NetCDF for water resources with Python for dummies (CHIRPS dataset)

NetCDF has become a popular choice for storing and delivering precipitation and water resources related data. Its capacities to store multiple geospatial raster layers over time allow another level of abstraction on data analysis, however the format is of limited use on normal desktop applications and most times we are required to use a programming language such as Python or R. We have done an applied example of exploration analysis from a NetCDF file that has the CHIRPS dataset for year 2022. The dataset is opened with Python and Rasterio and clipped to country extent where an interactive visualization of precipitation is performed. Finally, a daily precipitation hydrograph is generated over the coordinates of a given city.

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, Nov 17 2023 6:00 p.m. Amsterdam Time

Hosted by / Organizado por:

Hatarilabs

Stream link / Enlace de transmisión:

https://meet.google.com/ngb-dfer-tgt

Input data / Datos de entrada:

https://owncloud.hatarilabs.com/s/lr4q8CRMzvavMeG

Additional instructions / Instrucciones adicionales:

Password to download data: Hatarilabs. You need Anaconda installed on your computer.