Performance and sensitivity analysis of stormwater models using a Bayesian approach and long-term high resolution data

Environmental Modelling and Software

Volumn 26, Issue 10, 2011, Pages 1225-1239

  Dotto, C B S ^a   Kleidorfer, M ^b   Deletic, A ^a   Rauch, W ^b   McCarthy, D T ^a   Fletcher, T D ^a  

^a MONASH UNIVERSITY   (Australia)

^b UNIVERSITY OF INNSBRUCK   (Austria)

Author keywords

Calibration; Monte Carlo Markov chain; Rainfall runoff model; Sensitivity analysis; Water quality model

Indexed keywords

BAYESIAN APPROACHES; DATA SETS; DRY WEATHERS; EMPIRICAL REGRESSION MODEL; HIGH RESOLUTION DATA; MEASURED DATA; MELBOURNE , AUSTRALIA; MODEL CALIBRATION; MODEL OUTPUTS; MODEL PERFORMANCE; MONTE CARLO MARKOV CHAIN; OBSERVED DATA; PARAMETER SENSITIVITIES; PARAMETER UNCERTAINTY; RAINFALL/RUNOFF; SOURCES OF UNCERTAINTY; STORMWATER MODELS; STORMWATER POLLUTANTS; URBAN DRAINAGE SYSTEMS; WATER QUALITY MODEL; WATER QUALITY MODELS;

BAYESIAN NETWORKS; CALIBRATION; CATCHMENTS; DRAINAGE; INFORMATION MANAGEMENT; MARKOV PROCESSES; QUALITY CONTROL; REGRESSION ANALYSIS; RUNOFF; WATER QUALITY;

SENSITIVITY ANALYSIS;

BAYESIAN ANALYSIS; CALIBRATION; CATCHMENT; DATA SET; MARKOV CHAIN; MODEL TEST; MONTE CARLO ANALYSIS; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; RAINFALL-RUNOFF MODELING; REGRESSION ANALYSIS; RESOLUTION; RUNOFF; STORMWATER; UNCERTAINTY ANALYSIS; URBAN DRAINAGE; WATER QUALITY;

AUSTRALIA; MELBOURNE; VICTORIA [AUSTRALIA];

EID: 79957854749     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2011.03.013     Document Type: Article

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