Open Webinar: Groundwater Modeling on a Hillslope Area - Model Construction

After the review and compilation of relevant data and the development of a conceptual model we are ready for the construction of a groundwater numerical model on a hillslope area at Mukilteo city, Washington, US. The model will be constructed in MODFLOW 6 with Model Muse with boundary conditions for regional flow, sea, recharge, drains and evapotranspiration, the model has also 24 observations points. Input data is inserted from vector (shp) and gridded (raster) data. The webinar includes all the steps of model construction and package configuration with a final display of calculated - observed head values done with Flopy. This webinar is the base for a coming webinar on manual calibration and a subsequent webinar of sensibility analysis and machine learning assisted calibration.

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, February 7, 2022 6:00 p.m. Amsterdam Time

Hosted by / Organizado por:

Hatarilabs

Stream link / Enlace de transmisión:

https://meet.google.com/vcv-xfec-uiv

Input data / Datos de entrada:

https://owncloud.hatarilabs.com/s/8D3t7JiZMTLI4SC

Additional instructions / Instrucciones adicionales:

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