A new spin on global sensitivity analysis: worldwide sensitivity analysis of the SUMMA model
Abstract
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. Sensitivity analysis is a powerful tool to reveal how various factors influence hydrologic model behavior. Here we evaluate the worldwide applications of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model to identify the dominant hydrologic processes and sensitive model parameters. First, sensitivity indices of the SUMMA parameters are computed using the Sobol and VISCOUS methods. Second, the sensitivity indices are summarized into processes (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) based on model performance statistics (mean, coefficient of variance, and autoregressive lag 1). The summarized sensitivity indices enable modelers to identify the most dominant hydrologic processes in each basin by associating the most sensitive parameters the respect processes. The results of this study will provide a foundation to estimate parameters in large-domain applications of process-based hydrologic models.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.H55J0846L