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Overview of Urban Drainage Flood Prediction Methods and Approaches J.Y. Chen 1 and B.J. Adams 2 1. Water Survey Division, Environment Canada 2. Department of Civil Engineering, University of Toronto 2008. 05. 06. Presentation Outline. Urban drainage modeling approaches
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Overview of Urban Drainage Flood Prediction Methods and ApproachesJ.Y. Chen1 and B.J. Adams21.Water Survey Division, Environment Canada2. Department of Civil Engineering, University of Toronto2008. 05. 06
Presentation Outline • Urban drainage modeling approaches • Analytical model development • Model evaluation and comparison • Conclusions
Methods for Urban Drainage Flood Prediction • Statistical/stochastic methods • Flood frequency analysis • Regional flood frequency analysis • Time series analysis • Deterministic methods • Conceptual models
Deterministic Conceptual Modeling Methods Water budget Model inputs Model structure Runoff routing Model calibration Model verification Prediction
Approaches Used for This Study • Design storm approach • Simulation approach • Continuous simulation • Event simulation • Derived probability distribution approach
Analytical Model Development • Closed-form analytical models are developed with derived probability distribution theory • Probability distributions of runoff volumes and peak flow rates can be derived from probability distributions of rainfall characteristics
Rainfall-Runoff Transformation • Runoff coefficient based • Extended form
Rainfall-Runoff Transformation (Cont’d) • Infiltration based
Analytical Model Statistic analysis of rainfall records Rainfall characteristics, e.g., rainfall event volume, duration & interevent time Overflow Storage facility Exceedance probability of a runoff spill volume Probability distributions of rainfall characteristics Rainfall-runoff transformation Average annual volume of spills Average annual number of spills PDF or CDF of runoff event volume Expected value of runoff event volume Average annual runoff volume Average annual runoff control efficiency
Rational Method • Peak flow rate • Runoff volume • Storage Post-development peak Pre-development peak Tbase=2tc or 2.67tc
Simulation Models • Event simulation models • OTTHYMO (Canada) • HEC-HMS (US) • SWMM (US) • Continuous simulation model • SWMM
Model Calibration Rational method OTTHYMO
Model Calibration (Cont’d) HEC-HMS SWMM
Conclusions • Peak flow rates from event simulation models appear to be lower than the results from continuous simulation model • Event simulation models appear to be more conservative than continuous simulation model for runoff volume estimation
Conclusions (Cont’d) • The closed-form analytical models developed with derived probability distribution theory, are capable of providing comparable results to continuous simulation results • Different models may vary not only in modeling approach, but also in the level of complexity, it can be challenging to select an appropriate model with a desired level of performance