Take sessions at any time, at your own pace with unlimited access for 30 days on sign up.
This comprehensive four‑part course builds practical, hands‑on skills in using RMC‑BestFit for modern flood‑frequency analysis. Participants learn how to work with time‑series data, incorporate historical information, perform distribution fitting and Bayesian analysis, and apply core techniques used in contemporary hydrological studies.
The course extends into advanced topics including nonstationary analysis, peaks‑over‑threshold methods, mixture models, composite distributions and model averaging. These modules deepen participants’ understanding of complex hydrologic behaviour and prepare you to address sophisticated flood‑frequency challenges with confidence.
Throughout the course, participants will learn the latest features using real‑world Australian and US gauge data. Participants follow complete data‑to‑model workflows, from downloading international datasets (USGS, Australian BoM, GHCN, CHMN) to fitting Bayesian models, managing censored data, estimating rating curves and applying point‑process methods, building the capability to produce robust, practical flood‑frequency estimates.
Haden Smith is a Lead Engineer with the USACE Risk Management Center, specialising in developing risk methodologies, conducting flood hazard assessments for high-priority dams and levees, and advancin... Read more about Haden Smith
Rory is a Professor at the University of Melbourne and has over 40 years’ experience in engineering and environmental hydrology, mostly in industry, and now focuses his time on research and teaching... Read more about Rory Nathan
Declan O’Shea is a Senior Hydrologist at HARC with over 7 years of experience in hydrology and water resources working in both research and consulting. Declan has experience in a range of hydrologi... Read more about Declan O'Shea
Course Overview
This four‑part course builds practical skills in using RMC‑BestFit for modern flood‑frequency analysis. Participants learn data preparation, distribution fitting, Bayesian methods and advanced modelling techniques. Real‑world examples and full data‑to‑model workflows help develop confident, defensible analysis using the latest RMC‑BestFit capabilities.
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:
Prepare, manage and analyse hydrologic time‑series data for flood‑frequency studies.
Fit univariate, Bulletin 17C and advanced frequency models using RMC‑BestFit.
Apply nonstationary, peaks‑over‑threshold, mixture and composite modelling techniques.
Build complete data‑to‑model workflows using international gauge datasets.
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.
Part 4: Comprehensive Flood Frequency Analysis with RMC-BestFit
(This part builds on the foundations from Parts 1-3 and introduces the advanced features in RMC-BestFit 2.0)
Data acquisition and preparation: downloading time series from USGS, BoM, GHCN, and CHMN; input data types (exact, uncertain, interval, threshold); hypothesis tests and diagnostics; block maximum and POT extraction.
Core frequency analysis: stationary and nonstationary univariate models with quantile priors; Bulletin 17C (Log-Pearson III); point process models for POT data with censored observations.
Advanced distribution models: mixture distributions, composite distributions (competing risks, mixed populations, Bayesian model averaging), and copula-based bivariate analysis.
Supporting analysis: coincident frequency analysis, stage-discharge rating curve estimation, and ARIMAX time series modelling.
Demonstrations: download BoM data and fit a LP3 univariate analysis; create POT data and fit a seasonal point process; download USGS stage-discharge data and fit a rating curve.
Format
8+ 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 4 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
If you have completed the first three parts of the RMC-BestFit Deep Dive course and are ready to build on your foundational skills, you can now enrol in the RMC‑BestFit 2.0 course. This is Part 4 of this course.
The 2.0 course introduces the latest RMC‑BestFit features through practical, hands‑on workflows. Participants learn to prepare hydrologic data, run univariate and Bulletin 17C analysis, and explore advanced modelling options. The course covers full data‑to‑model workflows using international sources (USGS, Australian BoM, GHCN, CHMN).
If you are new to RMC-BestFit, enrol in this course and take advantage of the core concepts and knowledge needed to model real flood-frequency challenges.
