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Cited by 311

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Catchment hydrologic response with a fully distributed triangulated irregular network model

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Ivanov, Valeriy Y., Vivoni, Enrique R., Bras, Rafael L., Entekhabi, Dara·2004·Water Resources Research

Abstract

This study explores various aspects of catchment hydrology based on a mechanistic modeling of distributed watershed processes. A new physics‐based, distributed‐parameter hydrological model that uses an irregular spatial discretization is introduced. The model accounts, on a continuous basis, for the processes of rainfall interception, evapotranspiration, moisture dynamics in the unsaturated and saturated zones, and runoff routing. Simulations of several mid‐ to large‐sized watersheds (∼10 3 km 2) highlight various dynamic relationships between the vadose zone–groundwater processes and their dependence on the land surface characteristics. It is argued that the model inferences can be used for interpretation of distributed relationships in a catchment. By exploiting a multiple‐resolution representation, the hydrologic features of the watershed terrain are captured with only 5–10% of the original grid nodes. This computational efficiency suggests the feasibility of the operational use of fully distributed, physics‐based models for large watersheds.

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Metadata

Authors
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., & Entekhabi, D.
Venue
Water Resources Research
Published
2004-11
Volume
40
Issue
11
ISSN
  • 0043-1397 (ISSN-L)
  • 1944-7973
OpenAlex
W1802734833
Cited by
311
References
0
FWCI
7.65
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Catchment hydrologic response with a fully distributed triangulated irregular network model. https://app.cochat.ai/papers/10.1029/2004wr003218
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Ivanov, V. Y., Vivoni, E. R., Bras, R. L., & Entekhabi, D. (2004). Catchment hydrologic response with a fully distributed triangulated irregular network model. Water Resources Research. https://doi.org/10.1029/2004wr003218

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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.