Dynamical and statistical downscaling of climate information and its hydrologic implications over west-central Florida

General circulation models (GCMs) have recently been developed for simulating current and future climate patterns. However, GCM results do not generally provide accurate prediction of climate variables on the scale needed to assess hydrologic impacts. In this study various existing dynamic and statistical GCM downscaling techniques were used to estimate precipitation fields over the state of Florida. These methods were quantitatively evaluated and found unable to reproduce fine-scale spatial characteristics of precipitation patterns. A new stochastic downscaling technique was developed which improves on previous methods and produces daily precipitation fields that accurately reproduces spatiotemporal variability of precipitation. The downscaled precipitation scenarios were used as input to an integrated hydrologic model to evaluate hydrologic implications of differences in the alternative downscaling methods. Results of this study should allow hydrologic modelers and water supply decision makers to more effectively use climate modeling results for water resource planning, management, and conservation. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html).