Case Study of a Cloud-based Web-camera Observation Framework for Streamgages in the Context of the USGS Next Generation Water Observing System

Abstract:

Substantial advances in water science, together with emerging breakthroughs in technical and computational capabilities, have led the U.S. Geological Survey (USGS) to develop a Next Generation Water Observing System (NGWOS). The USGS NGWOS is a broad program aimed at integrating fixed and mobile monitoring assets in the water, ground, and air toward an affordable, high-fidelity, system of monitoring networks to improve water-resource modeling and forecasting nationwide. When fully implemented, the NGWOS will provide high temporal and spatial resolution data on streamflow, evapotranspiration, snowpack, soil moisture, water quality, groundwater/surface-water connections, stream velocity distribution, a broad suite of water-quality constituents, and water use. As a part of this effort, a cloud-computing framework to ingest, process, and serve network camera observations and hydrologic measurements at USGS streamgages using Internet of Things (IoT) concepts is being developed. This case study is aimed at creating a robust and scalable enterprise system to support persistence, processing, and presentation of imagery data, derived data, and metadata. The core functionality of this system will include the ability to store, process, review and approve, and automatically disseminate images and hydrologic data derived from images. In this talk, the progress and status of this emerging cloud-computing framework will be discussed within the broader context of the NGWOS Program. A detailed overview of the architecture of the cloud framework, auto-provisioning functionality for IoT devices, integration with edge computing, and processing chains will be described. Finally, some perspectives on the future of an enterprise-level implementation of this cloud framework will be discussed.