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Triad Management
 Dynamic Work Strategies
 Key Concepts

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Key Concepts

Dynamic work strategies provide a basis for adapting work activities in response to real-time data while work is underway.

Dynamic work strategies are a product of the systematic planning process. When a review of decision uncertainty, as reflected by the CSM, indicates that there are key information deficiencies contributing to uncertainty, then the two other legs of the Triad, dynamic work strategies and real-time measurement systems, become important tools for cost-effectively managing that uncertainty. Dynamic work strategies address and reflect CSM data gaps. Dynamic work strategies are also an integral part of the feedback process for life-cycle systematic planning. Information generated as part of field activities associated with a dynamic work strategy contributes to the refinement and maturation of the CSM. The refined CSM, in turn, forms the basis for future decisions and additional data collection as necessary.

Dynamic work strategies are captured in planning documents. The implementation of the Triad in general and dynamic work strategies in particular, does not change the overall documentation process required under CERCLA or RCRA. There will still be the need for health and safety plans, quality assurance project plans, sampling and analysis plans, remedial action plans, standard operating procedures, etc., although the character of those plans will change to reflect dynamic work strategies. The nature of those changes will be discussed later in this section.

For any particular field activity, dynamic work strategies do not preclude the use of static strategies (i.e., strategies that specify exactly what field activities will take place). An example of a static data collection strategy is one where samples numbers, sample locations, and analytics are firmly established before field work begins. In fact, under the Triad work strategies will usually combine some level of fixed field activities with other activities that are more dynamic in nature. The best mix will be site and decision-need specific. In some cases a dynamic strategy may result in a work plan that is almost completely static in nature, with contingencies built in to accommodate possible results that are unlikely to occur. In other cases, a dynamic strategy may be based on very little pre-specified activities, with the bulk of work expected to be driven by information and circumstances encountered as work is underway.

An important distinction for dynamic work strategies is the distinction between strategies that actively acquire real-time information to reduce CSM uncertainty and use that information to change the course of field activities, versus strategies that include planning for unlikely project outcomes or conditions that may be encountered while work is underway, but that do not use real-time information gathering to determine whether those conditions exist or not. An example of the former are adaptive data collection programs used to bound contamination extent in soils, with new sample location selection determined by real-time results from previously sampled locations. An example of the latter is planning for field conditions that may adversely affect activities such as unusually wet soils, early snowfall, or high water conditions for programs involving sediments. The latter involves planning that would be expected for any well-managed program, whether the Triad is involved or not. The former is truly characteristic of the Triad.

The concept of a "region or interval of decision uncertainty" is important for dynamic work strategies. The uncertainty interval represents a CSM state, measurement result, or set of measurement results that are insufficient to support confident decision-making. The uncertainty region concept and its relationship to measurement results will be discussed in greater detail in the section entitled Real-Time Measurement Systems. For this section's purposes, what is important is that when information falls in the uncertainty interval, subsequent data collection will likely be required to reduce the uncertainty of the situation to acceptable levels. Additional data collection is "likely," but not "essential" since the cost of collecting additional information may not be worth the uncertainty reduction that will be achieved, and decision-makers may opt for a conservative course of action instead. For example, a real-time screening result may indicate the possibility of contamination above cleanup levels for a particular location. The decision-maker may choose to simply remediate that location if remediation costs are not significant compared to the cost of collecting more definitive information through the use of more rigorous analytical methods.

Contingency planning is a critical step in formulating dynamic work strategies. Contingency planning addresses situations where different possible field activity outcomes require different responses. Dynamic work strategies are usually captured as "if-then" statements, and often formalized as a decision tree. Examples of common generic Triad "if-then" statements built on real-time measurement results include:

  • If a real-time measurement result (or set of results) is below a particular field-based actin level, then contamination is at an acceptable level. Depending on where one is in the characterization/remediation process, an appropriate response might be labeling that area as no further action, skipping over that area during remediation, determining that remedial action performance is acceptable, designating the area for clean-closure confirmation sampling, or concluding that closure has been attained for that area.

  • If a real-time measurement result (or set of results) is above a particular investigation level, then contamination is above acceptable levels. Depending on where one is in the characterization/remediation process, an appropriate response might include labeling that location as an area of concern for future attention, collecting additional neighboring samples to bound extent or assist in estimating impacted volumes, initiating a remedial action at that location, identifying that result as a monitoring issue and taking appropriate corrective actions (including increasing monitoring frequency or checking adjacent wells), or concluding that closure requirements have not been met and initiating additional remedial activities.

  • If a real-time measurement result (or set of results) falls into a range defined as the region of decision uncertainty, then additional actions are required to address the uncertainty inherent in the result. These actions might include collecting additional real-time measurements in the vicinity to reduce sampling uncertainty, submitting one or more samples from that location for a more definitive analysis to control analytical or relational uncertainty, or initiating a remedial action at that location.

  • If a real-time measurement result indicates the possible presence of new contaminants of concern, then appropriate responses might include revisiting analytical requirements to allow for more definitive speciation and quantification of these new contaminants of concern, initiating a process to determine site-specific cleanup objectives for the new contaminants of concern, or revisiting remedial strategies to determine their appropriateness and potential effectiveness for the new contaminants of concern.

  • If focused QA/QC (i.e., QA/QC based on real-time quality control protocols) yields unexpected or unacceptable results, then appropriate corrective actions might include increasing the frequency of QC analyses, re-sampling and re-analyzing areas where results were suspect, modifying measurement approaches to improve overall data quality, or switching to alternative methods to manage quality control concerns.

Dynamic work strategies that involve data collection are typically associated with judgmental sampling programs. This is especially true when contamination is expected to be highly patterned due to release and/or migration mechanisms. Judgmental sampling programs are most commonly used to determine the presence or absence of contamination at levels of concern at specific locations. Location selection is driven by the "weight of evidence" derived from multiple sources of information pertinent to the contamination status of a site. There are also adaptive/sequential sampling program designs that are statistically based, and that can be used to estimate contaminated volumes, determine population characteristics such as the mean or median contamination concentration for an area, or bound contamination extent. While these techniques have not seen wide application, they can be very effective. For adaptive sampling strategies, it is important to have appropriate sampling program design expertise to ensure the program will be both technically defensible when complete, and that the approach is as cost-effective as possible. When considering technical expertise requirements for a project, one should remember that sampling program design issues are intimately intertwined with the selection of analytical techniques, and that addressing decision uncertainty means managing and balancing sampling, analytical, and relational uncertainties concurrently.

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