Each year, federal, state, private and public groups or agencies, industry, academic researchers and interested citizen organizations spend increasing amounts of time and money on water quality monitoring, data analyses and interpretation.

In order for the information gathered to be useful to other interested parties and to be used for an accurate, cost-effective and efficient assessment of water quality, all monitoring data must come from comparable project design, methods (including QA/QC), analyses and interpretation.

Collaboration among water quality monitoring programs and organizations is possible if there is a technical and administrative framework to promote data comparability and to assure data of known quality. In addition, environmental issues and related data operations are becoming increasingly complex.

Existing and anticipated environmental decision-making objectives drive the need to establish a systematic process and structure. Establishing these characteristics will ensure the data quality and consistency that decision-makers must have if they are to have confidence in the data that supports their decisions. 

Environmental data include any measurements or information that help describe:

• Environmental processes, location, and conditions
• Ecological and human health effects
• The performance of environmental technology 
• Information collected directly from measurements

Environmental data quality assurance and quality control are achieved by adhering to established methods, procedures, and techniques.