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Mehmet B. Ercan

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Summary Precipitation Cloud Computing Calibration Future Plans

A Python Tool for Multi-Gage Calibration

Use of multiple streamflow observation stations in calibration algorithms increases hydrologic model performance. SWAT is a comprehensive, semi-distributed river basin model that can benefit from multi-gage calibration. Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient multi-objective calibration algorithm in hydrologic modeling community including for SWAT models. Although NSGA-II has been used with SWAT before, there is no publicly available software tool for easily applying the calibration approach for SWAT models. Thus, I created a tool for applying NSGA-II method for multi-gage calibration of SWAT models using open source Python programing language. Then, I demonstrated the tool with a case study for Upper Neuse watershed in North Carolina with three observation gages and two fitness coefficients. Similar to previous studies, the NSGA-II method with multi-gage calibration improved SWAT model accuracy.


         Figure: NSGA-II SWAT Calibration Architecture*

*Ercan, M. B. and J. L. Goodall (2016), Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration., Environmental Modelling & Software, 84, 112-120.
doi: 10.1016/j.envsoft.2016.06.017

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Last updated Dec 14, 2016