Coeur d’Alene Trust Loading Analysis
Client: Successor Coeur d'Alene Custodial and Work Trust
Location: Kellogg, Idaho
The Coeur d’Alene Trust has been tasked with managing cleanup actions in the Upper Basin of the Coeur d’Alene River for the Bunker Hill Mining and Metallurgical Complex Superfund Site. Developing a prioritization strategy for cleanup actions that is based on data-driven decisions is integral to attaining remediation goals in the basin.
MFA has developed an assessment framework that uses a combination of data collection and management, contaminant modeling, and visualizations to adaptively prioritize projects in the Upper Basin. Use of a comprehensive contaminant mass loading assessment is one of the ways that MFA has been able to assist the Coeur d’Alene Trust by providing information about a complex system in a format that can be incorporated into the decision-making process. The loading assessment figures help stakeholders, including the U.S. Environmental Protection Agency (USEPA), quickly understand the relative contributions of contaminants from different sources throughout the basin.
The use of a comprehensive mass loading assessment for site prioritization has been integral in providing decision-makers with the information needed to identify which remediation projects would be most beneficial. Completion of an annual loading assessment also helps to identify data gaps, provides information for site design, and highlights changes over time.
The selected remedy for the Upper Basin of the Bunker Hill Superfund Site includes remediation work at over 145 sites, and work is expected to continue over a period of 30 years. The USEPA desires to remedy the “worst first.” What should the prioritization be?
MFA completed a comprehensive mass loading assessment for the Ninemile Creek Watershed to provide decisionmakers with the information needed to identify which remediation projects should be undertaken first. The work uses a combination of data collection and management, contaminant modeling, and visualizations to clearly represent complex data. The loading assessment also helps to identify data gaps, provides information for site design, and highlights changes in site conditions over time.