Project period: 4 9 25-4 8 26PROJECT title: hydrocams: large-scale automated image-based flood stage monitoring, phase 2 developmentthe USGS has strong interest in upgrading its current hydrological…

This Cooperative Agreement award from the U.S. Geological Survey (USGS) under the USGS Research and Data Collection program (CFDA 15.808) provides $249,965 to Northern Arizona University (NAU) to conduct research and development on an automated image-based flood stage monitoring system, known as HYDROCAMS.

The project aims to experimentally address key technical challenges in deploying a scalable, low-cost hydrological monitoring network using compact, grid-independent "HYDROCAM" sensor units. The research will evaluate factors such as accuracy of image-based stage detection, tradeoffs between sensor distance/resolution and lighting conditions, and reliability of the self-powered sensor nodes for 24/7 mission-critical operations. If successful, this technology could enable a significant expansion of the USGS surface water monitoring infrastructure at a fraction of current operational costs.

The performance period for this Phase 2 development effort is from April 9, 2025 through April 8, 2028.

Project period: 4 9 25-4 8 26PROJECT title: hydrocams: large-scale automated image-based flood stage monitoring, phase 2 developmentthe USGS has strong interest in upgrading its current hydrological monitoring infrastructure bymassively expanding its current surface water monitoring infrastructure using automated image basedstage monitoring technologies. If successful, this technology could allow a severalorders of magnitude increase in monitoring station density coverage at operational costs that aresimultaneously several orders of magnitude lower than current USGS monitoring solutions.while the promise of low-cost, accurate, and greatly expanded hydrological monitoring usingautomated image-based monitoring is compelling, numerous scientific and engineeringchallenges remain to be addressed to determine the practical potential of this concept in largescale, real-world deployment the aim of the hydrocams project is to experimentally addressthese questions. Phase 1 of the project evaluated engineering options to develop a suitableexperimental platform: a small, grid-independent smart camera prototype, which we call ahydrocam, representing the basic size, power, networking and other operational constraints fornext-GEN IOT sensing infrastructures . In this second (phase 2) project stage, using this platform to evaluate and characterize the real-world potential of image-based stagesensing technologies. Key applied research questions to be resolved include: how accurate can image-based stage detection be, as compared to existing methods inused by USGS? What are the tradeoffs between distance, resolution, and lightingconditions, as these relate to accuracy of automated image-based readings? How robust can small, grid-independent units be? Can such small, cost-effective unitsnonetheless provide reliable, 24-7-365 monitoring performance for mission criticaloperations? How does size power of solar system relate to image acquisition, processing, andtransmission to determine power efficiency? How can dynamic smart powermanagement potentially stretch this envelope? Can image-based monitoring effectively function at night, and in other poor lightingconditions? What are the tradeoffs between lighting, IR or other illumination, targetdistance type, and other factors? What is the optimal infrastructure architecture for such monitoring networks? Whattrade-offs exist between edge centralized processing, between centralized standalonesystem management, and their respective impact on overall operating efficiency?activities in phase 2 of this project center around shifting from lab testing to realistic fielddeployment, driving a series of tests and metrology experiments to answer the questions above.deliverables include reports to USGS, including the HIF, on the accuracy, power efficiency andother performance issues outlined above, as well as publication in national forums in sensing andenvironmental monitoring to disseminate our findings on the potential of image-basedmonitoring with the broader scientific community.keywords: big data, hydrology, flood management, smart cities, internet of things, cloudcomputing, environmental monitoring