2. Regulatory Framework and Challenges for Groundwater Statistics

This section identifies various issues and concerns to consider as you plan use of statistics at a specific site. Presented here is an overview of state and federal regulatory requirements and example applications of statistical methods as they are used in the private sector. The section also introduces some general challenges in the use and application of statistics.

2.1 Regulatory Issues and Barriers

Inconsistent federal, state, and local regulations often complicate the evaluation of groundwater data using statistical methods. Existing regulations differ widely and may not reflect the “state of the science” or recognize the advantages and limitations of current statistical practices. The following summary of regulatory challenges is not an authoritative guide to the regulations, but rather an overview of the widely varying requirements.

2.1.1 State Regulatory Perspective

Based on the ITRC groundwater statistics survey (Appendix E), state guidance on the use of statistics ranged from “not well defined” to “overly prescriptive.” Differences in using statistics exist among various programs within a state. The survey also revealed that some states are in the process of developing statistical guidance. In a few cases, specific programs reject statistical analysis outright.

2.1.2 Federal Regulatory Perspective

USEPA’s Unified Guidance provides recommendations for statistical methods and strategies that can be used to demonstrate compliance with federal RCRAResource Conservation and Recovery Act regulations for regulated units such as landfills and surface impoundments. Statistical evaluations under CERCLAComprehensive Environmental Response, Compensation, and Liability Act can also follow USEPA’s Unified Guidance. The data quality objectivesThe qualitative and quantitative statements derived for the DQO process that clarifies the study’s technical and quality objectives, defines the appropriate type of data, and specifies tolerable levels of potential decision errors that will be used as the basis for establishing the quality and quantity (USEPA 2002b). using USEPA’s seven-step data quality objective (DQO) process (2006a), and characteristics of the data sets (sample sizes and frequency of nondetects), usually drive the test selection. However, for the RCRA cleanup process and other remediation programs, statistical approaches from the earlier USEPA documents may be inconsistent with either the USEPA Unified Guidance or generally accepted current best practices for statistical evaluations. In addition, USEPA has a publication for monitored natural attenuation (MNA) that includes information about using statistics in groundwater evaluations for MNA sites (USEPA 2011).

2.2 Private Sector Perspective

Groundwater statistics are typically used in the private sector to support environmental project management, risk assessment, and decision making. Some of the uses typically include the selection of groundwater sampling frequency, comparison of results of different methods of sample chemical analysis, demonstrating results of differing sample techniques are comparable, and identification of background concentrations. Once statistical analyses are performed, private sector entities must secure regulatory and stakeholder concurrence on acceptability of results.

2.2.1 Examples of Statistics Usage in the Private Sector

Some examples of how statistics have been used for various types or stages of projects in the private sector and potential outcomes and concerns are presented below. Please note that these are for illustrative purposes only to demonstrate concerns that Private Sector users have addressed or need to address, and are by no means exhaustive with respect to either site type or method used. The methods described in these examples are further described in Section 5.

2.3 Challenges for Project Managers

Statistical analysis of groundwater data, and other forms of environmental monitoring data, can present challenges during different project activities (for example, planning, implementation, data interpretation, decision making, and communication). The following key challenges are addressed in this document and the Unified Guidance.

2.3.1 Planning Challenges

These challenges are related to the conceptual understanding of statistical methods, selecting and applying methods to answer study questions, and satisfying the project’s objectives:

2.3.2 Interpretation and Communication Challenges

These challenges are related to interpreting and communicating the results of statistical tests and evaluations to multiple audiences:

2.3.3 Common Misapplications

Just as the application of statistics to groundwater and environmental monitoring presents many challenges, it also affords many opportunities for misuse, misapplication, and misinterpretation. The following list summarizes common misapplications. A more thorough discussion is provided in Appendix B, along with suggestions on how to best address each issue.

Please refer to Appendix B for more common misapplications as well as suggestions for addressing these important issues.

2.3.4 Implementation Challenges

These challenges are related to selecting and using software, enhancing confidence in calculations, and gaining consensus on results:

Publication Date: December 2013

Permission is granted to refer to or quote from this publication with the customary acknowledgment of the source (see suggested citation and disclaimer).


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