The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Deuterium variations in storm rainfall: Implications for stream hydrograph separation
Abstract
Isotopic variation in storm rainfall is an important consideration in hydrograph separation using the mass balance approach but is rarely considered when determining the accuracy of old water estimates. Study of a small watershed on the South Island of New Zealand in which new water is a major component of the storm hydrograph shows that, in addition to the within‐storm isotopic variations themselves, rainfall weighting techniques may substantially influence estimates of old/new water as a function of both total runoff and total quick flow production. Two incremental approaches to rainfall weighting are presented. Results show that within‐storm incremental weighting is better than the standard weighting technique, which imposes a total storm rainfall value exogenously on the mass balance equation.
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Citations
Cites
Standard for Reporting Concentrations of Deuterium and Oxygen-18 in Natural Waters
Craig, H. (1961) · Science · doi:10.1126/science.133.3467.1833 · Cited by 2,013
Cited by
Isotope hydrograph separations and rapid delivery of pre-event water from drainage basins
Buttle, J. M. (1994) · Progress in Physical Geography: Earth and Environment · doi:10.1177/030913339401800102 · Cited by 535
Metadata
- Authors
- McDonnell, J. J., Bonell, M., Stewart, M. K., & Pearce, A. J.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1990-03
- Volume
- 26
- Issue
- 3
- Pages
- 455-458
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2021879766
- Cited by
- 297
- References
- 1
- FWCI
- 11.75
- 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.
