Water Quality Modeling using Remotely Sensed Watershed Characteristics

Abstract:

Despite the strong influence of watershed conditions on source water quality, most water utilities and water resource agencies do not currently have the capability to monitor watershed sources of contamination with great temporal or spatial detail. Typically, knowledge of source water quality is limited to periodic grab sampling; automated monitoring of a limited number of parameters at a few select locations; and/or monitoring relevant constituents at a treatment plant intake. While important, such observations are often not sufficient to inform proactive watershed or source water management at a monthly or seasonal scale. Satellite remote sensing data on the other hand can provide a snapshot of an entire watershed at regular, sub-monthly intervals, helping analysts characterize watershed conditions and identify trends that could signal changes in source water quality.

Under a NASA-supported applied research project, our research team has developed a set of data processing and modeling tools that enable utility and agency analysts to develop water quality predictions using remotely sensed vegetation indices and land cover parameters, combined with in situ measurements of hydrologic and weather conditions. We will discuss how these predictions can be used by water resources planners and operations staff in a variety of applications, including long-term infrastructure capital planning and seasonal to sub-seasonal system operations.