Presenters

Course Overview

This 3-part course is designed to provide engineers and hydrologists with the tools to perform robust flood frequency analysis using RMC-BestFit. Throughout the course, participants will explore at-site, nonstationary, and peaks-over-threshold methods, including Bayesian modelling, model averaging, and mixed population analysis.

Watch the intro video for a sneak peek into the course and discover the key functionalities of RMC-BestFit!

Learning Outcomes

In this course, you will be able to:

• Import, preprocess, and analyse time series data for at-site flood frequency analysis.
• Fit statistical distributions using Bayesian methods, including informative and quantile priors.
• Diagnose and model nonstationarity using trend functions and climate-informed priors.
• Apply advanced methods such as peaks-over-threshold, point-process analysis, and mixture models.
• Evaluate model performance and uncertainty using diagnostics, model selection criteria, and model averaging techniques.

Course Outline

Part 1: Comprehensive At-Site Flood Frequency Analysis

• Import and preprocess time series data for flow and rainfall.
• Derive annual maxima and incorporate historical flood information.
• Test for i.i.d. assumptions to validate frequency analysis inputs.
• Fit candidate distributions and apply Bayesian analysis with noninformative and informative priors.
• Assess Bayesian MCMC diagnostics and interpret posterior uncertainty.

Part 2: Nonstationary FFA and Model Averaging

• Import and prepare nonstationary time series data.
• Diagnose nonstationarity using hypothesis tests, ACF/PACF plots, and visual trend diagnostics.
• Model nonstationarity using trend functions.
• Incorporate climate-informed quantile priors to support scenario-based forecasting.
• Perform model selection and model averaging using AIC, BIC, DIC, and RMSE-based weights.

Part 3: Peaks-Over-Threshold and Mixed Populations

• Import time series data and perform peaks-over-threshold (POT) analysis using the Generalised Pareto distribution.
• Perform point-process analysis to compute annualised exceedance probabilities.
• Analyse mixed-population flow data (e.g., rain and snow) and diagnose multimodality in flood distributions.
• Fit mixture distributions to represent multiple flood-generating mechanisms.
• Use the competing risk framework to model annual maxima arising from distinct flood types.

Format

• 6+ hours of session recordings with unlimited access for 30-days;
• Pre-and-post-course materials to go through via the AWS learning platform;
• Homework exercises between the 3 parts;
• Additional resources and working model download/s;
• Ability to ask questions to the presenters at anytime through the learning platform.

Pre-requisites

• A basic understanding of hydrometeorology flood generating processes.
• A general understanding of statistical hydrology and flood frequency analysis.
• A working knowledge of setting up and running RMC-BestFit.
  • To learn the RMC-BestFit functionalities where our presenters step through their own data sets to develop flood frequency analyses, filter outliers, and incorporate non-stationarity, register for the On-demand Premium Webinar – Mastering FFA: incorporating extreme events and climate change.
• AWS Webinar to get an overview of the features and functionalities of RMC-BestFit
  

Requirements

• A good internet connection.
• Computer with Windows OS 10 or later.
• Dual monitor setup.
• Microsoft Excel for input data.
• Software requirements:
  • RMC-BestFit 2.0 (Beta-3): https://www.rmc.usace.army.mil/Software/RMC-BestFit/

Completion certification

• Participants earn CPD hours/points (i.e. with Engineers Australia) for at least 6 hours for the entire course. 
• On completion of the course attendees will be issued with a Certificate of Completion. 

Refund Policy

Frequent Asked Questions (FAQs)