We present an uncertainty-guided downward approach to model the hydrologic behavior of watersheds. A series of watershed models with increasing complexity is applied to interpret signatures of inter-annual, intra-annual and daily streamflow response behavior for 12 US watersheds across a range of hydro-climatic conditions. Model performance for each of these signatures is evaluated using a Monte Carlo framework. Probabilistic model performance measures are combined with fuzzy rules to provide guidance on the appropriate levels of model complexity that are necessary to represent watershed behavior at a certain scale. The objective of this work is to provide better a priori understanding of model selection for a range of hydro-climate conditions and timescales.
AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- 1800 HYDROLOGY;
- 1873 Uncertainty assessment (3275)