Network Of Hydrophones Research Articles

Hydroacoustic Evidence for Offshore Lava Emplacement During the 2018 Kīlauea Eruption

AbstractDuring the 2018 Kīlauea eruption, over half the erupted lava was deposited on the seafloor. Lava flows crossing the shoreline generated sounds that were recorded by a network of hydrophones. We show that short‐duration, broadband signals associated with lava‐water interactions occurred throughout the eruption but increased in number when the Ahalanui ocean entry initiated on July 11. These terminated in early August coincident with the eruption's end. We compare hydroacoustic data with transmission loss models and eruption photographs to show that coastal explosive activity was poorly recorded by the hydrophone network. Similarly, strong hydroacoustic signals did not correlate with observed activity. These results suggest that acoustic signals were generated by lava flowing up to 100 s of meters offshore. Offshore lava flows can be hazardous to boaters, but hydrophones provide a means by which these hazards can be detected.

Hydroacoustic Monitoring of Mayotte Submarine Volcano during Its Eruptive Phase

Submarine volcanoes are more challenging to monitor than subaerial volcanoes. Yet, the large eruption of the Hunga Tonga-Hunga Ha’apai volcano in the Tonga archipelago in 2022 was a reminder of their hazardous nature and hence demonstrated the need to study them. In October 2020, four autonomous hydrophones were moored in the sound fixing and ranging channel 50 km offshore Mayotte Island, in the North Mozambique Channel, to monitor the Fani Maoré 2018–2020 submarine eruption. Between their deployment and July 2022, this network of hydrophones, named MAHY, recorded sounds generated by the recent volcanic activity, along with earthquakes, submarine landslides, marine mammals calls, and marine traffic. Among the sounds generated by the volcanic activity, impulsive signals have been evidenced and interpreted as proxy for lava flow emplacements. The characteristics and the spatio-temporal evolution of these hydroacoustic signals allowed the estimation of effusion and flow rates, key parameters for volcano monitoring. These sounds are related to the non-explosive quenching of pillow lavas due to the rapid heat transfer between hot lava and cold seawater, with this process releasing an energy equivalent to an airgun source as used for active seismic exploration. Volcano observatories could hence use autonomous hydrophones in the water column to detect and monitor active submarine eruptions in the absence of regular on-site seafloor survey.

Monitoring fin and blue whales in the lower St. Lawrence Seaway with onshore seismometers

AbstractThe Lower St. Lawrence Seaway (LSLS), in eastern Canada, is an important habitat for several species of endangered baleen whale. As we seek to reduce the hazards that these endangered species face from human activity, there is increasing demand for detailed knowledge of their habitat use. Only a sparse network of hydrophones exists in the LSLS to remotely observe whales. However, there is also a network of onshore seismometers, designed to monitor earthquakes, that have sufficiently high sample rates to record fin and blue whale calls. We present a simple method for detecting band‐limited, regularly repeating calls, such as the 20 Hz calls of fin and blue whales, and apply the method to build a catalog of fin and blue whale detections at 14 onshore seismometers across the LSLS, over approximately a 4‐year period. The resulting catalog contains over 600 000 fin whale calls and almost 60 000 blue whale calls. Individual calls are rarely detected at more than one seismometer. Fin whale calls recorded onshore often consist of multiple seismic phases arriving as a ∼2 sequence. Onshore seismometers provide a valuable, previously unused source of data for monitoring baleen whales. However, in the LSLS, the current seismometer network cannot provide high‐precision whale tracking alone, so a denser deployment of onshore and/or offshore seismometers is required.

Characterizing Southern Resident killer whale calls using a particle filter for frequency contour extraction

With only 74 Southern Resident killer whales (SRKWs) remaining in the waters of the eastern Pacific, understanding these marine mammals is vital to their conservation. Invasive techniques such as focal follows or tagging whales could introduce stress to SRKWs. Instead, passive acoustic monitoring that uses a network of hydrophones one preferred tracking method, particularly in their critical habitat that overlaps the shipping lanes in the Salish Sea. The acoustic data, if processed in real-time using modern deep learning methods, can be used to detect whales and alert ships of the potential for spatial overlap to reduce risks of collision. In this project, we consider the differences in SRKW whale call types from archived recordings of each of J, K, and L pods recorded on regional hydrophones. The whale calls are extracted as functional observations in the time and frequency space from underwater recordings using a particle filter. Functional data analysis (e.g., functional clustering) are performed to characterize the whale calls and represent the variations in call types. Such statistical insights between pod-level call types should be useful for improving machine learning whale detection algorithms, and for identifying SRKW movement in a high ship traffic region of their critical habitat.

