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Exploring snow model parameter sensitivity using Sobol' variance decomposition.
- Source :
-
Environmental Modelling & Software . Mar2017, Vol. 89, p144-158. 15p. - Publication Year :
- 2017
-
Abstract
- This study advances model diagnostics for snowmelt-based hydrological systems using Sobol’ sensitivity analysis, illuminating parameter sensitivities and contrasting model structural differences. We consider several distinct snow-dominated locations in the western United States, running both SNOW-17, a conceptual degree-day model, and the Variable Infiltration Capacity (VIC) snow model, a physically-based model. Model performance is rigorously evaluated through global sensitivity analysis and a temperature warming analysis is conducted to explore how model parameterizations affect portrayals of climate change. Both VIC and SNOW-17 produce comparable results with SNOW-17 performing slightly better for shallower snowpacks and VIC performing better for deeper snowpacks. However, the lack of sensitivity of SNOW-17 to climate warming suggests that it may not be as reliable as a more sensitive model like VIC. Inter-model differences presented here offer insights into physical features with greatest uncertainty and may inform future model development and planning activities. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SNOWMELT
*HYDROLOGY
*CLIMATE change
*GLOBAL warming
*SENSITIVITY analysis
Subjects
Details
- Language :
- English
- ISSN :
- 13648152
- Volume :
- 89
- Database :
- Academic Search Index
- Journal :
- Environmental Modelling & Software
- Publication Type :
- Academic Journal
- Accession number :
- 120925956
- Full Text :
- https://doi.org/10.1016/j.envsoft.2016.11.024