Using Cooperative Water Quality Data for a Holistic Understanding of Rivers and Streams: A Study of the Neponset River, Massachusetts

Abstract

Water quality studies seeking to identify modes or processes of river systems often use targeted, researchdesigned, high-frequency data, whereas most water quality data today are collected for monitoring and reporting requirements are of low frequency and are collected through cooperative and volunteer programs. There exists in this situation an information gap between the science of understanding river system dynamics and the collection of data in most of these systems. Using data collected by volunteers in the Neponset Watershed (Massachusetts, U.S.), we demonstrate that multivariate analysis is a viable option for enhancing the use and information of spatially distributed, long-term monitoring data sets common in the United States. Additionally, the geographic, environmental, and time line information inherent in these community-maintained data leads to a more complete picture of river and stream dynamics. Principal component analyses of three distinct reaches with different channel characteristics and surrounding environments demonstrate differences in dominant modes, with undeveloped stretches driven by seasonal processes, and other stretches exhibiting organic or nutrient sources. This type of information can bridge gaps from problem identification or monitoring to a more complete understanding of river system processes influencing water quality, thereby leading to better stewardship of resources. Key Words: cooperative monitoring programs, principal components analyses, water quality.Los estudios de calidad del agua que buscan identificar los modos o procesos de los sistemas fluviales a menudo utilizan datos de alta frecuencia, específicos y diseñados con criterio investigativo, en tanto que ahora la mayor parte de los datos sobre calidad del agua son generados para monitoreo, y los que se requieren para efectos de informes son de frecuencia de flujo y se obtienen por medio de programas cooperativos y de voluntariado. En esta situación se presenta una brecha de información entre la ciencia que busca entender la dinámica de los sistemas fluviales y la recolección de datos en la mayoría de estos sistemas. Mediante el uso de datos recogidos por voluntarios en la Cuenca del Neponset (Massachusetts, EE.UU.), demostramos que el análisis multivariado es una opción viable para mejorar el uso e información de conjuntos de datos de