Current Research Projects

Incipient motion for particles in 3-D flow environments

Bedload particle movement is controlled by forces acting on a particle that include drag force, lift force, weight force, buoyancy force, and friction forces. The balance between these forces and their associated moments acting on the particle determines whether the particle will be stagnant or transported by the flow. The threshold condition between these two cases is termed incipient motion and is commonly evaluated by the use of a dimensionless shear stress, also known as the Shields parameter. Although predicting incipient motion of sediment is a significant challenge in sedimentology and geomorphology, identifying the value of critical Shields parameter remains crucial for estimating sediment-transport rates as a critical or reference Shields parameter is intrinsic to nearly all empirical formulas for computing sediment-transport rate. Critical Shields parameter values have previously been quantified using one-dimensional (1-D) experimental studies, which do not include three-dimensional (3-D) flow components that are prevalent in rivers. For this study, incipient motion of bedload material in a 3-D flow environment was investigated using a small-scale mobile-bed physical model coupled with Particle Image Velocimetry (PIV) measurements and 3-D numerical modeling. The PIV technique was initially validated for use in quantifying bedload velocities and subsequently used to determine the distribution of bedload velocities in the physical model. Three-dimensional numerical simulations of the physical model were conducted to determine the spatial distribution of bed shear stresses and associated Shields parameters. The range of critical Shields parameters was identified by comparing Shields parameters to observed particle velocities. The influence of local bed slope and grain-size distribution on particle velocities and critical Shields parameters was also investigated.

Mustafa, M.T. (2017). "Quantifying incipient motion of bedload material in 3-D flow environments. Ph.D. dissertation, Saint Louis University, St. Louis, Missouri.

Long-term forecasting of sediment transport and morphological response

US Army Corps of Engineers (USACE) (PI: P Soar at University of Portsmouth), Forecasting Sediment Transport and Morphological Response for River Management, Co-PI.

Working on the development of a new tool for geomorphic assessment

Forecasts river morphology (cross section, bed elevations, grain-size distributions, etc.)
Stochastic accounting for uncertainty of input parameters (e.g., hydrology and grain-size distributions)
Hybrid tool combining hydraulic calculations with geomorphic rules for channel adjustments such as channel widening, incising, sinuosity etc.

Provides:

Range of Plausible outcomes, not just one answer
Broad-scale assessment and strategic-level results
Critical information for planning studies
Insights into ranges of alternative outcomes
Assists with prioritizing reaches where resources can be directed for more detailed investigations

This is a collaborative project with the U.S. Army Corps of Engineers (ERDC), University of Portsmouth, University of Nottingham, and Mendrop Consulting.

Remote sensing of suspended sediment concentrations

Missouri Water Resources Research Center (MoWRRC), Satellite-Imagery Based Method for Water-Quality Monitoring and Sediment Budgeting along the Middle-Mississippi River and Its Tributaries Phase 2, PI: 3/1/17 – 2/28/18.

The Middle-Mississippi River and lower Missouri River provide critical navigation waterways, ecological habitat, and flood conveyance. They are also directly linked to processes affecting the geomorphic and ecological conditions in the lower Mississippi River and Delta. For this study, a method was developed to measure SSC and turbidity along the Middle-Mississippi River and the lower Missouri River using Landsat Imagery. Data from eleven USGS water-quality monitoring stations were used to create a model-development dataset and a model-validation dataset. Concurrent gaging data were identified for available Landsat images to generate the datasets. Surface-reflectance filters were developed to eliminate images with cirrus cloud coverage or vessel traffic. Using the filtered model-development dataset, unique reflectance-SSC and reflectance-turbidity models were developed for three Landsat sensors: Landsat OLI, Landsat 7 ETM+, and Landsat 4-5 TM.

Pereira, L. S. F. (2016). "Landsat imagery based method for characterization of suspended-sediment concentration along the Middle-Mississippi River and Lower Missouri River" Masters thesis, Saint Louis University, St. Louis, Missouri.

Pereira, L.S.F., Andes, L.C., Cox, A.L., and Ghulam, A. (In Press). “Measuring Suspended-Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers using Landsat Data.” Journal of the American Water Resources Association.

Example of Landsat Images used for Analysis

USGS gage station at Thebes, IL

Example application at Missouri and Mississippi River Confluence

List of Current and Past Research Projects at Saint Louis University

Missouri Department of Natural Resources, MoHIC Stream Prioritization for Gage Network Expansion, SLU PI: 2024 – 2026.

U.S. Army Corps of Engineers (USACE ), Improving Data Anomaly Detection and Forecasting in the US Army Corps of Engineers Reservoir Sedimentation Information (RSI) Database, PI: 2023 – 2025.

U.S. Army Corps of Engineers (USACE ), Hindcasting sediment transport and morphological responses to management features in the Lower Mississippi River, SLU PI: 2023 – 2025.

Midwest Water Initiative, Shoal Creek Watershed Restoration Initiative, PI: 2022 – 2023.

U.S. Army Corps of Engineers (USACE ), River Evolution Fast Forward (REFF): Reduced complexity forecasting of long-term morphological adjustment for channel stabilization and restoration projects, SLU PI: 2021 – 2023.

National Science Foundation (NSF), Collaborative Research: River Morphology Data and Analysis Tools (RiverMorph): A Web Platform for Enabling River Morphology Research, SLU PI: 2020 – 2024.

U.S. Army Corps of Engineers (USACE ), Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers' Reservoir Sedimentation Information (RSI) Database, PI: 2020 – 2022.

SLU Presidential Research Fund, Can river sediments sequester nutrient pollution? A pilot study on river nutrient and sediment dynamics to support collaborative research, Co-PI: 2020 – 2021.

Missouri Department of Transportation (MoDOT), Scour Analysis at Missouri Bridges, PI: 2020 – 2023.

U.S. Army Corps of Engineers (USACE ), Future River Analysis and Management Evaluation (FRAME) Tool, SLU PI: 2019 – 2021.

National Concrete Masonry Association Foundation (NCMA), ACB Revetment Systems under High-Velocity Flow Conditions - Design Guidelines, PI: 2018.

Missouri Department of Transportation (MoDOT)/Federal Highway Administration (FHWA), (PI: J Kianfar), 2017 St. Louis Summer Transportation Institute, Co-PI: 2017.

U.S. Army Corps of Engineers (USACE ), Forecasting Sediment Transport and Morphological Response for River Management, SLU PI: 2016 – 2017.

Missouri Department of Transportation (MoDOT), Erosion Control Blanket Workshop Training, PI: 2016 – 2017.

Missouri Department of Transportation (MoDOT)/Federal Highway Administration (FHWA), (PI: J Kianfar), St. Louis Summer Transportation Institute, Co-PI: 2015.

Missouri Department of Transportation (MoDOT), Evaluation of Erosion Control Blanket Properties and Test Criteria, PI: 2015 – 2016.

U. S. Army Corps of Engineers (USACE), Investigation of Similitude and Distortion in Large-Scale versus Small-Scale Movable-Bed Models, PI: 6/1/14 – 1/31/16.

SLU Presidential Research Fund (PRF), Identification of regional sites, data sources, and collaborations to support studies of sustainable river-reservoir systems, PI: 2014 – 2015.

U.S. Bureau of Reclamation (USBR) (PI: C Thornton at Colorado State University), Numerical Modeling of Transverse River Training Structures, Co-PI: 2013 – 2014

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