments into facies to reduce the complexity of this very heterogeneous system into classes with distinct sediment texture that correspond to variations in hydrologic properties. The use of riverine facies thereby enables more accurate modeling of hydrologic exchange flows and biogeochemical processes.
In the Hanford Reach of the Columbia River, the texture of sediments on the riverbed have a strong influence on the exchange of groundwater and surface water greatly influences biogeochemical activity. This layer of sediments is strongly heterogeneous, making it a challenge to model, for example, the impact of increased river flows on biogeochemical activity.
To overcome this type of heterogeneity challenge in subsurface aquifers, researchers often make use of facies, a sediment classification scheme that groups complex geologic materials into a set of discrete classes according to distinguishing features. The facies can then be used to assign heterogenous material properties to grid cells of numerical models of aquifers found in the subsurface.
The usefulness of the facies approach, however, hinges on the ability to relate facies to quantitative properties needed for flow and reactive transport modeling. Previous research has shown that the grain size distribution of sediments in the riverbed is associated with properties of interest to the exchange of groundwater and surface water and related biogeochemical activity. Direct observational data on grain size distribution in the Hanford Reach of the Columbia River, however, is limited to selected locations with inadequate spatial coverage and resolution.
To map facies in the Hanford Reach of the Columbia River, the authors integrated high-resolution observations such as the river geomorphology, depth, slope, and signs of erosion with numerical simulations of historical river flows such as floods that are known to shape sediment texture by washing rocks and pebbles downstream. The team used machine-learning models to determine which factors have the best correspondence with distinct distributions of sediment texture, creating a facies map with four classes of sediment textures that correspond to variations in hydrologic properties.
Identification and mapping of facies in the Hanford Reach of the Columbia River will enable more accurate modeling of the behavior of surface water/groundwater exchanges as well as biogeochemical activity within the system. This understanding will enable more robust predictions of the fate and migration of groundwater contaminant plumes from the Hanford Site as well as the impact of nearby agricultural practices on biogeochemical activity in the river system.
Pacific Northwest National Laboratory
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science and DOE Environmental Molecular Sciences Laboratory
Funding for this research came from the Office of Biological and Environmental Research, within the U.S. Department of Energy (DOE) Office of Science, and Pacific Northwest Laboratory Subsurface Biogeochemical Research SFA.
Hou, Z., Scheibe, TD, Murray, CJ, et al . "Identification and mapping of riverbed sediment facies in the Columbia River through integration of field observations and numerical simulations". Hydrological Processes 33 (8), 1245–59 (2019). https://dx.doi.org/10.1002/hyp.13396,