Design of a network of robotic Lagrangian sensors for shallow water environments with case studies for multiple applications

Oroza, Carlos A.; Tinka, Andrew; Wright, Paul K.; Bayen, Alexandre M.

doi:10.1177/0954406213475947

Cited by 12 publications

(7 citation statements)

References 14 publications

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“…Information gained Limitations and estuaries (Schacht and Lemckert 2007, Mullarney and Henderson 2013, Landon et al 2014. Un-instrumented drifters are being used to track the movement of water parcels (MacMahan et al 2009, Oroza et al 2013, Wu et al 2015, and the flow path of individual particles can be measured with tracers (Kemp et al 2010). 'Pseudo-Lagrangian'…”

Section: Approachmentioning

confidence: 99%

New strategies for measuring rates of environmental processes in rivers, lakes, and estuaries

Ensign¹,

Doyle²,

Gardner³

2017

Freshwater Science

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A central goal in limnology is measurement of physical, biogeochemical, and biological process rates. We can measure process rates from the temporal and spatial patterns they create in a measured variable, and we use 3 approaches for making those measurements: the fixed-site approach for detecting temporal pattern at a location, the snapshot approach for detecting spatial pattern at an instant in time, and the flow path approach for detecting temporal pattern as it changes through space. To compare and contrast these approaches, we present patterns in temperature collected simultaneously based on all 3 approaches. Translating these patterns into process rates requires different assumptions for each approach, and these assumptions lead to uncertainty in process rates. We propose that these assumptions and related uncertainty can be reduced by making simultaneous measurements based on all 3 approaches. Each approach fills gaps in the spatial and temporal patterns measured by the others, and these patterns can be combined to derive a process rate. We develop a conceptual theory to support this strategy for measuring process rate based on 2 criteria: the mixing time of a water body and the analytical limitations of the measurement. This new strategy for measuring process rates in aquatic environments has the potential to increase the resolution of rate measurements, reduce their uncertainty, and enhance limnologists' ability to resolve process rates from an increasing flow of environmental data.

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Section: Approachmentioning

confidence: 99%

New strategies for measuring rates of environmental processes in rivers, lakes, and estuaries

Ensign¹,

Doyle²,

Gardner³

2017

Freshwater Science

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“…Previous generations of drifters developed by the Floating Sensor Network team included custom developed electronics and additional features, notably autonomous propulsion [ Oroza et al ., ]. The design priorities for this generation of drifter were to increase the amount of collected data through higher fleet numbers (requiring lower production cost per unit), greater reliability, and improved manufacturability.…”

Section: A Field Operational Test In the Sacramento River And Georgiamentioning

confidence: 99%

Variational Lagrangian data assimilation in open channel networks

Tinka

Weekly

et al. 2015

Water Resources Research

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This article presents a data assimilation method in a tidal system, where data from both Lagrangian drifters and Eulerian flow sensors were fused to estimate water velocity. The system is modeled by first-order, hyperbolic partial differential equations subject to periodic forcing. The estimation problem can then be formulated as the minimization of the difference between the observed variables and model outputs, and eventually provide the velocity and water stage of the hydrodynamic system. The governing equations are linearized and discretized using an implicit discretization scheme, resulting in linear equality constraints in the optimization program. Thus, the flow estimation can be formed as an optimization problem and efficiently solved. The effectiveness of the proposed method was substantiated by a large-scale field experiment in the Sacramento-San Joaquin River Delta in California. A fleet of 100 sensors developed at the University of California, Berkeley, were deployed in Walnut Grove, CA, to collect a set of Lagrangian data, a time series of positions as the sensors moved through the water. Measurements were also taken from Eulerian sensors in the region, provided by the United States Geological Survey. It is shown that the proposed method can effectively integrate Lagrangian and Eulerian measurement data, resulting in a suited estimation of the flow variables within the hydraulic system.

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“…The design of the active drifters was constrained by a number of functional requirements concerning actuation, form factor, and mission time. The design process is fully documented in (Oroza et al., ) and summarized here. Figure shows an annotated front and side view of the active drifter.…”

Section: Floating Sensor Network System Descriptionmentioning

confidence: 99%

“…Previous work essential to the system description is reproduced in summary here. This work includes design studies of the individual drifter devices (Oroza, Tinka, Wright, & Bayen, ; Beard, Weekly, Oroza, Tinka, & Bayen, ), advances in data assimilation techniques (Wu & Bayen, ), and the Hamilton‐Jacobi‐Bellman‐Isaacs partial differential equation‐ based navigation and obstacle avoidance control system for the actuated drifters (Weekly, Tinka, Anderson, & Bayen, ; Mitchell, Bayen, & Tomlin, ).…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Fleets of Active and Passive Floating Sensors for River Studies

Tinka

Weekly

et al. 2015

J. Field Robotics

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Lagrangian sensing for tracing hydrodynamic trajectories is an innovative approach for studying estuarial environments. Actuated Lagrangian sensors are capable of avoiding obstacles and navigating when active and retain a passive hydrodynamic profile that is suited for Lagrangian sensing when passive. A heterogeneous fleet of actuated and passive drifting sensors is presented. Data assimilation using a high-performance computing (HPC) cluster that runs the ensemble Kalman filter (EnKF) is an essential component of the estuarial state estimation system. The performance of the mixed capability fleet and the data assimilation backend is evaluated in the context of a landmark 96-unit river study in the Sacramento-San Joaquin Delta region of California. C 2015Wiley Periodicals, Inc.Passive drifters have proved very successful for oceanographic applications, where fixed infrastructure can be impractical to install. A logical extension of the oceanographic research in Lagrangian sensing is to develop sensors for nearshore environments such as rivers and bays. Lagrangian sensors can be used in this context to better monitor the flow of freshwater and the transport of constituents therein. Specific examples include assessing vulnerabilities to contaminant spills or infrastructure failure in Journal of Field Robotics DOI 10.1002/rob Tinka et al.: Heterogeneous Fleets of Active and Passive Floating Sensors • 3 Contributions of this ArticleThis article presents a system-level description of a heterogeneous FSN, including actuated drifters, passive drifters, and communication relays; the description of a field operation to demonstrate system functionality and to validate core assumptions about drifter operations in estuarial environments; an analysis of the utility of the actuation capability of the active component of the fleet; the design and implementation of a back-end data assimilation server cluster; and an analysis of the assimilation system performance and output using the data gathered in these experiments. This experiment represents a significant step in the deployment of autonomous floating robotics systems in unstructured natural environments. To our knowledge, this experiment is the first of its kind in the field of estuarial hydrodynamics Journal of Field Robotics

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Design of a network of robotic Lagrangian sensors for shallow water environments with case studies for multiple applications

Cited by 12 publications

References 14 publications

New strategies for measuring rates of environmental processes in rivers, lakes, and estuaries

New strategies for measuring rates of environmental processes in rivers, lakes, and estuaries

Variational Lagrangian data assimilation in open channel networks

Heterogeneous Fleets of Active and Passive Floating Sensors for River Studies

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