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4. Figure code for model archive: Identifying structural priors in a hybrid differentiable model for stream water temperature modeling

Dates

Publication Date
Start Date
2009-10-01
End Date
2016-09-30

Citation

Rahmani, F., Appling, A., Feng, D., Lawson, K., and Shen, C., 2023, Identifying structural priors in a hybrid differentiable model for stream water temperature modeling at 415 U.S. basin outlets, 2010-2016: U.S. Geological Survey data release, https://doi.org/10.5066/P9UDDHVD.

Summary

This section provides code for reproducing the figures in Rahmani et al. (2023b). The full model archive is organized into these four child items: 1. Model code - Python files and README for reproducing model training and evaluation 2. Inputs - Basin attributes and shapefiles, forcing data, and stream temperature observations 3. Simulations - Simulation descriptions, configurations, and outputs [THIS ITEM] 4. Figure code - Jupyter notebook to recreate the figures in Rahmani et al. (2023b) The publication associated with this model archive is: Rahmani, F., Appling, A.P., Feng, D., Lawson, K., and Shen, C. 2023b. Identifying structural priors in a hybrid differentiable model for stream water temperature modeling. Water Resources [...]

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Attached Files

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WRR_figures.ipynb 42.15 KB text/plain

Purpose

Water quality research; proof of concept for advancement of hydrologic process representations and predictions via machine learning

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  • USGS Data Release Products

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