The Green Roof at the OnCenter in Syracuse, New York: Measurements and Modeling with Curve Number and Rational MethodsSource: Journal of Sustainable Water in the Built Environment:;2025:;Volume ( 011 ):;issue: 003::page 04025005-1DOI: 10.1061/JSWBAY.SWENG-529Publisher: American Society of Civil Engineers
Abstract: Green roofs are a modern stormwater management tool with an increasing number of applications across the globe. Implementing these technologies requires conformance with regulatory requirements, for which two methods dominate: the curve number method and the rational method. Universally accepted model inputs (curve number CN and runoff coefficient CV, respectively) do not exist for green roofs, and calculated values vary greatly based on roof composition and location. In this paper, CN and CV are calibrated using 6.3 years of rainfall-runoff data (313 events>2 mm depth) measured on a large extensive green roof in Syracuse, NY. Using calculations recommended by the National Resources Conservation Services (NRCS) to determine curve number, the median event CN and a least-squares estimate both result in a CN of 96. Removing small events (rain depth<12.5 mm) does not change the CN integer value. CN also varies by season: 98 in winter (identical to the value for an impervious surface), 94 in summer, and 96 in spring and fall. Use of the step function method gives CN=94 for the 313 events. Based on the rational method, event CV ranges from 0 to 0.99 with a mean of 0.31 and a median of 0.22; when small events are removed (P<10 mm), the values of CV have a mean of 0.46 and a median of 0.46. Overall, the values skew toward the higher side of what is reported in the literature. This probably reflects the impact of a shallow depth of growth medium, 76.2 mm, and the presence of drain conduits which short-circuit water flows to the drains. The results of this study suggest that the curve number method and rational method are too simple to reflect the complex hydrologic processes taking place on a green roof. However, when a large set of rainfall and runoff data is available, the data can be used to estimate a curve number and runoff coefficient that can then be used to roughly estimate total runoff expected over a long period of time. Designers of stormwater management systems, either gray or green, are required to demonstrate through modeling that their design satisfies regulations for stormwater capture set by the authority-having-jurisdiction (AHJ), usually a local municipality or state. Many modern regulations in urban areas require the use of at least some green infrastructure, limiting new applications of gray infrastructure. In dense urban areas where the surface is mostly covered by concrete or asphalt, green roofs may offer one of the best opportunities for reducing stormwater runoff using green infrastructure. AHJs may specify an appropriate curve number CN or a rational method runoff coefficient CV that designers must use in modeling a practice in their jurisdiction. However, there is limited information available on what reasonable values of CN or CV might be for different designs of green roofs. This research uses six years of hydrologic data from an extensive green roof to find the best estimates of CN and CV. Knowing the characteristics of this green roof and the record of rainstorms over the six-year period, the data presented here can help both regulators and designers of green roofs better understand what values of CN and CV can be reasonably expected.
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| contributor author | Mallory Squier-Babcock | |
| contributor author | Cliff I. Davidson | |
| date accessioned | 2025-08-17T22:21:45Z | |
| date available | 2025-08-17T22:21:45Z | |
| date copyright | 8/1/2025 12:00:00 AM | |
| date issued | 2025 | |
| identifier other | JSWBAY.SWENG-529.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4306828 | |
| description abstract | Green roofs are a modern stormwater management tool with an increasing number of applications across the globe. Implementing these technologies requires conformance with regulatory requirements, for which two methods dominate: the curve number method and the rational method. Universally accepted model inputs (curve number CN and runoff coefficient CV, respectively) do not exist for green roofs, and calculated values vary greatly based on roof composition and location. In this paper, CN and CV are calibrated using 6.3 years of rainfall-runoff data (313 events>2 mm depth) measured on a large extensive green roof in Syracuse, NY. Using calculations recommended by the National Resources Conservation Services (NRCS) to determine curve number, the median event CN and a least-squares estimate both result in a CN of 96. Removing small events (rain depth<12.5 mm) does not change the CN integer value. CN also varies by season: 98 in winter (identical to the value for an impervious surface), 94 in summer, and 96 in spring and fall. Use of the step function method gives CN=94 for the 313 events. Based on the rational method, event CV ranges from 0 to 0.99 with a mean of 0.31 and a median of 0.22; when small events are removed (P<10 mm), the values of CV have a mean of 0.46 and a median of 0.46. Overall, the values skew toward the higher side of what is reported in the literature. This probably reflects the impact of a shallow depth of growth medium, 76.2 mm, and the presence of drain conduits which short-circuit water flows to the drains. The results of this study suggest that the curve number method and rational method are too simple to reflect the complex hydrologic processes taking place on a green roof. However, when a large set of rainfall and runoff data is available, the data can be used to estimate a curve number and runoff coefficient that can then be used to roughly estimate total runoff expected over a long period of time. Designers of stormwater management systems, either gray or green, are required to demonstrate through modeling that their design satisfies regulations for stormwater capture set by the authority-having-jurisdiction (AHJ), usually a local municipality or state. Many modern regulations in urban areas require the use of at least some green infrastructure, limiting new applications of gray infrastructure. In dense urban areas where the surface is mostly covered by concrete or asphalt, green roofs may offer one of the best opportunities for reducing stormwater runoff using green infrastructure. AHJs may specify an appropriate curve number CN or a rational method runoff coefficient CV that designers must use in modeling a practice in their jurisdiction. However, there is limited information available on what reasonable values of CN or CV might be for different designs of green roofs. This research uses six years of hydrologic data from an extensive green roof to find the best estimates of CN and CV. Knowing the characteristics of this green roof and the record of rainstorms over the six-year period, the data presented here can help both regulators and designers of green roofs better understand what values of CN and CV can be reasonably expected. | |
| publisher | American Society of Civil Engineers | |
| title | The Green Roof at the OnCenter in Syracuse, New York: Measurements and Modeling with Curve Number and Rational Methods | |
| type | Journal Article | |
| journal volume | 11 | |
| journal issue | 3 | |
| journal title | Journal of Sustainable Water in the Built Environment | |
| identifier doi | 10.1061/JSWBAY.SWENG-529 | |
| journal fristpage | 04025005-1 | |
| journal lastpage | 04025005-10 | |
| page | 10 | |
| tree | Journal of Sustainable Water in the Built Environment:;2025:;Volume ( 011 ):;issue: 003 | |
| contenttype | Fulltext |