Managing Uncertainty with Systematic Planning
For Environmental Decision Making

Abstract:

The U.S. Department of Energy, EH-31, in cooperation with the DOE Richland Operations Office, and Bechtel Hanford, Inc., has developed a 3-day training course with the objective to "institutionalize" managing uncertainty with systematic planning for environmental decision-making throughout the DOE complex and the environmental community.

The EPA has recognized the Data Quality Objectives process as an excellent method to manage uncertainty via systematic planning. The course provides instruction on the practical management and implementation of the U.S. EPA's 7-Step DQO Process. The target audience is DOE, DOD, Tribes, State and Federal regulators, their management, technical support staff, and their contractor project managers/engineers and technical support staff. The first day explains the "big picture" and the last two days provide the details of implementation of the DQO Process.

During the first day, the audience is introduced to the successful DOE EH-31 DQO Process implementation model which evolved in the field in direct response to the observed flaws and inefficiencies in project DQO efforts. The EPA Office of the Inspector General has recognized this DQO implementation model as a "best practice." Using a wall-chart depicting the model as a "work-flow" diagram, the audience is taken through DQO process implementation, showing all the logistical, schedule, budget, inputs, actions, approvals, and documentation steps. The focus of the implementation is to streamline and document the process and provide a standard approach to systematic planning.

The course includes an introduction to basic statistical concepts in a non-threatening manner via demonstrations using common objects such as coins, marbles, and beads.
We then build on these concepts, demonstrating the fundamentals of statistically based sample designs and decision performance diagrams. The statistical concepts are reinforced through a demonstration of Visual Sample Plan, which is the state-of-the-art sampling design software package. It allows decision-makers to quickly see and evaluate various sampling designs, make real time changes, and select the optimal cost and quality design during the DQO process.

During the course, Steps 1-7 of the DQO Process are discussed in detail. For each step (and action), there are generic examples and a case study. The case study provides an example that shows the continuity of the logic required to implement the process. The format of the examples is based on the DQO electronic "workbook", which was modeled after the EPA DQO guidance (QA-G4, 1994 & 2000). The course materials are available on the DOE Hanford DQO web site (http://www.hanford.gov/dqo/).

In addition, students perform hands-on exercises designed to demystify statistical concepts and teach the user how to implement these concepts. Computer simulations reinforce the hands-on exercises and provide visually compelling illustrations of key concepts. These examples show the necessity of developing valid sampling designs so that the populations of waste, soil, etc., are properly characterized. The student learns how to use the DQO e-Workbook and an overview of the DQO Web Page is presented.

At the end of the three days, the student has the knowledge to generate defensible sampling designs that support making correct environmental decisions. The course is applicable to projects that require data to support decisions such as those related to site assessment, investigation, characterization, and remediation, surface and groundwater compliance, decontamination and decommissioning, waste classification and management, and long-term stewardship.