Conference Editor

Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer

Location

Syracuse, NY

Event Website

http://ibpc2018.org/

Start Date

25-9-2018 3:15 PM

End Date

25-9-2018 5:00 PM

Description

Green roof technology plays a large role managing stormwater runoff in urban areas, where impervious surfaces cause substantial amounts of stormwater runoff to enter combined sewer systems. If the stormwater flow exceeds the capacity of treatment plants, this often results in the discharge of raw sewage into nearby bodies of water. Green roofs can reduce the occurrence of raw sewage discharge by decreasing the amount of mixed wastewater and stormwater flowing into combined sewers. Engineers and designers are looking for ways to improve the performance of green roofs and to understand parameters such as field capacity and time to onset of runoff. A better understanding of field capacity could be used to test hydrologic models that predict how much water a green roof could store under different conditions and to estimate how much runoff could be reduced. In this project, a drip-type rain simulator is used to estimate field capacity of a plot of soil and sedum taken from the green roof on the Onondaga County Convention Center in Syracuse, NY. Three soil moisture sensors place d into the plot are used with different rain intensities to track the increase in soil water content during rain and the decrease following the end of the rain. The experimental results show that the field capacity of the Convention Center green roof is about 0.081 m3 water / m3 soil. This value is lower than expected and additional testing is underway. It is also shown that as rain intensity increases, time to onset of runoff decreases. With additional experiments to be conducted in Summer 2018, results of this work can be used by engineers to design and install green roofs with field capacities that complement average rain intensities and peak rain intensities and effectively reduce runoff.

Comments

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DOI

https://doi.org/10.14305/ibpc.2018.ps04

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 25th, 3:15 PM Sep 25th, 5:00 PM

A Rain Simulator to Examine Green Roof and Soil Moisture Sensor Performance

Syracuse, NY

Green roof technology plays a large role managing stormwater runoff in urban areas, where impervious surfaces cause substantial amounts of stormwater runoff to enter combined sewer systems. If the stormwater flow exceeds the capacity of treatment plants, this often results in the discharge of raw sewage into nearby bodies of water. Green roofs can reduce the occurrence of raw sewage discharge by decreasing the amount of mixed wastewater and stormwater flowing into combined sewers. Engineers and designers are looking for ways to improve the performance of green roofs and to understand parameters such as field capacity and time to onset of runoff. A better understanding of field capacity could be used to test hydrologic models that predict how much water a green roof could store under different conditions and to estimate how much runoff could be reduced. In this project, a drip-type rain simulator is used to estimate field capacity of a plot of soil and sedum taken from the green roof on the Onondaga County Convention Center in Syracuse, NY. Three soil moisture sensors place d into the plot are used with different rain intensities to track the increase in soil water content during rain and the decrease following the end of the rain. The experimental results show that the field capacity of the Convention Center green roof is about 0.081 m3 water / m3 soil. This value is lower than expected and additional testing is underway. It is also shown that as rain intensity increases, time to onset of runoff decreases. With additional experiments to be conducted in Summer 2018, results of this work can be used by engineers to design and install green roofs with field capacities that complement average rain intensities and peak rain intensities and effectively reduce runoff.

https://surface.syr.edu/ibpc/2018/posters/4

 

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