Robotic Monitoring for Turbidity Management in Multiple Reservoir Water Supply

Abstract

The delivery of large quantities of turbidity-causing particles over relatively brief intervals of high stream flow and the complexity of the resulting turbidity (Tn) patterns imparted to receiving lakes and reservoirs requires the use of innovative technologies to fully resolve both the driving signals and the resulting signatures in the receiving waters. The design and implementation of a robotic monitoring network to address the problem of high Tn events in reservoirs of New York City’s multireservoir unfiltered water supply are described. The evolution of the role of these technologies in supporting management of the system related to the Tn issue is described, including (1) resolution of cause and effect relationships between tributary inputs and in-reservoir patterns; (2) insights into mediating processes; and (3) critical support for the development, testing, and application of mechanistic mathematical models. The contemporary robotic monitoring network of eleven tributary and reservoir deployments continues to support management deliberations of alternatives to minimize the effect of major runoff events as they occur. These data streams are being integrated into a forthcoming near-real-time decision support tool that will provide automated guidance in the context of multiple factors and objectives for this complex water supply.