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Watershed Planning within a Quantitative Scenario Analysis Framework

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Improving event-based methods for modelling flood risk in a variable and non-stationary climate.

¹Department of Infrastructure Engineering, The University of Melbourne, Melbourne, Victoria, Australia.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|July 31, 2025

Summary

Reproducing flood frequency curves is difficult, especially with climate change. This study explores challenges and methods for deriving these relationships in a non-stationary climate for better flood risk management.

Keywords:

Monte Carlo analysis aleatory uncertainty climate change epistemic uncertainty event-based flood modelling

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Area of Science:

Hydrology
Climate Science
Environmental Engineering

Background:

Simulating flood hydrographs is simpler than reproducing magnitude-frequency relationships, particularly across diverse spatial and temporal scales within catchments.
Climate change exacerbates the challenges in accurately modeling flood behavior and frequency curves.

Purpose of the Study:

To discuss key aspects of flood behavior for deriving magnitude-frequency relationships under non-stationary climate conditions.
To address sources of uncertainty, both irreducible (natural variability) and reducible (data limitations, imperfect knowledge).
To guide the shift from deterministic to stochastic modeling frameworks for flood risk assessment.

Main Methods:

Discussion of hydroclimatic factors influencing non-stationary flood behavior due to global warming.
Analysis of uncertainty sources in flood frequency analysis.
Exploration of design information and tools for stochastic flood modeling.

Main Results:

Identifies critical factors for deriving flood magnitude-frequency relationships in non-stationary climates.
Highlights the need to differentiate between irreducible and reducible uncertainties.
Emphasizes the necessity of stochastic frameworks over deterministic models for planning and design.

Conclusions:

Enhanced methods are needed to support the development and application of robust flood risk assessments.
Addresses the gap between academic research and hydrologic practice.
Stresses the importance of considering climate change impacts on flood frequency analysis.