Executive Summary

Spatial Patterns in Land Use and Water Quality in the Tillamook Bay Watershed: A GIS Mapping Project

Degradation of water quality is important to the residents and visitors of Tillamook Bay because it has been linked to loss of income due to oyster bed closures, declines in salmonid populations and can result in a decrease of recreational use of the estuary’s resources. Both point and non-point sources of pollution have been targeted for investigation by the Tillamook Bay National Estuary Project (TBNEP), a project designed to bring local stakeholders and citizens together with State and Federal regulators and scientists.

The process undertaken by all estuary projects admitted into the National Estuary Program follows the sequence: establishment of key environmental problems, gathering of available information pertaining to these key problems, and development of a conceptual framework that can be used to identify data gaps and guide scientific research efforts. The ultimate outcome of all National Estuary Projects is to develop a science-based, Comprehensive Conservation Management Plan. To this end, TBNEP has developed a geographic information system (GIS) to organize, analyze and archive data collected and generated during this four year project. Presently, more than 120 separate GIS data layers have been archived within the TBNEP GIS, yet few studies have been completed that use the tremendous analytical power of GIS. Therefore, this study was commissioned to demonstrate how existing data could be used to address a TBNEP priority problem: contamination of the waters of Tillamook Bay by water-borne pathogens as indicated by fecal coliform bacteria.

Patterns in land use and water quality were explored using 12 existing layers from the TBNEP GIS. One new data layer (1:24,000 DEM) was acquired for this research and 13 new data layers generated during the course of the modeling. The first part of this report characterizes portions of the Tillamook Bay watershed as it relates to dairy herd densities by subbasin. The modeled results showed dairy herd densities to range from 0.52 cows acre-1 within a subbasin of the Kilchis River to 33.86 cows acre-1 within a subbasin of the Miami River. Also in this report, STORET water quality monitoring data were summarized using GIS. This exercise demonstrated that it was difficult to actually get the data from DEQ to analyze and that the paucity of data dramatically limited the scope of analysis such that even a simple trend analysis of the yearly averages of selected variables was difficult to interpret. Finally, this report presents a prescriptive mapping scenario to demonstrate how GIS can be used by resource managers to examine probable outcomes of management actions using computer models.

This work demonstrates how science can be linked with adaptive management. First, existing data were examined and spatial analysis performed. Second, results were presented in several ways along with study assumptions and limitations and various management alternatives were presented. Finally, studies were suggested to fulfill data needs so that better prescriptions can be developed in future iterations. In this way, managers know what scientists need to refine management alternatives and resource managers know the limitations imposed upon study results by inadequate or poor quality data.