東華大學圖書館 |

Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs // Lin Zheng.
Author:	Zheng, Lin,
Description:	1 electronic resource (134 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
Contained By:	Dissertations Abstracts International86-05A.
Subject:	Water resources management. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31564520
ISBN:	9798342749435

Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs /
Zheng, Lin,

Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs /Lin Zheng. - 1 electronic resource (134 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: A.

Stormwater runoff carries pollutants into the environment and causes damage to properties. Green Stormwater Infrastructure (GSI) is a growing and promising nature-based solution for stormwater management, but the knowledge of its hydrologic processes and ecologic performance under various meteorological and field conditions remains limited. This dissertation research focused on two Green Stormwater Infrastructure practices: constructed permeable surfaces and green roofs. On the one hand, the quantification of rainfall-runoff relationships and initial abstraction (the maximum rainfall loss before surface runoff occurs during a storm event) are among the most significant but uncertain components in hydrologic models to determine the amount of surface runoff from permeable surfaces. On the other hand, though the hydrologic process of green roofs has been widely studied, harsh microclimates on green roofs and the resulting spatial heterogeneity of plant growth have yet to be fully disclosed. The objectives of this dissertation research were to 1) analyze the rainfall-runoff relationships and initial abstraction characteristics of permeable surfaces through comprehensive laboratory experiments and physically based models; 2) identify and quantify the impacts of high substrate temperature on green roof plant growth through field studies.For permeable surfaces, a comprehensive laboratory study covering a wide range of rainfall intensity and subsoil hydraulic conductivity was conducted. Covers of gravel, vegetation, porous hot mix asphalt (HMA), and bare soil were placed on top of subsoils as composite soil columns. Rainfall and runoff quantities of the soil-cover complexes were continuously measured. The rainfall-runoff relationships under various field and meteorological conditions were revealed for the permeable surfaces. Moreover, the data obtained from the laboratory experiments was used to calibrate and validate Rosetta, a program for estimating soil hydraulic parameters in the Richards equation embedded in Hydrus-1D, a physically based mechanistic model to accurately quantify the initial infiltration of the permeable surfaces. A simplified physically based model was proposed utilizing the empirical initial infiltration relationship obtained from the study for easier estimation of initial abstraction of permeable surfaces.For green roofs, field monitoring was conducted on a green roof subject to intense sunlight reflection off the building's exterior wall. Over the span of a year, soil sensors were used to record substrate conditions every 15 minutes, while plant growth metrics were collected manually on a monthly basis. A scoring system was developed to evaluate plant growth. Statistical analyses revealed significant disparities in substrate temperature, moisture content, and plant growth across the green roof. The field observations recorded a maximum substrate temperature of 53°C on the year's hottest day, with a notable maximum spatial temperature variation of approximately 6°C. Through regression analysis, a strong link was found between plant growth and high substrate temperature caused by excessive reflective heat.This dissertation research on constructed permeable surfaces provides civil and environmental engineers with more reliable relationships to simulate initial abstraction and runoff generation for their design and modeling. The modeling efforts help assess the capability of the existing mechanistic model in accurately predicting the initial abstraction and infiltration process of permeable surfaces. This dissertation's research on green roofs highlights the critical issue of reflective heat leading to suboptimal plant growth in certain areas of green roofs, suggesting that architects and practitioners should consider microclimate factors in their designs or incorporate shade structures when necessary. The research results will ultimately lead to enhanced strategies for planning and designing Green Stormwater Infrastructure practices and improve their hydrologic and ecological performance to achieve their long-term success.

