Cited by 6,670Hydrology and Watershed Management StudiesGroundwater and Watershed AnalysisSoil Moisture and Remote Sensing

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A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant

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BEVEN, K. J., KIRKBY, M. J.·1979·Hydrological Sciences Bulletin

DOI 10.1080/02626667909491834

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Abstract

A hydrological forecasting model is presented that attempts to combine the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lumped parameter basin models. Quick response flow is predicted from a storage/contributing area relationship derived analytically from the topographic structure of a unit within a basin. Average soil water response is represented by a constant leakage infiltration store and an exponential subsurface water store. A simple non-linear routing procedure related to the link frequency distribution of the channel network completes the model and allows distinct basin sub-units, such as headwater and sideslope areas to be modelled separately. The model parameters are physically based in the sense that they may be determined directly by measurement and the model may be used at ungauged sites. Procedures for applying the model and tests with data from the Crimple Beck basin are described. Using only measured and estimated parameter values, without optimization, the model makes satisfactory predictions of basin response. The modular form of the model structure should allow application over a range of small and medium sized basins while retaining the possibility of including more complex model components when suitable data are available.

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Handbook of applied hydrology
Chow, V. T. (2010) · Cited by 3,340
The Rôle of infiltration in the hydrologic cycle
Horton, R. (1933) · Transactions American Geophysical Union · doi:10.1029/tr014i001p00446 · Cited by 1,828
Partial Area Contributions to Storm Runoff in a Small New England Watershed
Dunne, T., & Black, R. D. (1970) · Water Resources Research · doi:10.1029/wr006i005p01296 · Cited by 1,191
A stochastic‐conceptual analysis of one‐dimensional groundwater flow in nonuniform homogeneous media
Freeze, R. A. (1975) · Water Resources Research · doi:10.1029/wr011i005p00725 · Cited by 1,011
The form of the instantaneous unit hydrograph
Nash, J. E. (1957) · NERC Open Research Archive (Natural Environment Research Council) · Cited by 676
A general theory of the unit hydrograph
Dooge, J. C. I. (1959) · Journal of Geophysical Research Atmospheres · doi:10.1029/jz064i002p00241 · Cited by 453
What is watershed runoff?
Betson, R. P. (1964) · Journal of Geophysical Research Atmospheres · doi:10.1029/jz069i008p01541 · Cited by 444
Role of subsurface flow in generating surface runoff: 2. Upstream source areas
Freeze, R. A. (1972) · Water Resources Research · doi:10.1029/wr008i005p01272 · Cited by 373
Storage and the Unit Hydrograph
Clark, C. O. (1945) · Transactions of the American Society of Civil Engineers · doi:10.1061/taceat.0005800 · Cited by 359
Spatial analysis in geomorphology
Krumbein, W. C. (1973) · Earth-Science Reviews · doi:10.1016/0012-8252(73)90079-2 · Cited by 345

Show all 27 references

Research works printed but not linked: 16

Beven K.J., 1975, A deterministic, spatially distributed model of catchment hydrology. Unpublished Ph D thesis, School of Environmental Sciences, University of East Anglia.
Beven K.J., 1976, Working Paper 146, School of Geography, University of Leeds.
Beven K.J., 1976, Working Paper 154, School of Geography, University of Leeds.
Douglas J.R., 1974, Report No. 24, Institute of Hydrology, Wallingford.
Dunne T., 1975, Hydrol. Sci. Bull., 20, 305
Freeze R.A., 1972, Wat. Resour. Res. 8 (5), 1272.
Harris G., 1975, Working Paper No. 102, School of Geography, University of Leeds.
Kirkby M.J., 1969, Water, Earth and Man, 215
Kirkby M.J., 1974, Seminar Paper Series B, No. 3, Department of Geography, University of Bristol.
Kirkby M.J., 1976, Working Paper No. 167, School of Geography, University of Leeds.
Knapp B.J., 1974, Fluvial Processes in Instrumented Watersheds
Lambert A.O., 1969, J. Instn Wat. Engrs, 23, 231
Lambert A.O., 1972, J. Instn Wat. Engrs, 26
Nash J.E., 1957, General Assembly of Toronto, Vol. III Surface Waters, Prevision, Evaporation, 114
1975, Flood Studies Report.
Plinston D.T., 1971, Symposium on mathematic models in ecology

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Authors: BEVEN, K. J., & KIRKBY, M. J.
Affiliations: University of Leeds (GB)
ORCID: BEVEN, K. J.
KIRKBY, M. J.
Venue: Hydrological Sciences Bulletin
Publisher: Informa UK Limited
Published: 1979-03
Volume: 24
Issue: 1
Pages: 43-69
ISSN: 0303-6936 (ISSN-L)
DOI: 10.1080/02626667909491834
OpenAlex: W1981646498
Cited by: 6,670
References: 27
Citations by year: 2026: 415 · 2025: 413 · 2024: 381 · 2023: 340 · 2022: 444 · 2021: 415 · 2020: 320 · 2019: 335 · 2018: 284 · 2017: 262 · 2016: 287 · 2015: 240 · 2014: 219 · 2013: 226 · 2012: 208
FWCI: 6.23
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Hydrological Sciences Bulletin (publishedVersion)
Funders: Natural Environment Research Council
Topics: Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
Physical Sciences › Environmental Science › Environmental Engineering › Groundwater and Watershed Analysis
Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
Keywords: river basin hydrology, ungauged sites, physically based hydrological model

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A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant

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