Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Storm runoff from four characteristic types of residential roofs and incident rainwater were monitored for 47 storm events over a six‐month period at Nacogdoches, Texas, to study water quality conditions for 20 element and four chemical variables. The total element concentration in storm runoff from each roof type was greater than that of rainwater in the open. Differences in element concentrations in storm runoff among the four roof types were statistically significant (α≤ 0.05) with the differences for the wood shingle roof being the greatest and that for terra cotta clay roof being the least. The median concentrations of four element variables exceeded the Texas surface water quality standards, while 12 variables exceeded the standards at least one time in all samples collected. Zinc concentrations violated the Standard ranging from 85.7 percent of the samples for the wood shingle roof to 66.0 percent for the composite shingle, the greatest exceedances of all 24 variables studied. Storm characteristics and gutter maintenance level had some effects on these water quality conditions. The study suggested that roof types can be important to water pollution management programs. More detailed studies on roof water quality in major municipalities are required.
Storm runoff from four characteristic types of residential roofs and incident rainwater were monitored for 47 storm events over a six‐month period at Nacogdoches, Texas, to study water quality conditions for 20 element and four chemical variables. The total element concentration in storm runoff from each roof type was greater than that of rainwater in the open. Differences in element concentrations in storm runoff among the four roof types were statistically significant (α≤ 0.05) with the differences for the wood shingle roof being the greatest and that for terra cotta clay roof being the least. The median concentrations of four element variables exceeded the Texas surface water quality standards, while 12 variables exceeded the standards at least one time in all samples collected. Zinc concentrations violated the Standard ranging from 85.7 percent of the samples for the wood shingle roof to 66.0 percent for the composite shingle, the greatest exceedances of all 24 variables studied. Storm characteristics and gutter maintenance level had some effects on these water quality conditions. The study suggested that roof types can be important to water pollution management programs. More detailed studies on roof water quality in major municipalities are required.
Multievent, conceptually based models and a single-event, multiple linear-regression model for estimating storm-runoff quantity and quality from urban areas were calibrated and verified for four small (57 to 167 acres) basins in the Denver metropolitan area, Colorado. The basins represented different land-use types light commercial, single-family housing, and multifamily housing. Both types of models were calibrated using the same data set for each basin. A comparison was made between the storm-runoff volume, peak flow, and storm-runoff loads of seven water-quality constituents simulated by each of the models using identical verification data sets. The multievent, conceptually based models studied were the U.S. Geological Survey's Distributed Routing Rainfall-Runoff Model Version II (DR3M-II) (a runoff-quantity model designed for urban areas), and a multievent, urban runoff-quality model, DRsM-QUAL. Water-quality constituents modeled were chemical oxygen demand, total suspended solids, total nitrogen, total phosphorus, total lead, total manganese, and total zinc. A multiple linear-regression analysis, based both on log-transformed and untransformed data, was made. A separate regression equation was developed for each runoff characteristic or water-quality constituent, and all the regression equations were basin specific. The two types of models produced comparable results for most runoff characteristics and water-quality constituents in the basins studied. However, development and implementation of multievent, conceptually based models are more costly and time consuming than development and implementation of single-event, multiple linear-regression models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.