Green Infrastructure System Function Remains Uncertain due to Inadequate Monitoring

Abstract:

Aging infrastructure creates an opportunity to widely implement green infrastructure (GI) systems and address multiple bottom lines. Many times, GI is implemented in an adaptive management framework where observations of GI are assumed to improve design. However, the function of GI systems is not uniformly assessed, undermining the adaptive management process. Our work gathers and synthesizes a wide variety of GI monitoring data from Pittsburgh (PA, USA), a city facing a multi-billion-dollar consent decree to eliminate sewer overflows. These data are typically gathered by ad hoc groups of volunteers and non-profit organizations using available and affordable sensors. Evaluation of long-term data series (>1 year) reveals consistent processes that diminish the value of the GI characterizations: 1) Substantial changes in sensor data streams do not necessarily result in changes to GI management or maintenance.; 2) Reliance on “summer intern” monitoring fails to capture seasonal dynamics, limiting inference.; 3) Rapid turnover in personnel and ambiguity in responsibility leads to data gaps and uncertain data. For example, observations of extreme conductivities are hard to interpret as calibration ranges are not recorded (if the sensors are calibrated at all) and observations of these extreme values are not evaluated with field checks. GI monitoring remains inadequate and this poor documentation of GI function inhibits adoption of these management tools and degrades potential benefits to multiple bottom line accounting.