The DOI matches its Crossref record.
The concept of entropy in landscape evolution
Open accessAbstract
The concept of entropy is expressed in terms of probability of various states. Entropy treats of the distribution of energy. The principle is introduced that the most probable condition exists when energy in a river system is as uniformly distributed as may be permitted by physical constraints. From these general considerations equations for the longitudinal profiles of rivers are derived that are mathematically comparable to those observed in the field. The most probable river profiles approach the condition in which the downstream rate of production of entropy per unit mass is constant. Hydraulic equations are insufficient to determine the velocity, depths, and slopes of rivers that are themselves authors of their own hydraulic geometries. A solution becomes possible by introducing the concept that the distribution of energy tends toward the most probable. This solution leads to a theoretical definition of the hydraulic geometry of river channels that agrees closely with field observations. The most probable state for certain physical systems can also be illustrated by random-walk models. Average longitudinal profiles and drainage networks were so derived and these have the properties implied by the theory. The drainage networks derived from random walks have some of the principal properties demonstrated by the Horton analysis; specifically, the logarithms of stream length and stream numbers are proportional to stream order.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/f80-017 · Cited by 9,984
Statistical Law of Stream Numbers
Shreve, R. L. (1966) · The Journal of Geology · doi:10.1086/627137 · Cited by 940
Corenblit, D., Tabacchi, E., Steiger, J., & Gurnell, A. M. (2007) · Earth-Science Reviews · doi:10.1016/j.earscirev.2007.05.004 · Cited by 721
Scaling, Universality, and Geomorphology
Dodds, P. S., & Rothman, D. H. (2000) · Annual Review of Earth and Planetary Sciences · doi:10.1146/annurev.earth.28.1.571 · Cited by 304
Stream Lengths and Basin Areas in Topologically Random Channel Networks
Shreve, R. L. (1969) · The Journal of Geology · doi:10.1086/628366 · Cited by 269
Metadata
- Authors
- Leopold, L. B., & Langbein, W. B.
- Venue
- Professional Paper
- Publisher
- US Geological Survey
- Published
- 1962
- Pages
- A1-A20
- ISSN
- 1044-9612 (ISSN-L)
- 2330-7102
- OpenAlex
- W1550798515
- Cited by
- 679
- References
- 0
- Type
- report
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.