Communicating River Quality with Color

The Allegheny and Monongahela combine at the Point near downtown Pittsburgh.

Water color as the human eye sees it is an inherent indicator for quality.  When one imagines a healthy body of water, the color blue comes to mind.  When they imagine a drinkable cup of water, it is clear of floating bits.  And if for some reason that imaginary cup of water was tainted by a bit of stuck-on food that survived the dishwasher, they might pour it down the drain and fetch a new glass.  It is indeed with good reason to consider blue water safe for consumption; pure water, which is free of debris like that stuck-on food, is blue (Lehmann et al.).  When reflecting on the purpose and significance of my research, I recall the instinctive notion inside everyone’s head that “blue water is good”.  Water is also fundamental to life, and in Pittsburgh much of that necessary water is sourced from our rivers.  However, these rivers are presently disturbed by human practices like combined sewer overflow or haunted by acid mine drainage, a reminder of the region’s extensive coal industry.  If one can deem a glass of water unfit for consumption based on a glance at its color, then how might this methodology be translated to our rivers?  Satellites, particularly those of the Landsat missions, have been collecting images of Earth since the mid 1980s.  And like the human eye, they are able to perceive color.  Just as you would check your glass of water before drinking from it, these satellites are able to check the rivers.  Additionally, remotely-sensed imagery from satellites allows for a convenient glance to be made rather than having to send someone into the field for a direct sample (why would you send your glass of water to the lab to test if it is cloudy?).  This is why water color has potential as a quality indicator; Pittsburgh’s unique history and quality-influencing events can be investigated to determine the response in river color. Thus, satellites can keep an eye out for those signals and the rivers can be checked without the need to scoop a jar from them.

Major rivers in the Northeastern United States with points superimposed from which I am deriving water color.

Pursuing water color as a quality indicator reflects my professional goals due to its simultaneous simplicity and appeal.  My enrollment in the sustainability certificate and work as an Eco-Rep has revealed to me that in order to foster participation, whether that is an adoption of stewardship or willingness to listen, the argument must be eye catching.  The challenges addressed in sustainability often require changes in human habit, so the general public will always be an audience I must interact with if I am to be an effective steward of my ambitions.

Observations of river color may not describe a water’s contents as detailed as direct sampling, but it is a metric that requires no instrument (unless you wish to automate its observations with satellites) and offers emotional, eye-catching appeal. There is a relationship between residents and their rivers. I hope to utilize water color to help this relationship become further realized. I will be constructing a map of expected river colors along the major rivers in the Greater Pittsburgh Region and communicate it through avenues with my community partner, Three Rivers Waterkeeper, and the Pittsburgh Water Collaboratory. I will also be visualizing color trends and distributions through data visualizations as to build an understanding of the color response to quality impacting events.

I intend to articulate this experience largely through the skills I have gained through working with satellite data and coding software.  A working knowledge of remote sensing is important for understanding large-scale concerns and I hope to utilized my gained skills in a career that allows me to foster the connection between humanity and the Earth.  Immediately after undergraduate life I will continue to seek opportunities that recognize these skills and interests, whether that is continued experiences in internships or graduate school.

Lehmann MK, Nguyen U, Allan M, Van der Woerd HJ. Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types. Remote Sensing. 2018; 10(8):1273.

2 Comments Add yours

  1. jacksonfilosa says:

    Great post Aaron! I don’t have a lot of previous knowledge about your research topic but you broke it down really well and made it very easy to understand. I’m excited to see what you will continue to find this summer!

  2. staciedow says:

    I agree with Jackson – your first paragraph really broke down your project well for those of us who are not studying in the field. (:

Leave a Reply