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Rainfall–runoff modelling is at the core of hydrology, flood estimation, and water resources engineering. But with so many different models available, choosing the right one can be confusing. In this video, I provide a clear and structured overview of rainfall–runoff models, starting with a brief explanation of the rainfall–runoff process and then introducing four key dimensions used to classify hydrological models. For each classification, I explain: • The key characteristics • Typical applications • Strengths and limitations • Examples of well-known hydrological models This video is ideal for hydrology students, civil and water engineers, researchers, and practitioners who want to understand how rainfall–runoff models differ and when each type should be used. ________________________________________ 📌 Topics Covered •Rainfall–runoff process fundamentals •Process Representation: Empirical, conceptual, and physically-based models •Spatial Discretisation: Lumped, semi-distributed, and distributed models •Temporal Scope: Event-based vs continuous modelling •Treatment of Uncertainty: Deterministic vs stochastic hydrological models ________________________________________ ⏱️ Timestamps 00:00 Introduction and motivation 00:35 What is the rainfall–runoff process? 01:28 Classification by Process Representation 01:37 Empirical (black-box) models 02:14 Conceptual (grey-box) models 03:00 Physically-based (white-box) models 03:37 Classification by Spatial Discretisation 03:47 Lumped models 04:13 Semi-distributed models 04:53 Distributed models 05:27 Classification by Temporal Scope 05:35 Event-based models 05:51 Continuous models 06:11 Classification by Treatment of Uncertainty 06:19 Deterministic models 06:38 Stochastic models 07:02 Concluding notes Keywords: #rainfallrunoffmodel #hydrology #floodmodelling #hydrologicalmodelling #waterresourcemanagement #hydrologytutorial #empiricalmodels #conceptualmodels #physically-basedmodel #lumpedmodel #deterministicmodel #stochasticmodel #event-based #continuousmodelling #distributedmodel #semi-distributedmodel