Literature DB >> 27094440

Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management.

Scott M Beck1, Melissa R McHale2, George R Hess2.   

Abstract

Impervious surfaces degrade urban water quality, but their over-coverage has not explained the persistent water quality variation observed among catchments with similar rates of imperviousness. Land-cover patterns likely explain much of this variation, although little is known about how they vary among watersheds. Our goal was to analyze a series of urban catchments within a range of impervious cover to evaluate how land-cover varies among them. We then highlight examples from the literature to explore the potential effects of land-cover pattern variability for urban watershed management. High-resolution (1 m(2)) land-cover data were used to quantify 23 land-cover pattern and stormwater infrastructure metrics within 32 catchments across the Triangle Region of North Carolina. These metrics were used to analyze variability in land-cover patterns among the study catchments. We used hierarchical clustering to organize the catchments into four groups, each with a distinct landscape pattern. Among these groups, the connectivity of combined land-cover patches accounted for 40 %, and the size and shape of lawns and buildings accounted for 20 %, of the overall variation in land-cover patterns among catchments. Storm water infrastructure metrics accounted for 8 % of the remaining variation. Our analysis demonstrates that land-cover patterns do vary among urban catchments, and that trees and grass (lawns) are divergent cover types in urban systems. The complex interactions among land-covers have several direct implications for the ongoing management of urban watersheds.

Keywords:  GIS; Remote sensing; Urban ecology; Water quality

Mesh:

Year:  2016        PMID: 27094440     DOI: 10.1007/s00267-016-0700-8

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  5 in total

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Authors:  A P Davis; M Shokouhian; S Ni
Journal:  Chemosphere       Date:  2001-08       Impact factor: 7.086

2.  A watershed-scale model for predicting nonpoint pollution risk in North Carolina.

Authors:  Kevin M Potter; Frederick W Cubbage; Gary B Blank; Rex H Schaberg
Journal:  Environ Manage       Date:  2004-05-13       Impact factor: 3.266

3.  Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

Authors:  Bethany Pratt; Heejun Chang
Journal:  J Hazard Mater       Date:  2012-01-10       Impact factor: 10.588

4.  Storm water runoff concentration matrix for urban areas.

Authors:  P Göbel; C Dierkes; W G Coldewey
Journal:  J Contam Hydrol       Date:  2006-12-13       Impact factor: 3.188

5.  The influence of urban density and drainage infrastructure on the concentrations and loads of pollutants in small streams.

Authors:  Belinda E Hatt; Tim D Fletcher; Christopher J Walsh; Sally L Taylor
Journal:  Environ Manage       Date:  2004-05-28       Impact factor: 3.266

  5 in total
  4 in total

1.  Driving forces of impervious surface in a world metropolitan area, Shanghai: threshold and scale effect.

Authors:  Bingbing Fu; Yuru Peng; Jun Zhao; Chenhao Wu; Qiuxia Liu; Kexin Xiao; Guangren Qian
Journal:  Environ Monit Assess       Date:  2019-11-26       Impact factor: 2.513

2.  Spatio-temporal dynamics of water quality and their linkages with the watershed landscape in highly disturbed headwater watersheds in China.

Authors:  Wangshou Zhang; Dongqiang Chen; Hengpeng Li
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-19       Impact factor: 4.223

3.  Influence of high-resolution data on the assessment of forest fragmentation.

Authors:  J Wickham; K H Riitters
Journal:  Landsc Ecol       Date:  2019-09-01       Impact factor: 3.848

4.  Analysis of urban land cover influence to organic carbon and nutrients in surface water via impacted groundwater.

Authors:  Katarzyna Puczko; Elżbieta Jekatierynczuk-Rudczyk
Journal:  Environ Monit Assess       Date:  2020-01-27       Impact factor: 2.513

  4 in total

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