Greetings, water observing technology leaders! The University of Alabama’s Alabama Water Institute (AWI) and the USGS Next Generation Water Observing System (NGWOS) are excited to announce the inaugural Water Observing Technology Forum (WOTF). The WOTF will be a three-day event occurring April 23-25, 2024, at the Bryant Conference Center in Tuscaloosa, Alabama. The Organizing Committee is comprised of representatives from the AWI, the Alliance for Coastal Technologies (ACT), and the U.S. Geological Survey (USGS) and represent a wide range of knowledge and expertise in water observing technologies. The planning and delivery of the WOTF is supported by the Cooperative Institute for Research to Operations in Hydrology (CIROH) through CIROH’s partnership with the USGS. We are excited to bring the water observing community together for this exciting event and to see what new opportunities will come from it!
The WOTF will showcase the latest research into innovative technologies and methods for measuring water quantity, quality, and availability. Special focus will be placed on exposing gaps in our traditional monitoring technologies and where science, innovation, and partnerships can help fill those gaps. Speakers will include Federal agency representatives, academic researchers, and industry leaders. This year’s forum will focus on the following technology themes:
Research into the utility of imagery-based observing platforms in regional and national surface and ground water monitoring networks has expanded greatly in the last five years. This research has included evaluation of methods that incorporate satellite, airborne, proximal, and mobile in-situ remote sensing platforms and has yielded useful and exciting results. Establishing data requirements and standards as well as data transfer and delivery tools for imagery data are critical gaps that have been addressed through several coordinated efforts that will be discussed at the Forum.
The water monitoring community is also exploring the use of mobile monitoring systems to measure water parameters. These systems include small uncrewed aerial and underwater vehicles as well as surface vessels. Having the ability to locate sensors in locations that are otherwise expensive or unsafe to send field staff and collect data over a large area in a short amount of time makes these platforms attractive. As advancements in artificial intelligence and machine learning continue to expand this field, the application of these types of models into the operational algorithms of uncrewed automated observing platforms could lead to the capability for “smart swarming” algorithms.
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