Echo grid integration: a novel method for preprocessing multibeam water column data to quantify underwater gas bubble emissions
Urban, P.; Veloso-Alarcón, M.E.; Greinert, J. (2023). Echo grid integration: a novel method for preprocessing multibeam water column data to quantify underwater gas bubble emissions. Limnol. Oceanogr., Methods 21(7): 377-400. https://dx.doi.org/10.1002/lom3.10552 In: Limnology and Oceanography: Methods. American Society of Limnology and Oceanography: Waco, Tex.. ISSN 1541-5856; e-ISSN 1541-5856, more |   |
| Abstract | Water column imaging multibeam echo sounder systems (MBESs) are a promising technology for quantitative estimates of the gas bubble volume flow within large gas seepage areas. Considerable progress has been made in recent years toward applicable calibration methods for MBESs as well as developing inversion models to convert acoustically measured backscattering cross sections to gas bubble volume flow. However, MBESs are still not commonly used for quantitative gas flow assessments. A reason for this is the absence of published processing methods that demonstrate how MBES data can be processed to quantitatively represent bubble streams. Here, we present a novel method (echo grid integration) that allows for assessing the aggregated backscattering cross section of targets within horizontal water layers. This derived value enables quantifying bubble stream gas flow rates using existing acoustic inversion methods. The presented method is based on averaging geo-referenced volume backscattering coefficients onto a high-resolution 3D voxel-grid. The results are multiplied with the voxel volume to represent measurements of the total backscattering cross-section within each voxel cell. Individual gridded values cannot be trusted because the beam pattern effects cause the values of individual targets to “smear” over multiple grid-cells. The true aggregated backscattering cross-section is thus estimated as the integral over the grid-cells affected by this smearing. Numerical simulation of MBES data acquisition over known targets assesses the method's validity and quantify it's uncertainty for different, realistic scenarios. The found low measurement bias (< 1%), and dispersion (< 5%) are promising for application in gas flow quantification methods. |
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