Webinar detail / Detalle del Webinar
Open webinar: Automatic calibration drainage groundwater model with sheet piles with MODFLOW6 and Model Muse
The application of PEST to real conditions is a challenge since it involves the setup of the automated parameter estimation and the complexities of the groundwater response. We have developed an applied case of automatic parameter estimation on a groundwater flow model related to a site drainage with 6 pumps and steel sheet piles. The calibration is based on observations from a pumping well and two outer monitoring points over a period of 120 days. The case involves as well the sensitivity analysis of hydraulic conductivities from heterogeneous soil and sheet piles together with the conductance of neighboring water channels.
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 13 2024 6:00 p.m. Amsterdam Time
Hosted by / Organizado por:
Hatarilabs
Stream link / Enlace de transmisión:
https://meet.google.com/bkg-wjma-nisInput data / Datos de entrada:
https://owncloud.hatarilabs.com/s/sHSAxQ3jHNfDCCD
Additional instructions / Instrucciones adicionales:
Password to download data: Hatarilabs