HGS RESEARCH HIGHLIGHT - Combined analysis of time-varying sensitivity and identifiability indices to diagnose the response of a complex environmental model
AUTHORS: Mehdi Ghasemizade, Gabriele Baroni, Karim Abbaspour, and Mario Schirmer
Physically based models for simulating environmental processes are usually criticized due to having many parameters. This issue leads to over-parameterization and can finally reduce the uncertainty (reliability) of the simulated outputs. Sensitivity and identifiability analyses are common diagnostic tools to address over-parametrization in complex environmental models. In this study, we performed a temporal global sensitivity and identifiability analyses of HydroGeoSphere (HGS) model parameters. HGS was used to simulate daily evapotranspiration, water content, and recharge based on high quality data of a weighing lysimeter. Figure below shows the schematic of the lysimeter as well as the conceptual model for simulating the lysimeter. The model has four soil layers in addition to a preferential flow component. We found that identifiability of a parameter does not necessarily reduce output uncertainty. It was also found that the sensitivity of the model parameters is required to allow uncertainty reduction in the model output.
Schematic of the weighing lysimeter.
Conceptual Model.