This presentation focuses on the use of pressure-based loggers to determine water level measurements for sea level monitoring, tidal averaging, and pressure-derived wave measurements. The paper will also discuss the use of pressure-based loggers for monitoring oceanographic moorings for knock down and evidence of trawling, and their use on profiling bodies and autonomous vehicles. Topics covered include accuracy, resolution, data quantity, endurance, and cost. ‘Pros and cons’ of the different methods of water level determination will be considered, along with a discussion on the difference between accuracy and resolution in this context, understanding drift and the importance and frequency of recommended calibration. This will also include factors affecting accuracy and methods to get the highest accuracy out of your instrument. Processing of water level data is also detailed including determining tide and/or wave parameters from the raw data and how to remove the atmospheric pressure component from the pressure signal recorded at the sensor. Examples of different deployment programs using pressure-based loggers will be given, along with deployment methodologies. Finally, the paper will look at recent developments including the integration of bottom based pressure sensors into a ‘Smart Mooring’ to not only allow real- time data transmission to shore, but also comparison between that data and the buoy determined data recorded at the surface buoy.

The International Great Lakes Datum (IGLD) is a common vertical reference used throughout the Great Lakes – St. Lawrence River system to measure water levels. IGLD was first released in 1962 by the Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data, a bi-national committee dedicated to joint water resource management. IGLD (1955) was updated to IGLD (1985) in 1992, and IGLD (1985) is expected to be replaced with IGLD (2020) in 2027. To maintain consistency with national datums, IGLD (2020) will be aligned with the new geoid-based North American-Pacific Geopotential Datum of 2022 (NAPGD2022) that is expected to be adopted in the United States by 2025 and will be compatible with the Canadian Vertical Datum of 2013 (CGVD2013), which is presently in use in Canada. With the update to the International Great Lakes Datum to IGLD (2020), access to the datum will also fundamentally change. Instead of primary access through leveling from benchmarks, modern GNSS technology will be used. We will give an overview of the datum development, new methods of accessing the datum, tools for transformations and a status update on implementation.

This investigation focuses on the exploration of water level data collection methods in the Great Lakes, tracing its history and the ongoing investigation by the Canadian Hydrographic Service (CHS) into alternative sensor technologies. The assessment of the advantages and disadvantages of different sensor configurations are examined, leading to the conceptualization of an ideal sensor and its acceptance criteria. The presentation also touches upon the standardization, coordination, and collaboration between CHS and the National Oceanic and Atmospheric Administration (NOAA) to date. The findings could have implications for future water level data collection strategies in the Great Lakes region and the potential for extending these to other Canadian Hydrographic Service (CHS) regions. The pivotal question this research seeks to answer is: Can we transition to a different sensor configuration in the Great Lakes to reduce costs without compromising (and possibly improving) data quality?

In the changing environment where our coasts and shorelines are vulnerable and sensitive, our ability to comprehensively map the land-to-sea scape has never been more important. Single-sensor, narrow scoped projects are giving way to broad scale mapping missions requiring a variety of tools and survey approaches to address a host of data-driven management decisions. This presentation delves into the pivotal aspects of adaptability, alignment, and evaluation in coastal resilience mapping and nautical charting projects. Real-world examples from projects in Texas, North Carolina, and Florida illustrate the significance of ongoing evaluation, shedding light on lessons learned and strategies for overcoming challenges. The imperative of integrating and sequencing ground-based and remotely sensed reconnaissance with sonar projects and topobathymetric lidar projects aligns seamlessly with the emerging trend observed across multi-agencies, reflecting a collective desire to harness data that serves diverse use cases. Recognizing the distinct accuracy, density, and cost attributes of each technology, this strategic integration not only optimizes data quality but also responds to the growing demand for versatile datasets capable of fulfilling multiple purposes within the broader spectrum of coastal survey and mapping. Importantly, this approach is cost-effective and scalable, offering a practical solution for covering extensive areas while ensuring the efficient use of resources. The continuous practice of adaptation, stakeholder alignment, and rigorous evaluation are key elements defining project success in the realm of coastal resilience.

The collection of full-scale vessel motion data at commercial ports can be logistically challenging, frequently when vessel motions are of most concern and therefore of most value to observe. This tends to limit the opportunity for data collection. Recently, IoT (internet of things) devices have become widely available, allowing for provisioning of sensor data easily and cost-effectively. Accordingly, internet-connected vessel motion sensors have been developed at OMC to collect and deliver measurements in a port setting, making use of cellular connectivity. This allows vessel motion data to be made available in near real-time, or automatically as a cell-tower comes into range. The capability of measuring ship motions in full-scale has been used to provide data for the validation and calibration of models and simulations. Due to the difficulties in obtaining the data, this has typically been done in focussed campaigns and entails multi-stage collection and processing tasks. The analysis of vessel movements can be useful for pilots on an individual and group level for achieving and improving best-practice for both horizontal movements e.g., to optimise seakeeping for pilot transfer risk mitigation, and to manage vertical under-keel clearance (UKC) factors. The collection of vessel motion data on a larger scale can be used to better understand the operability and dynamics of the port and vessel movements. OMC’s edge devices accurately measure vessel positions and dynamic roll, pitch and heave in a convenient package, allowing data collection to be integrated into business-as-usual for pilotage operations. These are aggregated and combined with predictions of meteorological conditions to achieve modelling excellence, to improve navigational safety and port throughput volumes.

While ports around the world try to accommodate newer and larger vessels, operating margins have become narrower as the growth rate of ports has not matched the same level of growth in vessel dimensions as discussed in PIANC Report N 117 – Use of Hydro/Meteo Information for Port Access and Operations (2012). Therefore, decision making aided by good quality real-time environmental data is key in the pursuit of increased port safety and productivity. With an increase in extreme weather events due to climate change, there is a heightened need to accurately predict future conditions. This serves to reduce delays due to adverse weather while ensuring the safety of port operations and personnel. While there are a lot of advancements being made in weather forecasting, the quality of a forecast is still limited by the quality of the real-time data that feeds into the model. This highlights the need for standards and systems that ensure reliability and quality control of real-time data. Identification of data quality issues is important for port operations. Using the QARTOD framework in conjunction with other QA processes helps OMC to identify issues quickly. This allows for a faster response time to get good quality data and downstream applications back up and running, as shown in the case studies. Visual monitoring and manual checks of real-time environmental data are important to recognize data anomalies that may not be identified by automated QC tests. Monitoring dashboards were developed as a solution to assist in verifying the quality of real-time data that has been subject to the automated QC tests. The implementation of QARTOD, along with visual monitoring, alerting, reporting, and diagnostics provides OMC with a method to improve real-time outcomes in assessing the quality of data that is critical for port operations.