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| Created: | Aug 23, 2021 at 10:18 p.m. | |
| Last updated: | Aug 23, 2021 at 11:42 p.m. | |
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Abstract
The multiple-try Differential Evolution Adaptive Metropolis (ZS) (MT-DREAM(ZS)) algorithm was used to quantify the uncertainty in the prediction of the Indicators of Hydrologic Alteration (IHA) and The Magnificent Seven indices from simulated streamflows. For modeling purposes, we used the Soil and Water Assessment Tool (SWAT) in an agriculture-dominated watershed in Michigan, US. We linked multi-objective calibration results using the U-NSGA-III algorithm with Bayesian parameter estimation via the prior distribution for model parameters. Here we provide the (posterior) sampled parameter values, the streamflow predictions, and the relative errors for the predicted hydrologic indices under different calibration settings. In addition, we provide the MATLAB codes for reproducing figures representing model parameter variability ranges, performance of streamflow predictions, and variability in predicted hydrologic indices.
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| The content of this resource was created by a related App or software program | https://github.com/jshernandezs/swat-pytools/tree/main/src/MTDREAM_ZS |
| The content of this resource references | https://doi.org/10.1016/j.envsoft.2015.08.013 |
| The content of this resource references | https://doi.org/10.1016/j.envsoft.2021.105161 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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