Date of Award:

5-2019

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Advisor/Chair:

Jeffery S. Horsburgh

Co-Advisor/Chair:

R. Ryan Dupont

Third Advisor:

David K. Stevens

Abstract

The introduction of pavement, buildings, and other impervious surfaces to urban landscapes greatly influences the quantity and quality of urban stormwater runoff. In this study, we designed and implemented modern stormwater monitoring technologies to establish a “smart” stormwater sensor network within the Northwest Field Canal (NWFC), an urban water conveyance located in Logan, Utah, USA. This network was designed to collect flow and water quality data at high frequencies and simultaneously at multiple locations. The observatory’s innovative method of inter-site communication and changing sampling frequencies during storm events was able to capture short duration events at the upstream and downstream ends of the NWFC and at multiple outfalls in the canal simultaneously without human intervention. We then investigated statistical regression models between turbidity and TSS so as to predict TSS at high frequencies. Finally, the addition of the high-frequency discharge data in the calibration procedure for a stormwater simulation model developed using the Environmental Protection Agency’s Stormwater Management Model did little to improve model performance at the downstream end of the canal, but did provide important insight into the overall contribution of discharge from individual stormwater outfalls to the NWFC. The results of this study inform water professionals on how to build and operate automated monitoring systems and how to create high-frequency estimates of TSS and TP loads in urban water systems.

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