Live Course: Python for Hydrology and Hydrogeology
Explore Python programming for water modelling.
In this 3-session course attendees will learn how to perform; data wrangling and multivariate exploratory data analysis, time series analysis and data visualisation. Each session will be hosted by experts in their field, who will delve in-depth into the key topic, explaining best practice techniques and approaches. Practical examples and demonstrations will be analysed, allowing attendees to apply the knowledge gained and learn hands-on how to use Python- in order to save you time, money and integrate systems effectively.
The course will consist of 3 live and interactive 2-hour sessions, over three weeks. There is also pre and post course material to develop and solidify your learning. Don't miss the opportunity to have your questions answered live or via our interactive learning platform.
Thursday, 3 June 2021 - Thursday, 17 June 2021
Luk has over 10 years research experience in environmental impact assessment and modelling groundwater dynamics at regional to continental scales for water resource management. His research features a... Read more
Chris is an Adelaide-based hydrogeologist in Land and Water's Regional Scale Groundwater Analysis team. His research primarily involves the characterisation of various aspects of regional-scale ground... Read more
Vincent is a hydrogeologist with over 10 years of experience in Python programming. He uses it on a daily basis for many if not all of his tasks, such as working with logger data, preparation of model... Read more
This course is designed to be highly practical, with x3, 2-hour live and interactive training sessions over three weeks.
The course will cover 3 main topics across 3 live sessions, that are recorded and uploaded to our learning platform if you cannot attend live;
Session 1: Thursday 3rd June | Lead by Luk Peeters
Data wrangling and multivariate exploratory data analysis
1. Hydrochemistry data
Download data from GA’s website
Explore data through scatter plots
Make a Piper plot (and map)
Multivariate analysis: principal component analysis, clustering (touching on machine learning in scikit learn)
2. Exploratory Data Analysis APY Lands groundwater dataset
Load pre-compiled dataset
Visually explore relationships and test hypothesis in the dataset using violin-plots
3. Datacube: AWRA
Load dataset of Australian Water Resources Assessment model from Bureau of Meteorology website
Visualise and explore maps and time series of AWRA outputs
Multivariate analysis and visualisation
Session 2: Thursday 10th June | Lead by Chris Turnadge
Time series analysis
1. Data pre-processing
Using interpolation to fill gaps
Detection and removal of outliers
Resampling to higher or lower sampling resolution
Detrending data using time and frequency domain methods
2. Decomposing hydrograph data
Quantifying the relative contributions of component processes
3. Interpreting responses to time-lagged processes
Demonstration of convolution
4. Interpreting responses to periodic processes
The discrete Fourier transform
Harmonic least squares
Session 3: Thursday 17th June | Lead by Vincent Post
1. Data visualisation and linking it with Google Earth
2. Visualisation of modelled flowpaths in 3D
3. Evaluation of pumping tests
The course is delivered through units via the learning platform
3 live and interactive sessions of 2 hours over three weeks
Thursday, 3rd June 2021, 3-5pm (Sydney Time)
Thursday, 10th June 2021, 3-5pm (Sydney Time)
Thursday, 17th June 2021, 3-5pm (Sydney Time)
Sessions are recorded & uploaded to the learning platform (within 24hrs after session), if you cannot attend live.
Pre-and-post-course materials to go through via the learning platform.
Exercises between the live sessions.
Manual of the course and working model download/s.
Ability to access all the online course materials for up to a month after the course. The pre-readings/videos and manual/s are available for ongoing learning.
Pre-course reading and video watching is encouraged. There is also an opportunity to tailor the sessions to your direct questions via the initial survey. After the first two sessions you will be given some exercises to complete, prior to the next session.
A good internet connection and software and downloads as described in the learning platform.
On completion of the course attendees will be issued with a Certificate of Participation.