The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis
Abstract
The topography of hillslopes or whole catchments is analyzed numerically to calculate local geometric and drainage attributes that can be combined to test for the expectation of soil waterlogging. At locations where accumulated drainage flux from upslope exceeds the product of soil transmissivity and the local slope, saturation to the soil surface occurs. Results of the analysis of specific landscapes are presented as a location dependent function. The function may be mapped as isolines to define successive boundaries of zones of soil saturation, depending on the wetness state of the landscape as a whole. The analysis is applied to two catchments, to predict the growth or contraction of zones of waterlogging for a range of drainage fluxes and to simulate the effects of transpiration changes in part or all of the catchment. In the second application, the predicted boundaries of saturated zones are used to calculate the minimum proportion of a catchment's area that produces rapid surface runoff. This proportion is shown to depend on the value of a normalized wetness parameter. Storm runoff data support the predicted form of the relationship.
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Citations
Cites
BEVEN, K. J., & KIRKBY, M. J. (1979) · Hydrological Sciences Bulletin · doi:10.1080/02626667909491834 · Cited by 6,670
Metadata
- Authors
- O'Loughlin, E. M.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1986-05
- Volume
- 22
- Issue
- 5
- Pages
- 794-804
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2142465731
- Cited by
- 752
- References
- 1
- FWCI
- 25.12
- Type
- journal article
- Language
- en
- Open access
- closed
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- O'Loughlin, E. M. (1986). Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis. Water Resources Research. https://doi.org/10.1029/wr022i005p00794
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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.