The DOI matches its Crossref record.
Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach
Abstract
A geostatistical approach is proposed for characterizing the uncertainty about the transmissivity field of an aquifer and analyzing its effect on predicted head values. A new methodology is developed, which couples conditional simulation and groundwater flow modeling. Conditional simulation is used for generating different two‐dimensional transmissivity fields that all have the same spatial variability as the true field and are consistent with the measured T values at well locations. Two case studies are presented in order to illustrate the method, and conclusions are drawn for future investigation.
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Cited by
The future of distributed models: model calibration and uncertainty prediction
Beven, K., & Binley, A. (1992) · Hydrological Processes · doi:10.1002/hyp.3360060305 · Cited by 4,527
Causes and consequences of error in digital elevation models
Fisher, P. F., & Tate, N. J. (2006) · Progress in Physical Geography: Earth and Environment · doi:10.1191/0309133306pp492ra · Cited by 405
Metadata
- Authors
- Delhomme, J. P.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1979-04
- Volume
- 15
- Issue
- 2
- Pages
- 269-280
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2040525640
- Cited by
- 514
- References
- 0
- FWCI
- 29.37
- Type
- journal article
- Language
- en
- Open access
- closed
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- Delhomme, J. P. (1979). Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach. Water Resources Research. https://doi.org/10.1029/wr015i002p00269
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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.
