Stochastic Nonparametric Techniques : Applications to Hydroclimate Modeling

Balaji Rajagopalan
Dept. of Civil, Environmental and Architectural Eng., University of Colorado

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Nonparametric techniques for functional (probability density functions or regression) estimation provide a flexible and adaptive data exploration framework. These techniques involve "local estimation" - in that, functional estimation at a point is based on a few nearest neighbors. This provides the ability to capture nonlinearities and non-Gaussian features exhibited by the data. Utility of these techniques will be demonstrated through a variety of hydroclimate applications. These applications include:

1. Scenario Generation
- stochastic weather generation conditioned on large scale climate features.

2. Time series Forecasting
- Ensemble streamflow forecasting using climate indices
- Streamflow simulation for salinity analysis

3. Extreme value analysis
(e.g. flood frequency estimation)

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30 Oct, 2002
2 PM/ DSRC 1D 403
(Coffee at 1:50 PM)
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