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Cited by 1,516

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The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models

Quinn, P., Beven, K., Chevallier, P., Planchon, O.·1991·Hydrological Processes

Abstract

The accuracy of the predictions of distributed hydrological models must depend in part on the proper specification of flow pathways. This paper examines some of the problems of deriving flow pathways from raster digital terrain data in the context of hydrological predictions using TOPMODEL. Distributed moisture status is predicted in TOPMODEL on the basis of spatial indices that depend on flow path definition. The sensitivity of this index to flow path algorithm and grid size is examined for the case where the surface topography is a good indicator of local hydraulic gradients. A strategy for the case where downslope subsurface flow pathways may deviate from those indicated by the surface topography is described with an example application.

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Crossref · 10.1002/hyp.3360050106

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Metadata

Authors
Quinn, P., Beven, K., Chevallier, P., & Planchon, O.
Venue
Hydrological Processes
Publisher
Wiley
Published
1991-01
Volume
5
Issue
1
Pages
59-79
ISSN
  • 0885-6087 (ISSN-L)
  • 1099-1085
OpenAlex
W2111552444
Cited by
1,516
References
1
FWCI
27.74
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. https://app.cochat.ai/papers/10.1002/hyp.3360050106
The paper
Quinn, P., Beven, K., Chevallier, P., & Planchon, O. (1991). The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrological Processes. https://doi.org/10.1002/hyp.3360050106

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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.