Climate models are common tools for developing design standards in the hydrologic field; however, these models contain uncertainties in multi-model and scenario selections. Along with these uncertainties, biases can be attached to the models. Such biases and uncertainties can present difficulties in predicting future extremes. These hydrologic extremes are believed to be non-stationary in character. Only in the recent past have model users come to terms that the current hydrologic designs are no longer relevant due to their assumption of stationarity. This study describes a systematic method of selecting a best fit model in relationship to location and time, along with the use of that best fit model for evaluation of future extremes. Rain gage stations throughout Florida are used to collect daily precipitation data used in extreme precipitation and quantitative indices. Through these indices conclusions are made on model selection and future extremes, as they relate to hydrologic designs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

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