A comparison of EAR and SoundTrap performance for acoustic monitoring of resident killer whales

Since 2006, a network of hydrophones has been deployed along the outer coasts of Washington, Oregon, and California to improve our understanding of endangered Southern Resident killer whale (SRKW) movements outside the inland waters of the Salish Sea and refine Critical Habitat designation. During this time period, improvements in methods and equipment have resulted in longer deployments, improved ability to detect resident killer whales (RKW) and monitor their acoustic behavior, and added the capability to characterize ambient and ship noise throughout SRKW range. It is important to understand how these changes might impact the results of long term studies on RKW movements and distribution. In this study, we co-located Ecological Acoustic Recorders (EARs) and SoundTraps at five locations along the Washington coast, analyzed each data set separately, and compared the results. Preliminary analysis of these data resulted in a 1.6 to 3.4 times increase in the number of days with RKW detections in the SoundTrap data compared to the EAR data depending on location. We will present the results of this comparison, investigate potential causes of the differences between recorder type, and highlight the implications of these differences to previous knowledge of RKW movements along the Washington coast.

Orcasound: Open source software for catalyzing conservation of endangered Southern Resident killer whales in real-time

Over the last 20 years, Orcasound has evolved from a cooperative network of real-time hydrophones to an open source software and hardware project. Orcasound connects cabled hydrophones deployed in critical habitat of the Southern Resident killer whales (SRKWs) with a web app that enables community scientists to listen and tag audio data in real-time. The live audio feeds are also monitored by automated algorithms (e.g., OrcaHello), archived in Amazon data “buckets” which are publicly accessible for free and governed by a Creative Commons license that promotes non-commercial data sharing and specifies appropriate attribution. Many of these open data have been annotated through crowd-sourcing tools built by the Orcasound community, like Pod.Cast and OrcaAL, generating open test and training data sets needed for development of more advanced classifiers. We present the latest version of Orcasound’s live-listening app as a novel conservation tool, and describe our evolving architecture for: generating audio streams with low-cost hydrophones and hardware, and free software; deploying diverse algorithms, including on non-Orcasound hydrophone data streams; validating, annotating, and analyzing acoustic detections; aggregating them in an open data cooperative along with regional data from sighting networks; and issuing notifications to network members as well as conservation stewards.

Measuring Ambient Ocean Sound During the COVID-19 Pandemic

An expanded nonmilitary hydrophone network provides new opportunities to understand the variability and trends of ocean sound and the effects of sound on marine organisms.

Tracking fin whales in a coastal fjord using passive acoustics

In the north-eastern Pacific, fin whales (Balaenoptara physalus) are typically found and studied in open waters near or seaward of the continental shelf. The Kitimat fjord system is a network of sounds and channels along the coast of British Columbia, Canada, and is one of only a few known fin whale habitats within confined coastal waters. In 2018, we deployed a network of hydrophones in Squally Channel, a proposed shipping lane located at the center of the fjord system, to monitor and track fin whales for a period of 2 years. The work is part of an effort to mitigate anthropogenic stressors on whales in the traditional territory of the Gitga'at First Nation. Here, we present spatial-temporal habitat use by fin whales in this confined inshore ecosystem based on more than 30 000 call detections and 7000 source localizations. Two distinct call types were recorded, a 20 Hz and a 40 Hz pulse, with distinctly different seasonal and diel trends. About 100 individual tracks were reconstructed from 20 Hz call sequences and analyzed for calling characteristics and movement patterns. A better understanding of fin whale habitat in the north-east Pacific is of special importance in light of an active discussion about the conservation status of this large baleen whale in Canadian waters.

Automated localization of whales in coastal fjords.

