View source for SURF 2019: River Mapping with Autonomous Surface Vehicles for Flood Hazard Monitoring

'''[[SURF 2019|2019 SURF]]: project description'''
* Mentors: Richard M. Murray, Woody Fischer, Mike Lamb
* Co-mentor: Chris Clark (HMC)

River flooding is among one of the most hazardous natural disasters in the world. Over the past ten years, the damage of river floods across the globe had amounted to a staggering 50 billion dollars [1]. Most rivers are conduits of water and sediments and their geometry evolves over time due to erosion and deposition. It is possible to determine where and when a flooding might occur given an accurate profile of river geometry. Costs and damages can often be reduced with such predictions. Unfortunately, the vast majority of the river bed topography and flow rate profiles are either outdated or unavailable [2]. Most rivers have the tendency to self-adjust their geometry to increase flow capacity [3], and the current methods of sampling for river bed topography with boats are not frequent enough to account for those changes. For example, the current flood prediction of Mississippi river relies on outdated river profiles that were sampled by the U.S. army in 1974 with boat [4]. Although high resolution digital mapping from airborne laser-based instruments could potentially be put in use for river mapping [5], those methods are not suitable for river environment with turbid currents. Using automated vehicles capable of mapping turbid rivers at a high frequency can fill in the knowledge vacuum that we have at the moment.

[[Image:thor-setup.png|right|400px]]
The goal of this project is to apply the techniques of autonomous navigation and state estimation in river mapping. Last summer we configured an Autonomous Surface Vehicle (ASV) and equipped it with an Acoustic Doppler Current Profiler (ADCP) to create high resolution river bed topographies and flow rate profiles. Although autonomous vehicles have been used extensively to create topography of oceans and lakes [6], much less have been done for river beds because of the difficulties associated with turbid current and shallow depths. Although lawnmower pattern path will provide adequate coverage for most still water environment, high current flow in rivers might make certain region impossible to traverse. This years project will extend the work from last summer to add features such as autonomous docking/recharging and the ability to navigate more complex current patterns.

=== Useful skills ===
* Programming experience in C/C++ and Python
* Experience with ROS or other real-time operating systems for robotics
* Course work in robotics and/or control systems

=== References ===
# Aon Benfield, 2016, 2016 Annual Global Climate and Catastrophe Report, 56 pp.
# Lamb, M.P., J. Nittrouer, D. Mohrig, J. Shaw, 2012, Backwater and river-plume controls on scour upstream of river mouths: Implications for fluvio-deltaic morphodynamics. Journal of Geophysical Research Earth Surface, v. 117, F01002, doi:10.1029/2011JF002079. 
# Phillips, C.B. and Jerolmack, D.J., 2016, Self-organization of river channels as a critical filter on climate signals, Science, p. 694-697.
# Lamb, M.P., J. Nittrouer, D. Mohrig, J. Shaw, 2012, Backwater and river-plume controls on scour upstream of river mouths: Implications for fluvio-deltaic morphodynamics. Journal of Geophysical Research Earth Surface, v. 117, F01002, doi:10.1029/2011JF002079.
# National Research Council of the National Academies, 2010, Landscapes on the Edge: New Horizons for Research on Earth’s Surface, National Academies Press, 161 pp.
# Russell B. Wynn, Veerle A.I. Huvenne, Timothy P. Le Bas, Bramley J. Murton, Douglas P. Connelly, Brian J. Bett, Henry A. Ruhl, Kirsty J. Morris, Jeffrey Peakall, Daniel R. Parsons, Esther J. Sumner, Stephen E. Darby, Robert M. Dorrell, James E. Hunt, Autonomous Underwater Vehicles (AUVs): Their past, present and future contributions to the advancement of marine geoscience, Marine Geology, Volume 352, 2014, Pages 451-468