The DOI matches its Crossref record.
Noah, Joseph, and Operational Hydrology
Abstract
By ‘Noah Effect’ we designate the observation that extreme precipitation can be very extreme indeed, and by ‘Joseph Effect’ the finding that a long period of unusual (high or low) precipitation can be extremely long. Current models of statistical hydrology cannot account for either effect and must be superseded. As a replacement, ‘self‐similar’ models appear very promising. They account particularly well for the remarkable empirical observations of Harold Edwin Hurst. The present paper introduces and summarizes a series of investigations on self‐similar operational hydrology.
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Cited by
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Bariviera, A. F. (2017) · Economics Letters · doi:10.1016/j.econlet.2017.09.013 · Cited by 617
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Eliazar, I. I., & Sokolov, I. M. (2010) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2009.08.006 · Cited by 85
Metadata
- Authors
- Mandelbrot, B. B., & Wallis, J. R.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1968-10
- Volume
- 4
- Issue
- 5
- Pages
- 909-918
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2036608004
- Cited by
- 1,117
- References
- 0
- FWCI
- 37.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Noah, Joseph, and Operational Hydrology. https://app.cochat.ai/papers/10.1029/wr004i005p00909
- The paper
- Mandelbrot, B. B., & Wallis, J. R. (1968). Noah, Joseph, and Operational Hydrology. Water Resources Research. https://doi.org/10.1029/wr004i005p00909
Data sources
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.
