Modeling the Estuarine Turbidity Maxima of the Columbia River Estuary

Jesse Lopez, Oregon Health and Science University

Photo of Jesse Lopez

A dynamic feature characterized by high concentrations of sediments and strong biological activity, the estuarine turbidity maxima (ETM) plays an integral role in the biogeochemical cycles of the Columbia River estuary. Located at the interface of freshwater and seawater, the ETM migrates nearly in tandem with the salt wedge, varying in intensity and location in response to tidal and river conditions. We are studying the Columbia River ETM with a combination of observations and simulations. Here we present the validation of a 3-D sediment model, which is in development on top of an established circulation model (SELFE). The modeling skill is assessed by comparing retrospective simulations against observations, in particular casts from cruises and high-resolution time series from endurance stations. We also present an analysis of the sensitivity of suspended sediment concentration and grain size distribution within the ETM to the inclusion of flocculating sediment classes. Our results show that the model represents suspended sediment concentrations outside of the ETM accurately and represents the timing and relative intensity of the ETM with moderate skill. Furthermore, our results show that flocculation is not required to create ETM-like conditions, but does improve representation of the concentrations and distribution of sediment classes within the ETM. Future work will include using the sediment model – in coordination with biogeochemical models – to study the role of sediments in estuarine ecosystem services, including provision of habitat to juvenile salmonids. Of ultimate interest is understanding the response of Columbia River estuary sediments – and supported ecosystem services – to climate change, changes in hydropower operations, and navigation improvements.

Abstract Author(s): Jesse Lopez and António M. Baptista NSF Science and Technology Center for Coastal Margin Observation & Prediction (CMOP), Oregon Health & Science University, Portland, Ore.