Inversion of Acoustic Zooplankton Measurement for Adaptive Physical-Biological Ocean Forecast by Bertrand Renard alumnus of Ecole Normale Superieure de Cachan, Agr6gation in Civil Engineering, Technological and Energetical Equipments, 2001 Submitted to the Departments of Ocean Engineering and Material Science and Engineering in Partial Fulfillment of the Requirements for the Degree of Master of Science in Ocean Engineering MASSACHUSETTS INSTiTUTE at the OF TECHNOLOGY Massachusetts Institute of Technology June 2003 AUG 2 5 2003 C 2003 Bertrand Renard LIBRAR IES All rights reserved The author hereby grants MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part. A u th or ................................................................................................. ...... .................................. Bertrand Renard Department of aE ,003 Certified b y ............................................................................ fik Schmidt Professor and Department Head, a Engineering, Chairman, Dept Committee on Graduate Students, Graduat dmissions Officer, d") , I ', ,, Thesis Supervisor Accepted by ........................................................ .......... Michael Triantafyllou Professor of Ocean Engineering Chairman, Departmental Committee on Graduate Studies Room 14-0551 77 Massachusetts Avenue Cambridge, MA 02139 Ph: 617.253.2800 MITLibraries Email: [email protected] Document Services http://Iibraries.mit.edu/docs DISCLAIMER OF QUALITY Due to the condition of the original material, there are unavoidable flaws in this reproduction. We have made every effort possible to provide you with the best copy available. If you are dissatisfied with this product and find it unusable, please contact Document Services as soon as possible. Thank you. The images contained in this document are of the best quality available. This research is performed as part of the Poseidon project, at the Massachusetts Institute of Technology department of Ocean Engineering, in cooperation with the Harvard University department of Earth and Planetary Sciences. Funding for this research was provided by: The National Science Fundation (NSF), via Information Technology Research (ITR), A and by the US Department of Commerce (DOC), via the National Oceanic and Atmospheric Administration (NOAA) and the National Sea Grant program (Sea Grant) as part of the Poseidon project. Principal Investigators: Profs. Nicholas M. Patrikalakis and Henrik Schmidt, Department of Ocean Engineering, Massachusetts Institute of Technology and Profs. Allan R. Robinson and Jim McCarthy, Department of Earth and Planetary Science, Harvard University kTeA2 2 Abstract The Poseidon project is aimed at bringing multi disciplinary oceanographic data together on an Information Technology backbone in real-time, for improved understanding and forecasting. In this framework zooplankton acoustic backscatter is needed for better biology understanding, and can in turn benefit from the input of physical and biological models. Zooplankton backscatter models are subdivided in three categories: fluid-like, hard elastic shells, and gas bladder animals. Zooplankton species neither dominant in number, size or biomass can overwhelm part of the acoustic target strength spectrum, implying a necessary species-specific measurement. Furthermore, the too few high frequencies sampled by available sonars leave the acoustic inversion widely underdetermined. Real data inversion from WHOI's BiomaperlI has provided plankton population estimation comparable to what nets data and counting had recorded. Multiple species acoustic inversion has been demonstrated with the fluid-like and the elastic-shelled model. Purely acoustic field data inversion would require unjustifiable assumptions and lead to unbearable levels of uncertainty, which have always been reduced by cameras and labor-intensive direct tows. While other methods remain necessary to validate large-scale acoustic data, the Poseidon project's adaptive modeling, sampling, and the automatic input of biological information as part of data assimilation could significantly reduce acoustic uncertainty. Other issues addressed are acoustic inversion simulation behavior with various target sizes, the inversion's probabilistic validation, multiple species inversion, bubbles detection, application on WHIIG's BiomaperlI data, sources of error and adaptive modeling. Keywords Zooplankton acoustics, bioacoustics, model inversion, adaptive sampling. 3 Foreword I want to pay a special tribute to my parents for the best gift of all: life. My warmest gratitude goes to my advisor who was always smiling and focused although he had to squeeze me in his tight schedule as department head. For their invaluable criticism, teaching and advice on my research I would like to thank Dr. Andone Lavery, Dr. Tim Stanton, Dr. Peter Wiebe, Prof. James J. McCarthy, Dr. Van Holliday, Prof. Nicholas Patrikalakis, Dr. Pierre Lermusiaux, Dr. Constantinos Evangelinos, Dr. Michele Zanolin, Gareth Lawson, Luiz Souza, Joshua Wilson, Patricia Moreno, Ding Wang and Da Guo. For their help and support: Sabina Rataj, Geoffrey Fox, Kathy de Zengotita, Eda Daniel and Mary Mullowney For their cheering support, allow me to mention my Ocean Engineering friends: Nick (also known as Prof. Nicholas C. Makris), Dr. Purnima Ratilal, Dr. Monica Montanari, Yi-san Lai, Irena Veljkovic, Wenyu Luo, Tianrun Chen, Hwee Min Charles Low, Sunwoong Lee, Travis Poole, Joe Edwards, Andrea Kraay, Jennifer Watson, Ian Ingram; The friends who helped me create the Club Francophone: Olivier Grunberg, Fr6d&ric Latour, Yannick Foing, Geraldine Kim, Prof. Johann Sadock, Wesley Farfan; and my other friends: Moshe Alamaro, Patricia Sampson, Raihan Khan, Dr. Pavel Hradecky, Adam Saffer, Todd Garvin, Oliver Pfeil. 4 Table of content ABSTRACT....................................................................................................................... 3 Key w o rds ..................................................................................................................... 3 FO REW O RD .................................................................................................................... 4 INTRO DU CTIO N ....................................................................................................... 7 1. ZOOPLANKTON ACOUSTICS BACKGROUND .......................................... 9 1.1 CHALLENGES OF ZOOPLANKTON BIOMASS ASSESSMENT ................................... 9 1.11 Introduction.................................................................................................. 9 1.12 Net tows...................................................................................................... 10 1.13 Video camera counting ............................................................................. 11 1.2 CHARACTERISTICS OF ACOUSTIC BACKSCATTER ............................................. 12 1.21 Zooplankton ............................................................................................... 12 1.22 Acoustic sensors......................................................................................... 14 1.23 Relevant acoustical-biologicalparameters ............................................... 16 1.3 ACOUSTIC BACKSCATTER OF BIOLOGICAL TARGETS: ......................................... 18 1.31 Fluid-like animals...................................................................................... 19 1.32 Hard elastic shelled and gas bladdered animals....................................... 22 1.33 Backscatter addition and considerations.................................................. 23 2. M ETH O D S .............................................................................................................. 25 2.1 FROM TARGET TO BACKSCATTER: MEASUREMENT MODELS ............................ 25 2.11 Empirical methods .................................................................................... 25 2.12 Model-based methods ............................................................................... 26 2.13 Acoustics adaptive modeling....................................................................... 27 2.2 THE COMPUTATIONAL MEASUREMENT MODEL ................................................... 28 2.21 Physical basis............................................................................................. 28 2.22 Geometry of the instrumentalsonars........................................................ 29 2.23 Towing method and data presentation...................................................... 31 2.3 ACOUSTIC INVERSION ........................................................................................ 34 2.31 Least squares minimum norm inversion ................................................... 34 2.32 Newton polynomials implementation........................................................ 35 2.33 Multiple models inversion........................................................................ 36 5 3. RESU LTS ................................................................................................................ 37 3.1 SINGLE SPECIES SIMULATION .......................................................................... 37 3.11 Fluid-like animals: euphausiids, copepods, krill....................................... 37 3.12 Standard deviation robustness.................................................................. 40 3.13 Plankton radius andpolynom ial order influence