TY - JOUR
T1 - Calibration of conceptual hydrological models revisited
T2 - 1. Overcoming numerical artefacts
AU - Kavetski, Dmitri
AU - Kuczera, George
AU - Franks, Stewart
PY - 2006/3/30
Y1 - 2006/3/30
N2 - Conceptual hydrological modelling has traditionally been plagued by calibration difficulties due to the roughness and complex shape of objective functions. These problems led to the abandonment of powerful classical analysis methods (Newton-type optimisation, derivative-based uncertainty analysis) and have motivated extensive research into nonsmooth optimisation and even new parameter estimation philosophies (e.g. GLUE). This paper shows that some of these complexities are not inherent features of hydrological models, but are numerical artefacts due to model thresholds and poorly selected time stepping schemes. We present a numerically robust methodology for implementing conceptual models, including rainfall-runoff and snow models, that ensures micro-scale smoothness of objective functions and guarantees macro-scale model stability. The methodology employs robust and unconditionally stable time integration of the models, complemented by careful threshold smoothing. A case study demonstrates the benefits of these techniques.
AB - Conceptual hydrological modelling has traditionally been plagued by calibration difficulties due to the roughness and complex shape of objective functions. These problems led to the abandonment of powerful classical analysis methods (Newton-type optimisation, derivative-based uncertainty analysis) and have motivated extensive research into nonsmooth optimisation and even new parameter estimation philosophies (e.g. GLUE). This paper shows that some of these complexities are not inherent features of hydrological models, but are numerical artefacts due to model thresholds and poorly selected time stepping schemes. We present a numerically robust methodology for implementing conceptual models, including rainfall-runoff and snow models, that ensures micro-scale smoothness of objective functions and guarantees macro-scale model stability. The methodology employs robust and unconditionally stable time integration of the models, complemented by careful threshold smoothing. A case study demonstrates the benefits of these techniques.
KW - Degree-day snow model
KW - Implicit time stepping
KW - Model smoothing
KW - Model stability
KW - Model thresholds
KW - Numerical artefacts
KW - Parameter estimation
KW - Rainfall-runoff models
KW - SPM
U2 - 10.1016/j.jhydrol.2005.07.012
DO - 10.1016/j.jhydrol.2005.07.012
M3 - Article
AN - SCOPUS:33644550945
VL - 320
SP - 173
EP - 186
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
IS - 1-2
ER -