Global Sensitivity Analysis and Uncertainty Analysis on SWAT Microbial Water quality model in Central Michigan

Huiyun Wu, S. Thomas Purucker, and Marirosa Molina

Highlights

• Global sensitivity analysis was used with the SWAT model to predict microbial water quality in a central Michigan watershed.
• Important SWAT input parameters controlling microbial water quality in the Red Cedar River Watershed model include bacterial die-off/growth factors, temperature, and hydrology.
• Parameter and model uncertainty were quantified using Monte-Carlo simulation coupled with an Approximate Bayesian Computation approach.
• Integrating SWAT streamflow and bacterial predictions, sensitive parameter refinement, and uncertainty analysis supports and improves watershed pollution management.

These metadata describes the input/output data, files, parameters used to develop the modeling approach described in the associated publication, which can be found @ https://github.com/microbial-genomics/wu_redcedar2

For details about the observed data, please contact the corresponding author, Dr Huiyun Wu Wu ( huiyun.wu@wsu.edu)

Observed data was obtained by Dr Wu under her previous association with Michigan State University