Integrated DNAPL Site Characterization Process
Integrated site characterization (ISC) is a process for improving the efficiency and effectiveness of characterization efforts at DNAPL sites. It encourages characterization at a sufficient resolution to capture the effects of the heterogeneities that direct contaminant distribution, fate, and transport, and remediation effectiveness, so that an integrated three-dimensional conceptual site map (CSM) can be developed and refined.
ISC (Figure 1) supports iterative refinement of the CSM over the project life cycle with information obtained during site investigation, remedy design, and remedy optimization. ISC relies on a systematic objectives-based site characterization process specified in the following. Through ISC, the most appropriate and up-to-date site characterization tools are selected to effectively characterize site stratigraphy, permeability, and contaminant distribution. Once the data are collected, the process includes evaluating and interpreting the data and updating the CSM.
The specific steps in an ISC process are as follows:
- Define the problem and uncertainties in the CSM.
- Identify the data gaps and spatial resolution required in the investigation.
- Establish the data collection objectives.
- Design the data collection process.
- Select the appropriate investigative tools
- Manage, evaluate, and interpret the data.
Figure 1: Integrated site characterization cycle
Define the problem and assess the CSM
The goal of DNAPL ISC is to develop a CSM with sufficient depth and clarity to accurately assess risks and develop appropriate remediation strategies. The first step of the ISC approach is to review the current CSM and determine its adequacy against that goal. If a problem becomes apparent, it should be defined in terms of uncertainties/deficiencies with the CSM so that data needs/gaps and resolution can be identified and characterization objective(s) established. An advantage of defining the problem in terms of uncertainties is that it can help determine the cost benefit, or sustainable return on remediation, of collecting additional data.
Figure 2: Conceptual site model created with data obtained by HRSC tools
Identify Data Needs/Gaps and Resolution
Once the uncertainties in the CSM are recognized, specific data needs (for example, type, location, amount, and quality) as well as data resolution (spacing or density) can be described. Spatial resolution should be assessed laterally and vertically. The goal is to achieve a data resolution related to the scale of subsurface heterogeneity that is effectively controlling contaminant transport and distribution. Data resolution should be commensurate with that scale to ensure that the distribution of contaminants is sufficiently delineated and that an effective remedial strategy, if necessary, can be developed.
Figure 3: HRSC tool such as laser induced fluorescence can provide higher vertical resolution of DNAPL distribution
Establish Data Collection Objectives
Once the data needs (including type and resolution) are identified, specific objectives can be established. Often data collection objectives are vague statements that do not fully describe the intentions and needs of a sampling program—for example, an objective might be to define the lateral and vertical contaminant distribution, and without further specificity, it would be difficult to demonstrate that this objective was met. In this example, the characterization objective should be developed in a way that considers (1) the type of data needed (for example, chemical concentrations); (2) the data density and spatial resolution (for example, lateral and vertical spacing and depth); and (3) the specific concentration endpoints for each contaminant.
Design Data Collection and Analysis Process
Data collection and analysis is simply the implementation of the chosen data measurement system and the subsequent organization of the collected data. Three types of data—quantitative, semiquantitative, and qualitative—are generally collected. All may be collected and analyzed differently. Effective data collection objectives determine the type of data collection required, which tools to use, and how the data will be analyzed. The Tool Selection Worksheet (link to the Worksheet) will aid in selecting the most appropriate tool.
Figure 4: Groundwater sampling is important for collecting direct measurement on DNAPL contaminants
Find more detail in Site Characterization tool Selection that provides guidance on use of the Tool Selection Worksheet.
Perform Data Evaluation and Interpretation
The objective of evaluation and interpretation of site characterization data is to gain a clear understanding of past, present, and potential future environmental conditions at a site. Through the context of the CSM, data evaluation and interpretation can facilitate more informed remedial decisions for the site. Thus, only through data analysis and interpretation can the project team make decisions (for example, characterization efforts answer a stated characterization objective, or an assumption about the conditions of the subsurface are not supported by the data, and the original assumptions must be revisited). Specifically, the data should reduce the levels of uncertainty in the CSM, with respect to the data collection objectives at the site, to an acceptable level. Through integration of all of the data types (geologic, hydrologic, and chemical), collaborative data sets can be generated. This multiple-lines-of-evidence approach enables the CSM to provide a clearer description of contaminant transport, storage, and attenuation.
Update Conceptual Site Model
The overall goal of an ISC is to collect the data necessary to provide an updated, site-specific, three-dimensional CSM, sufficiently detailed at the relevant scale, to effectively and efficiently guide site environmental management. The process of developing and updating the CSM includes compiling and synthesizing existing information, identifying data gaps and uncertainties, and determining subsequent data needs. Oversimplified characterization of subsurface conditions has led to the concept of engineering around geology; however, remedy performance track records have shown that concept to often be flawed.