TY  - JOUR
A1  - Ghasemizade, Mehdi
A1  - Baroni, Gabriele
A1  - Abbaspour, Karim
A1  - Schirmer, Mario
T1  - Combined analysis of time-varying sensitivity and identifiability indices to diagnose the response of a complex environmental model
JF  - Environmental modelling & software with environment data news
N2  - Sensitivity and identifiability analyses are common diagnostic tools to address over-parametrization in complex environmental models, but a combined application of the two analyses is rarely conducted. In this study, we performed a temporal global sensitivity analysis using the variance-based method of Sobol’ and a temporal identifiability analysis of model parameters using the dynamic identifiability method (DYNIA). We discuss the relationship between the two analyses with a focus on parameter identification and output uncertainty reduction. The hydrological model HydroGeoSphere was used to simulate daily evapotranspiration, water content, and seepage at the lysimeter scale. We found that identifiability of a parameter does not necessarily reduce output uncertainty. It was also found that the information from the main and total effects (main Sobol' sensitivity indices) is required to allow uncertainty reduction in the model output. Overall, the study highlights the role of combined temporal diagnostic tools for improving our understanding of model behavior.
KW  - Temporal sensitivity
KW  - Identifiability
KW  - Preferential flow
KW  - HydroGeoSphere
KW  - Output uncertainty
Y1  - 2016
U6  - https://doi.org/10.1016/j.envsoft.2016.10.011
SN  - 1364-8152
SN  - 1873-6726
VL  - 88
SP  - 22
EP  - 34
PB  - Elsevier
CY  - Oxford
ER  -