Localization and tracking of vocalizing marine mammals are powerful tools for understanding and mitigating the impacts of anthropogenic stressors such as vessel noise on habitat use of cetaceans. A large-aperture hydrophone network has been installed in the Kitimat Fjord System, an ecologically, culturally, and economically valued marine environment in northern British Columbia, Canada. This network consists of four synchronized bottom-mounted hydrophones that permanently record and radio-transmit data to a land-based laboratory. An automated system has been developed which includes routines to localize transient bio-acoustic signals from three or more streaming hydrophones in near real-time. These routines comprise the correlation of hydrophone signals, the construction of a time lag model, and signal localization and error estimation from a spatial likelihood surface. The localization method was tested experimentally and subsequently applied to vocalizations from humpback whales, fin whales, and killer whales. Refractive and reflective sound propagation effects in the confined fjords are assessed using ray tracing propagation models. Automated localization results are compared to ground-truth data and shown to provide good accuracy.

Sounds from airguns and blue whales recorded from a long term hydrophone network in the Southern Indian Ocean

The Southern Indian Ocean is a seasonal habitat for different blue whale sub species and sub populations. Their presence has been demonstrated by continuous acoustic records from the OHASISBIO hydrophone network, deployed since 2010 and which comprises 5 to 9 fixed mooring sites spread over a region from 24 deg to 56 deg South and from 52 deg to 83 deg East. Automated detection based on dictionaries and sparse representation has been used to detect and count the different stereotyped or non-stereotyped calls emitted by blue whales and recorded in this long-term dataset. However false alarm rate increased sometimes by the detection of a recurrent interference in the same frequency band of blue whales: the airgun shots produce during surveys for oil and gas located somewhere in the Indian Ocean and beyond. This finding allows us to characterize the seasonal and interannual variability in airgun sounds in this blue whale habitat. This study reinforce the fact that anthropogenic noise could be detected at large scale in pelagic environment and may affect marine mammal specially species who used low frequency bands.

Estimating group size from acoustic footprint to improve Blainville’s beaked whale abundance estimation

The numbers of animals in groups and the density of Blainville’s beaked whale Mesoplodon densirostris (Md) were estimated using passive acoustic data collected on the Atlantic Undersea Test and Evaluation Center (AUTEC). Md typically associate in groups, producing ultrasonic echolocation signals when foraging, and are routinely detected year-round on the AUTEC range. AUTEC includes a large network of hydrophones cabled to shore that can be used to detect Md echolocation signals. Using a first data set, with known group sizes, we used generalized linear models (GLMs) to model group size as a function of the acoustic footprint of a detected deep dive as perceived on the AUTEC hydrophones. The most important variable to explain group size was the detected click rate (total number of clicks detected divided by total length of vocal period duration). Using a second data set, covering 3 separate time periods in 2011 with automated group dive detections, we estimated beaked whale density using a dive counting approach. False positives were removed through manual inspection, removing dives with biologically infeasible characteristics. This led to a total of 8271 detections of beaked whale deep dives, with the average number per day in the three time periods considered being 75, 80 and 76 respectively. Using the selected GLM, the mean estimated group size was 2.36 (95% CI 2.15–2.60), 2.30 (95% CI 2.08–2.56), and 2.33 (95% CI 2.19–2.58) whales/group for the 1st, 2nd and 3rd time period. Md density was estimated at 15.8 (95% CI 13.6–21.9), 16.5 (95% CI 13.8–22.4), and 15.8 (95% CI 13.2–21.2) whales/1000 km2, respectively. These results support findings from previous studies, and will allow a more precise estimation of group sizes and densities for Md in future research.

Broad-scale study of the seasonal and geographic occurrence of blue and fin whales in the Southern Indian Ocean

