EGU23-3985, updated on 15 Mar 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Sensitivity Analysis of the SUMMA Model on the Global Scale

Hongli Liu1, Martyn Clark2, Guoqiang Tang3, Wouter Knoben2, Shervan Gharari4, Jim Freer2, Louise Arnal2, and Dave Casson2
Hongli Liu et al.
  • 1University of Alberta, Department of Civil & Environmental Engineering, Edmonton, Canada
  • 2University of Saskatchewan, Coldwater Lab, Canmore, Canada
  • 3National Center for Atmospheric Research, Climate & Global Dynamics Lab, Boulder, USA
  • 4University of Saskatchewan, School of Geography and Planning, Saskatoon, Canada

Despite the recent advances, the identification of influential hydrologic processes and parameters of the process-based hydrologic model is still challenging. Part of the reason is the uncertain and interacting hydrologic process and the high dimensional parameter space. The motivation for this work is to effectively select an appropriate set of hydrologic processes and parameters for each basin on the globe, which is not necessarily the same everywhere. Here we evaluate the applications of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model to a large number of representative areas on the globe. Our objective is to identify the dominant hydrologic processes and sensitive model parameters for each representative area. First, sensitivity indices of the SUMMA parameters are computed using the VISCOUS global sensitivity analysis method. VISCOUS is the abbreviation of Variance-based Sensitivity Analysis using Copulas. Second, the sensitivity values are summarized per hydrologic process (e.g., snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, baseflow, and runoff) and per simulation statistic (e.g., mean, coefficient of variance, and autoregressive lag 1). The summarized sensitivity indices enable modelers to identify the most dominant hydrologic processes in each representative area. The results of this study will provide a foundation to estimate parameters in large-domain applications of process-based hydrologic models.

How to cite: Liu, H., Clark, M., Tang, G., Knoben, W., Gharari, S., Freer, J., Arnal, L., and Casson, D.: Sensitivity Analysis of the SUMMA Model on the Global Scale, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3985,, 2023.