Analyzing and Visualizing Flows in Rivers and Lakes with MATLAB
ADCPs and VMT have increased the pace of studies that rely on flow data. Find out how these toolkits from MathWorks are revolutionizing the analysis and visualisation processes.
Hydrologists and other scientists use acoustic Doppler current profilers (ADCPs) to measure the volume rate of water flow, or discharge, in rivers and other waterways. Discharge measurements are used to predict flooding and low-water conditions. While such measurements are valuable, the data provided by ADCPs can also be used to create a much more detailed picture of the water velocity distribution in a river.
The Velocity Mapping Toolbox (VMT), built in MATLAB®, enables the U.S. Geological Survey (USGS) to rapidly process all the raw data recorded by ADCPs. The result is a better understanding of spatial flow distributions and temporal flow variations, making VMT a valuable tool for a variety of applications. Environmental scientists use it to examine flow distributions around structures near wildlife habitats. Energy companies use it to identify the best position for tidal turbines.
The USGS has used VMT on a variety of projects and studies. For example, they used it to help the U.S. Army Corps of Engineers assess flow distributions at the confluence of the Mississippi and Ohio Rivers so that barges could safely navigate the swollen rivers during the record flooding of 2011. USGS scientists use VMT to study meander bends in rivers and determine where shoreline protection might be needed to prevent erosion, visualize flow in nearshore and rivermouth regions of the Great Lakes to understand contaminant transport and aid beach health studies, and study the capability of Great Lakes tributaries for transport of Asian carp eggs to identify suitable spawning habitats for the invasive species.
VMT and ADCPs have increased the pace of studies that rely on flow data. Before the introduction of the ADCP, researchers used acoustic Doppler velocimeters or mechanical current meters, which sampled one point in the water column instead of the entire water column essentially simultaneously. Teams could spend days taking the flow measurements and months processing the data with spreadsheets. Today, VMT can complete the same analysis within minutes.
Flow data is collected by transecting the river, the stream, or the lake in a boat equipped with an ADCP (Figure 1).
The ADCP transmits sound pulses into the water and processes echoes reflected back from particles moving in the fluid flow (Figure 2).
By determining the Doppler frequency shift of emitted pulses returning to the ADCP, the velocity of the particles can be computed using a priori knowledge of the transducer geometry and trigonometric relationships. As the boat moves, the ADCP records its position using a GPS. Using pulse frequency measurements together with pitch, roll, heading, and positional data, the instrument calculates and records vectors of 3D velocity data for the water column below the instrument. Additionally, the ADCP records depth soundings, the water surface temperature, and acoustic backscatter (the amount of sound reflected by the particles in the water column). With proper calibration, acoustic backscatter can indicate the amount of sediment suspended in the water.
Data collection is an iterative process, with a vertical velocity profile being measured at least once per second, resulting in huge amounts of data. To obtain an accurate measurement of the flow across a body of water, USGS researchers complete multiple transects of the river, each consisting of hundreds to thousands of vertical samples. A vertical sample is represented by a set of vectors that may contain dozens of individual 3D velocity measurements. It is not unusual for a data set for a single large river cross section to contain more than 100,000 data points, and a complete study might require 10 to 30 cross sections.
Developing the Velocity Mapping Toolbox
VMT evolved from MATLAB code developed for past research projects. To allow researchers to process and visualize their own ADCP data, the code behind VMT was modified for general-purpose use. Modifications to the application included adding new features and enhanced functionality for data analysis and visualization. Novel algorithms for aggregating the results from multiple transects were developed using the robust built-in interpolation techniques in MATLAB. By employing Mapping Toolbox™ functionality, VMT is able to produce presentation-quality georeferenced visualizations of measured flow fields—a feature that enables researchers to set their analyses within the context of the physical surroundings where measurements are made.
Top Stories Past 30 Days