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Earth Science

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Earth Science

Rivers continuously evolve over time and space and are often the key in surficial processes and landscape evolution. Often, the earth and engineering sciences cannot accurately predict morphologic changes in response to alterations imposed on river systems by dams, water withdrawals, and invasive non-native vegetation, among others. However, process-based, distributed modeling supported by accurate information are emerging tools to understand and forecast such changes. Sustainable management of rivers and reservoirs requires substantial enhancement of theoretical and modeling abilities. 

The Center’s research interests in the Earth Sciences focuses on the links between water resources, turbulent flow patterns, rates of erosion and deposition, and river morphodynamics, in interaction with, ecological dynamics over a wide range of spatial and temporal scales. This research approach combines mathematical, computational, and experimental techniques. We want to better understand river systems and reservoirs, as essential features of the landscape that provide natural water resources and habitat for aquatic ecosystems.

The current research efforts follow two main tracks of investigation: 1) autonomous systems applied to water-mediated environments, and 2) Large Eddy Simulation models of turbulence, sediment and riverbed evolution.

Autonomous Systems Applied to Water Mediated Environments

We are developing a method to utilize autonomous boats and unmanned aerial systems (UAS) to study fluvial geomorphology and earth science. Autonomous systems are becoming an alternative to conventional methods of mapping water features or taking bathymetric surveys because they significantly reduce the time of data collection and thus decrease the human power hours required. We are implementing a cost-effective alternative to retrieve submerged topography and quantify water storage in river systems and reservoirs using UAS and multibeam echo-sounding. Under the direction of Dr. Laura Alvarez, CASS engineers and undergraduate research assistants are developing an autonomous boat that utilizes a Pixhawk autopilot system running ArduBoat for mission planning with a multibeam sonar to capture bathymetry measurements in any water body as well as measure velocity and discharge rates in rivers and streams. Additionally, uncrewed aerial vehicles (UAVs) carrying RBG and multispectral cameras can be flown over the water bodies being examined to estimate water depths for extremely shallow areas where the boat is unable to reach using refraction correction algorithms that are being developed. The Structure from Motion (SfM) technique is used to reconstruct the Digital Elevation Models (DEMs) by overlapping multiple 2D image sequences acquired from different viewpoints, such as from the sonar and the camera, and creating a high fidelity map of the terrain of the water body.

The first (top right) and second prototypes (top left) of intelligent autonomous watercraft systems for the observation of geomorphologic processes developed by CASS.
The first (top right) and second prototypes (top left) of intelligent autonomous watercraft systems for the observation of geomorphologic processes developed by CASS. Here, we have a bathymetric map of a reservoir (bottom left) taken with our first prototype coupled with a multibeam echo-sounder (bottom right).


This research is also utilizing innovations in adaptive sampling and machine learning to improve decision making and information compression into intelligent systems for effective and efficient spatial reconnaissance. The research objectives are tackled though computer modeling with real-world observations and then tested in our robotic systems for surveying submerged features under mission time, energy, memory, and global positioning system constraints. These datasets can also serve as secondary data that can be used to construct computational domains and validate physically-based models.

Large Eddy Simulation (LES) Models of Turbulence, Sediment, and Riverbed Evolution

Dr. Alvarez is also investigating the physics of turbulent flows using a physically-based, eddy-resolving model in large-scale rivers. This work builds on the development of one of the first massively parallel, high performance computational model at the river reach scale. This applies Large Eddy Simulation (LES) techniques in which turbulence structures are directly calculated. This type of analysis gives physical insight into the turbulent flow patterns and coherent turbulence structures generated at a free shear layer downstream of flow separation zones.  The results demonstrate that these turbulence structures play a fundamental role in controlling the deposition and erosion rates at the riverbed and banks.  Sharp meanders, channel constrictions, many engineering structures, vegetation, and certain types of bedforms all cause flow separation, secondary circulation, and free shear layers.

One of the gaps in the scientific knowledge of fluvial systems is the low predictive capabilities of some available three and two-dimensional quasi-steady and steady models in complex river settings. This three dimensional, parallelized, turbulence resolving model can capture the instantaneous turbulent structures, sediment transport and geomorphologic changes. Results show realistic predictions of the geomorphologic changes in complex river systems featured by secondary flows and massive flow separation. The final objective is to provide a forecasting research tool to quantify the evolution of river landscapes.

Detached Eddy Simulation of a 1.4-km transect of the Colorado River along Grand Canyon, Arizona. It shows instantaneous contours of Q-criterion displayed by the velocity magnitude taken during 1000 seconds of simulation. This three-dimensional eddy resolving model was developed in the OpenFOAM environment.

Some specific current and future projects related to earth science include:

  • Understanding earth surface processes through utilizing UAS, autonomous boats, and other emerging techniques (echosounders, structure from motion, photogrammetry, etc).
  • Development of autonomous boats for reconnaissance using machine learning
  • Examining the mechanics of turbulence, sediment transport and bed evolution in large scale river systems using Large Eddy Simulation (LES)