North-Central Section - 50th Annual Meeting - 2016

Paper No. 14-8
Presentation Time: 4:10 PM


PEREIRA, Leticia S.F.1, ANDES, Lisa C.1, COX, Amanda L.1 and WULAMU, Abuduwasiti2, (1)Civil Engineering, Saint Louis University, Saint Louis, MO 63103, (2)Center for Sustainability, Saint Louis University, Saint Louis, MO 63108,

Suspended sediment concentration (SSC) and suspended sediment load (SSL) along the Middle-Mississippi River (MMR) and its tributaries are of significant interest to researchers, engineers, scientists, and water resources managers as sediment erosion, deposition, and transport are fundamental to its geomorphic and ecological condition. Due to the importance of understanding the local sediment budget of the MMR, considerable state and federal funds have been spent to continuously monitor and characterize the spatial and temporal variability of SSC and SSL within the region. A network of continuous monitoring stations along the Mississippi River and its tributaries supply publically-available measurements of SSC, SSL and turbidity that have been used to quantify regional and basin wide sediment transport. Currently, there are 14 gauges that monitor water quality parameters along five rivers that empty into the MMR in the states of Missouri and Illinois. While this network provides relevant information about sediment supply to the Mississippi River from larger tributaries, these stations are many kilometers apart and have discontinuities due to funding limitations related to maintaining such a robust network. The coarse spatial resolution of the monitoring stations and fragmented nature of datasets create large uncertainties in quantification the local sediment budget. Recent advancements of remote sensing technology have led to capabilities to characterize surficial SSC in fluvial environments that can be used to supplement the data gaps in many SSC and SSL time-series at monitoring stations in the region. The objective of this study is to present (1) implementation of regionally-transferable regression model of satellite imagery reflectance and SSC using freely available Landsat imagery and SSC/SSL, and (2) demonstration of the applicability of this model to supplement data gaps of SSC and SSL at the 14 USGS gauge stations along the MMR.