Making Water Quality Data Understandable Through Online Mapping

Sam McKinley, RA Consultants, LLC

The Metropolitan Sewer District of Greater Cincinnati (MSDGC) has taken on the challenge of making over 4,700 annual water quality data points understandable and accessible to the general public. The data are collected several times a month at 40 testing sites throughout Hamilton County, and track 11 variables that characterize surface water quality. This huge mass of data is difficult for even water quality professionals to put into any meaningful order. Through a new initiative now underway, MSDGC plans to make this data available and understandable to everyone through a new tool that will be launched next year.

MSDGC is under a Clean Water Act consent decree to nearly eliminate the negative effects of the sewer system, combined sewer overflows, and sanitary sewer overflows on water quality. Meeting the requirements of the consent decree is expected to cost over $2 billion and take two decades. The ability to communicate not only the water quality of rivers and streams, but especially the associated improvements to the general public is therefore very important to track improvements to regional water quality.

The planners on the project, not themselves water experts, quickly found that the data must be interpreted in the context of both space and time. For example, water quality can vary significantly as a result of rainfall and seasonal variation. Furthermore, many of the variables must be interpreted in combination. A wide variety of complex data are required to answer the question “how clean is the water in our rivers and streams?”

As a result of the ongoing development of internet mapping applications, the public increasingly accepts, understands, and expects to have access to rich spatial information through the Internet. Planners called on GIS experts to code a custom JavaScript application to give the project a web interface. First, monitoring locations are shown on a county map as clickable icons. Clicking one pulls up both a table of the data at that site and a choice of time-graphs for the individual variables, all from a database on a secure server. The data become available in some form relatively quickly, but water quality professionals on the project can keep working to interpret the data, perhaps to fewer variables or even a single water quality index score. Meanwhile, work can proceed on additional watershed variables, such as rainfall, slope, and imperviousness that help explain the measurements. Finally, planners help determine both what data are technically meaningful and what is meaningful to the general public.

When it launches next year, this powerful tool will help planners work to improve water quality by putting complex data in the hands of planners, policymakers, and average citizens alike.

The author can be reached at
sam_mckinley (at) yahoo (dot) com