English

ISBN: 9798342749435Subjects--Topical Terms:

794747
Water resources management.
Subjects--Index Terms:

Curve number

Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs /
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100 1 $a Zheng, Lin, $e author. $0 (orcid)0009-0004-7580-4115 $3 3830306
245 1 0 $a Green Stormwater Infrastructure: Rainfall-Runoff Relationships for Constructed Permeable Surfaces and Microclimatic Effects on Green Roofs / $c Lin Zheng.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (134 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
500 $a Advisors: Guo, Qizhong Committee members: Miskewitz, Robert; Wang, Ruo-Qian; Nikolopoulos, Efthymios.
502 $b Ph.D. $c Rutgers The State University of New Jersey, School of Graduate Studies $d 2024.
520 $a Stormwater runoff carries pollutants into the environment and causes damage to properties. Green Stormwater Infrastructure (GSI) is a growing and promising nature-based solution for stormwater management, but the knowledge of its hydrologic processes and ecologic performance under various meteorological and field conditions remains limited. This dissertation research focused on two Green Stormwater Infrastructure practices: constructed permeable surfaces and green roofs. On the one hand, the quantification of rainfall-runoff relationships and initial abstraction (the maximum rainfall loss before surface runoff occurs during a storm event) are among the most significant but uncertain components in hydrologic models to determine the amount of surface runoff from permeable surfaces. On the other hand, though the hydrologic process of green roofs has been widely studied, harsh microclimates on green roofs and the resulting spatial heterogeneity of plant growth have yet to be fully disclosed. The objectives of this dissertation research were to 1) analyze the rainfall-runoff relationships and initial abstraction characteristics of permeable surfaces through comprehensive laboratory experiments and physically based models; 2) identify and quantify the impacts of high substrate temperature on green roof plant growth through field studies.For permeable surfaces, a comprehensive laboratory study covering a wide range of rainfall intensity and subsoil hydraulic conductivity was conducted. Covers of gravel, vegetation, porous hot mix asphalt (HMA), and bare soil were placed on top of subsoils as composite soil columns. Rainfall and runoff quantities of the soil-cover complexes were continuously measured. The rainfall-runoff relationships under various field and meteorological conditions were revealed for the permeable surfaces. Moreover, the data obtained from the laboratory experiments was used to calibrate and validate Rosetta, a program for estimating soil hydraulic parameters in the Richards equation embedded in Hydrus-1D, a physically based mechanistic model to accurately quantify the initial infiltration of the permeable surfaces. A simplified physically based model was proposed utilizing the empirical initial infiltration relationship obtained from the study for easier estimation of initial abstraction of permeable surfaces.For green roofs, field monitoring was conducted on a green roof subject to intense sunlight reflection off the building's exterior wall. Over the span of a year, soil sensors were used to record substrate conditions every 15 minutes, while plant growth metrics were collected manually on a monthly basis. A scoring system was developed to evaluate plant growth. Statistical analyses revealed significant disparities in substrate temperature, moisture content, and plant growth across the green roof. The field observations recorded a maximum substrate temperature of 53°C on the year's hottest day, with a notable maximum spatial temperature variation of approximately 6°C. Through regression analysis, a strong link was found between plant growth and high substrate temperature caused by excessive reflective heat.This dissertation research on constructed permeable surfaces provides civil and environmental engineers with more reliable relationships to simulate initial abstraction and runoff generation for their design and modeling. The modeling efforts help assess the capability of the existing mechanistic model in accurately predicting the initial abstraction and infiltration process of permeable surfaces. This dissertation's research on green roofs highlights the critical issue of reflective heat leading to suboptimal plant growth in certain areas of green roofs, suggesting that architects and practitioners should consider microclimate factors in their designs or incorporate shade structures when necessary. The research results will ultimately lead to enhanced strategies for planning and designing Green Stormwater Infrastructure practices and improve their hydrologic and ecological performance to achieve their long-term success.
546 $a English
590 $a School code: 0190
650 4 $a Water resources management. $3 794747
650 4 $a Urban planning. $3 2122922
650 4 $a Climate change. $2 bicssc $3 2079509
650 4 $a Environmental engineering. $3 548583
653 $a Curve number
653 $a Green stormwater infrastructure
653 $a Heat stress
653 $a Initial abstraction
653 $a Microclimates
653 $a Spatial heterogeneity
690 $a 0595
690 $a 0775
690 $a 0404
690 $a 0999
690 $a 0474
710 2 $a Rutgers The State University of New Jersey, School of Graduate Studies. $b Civil and Environmental Engineering. $e degree granting institution. $3 3828033
720 1 $a Guo, Qizhong $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-05A.
790 $a 0190
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31564520