Open Webinar: Calibration of a Groundwater Flow Model in MODFLOW 6 with Model Muse and Python

Calibration of hydrogeological models can be defined as the procedure to adjust the hydraulic parameters of the model where the resulting heads and flows are close to the observed values. Due to the complexities of hydraulic parameters distribution, model geometry, conceptualization of boundary conditions and other factors, the calibration procedure can be extensive and sometimes with limited success. We have developed an applied case of calibration of a groundwater flow model on a hillslope area where the hydraulic parameters and boundary conditions are modified methodically and the different hydraulic responses are compared to define right next steps in the calibration procedure. The groundwater flow model was developed on Modflow 6 and Model Muse while the head comparison and calibration statistics were done in Python and Flopy.

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:

Monday, March 28, 2022 6:00 p.m. Amsterdam Time

Hosted by / Organizado por:

Hatarilabs

Stream link / Enlace de transmisión:

https://meet.google.com/eyn-ayke-uon

Input data / Datos de entrada:

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

Additional instructions / Instrucciones adicionales:

Password to download the data: Hatarilabs. You need Model Muse with Modflow 6 and Anaconda installed on your computer