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Adaptive calibration of a conceptual model for flash flood forecasting
Author(s) -
Brath Armando,
Rosso Renzo
Publication year - 1993
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/93wr00665
Subject(s) - heteroscedasticity , ordinary least squares , autocorrelation , calibration , flash flood , econometrics , flood myth , least squares function approximation , computer science , statistics , mathematics , geography , archaeology , estimator
The adaptive use of a conceptual model for real‐time flow forecasting is investigated. Maximum likelihood and ordinary least squares estimation criteria are considered, and the performance of maximum likelihood techniques for autocorrelated (AMLE) and heteroscedastic (HMLE) errors is analyzed jointly with that provided by the commonly used ordinary least squares estimation (OLSE) technique. Streamflow forecasts are compared for three rivers in central Italy, obtained by AMLE, HMLE, and OLSE adaptive calibration of a simple conceptual model describing the rainfall‐runoff transformation by accounting for Hortonian infiltration and linear basin response to rainfall excess. Although model residuals display both autocorrelation and heteroscedasticity, OLSE is found to provide a rather satisfactory performance. Because the OLSE technique also requires less computational effort compared to that for AMLE and HMLE, one could consider OLSE as a suitable option for real‐time model operation.