Automatic calibration of previously manual calibrated MF6 Model with ModelMuse, Pest and Flopy

Man vs machine? Could the computer find better solutions than humans? Which are the tradeoffs between manual and automatic calibration? Do we risk the hydrogeological conceptual model to achieve better calibration statistics? Do we really trust our observed data? Having more tools and managing more data enhances us to reach a superior level of data analysis. This time we have developed an applied case of automatic calibration with PEST of a previously manual calibrated MF6 model on a hillslope area. Our main purpose was to analyze the increase / decrease in the calibration statistics for the automatic versus the manual calibration model and discuss what the new parameters tell us from the original hydrogeological conceptual model. The PEST setup was done with Model Muse and the calibration statistics and plot were performed on Flopy scripts.

Instructor / Instructor:

Saul Montoya M.Sc

Hydrogeologist - Numerical Modeler

Mr. Montoya is a Civil Engineer graduated from the Catholic University in Lima with postgraduate studies in Management and Engineering of Water Resources (WAREM Program) from Stuttgart University – Germany with mention in Groundwater Engineering and Hydroinformatics. Mr Montoya has a strong analytical capacity for the interpretation, conceptualization and modeling of the surface and underground water cycle and their interaction. He is in charge of numerical modeling for contaminant transport and remediation systems of contaminated sites. Inside his hydrological and hydrogeological investigations Mr. Montoya has developed an holistic comprehension of the water cycle, understanding and quantifying the main hydrological dynamic process of precipitation, runoff, evaporation and recharge to the groundwater system.

Language / Lenguaje:

English

Event date / Fecha del evento:

Friday, Sep 15 2023 6:00 p.m. Amsterdam Time

Hosted by / Organizado por:

Hatarilabs

Stream link / Enlace de transmisión:

https://meet.google.com/jvs-ysrj-src

Input data / Datos de entrada:

https://owncloud.hatarilabs.com/s/eDyjoc4CQPADBz5

Additional instructions / Instrucciones adicionales:

Password to download data: Hatarilabs. You need to have Anaconda and Model Muse installed on your computer.