The southern Indian Ocean is believed to be a natural territory for blue and fin whales. However, decades after commercial and illegal whaling decimated these populations, little is known about their current status, seasonal habitat or movements. Recent passive acoustic studies have described the presence of 4 acoustic populations of blue whales (Antarctic and 3 ‘pygmy’ types), but are generally limited temporally and geographically. Here, we examine up to 7 yr of continuous acoustic recordings (2010-2016) from a hydrophone network of 6 widely spaced sites in the southern Indian Ocean, looking for the presence of Antarctic and pygmy blue and fin whales. Power spectral density analyses of characteristic and distinct frequency bands of these species show seasonal and geographic differences among the different populations, and the overall patterns for each display interannual consistencies in timing and occurrence. Antarctic blue and fin whales are recorded across the hydrophone network, mainly from austral autumn to spring, with peak intensity in winter. Pygmy blue whales show spatial variation: Madagascan pygmy blue whales are mainly present in the west of the network, while the Australian call type is heard at the eastern sites. Both populations share a common seasonality, with a presence from January to June. Finally, the Sri Lankan call type is recorded only on a single site in the northeast. These results confirm the importance of the southern Indian Ocean for several populations of endangered large whales and present the first long-term assessment of fin whales in the southern Indian Ocean.

Low-frequency acoustic observations with cabled observatories on the Juan de Fuca Ridge

In the Northeast Pacific Ocean, the NSF Ocean Observatories Initiative (OOI) and Ocean Networks Canada (ONC) operate regional cabled observatories that include a network of seismometers and hydrophones enclosing the northern half of the Juan de Fuca plate, and local observatories at two sites on the Juan de Fuca Ridge: Axial Seamount (OOI) and the Endeavour segment (ONC). At each ridge site, local networks of seismometers and hydrophones provide a tool to monitor in real time the seismic and acoustic signals associated with volcanic, tectonic, and hydrothermal processes. In 2015, Axial Seamount erupted a few months after the installation of the OOI. Following the eruption, regionally recorded T-phases were used to track a dike propagating along the Axial North Rift. Acoustic signals from impulsive sources associated with lava flows, detected eruptions in the caldera and on the North Rift. Diffuse acoustic signals were also associated with the later stages of the eruption. The low-frequency acoustic capabilities of the OOI and ONC cabled observatories are underutilized and future applications could include the reestablishment of regional acoustic earthquake monitoring, tracking eruptions in real time to guide rapid autonomous and ship-based response efforts, and enhanced studies of fin and blue whales.In the Northeast Pacific Ocean, the NSF Ocean Observatories Initiative (OOI) and Ocean Networks Canada (ONC) operate regional cabled observatories that include a network of seismometers and hydrophones enclosing the northern half of the Juan de Fuca plate, and local observatories at two sites on the Juan de Fuca Ridge: Axial Seamount (OOI) and the Endeavour segment (ONC). At each ridge site, local networks of seismometers and hydrophones provide a tool to monitor in real time the seismic and acoustic signals associated with volcanic, tectonic, and hydrothermal processes. In 2015, Axial Seamount erupted a few months after the installation of the OOI. Following the eruption, regionally recorded T-phases were used to track a dike propagating along the Axial North Rift. Acoustic signals from impulsive sources associated with lava flows, detected eruptions in the caldera and on the North Rift. Diffuse acoustic signals were also associated with the later stages of the eruption. The low-frequency acoustic capabi...

Approximate Filtration of Noise Reflections in Hydroacoustic Signals

A method of approximate filtration of noise reflections is proposed for measurement of the coordinates of an object with a sound emitter moving in an aquatic environment. A passive hydroacoustic detection and ranging system based on a network of hydrophones is used in the measurements. A two-stage approximation algorithm is employed for digital processing of the Doppler hydroacoustic signals from the outputs of the hydrophones. An example illustrating implementation of the filtration method and its error is considered.

A method of measurement of the coordinates of a moving object with the use of a passive hydroacoustic detection and ranging system

A method of measurement of the coordinates of an object equipped with an acoustic radiator is proposed. The measurements are performed by means of a passive hydroacoustic detection and ranging system based on a network of hydrophones. Digital processing of Doppler signals from the outputs of the hydrophones and a two-stage approximation algorithm are used. An example illustrating the implementation of the method is given and the errors of the method are considered.

