Dynamic Work Strategies

Dynamic work strategies incorporate the ability to adapt project activities to site conditions as better information becomes available while work is underway.

Dynamic work strategies (DWS) are the second leg of the Triad. DWS refer to strategies that incorporate the ability to adapt project activities to site conditions as better information becomes available while work is underway. DWS are a product of the systematic planning process. When project partners determine during a systematic planning effort that information is needed to achieve project goals, then the other legs of the Triad, DWS and real-time measurement systems (RTMS), become important tools for gathering that information.

DWS are meant to close conceptual site model (CSM) data gaps identified by project planners while providing predetermined decision logic and sufficient flexibility for field crews and project stakeholders to react to site information in a time frame that allows adjustments during field efforts. DWS are also key as part of the feedback process of the project life cycle of systematic planning. Information generated as part of activities associated with a DWS, whether that is field activities (e.g., sampling soil, water, or tank contents) or searching archival records (aerial photographs or maps) contributes to the refinement and maturation of the CSM, which in turn forms the basis for future decisions.

With respect to site assessment activities at petroleum release sites, site characterization will typically involve some combination of a static plan and DWS. A static sampling plan consists of the well-known approach involving the collection of a finite number of samples from fixed points as documented in preapproved sampling and analysis plans. In contrast, DWS are typically based on minimum prespecified activities with the bulk of the work driven by information developed as work is underway. DWS are typically captured by "if-then" statements formalized as a decision tree.

Examples of "if-then" statements include:

• If an RTMS result is above a threshold concentration (i.e., 1,000 mg/kg of petroleum hydrocarbons), then the sampler will "step-out" X distance and collect an additional sample and continue to bound the contaminated medium.
  
  
• If an RTMS result is below a threshold concentration, then the sampler will "step-out" Y distance and collect another sample (see highlight box).

 Dynamic Work Strategy

DWS that involve the collection of environmental media samples for a UST-related project are usually associated with judgmental sampling programs (a sampling program based on professional judgment). A judgmental sampling approach is appropriate because contamination is suspected to have high spatial correlation in a typical UST CSM (Figure 2). To assess the extent of contamination, investigators will likely focus on areas near UST tank pits and product dispensing units, and along the paths of UST fill lines, product distribution pipe chases, and underground utilities. To assess potential receptors, investigators will likely focus on surface water features that drain the site in question, water supply wells, vapor migration/intrusion pathways to inhabited buildings, and sensitive ecological receptors.

Triad-based approaches can result in the rapid generation of significant amounts of data. For example, membrane interface probes (MIPs) can generate data continuously as the probe is advanced into the subsurface. Depending on the project and the data collection methods, data management tools may be needed to organize, manage, and present these data in a meaningful format and in a timely fashion to decision makers. Furthermore, decision makers may be on-site, or they may be physically distant from site activities. Thus, there could be a need to take advantage of multiple communication technologies to get data to the decision makers. The idea of in-field decision support is a unique characteristic of Triad-based work plans. It results in data management requirements that are not typically associated with more traditional sampling programs, where analytical data management becomes an issue only after field work is complete and seldom is time critical.