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Cited by 843

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Mathematical Modeling of Watershed Hydrology

Singh, Vijay P., Woolhiser, David A.·2002·Journal of Hydrologic Engineering
DOI 10.1061/(asce)1084-0699(2002)7:4(270

Abstract

Mathematical modeling of watershed hydrology is employed to address a wide spectrum of environmental and water resources problems. A historical perspective of hydrologic modeling is provided, and new developments and challenges in watershed models are discussed. These include data acquisition by remote sensing and space technology, digital terrain and elevation models, chemical tracers, geographic information and data management systems, topographic representation, upscaling of hydrologic conservation equations, spatial variability of hydraulic roughness, infiltration and precipitation, spatial and temporal scaling, model calibration, and linking with water quality models. Model construction, calibration, and data processing have received a great deal of attention, while model validation, error propagation, and analyses of uncertainty, risk, and reliability have not been treated as thoroughly. Finally, some remarks are made regarding the future outlook for watershed hydrology modeling.

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Metadata

Authors
Singh, V. P., & Woolhiser, D. A.
Venue
Journal of Hydrologic Engineering
Published
2002-07
Volume
7
Issue
4
Pages
270-292
ISSN
  • 1084-0699 (ISSN-L)
  • 1943-5584
DOI
10.1061/(asce)1084-0699(2002)7:4(270
OpenAlex
W2116397061
Cited by
843
References
2
FWCI
29.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Mathematical Modeling of Watershed Hydrology. https://app.cochat.ai/papers/10.1061/(asce)1084-0699(2002)7:4(270
The paper
Singh, V. P., & Woolhiser, D. A. (2002). Mathematical Modeling of Watershed Hydrology. Journal of Hydrologic Engineering. https://doi.org/10.1061/(asce)1084-0699(2002)7%3A4(270

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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.