Stochastic Optimization of Sensor Placement for Diver Detection

A comprehensive framework for diver detection by a hydrophone network in an urban harbor is presented. It includes a signal processing algorithm and a diver detection test and formulates optimal hydrophone placement as a two-stage stochastic optimization problem with respect to different scenarios of underwater noise. The signal processing algorithm identifies sound intensity peaks associated with diver breathing and outputs a diver number measuring the likelihood of diver presence, whereas the diver detection test aggregates the diver numbers obtained from the hydrophones in a linear statistic and optimizes the statistic's coefficients and a detection threshold for each noise scenario. The serial dependence of the diver numbers on a short time scale (several detection periods) is modeled by a hidden Markov chain, and finding the worst-case diver's trajectory for each hydrophone placement and noise scenario is reduced to a linear programming problem. The framework is tested in numerical experiments with real-life data for circular and elliptic hydrophone placements and is shown to be superior to a deterministic energy-based approach.

Shipping noise signatures.

Throughout 2010, underwater recordings have been made of each ship passing two separate Haro Strait nodes of the OrcaSound.net hydrophone network. About 20 ships pass each day. Each ship has been identified in real time [automatic identification system (AIS)]. Measurements of received underwater noise levels and AIS variables are recorded as each ship passes the listening stations. Individual ships are observed multiple times moving in either northerly or southerly directions at times separated by a day or two and also by intervals of months. A database has been developed that contains the spectrum level of each ship (bandwidth 96 kHz at one location and 22 kHz at the other) and the source level both in terms of intensity and angular distribution. Ship signatures in terms of frequency quantiles and angular distributions of emissions are quite reproducible. This database can be used to predict limitations on echolocating and vocalizing marine mammals’ active space due to specific ship noise emissions. In particular, predictions of marine mammal noise exposures in specific frequency bands can be made prior to specific vessels’ entry into an area opening the possibility of planning field observations to investigate correlations between behaviors and specific predicted noise exposures.

Quasi-all-optical network extension for submarine cabled observatories

Submarine cabled networks are designed to collect valuable data in geophysics, geochemistry, biology, or oceanography. Unfortunately, the development of such a network is expensive and needs complex subsea infrastructures. Once in place, a cabled network cannot be easily relocated. The current cost of cables and their installation are one of the major obstacles to these networks deployment. On the one hand, these cables are necessary to provide power supply and communication data, and on the other hand they drastically reduce the possibilities to extend the cabled observatory network in order to reach a closed area of significant interest. This is why, to address this issue, we propose a quasi-all-optical architecture to easily extend multidisciplinary cabled networks or to create a dedicated submarine hydrophone or seismometer network. This solution consists of using only a single fiber optic to transmit both the energy, required to supply the instrument, and the data, exchanged between the shore station or equivalent. In this paper, we present our proposed architecture, and we discuss its feasibility thanks to experimental results.

Killer whale scouting: Listen live for troops J, K, and L.

The southern resident killer whales are highly vocal, sharing almost 40 distinct calls. The endangered population of about 87 orcas live in matriarchal groups (like troops) known as J, K, and L pods. Each pod has a favorite call that is used about half the time pod members vocalize. If you hear a favorite call you can guess (or infer) which pod is present. A new way to listen for orcas is with hydrophones (underwater microphones) that are connected to the internet. The Northeast Pacific Hydrophone Network—http://orcasound.net—includes five hydrophones located near Seattle, WA within the summertime range of the orcas. You can listen live through iTunes to discover which pods are calling or to monitor the environment for noise pollution that could be a problem for the whales. This hands‐on activity teaches you how to listen, identify the three pods based on their favorite calls, and share your observations with other listeners. High school students can use free software to record orca calls, whistles, and clicks and analyze them, guided by a suite of citizen science projects.

Detection of $H$-Phase Signals From Hydroacoustic Data Using Quadratic Classification

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates a network of underwater hydrophones as part of the International Monitoring System (IMS). Data from this network are processed at the International Data Centre (IDC), Vienna, Austria. One of the objectives is to identify the signals that are due to an underwater explosion, the so-called <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -phase signals. Data provided by IDC were examined to investigate new automated processing schemes that could significantly reduce the number of signals needed to be analyzed by human experts, while still detecting with high probability the rare <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -phase signals. A variant of quadratic classification (QC) using four signal characteristics from the time, frequency, and cepstrum domains was applied to the problem. It was found that 97.5% of the received <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -phase signals are detected by the automated QC process. These <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -phase signals are among only about 1% of the signals which are allowed to form event solutions for further analysis by experienced experts.