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Quantifying sediment transport becomes increasingly important in a wide range of monitoring, river engineering and research applications. Under conditions of high sediment-load and high-discharge these measurements remain an enigmatic challenge in river hydrology. Born from expertise of measuring into active lahars and debris flows, non-invasive and cost-effective seismic methods have been developed at Massey University to obtain high-temporal resolution sediment transport data. These new techniques can be combined with conventional flow gauging and Acoustic Doppler Profiling methods and become highly valuable wherever permanent full catchment data of sediment transport is needed.
The challenge: Real-time measurements of sediment transport in violent sediment-rich floods
Currently, long-duration tests for adapting and customising these methods are underway in a variety of river channel settings in the North Island of New Zealand, including the Whangaehu, Manawatu, Pohangina and Stony River. These tests include calibration of depth-averaged sediment discharge using one-component sensors; calibration of bedload- and suspension load- resolved transport using three-component sensors; as well as customising rugged and ultra low-power data storage, 3G-transmission and flood warning data logger units.
An example of deployment of these techniques is provided by recent work in the Whangaehu catchment (below).
The solution: Using an array of non-invasive, multi-component seismic sensor units to measure sediment transport in dynamic flood situations.
Water and sediment discharge curves can show marked deviation particularly in flood situations. Fast Fourier Transformation of digital 3-component seismic traces can resolve variations in vibrational energy due to river stage, suspended sediment load and sediment transported as bedload. The non-invasive technique provides a powerful tool when conventional methods fail.
Customised sensors with 3G transmitting and alert-enabled data loggers have been developed for fast installation in remote and rugged field applications.
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Last updated on Tuesday 17 April 2018