Paper No. JAWRA-10-0170-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.
Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling1
Article first published online: 22 AUG 2011
© 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA
JAWRA Journal of the American Water Resources Association
Volume 47, Issue 5, pages 916–932, October 2011
How to Cite
Brakebill, J.W., Wolock, D.M. and Terziotti, S.E. (2011), Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling. JAWRA Journal of the American Water Resources Association, 47: 916–932. doi: 10.1111/j.1752-1688.2011.00578.x
Re-use of this article is permitted in accordance with the Terms and Conditions set out at http://wileyonlinelibrary.com/onlineopen#OnlineOpen_Terms
- Issue published online: 10 OCT 2011
- Article first published online: 22 AUG 2011
- Received October 6, 2010; accepted March 30, 2011.
Brakebill, J.W., D.M. Wolock, and S.E. Terziotti, 2011. Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling. Journal of the American Water Resources Association (JAWRA) 47(5):916-932. DOI: 10.1111/j.1752-1688.2011.00578.x
Abstract: Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.