What can we learn from time-varying sensitivity analysis?
Abstract
As climate change induced effects on weather patterns are becoming more apparent, it is becoming increasingly important to analyze how hydrologic systems respond to these changes at inter- and intra-annual time scales. To examine this, we applied time-varying sensitivity analysis to five watersheds located in various sites across California. In particular, we sought to analyze how strong seasonal and annual weather shifts may result in differences in parameter sensitivity from year to year and within a given year. Our analysis centers on this region because of its tendency for extreme weather events, which allows us to better analyze how these variations affect seasonal and annual hydrologic controls, assessed via sensitivity indices. To assess whether time-varying sensitivity analysis can reveal unique patterns in parameter importance through time, we simulated streamflow using a simple rainfall-runoff model (Hymod) over a 33-year period (1981-2014). Sensitivity analysis revealed that annual scale sensitivity results differ based on the metric they are assessed with respect to, but do not vary through time, or correlate with observable weather patterns. On the other hand, we discovered that sub-annual scale sensitivity analyses paint a much clearer picture of differences in responses within and between dry and wet years. Sensitive model parameters vary with annual and sub-annual conditions, with different controls emerging seasonally as well as during dry and wet years. More importantly, sub-annual sensitivity analysis can help us identify when parameter sensitivities diverge from those observed using annual metrics alone, potentially revealing when different processes are at play for simulating streamflow, informing our understanding of both model improvements and watershed functioning.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H43J2169B
- Keywords:
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- 0430 Computational methods and data processing;
- BIOGEOSCIENCES;
- 1805 Computational hydrology;
- HYDROLOGY;
- 1846 Model calibration;
- HYDROLOGY;
- 1873 Uncertainty assessment;
- HYDROLOGY