Delta evolution and lobe building: the Yellow River fluvial-deltaic system
The Yellow River, China, is an end-member fluvial system as it is characterized by very high suspended sediment concentrations, variable water discharge over annual and decadal timescales, and dramatic anthropogenic influences. In the upper reaches of Lower Yellow River, dams and a sudden decrease in channel slope sequester massive volumes of sediment that have superelevated the channel bed with respect to the floodplain. In the lower reaches of the Lower Yellow River, the unique characteristics of the river combine to produce rapid channel bed aggradation that results in frequent overbank flooding and river avulsion.
My research seeks to advance the science regarding long-term fluvial-deltaic evolution through comprehensive numerical models of the Yellow River and detailed field observation. A broad aim of this research is to forward model delta growth for sustainable river-engineering practices, and therefore there is application to management of deltaic landscapes globally. My research is supported by an NSF Graduate Research Fellowship from 2016-2019. You can learn more about the project at its dedicated website here.
High-concentration flow dynamics: density stratification
Suspended sediment in a river results in density stratification that alters turbulent flow structure, thereby modulating water velocity and sediment transport capacity. However, measurements of such conditions, particularly from natural rivers, are quite limited. The Yellow River, China, has one of the highest sediment loads in the world; moreover, sediment concentration varies by an order of magnitude between base and flood flows, and so this location is ideal for documenting the effects of density stratification on flow. In my research to understand density stratification and high concentration flows, I take advantage of engineered floods—produced by water and sediment release from the Xiaolangdi Reservoir (~1000 km upstream of the river outlet)—to measure water velocity and sediment concentration variation on the lower Yellow River across a range of discharge conditions. Analyses of the data indicate the progressive development of density stratification, based on recorded modulations of both the velocity and concentration profiles. The observed stratification is correlated with additional measured properties of the river system, including local bed grain-size and shear stress, washload fraction, and bed slope. My research is supported by an NSF Graduate Research Fellowship from 2016-2019.
Active learning strategies improve student exam performance, engagement, attitudes, thinking, writing, self-reported participation and interest, and help students become better acquainted with one another. I am committed to using active learning approaches in the classrooms I lead. In particular, I am developing a comprehensive suite of interactive computer-based activities for sedimentology and stratigraphy courses (https://github.com/sededu/sededu). The figure at right is the rivers2stratigraphy (https://github.com/sededu/rivers2stratigraphy) activity, which illustrates basin-scale development of fluvial stratigraphy through adjustments in system kinematics including sandy channel migration and subsidence rates. The activity allows users to change these system properties, so as to drive changing depositional patterns.
 Prince, M. (2004). Does Active Learning Work? A Review of the Research. Journal of Engineering Education, 93(3), 223-231. doi: 10.1002/j.2168-9830.2004.
Drainage divide migration: long-wavelength topographic forcings
The drivers of continental scale drainage divide migration operate at a range of spatiotemporal scales, rendering the interaction of these forcings complex and thus poorly understood. My research utilizes isolated long-wavelength topography synthesized by a low-pass filter, and complemented by the channel metric Χ, provides a novel framework for predicting the direction of divide movement, as well as an estimate of the ultimate divide location. The methodology has been applied in two tectonically diverse settings to evaluate divide migration under the lens of geomorphic evidence that has generated 1) recent controversy over the geodynamic evolution of the Gibraltar Arc and Alboran Sea, and 2) over a century of speculation on the cause and timing of the Eastern North America (Appalachian) drainage divide migration. The result is compelling evidence that argues for the unsteady migration of drainage divides, through basin integration and drainage capture, that organizes major rivers to broad regional-scale landscape gradients.
This research evolved from my undergraduate thesis at Lehigh University under the supervision of Dr. Frank Pazzaglia. Some of my research on this subject was published in 2017 in Basin Research, see the full publication here. A preprint (submission version) can be found here, in accordance with the terms of the license agreement.
Appalachian 150 km filter overlain with contours of calculated total rock deformation (thick gray lines) since 3.5 Ma, resulting from the combined effects of mantle induced dynamic topography and the flexural response of the lithosphere to unloading and loading of sediments across the surface (Moucha & Ruetenik, 2017). Prince et al. (2011) suggest that the Roanoke River (R) will eventually capture the headwaters of the New River (N), causing the actual divide to jump farther west, ultimately approaching or reaching the synthetic divide. This prediction is consistent with patterns of rock deformation (Moucha & Ruetenik, 2017) and calculated χ values in the area, and crudely co-located with the Central Appalachian Anomaly (CAA) tomographically imaged by Schmandt & Lin (2014). Inset shows the record of sediment flux off the Appalachians into the Atlantic passive margin Baltimore Canyon Trough basin (Pazzaglia & Brandon, 1996). The unsteady flux is characterized by pulses in increased sediment deposition that are interpreted to result from large-scale drainage captures that rapidly incise an enlarged Atlantic slope drainage area.