Part 1 | 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;
• Summarise 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.

Part 2 | 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;
• Temporal differencing;
• 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;
• Regression deconvolution.

4. Interpreting responses to periodic processes

• The discrete Fourier transform;
• Periodogram-based approaches;
• Harmonic least squares.

Part 3 | Lead by Vincent Post | Data visualisation

1. Data visualisation and linking it with Google Earth;
2. Visualisation of modelled flowpaths in 3D;
3. Evaluation of pumping tests.

Format

The course is delivered through units via the learning platform (LMS).

• This course is designed to be highly practical, with 6+ hours of training session recordings;
• Pre-and-post-course materials to go through via the LMS;
• Exercises between the 3 parts;
• Manual of the course and working model download/s;
• Ability to access all the online course materials with unlimited course access for 30-days.

Preparation

Pre-course reading and video watching is encouraged.

Requirements

A good internet connection and software and downloads as described in the learning platform.

Outcome

On completion of the course attendees will be issued with a Certificate of Participation.

Refund Policy

Frequently Asked Questions (FAQ)