Parameter estimation and uncertainty analysis for a watershed model
Environmental Modelling & Software
CITY DRAIN © - An open source approach for simulation of integrated urban drainage systems
Environmental Modelling & Software
Urban runoff modelling uncertainty: Comparison among Bayesian and pseudo-Bayesian methods
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
On calibration data selection: The case of stormwater quality regression models
Environmental Modelling & Software
Efficient hydrological model parameter optimization with Sequential Monte Carlo sampling
Environmental Modelling & Software
Generating time-series of dry weather loads to sewers
Environmental Modelling & Software
Uncertainty in the river export modelling of pesticides and transformation products
Environmental Modelling & Software
Watershed model parameter estimation and uncertainty in data-limited environments
Environmental Modelling & Software
Parallel flow routing in SWMM 5
Environmental Modelling & Software
Review: A critical review of integrated urban water modelling - Urban drainage and beyond
Environmental Modelling & Software
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Stormwater models are important tools in the design and management of urban drainage systems. Understanding the sources of uncertainty in these models and their consequences on the model outputs is essential so that subsequent decisions are based on reliable information. Model calibration and sensitivity analysis of such models are critical to evaluate model performance. The aim of this paper is to present the performance and parameter sensitivity of stormwater models with different levels of complexities, using the formal Bayesian approach. The rather complex MUSIC and simple KAREN models were compared in terms of predicting catchment runoff, while an empirical regression model was compared to a process-based build-up/wash-off model for stormwater pollutant prediction. A large dataset was collected at five catchments of different land-uses in Melbourne, Australia. In general, results suggested that, once calibrated, the rainfall/runoff models performed similarly and were both able to reproduce the measured data. It was found that the effective impervious fraction is the most important parameter in both models while both were insensitive to dry weather related parameters. The tested water quality models poorly represented the observed data, and both resulted in high levels of parameter uncertainty.