The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Topographic Partition of Watersheds with Digital Elevation Models
Abstract
Digital elevation models are used to automatically map the stream channel and divide networks of a watershed. These topographic skeletons are used to partition the watershed into a set of fundamental, runoff producing subregions, each of which drains into one stream link. Construction of a code describing the network topology, along with parallel files containing attribute information of each drainage area and associated stream link may form the basis for an efficient watershed information system. Registration of remotely sensed imagery and maps of important soils information to the digital elevation model allows an effective organization of this data as input to hydrologic simulation models. The methodology described here is designed to aid in the efficient parameterization of a distributed components approach to watershed simulation.
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Citations
Cites
BEVEN, K. J., & KIRKBY, M. J. (1979) · Hydrological Sciences Bulletin · doi:10.1080/02626667909491834 · Cited by 6,670
Cited by
Tarboton, D. G. (1997) · Water Resources Research · doi:10.1029/96wr03137 · Cited by 2,476
Wang, L., & Liu, H. (2006) · International Journal of Geographical Information Science · doi:10.1080/13658810500433453 · Cited by 506
Physically based modeling in catchment hydrology at 50: Survey and outlook
Paniconi, C., & Putti, M. (2015) · Water Resources Research · doi:10.1002/2015wr017780 · Cited by 374
(1991) · Photogrammetric Engineering & Remote Sensing
Metadata
- Authors
- Band, L. E.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1986-01
- Volume
- 22
- Issue
- 1
- Pages
- 15-24
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2008746426
- Cited by
- 678
- References
- 1
- FWCI
- 18.56
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
