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Hydrologic monitoring and analysis of porous parking lot in Linden, New Jersey
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Meneses, Diego Martin. Hydrologic monitoring and analysis of porous parking lot in Linden, New Jersey. Retrieved from https://doi.org/doi:10.7282/t3-nrsj-ze58

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TitleHydrologic monitoring and analysis of porous parking lot in Linden, New Jersey
NameMeneses, Diego Martin (author); Guo, Qizhong (chair); Mazurek, Monica (internal member); Wang, Ruo-Qian (internal member); Rutgers University; School of Graduate Studies
Date Created2020
Other Date2020-05 (degree)
SubjectPavements, Porous -- New Jersey -- Linden, Civil and Environmental Engineering
Extent1 online resource (xii, 63 pages) : illustrations
DescriptionImpervious surfaces have long been implicated in the increase of stormwater runoff in urban watersheds, leading to flooding even during small to moderate rainfall events. Replacing impervious surfaces with porous pavement could restore the predevelopment hydrology and improve stormwater management. In this study, hydrologic observation and analysis were performed for a 1,450 m^2 porous parking lot located in Linden, New Jersey. Submerged velocity and water level sensors were tested and calibrated before and after data collection. These measurements include effective data from 16 rainfall events to quantify runoff volume, peak flow rate and lag to peak flow. The methods used in the analysis include: the NRCS Curve Number (CN) Method and the Rational Method. The watershed boundaries were delineated through high-resolution land surveys. 3D terrain surface point cloud datasets were obtained by Terrestrial laser scanning (TLS). The datasets generated were imported to the open-source software CloudCompare to perform point-cloud filtering analysis. ArcGIS tools were used to create a Digital Elevation Model (DEM) to perform drainage area delineation analysis. Results from the DEM delineation analysis showed an extra 25% drainage area outside the parking lot itself. Sensor analysis and calibration showed that the sensor works with high accuracy at water depths above 1.4 inches. Linear regression between measured and predicted runoff volume showed a R^2=0.90. The comparison showed a relative variation of 3% with a CN of 95 and 18% with a CN of 84. The rational method showed an overestimate of the peak flow reduction of 30% with a R^2=0.80. The analysis of October 27th rainfall event concluded that the incorporation of the outlet structure in October 2019 increased lag to peak by 34 minutes and reduced the peak flow rate by 72%.

The study demonstrated that a high-resolution drainage area delineation is necessary for small watersheds as the landscape varies over time. The CN of 95 resulted in a better fit for this study, showing the importance of the CN selection as soil conditions and properties are unique. The porous parking lot showed a significant peak flow reduction and a long lag of peak flow, contributing to flooding mitigation.
NoteM.S.
NoteIncludes bibliographical references
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/t3-nrsj-ze58
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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