Interest in volunteer fresh water monitoring in New Zealand has grown rapidly over the last 20 years, including for evaluating the effectiveness of restoration efforts and contributing to freshwater management discussions with local and central government agencies. There is an increasing expectation amongst many volunteer groups that their data will contribute to reporting and decision making, but for many reasons this may not occur. From a government perspective, there can be scepticism over the quality of volunteer-collected data. Volunteers inexperienced with best practice collection of scientific freshwater data can indeed cause bias or errors in data collection, impacting data quality. However, recent research by NIWA has demonstrated that, with good training and support, volunteers can reliably measure many elements of stream water quality and ecological health.
There is a rapidly emerging need to develop a national quality assurance (QA) framework for volunteer-based monitoring and crowd sourcing initiative. This framework needs to address various monitoring purposes, recognising that data accuracy, precision and QA requirements will likely vary with the intended end use(s) of the collected data. Such a framework would give regional authorities and other agencies responsible for water monitoring and management confidence that volunteer data are sufficiently robust for specific purposes. Conversely, a QA framework could provide a means of giving volunteers (e.g., catchment/stream care community groups and landowners) confidence that their measurements are reliable and useful. In addition, a QA framework could also demonstrate where and when volunteer water monitoring could be most effective in augmenting and complementing professionally-collected data (e.g., State of the Environment monitoring).
Here we outline considerations for a QA framework from discussions with various ‘stakeholders’ and a review of current frameworks in place worldwide. We will also outline approaches for comparing and validating freshwater data collected by community volunteers (i.e., replication, expert review, outlier screening).