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Python tool to modify SWAT model input files for the Spatial Factor Substitution (SFS) method


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Resource type: Composite Resource
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Created: Nov 20, 2019 at 6:28 p.m.
Last updated: Dec 03, 2019 at 8:29 p.m.
DOI: 10.4211/hs.94a5baa2cc774cd48ba3174bc9a71f22
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Sharing Status: Published
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Abstract

This site provides the Python code we used to modify SWAT model input files for the Spatial Factor Substitution (SFS) method of Jepsen and Harmon (in press). In the SFS method, categorical factors are transferred from a "source" subbasin to a "target" subbasin of a watershed according to a prescribed space-for-time substitution scenario. Categorical factors handled in this Python code are precipitation time series, air temperature time series, land cover, soil type, and slope. We developed the SFS method to resolve landscape contributions to an elevational gradient in long-term ET, and the influence of the "covariance-stationarity" assumption of a typical space-for-time substitution model of climate warming (Jepsen and Harmon, in press).

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Related Resources

The content of this resource is part of: Jepsen, S. M., & Harmon, T. C. (in press). Resolving drivers of a spatial gradient in evapotranspiration through the simulated translocation of landscape factors. Water Resources Research. https://doi.org/10.1029/2019WR025811

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
Inter-American Institute for Global Change Research (IAI) CRN3038
National Science Foundation CBET 1336839
University of California, Merced

How to Cite

Jepsen, S. M., T. C. Harmon (2019). Python tool to modify SWAT model input files for the Spatial Factor Substitution (SFS) method, HydroShare, https://doi.org/10.4211/hs.94a5baa2cc774cd48ba3174bc9a71f22

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
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