Equifinality in Hydrological Modelling: The Calibration Uncertainty Guide

Описание: Are you getting a perfect fit for the wrong reasons? In rainfall-runoff modelling, achieving a high Nash-Sutcliffe Efficiency (NSE) or low RMSE doesn't always mean your model is a reflection of physical reality. Because multiple parameter sets — and even different model structures — can reproduce observed data with comparable performance. This phenomenon is known as equifinality.

In this video, I explain what equifinality is, why it occurs, why it matters for engineering practice, and how modellers can diagnose and manage it within real workflows. We explore the key mechanisms driving equifinality, including parameter compensation, structural uncertainty, data limitations, over-parameterisation, optimisation behaviour, and scale effects. The video then discusses the implications of equifinality for infrastructure design, flood prediction, model reliability, and regulatory interpretation. Finally, I present practical strategies for detecting equifinality and outline best practices for managing modelling uncertainty through multi-objective calibration, parsimonious model selection, ensemble approaches, and improved data use.

This video is intended for civil engineers, hydrologists, researchers, and students interested in rainfall–runoff modelling, model calibration, and uncertainty analysis.

⏱️ Timestamps
00:00 – Introduction
00:43 – What is equifinality?
01:16 – Parameter compensation
01:43 – Structural equifinality
02:13 – Data limitations and observational deficits
02:54 – Over-parameterisation
03:20 – Optimisation behaviour and local optima
03:39 – Scale and aggregation effects
04:00 – Why equifinality matters – the consequences
04:47 – Diagnosing equifinality
05:50 – Practical strategies for managing equifinality
06:51 – Key takeaways and conclusion

🔎 Keywords
#equifinality #hydrology #hydrologicalmodelling #modelcalibration #uncertainty #rainfallrunoffmodel #sensitivityanalysis #correlationanalysis #civilengineering #hydrologytutorial #optimization #multiobjectiveoptimization #catchmentmodelling #ensemblemodelling #overfitting