APPLYING GEOSPATIAL TOOLS FOR CONCEPTUAL SITE MODEL DEVELOPMENT AT THE FORMER BOISE CASCADE MILL, YAKIMA, WASHINGTON, USA

Geospatial tools such as GIS and surface modeling software provide a relatively quick method to model contamination concentrations and to develop user friendly site maps displaying this data. Other useful information such as plume footprint volumes can also be estimated. ESRI ArcGIS Geostatistical Analyst and Goldensoftware’s Surfer were employed to develop these types of products using existing groundwater monitoring data for the Boise Cascade Mill cleanup sites. The data was previously submitted to the Washington State Department of Ecology following a number of studies by different environmental consultants and is available to the public.

The former Boise Cascade Mill site is located in northeast Yakima, Washington and covers an area of over 200 acres. A lumber mill operated from 1903 to 2006 and the facility is currently considered a brownfields site. A log pond located on the southern portion of the facility was drained in ~1963 and was filled with municipal solid waste for ~10 years. This unregulated landfill has been designated as a separate cleanup site by the Washington State Department of Ecology. Future cleanup of these sites will both protect human health and the environment, including receptors such as the Yakima River, and provide an economic boost to the community as the area is redeveloped into a mix of new land uses including eventual construction of a new major transportation corridor bisecting the sites.

Decomposition of large amounts of wood waste and municipal solid waste has led to a reduction of dissolved oxygen in the groundwater. The reducing conditions allow for metals, including arsenic, manganese, and iron, to precipitate into the groundwater over a wide area covering much of the 200 acres and beyond. Low pH in groundwater and elevated levels of sodium were also mapped for a portion of the area. Of the nine methods available in the ArcGIS Geostatistical Analyst, Kernel Smoothing, Inverse Distance Weighting, and Kriging/CoKriging provided the most representative groundwater elevation and contamination concentration contours. Data gaps in the well network for future investigation were also identified.