The objective of the research presented in this report is the development of relationships to estimate flood magnitudes for Indiana streams. In order to achieve this goal several probability distributions were evaluated. The Pearson (3) (LP(3)) and the Generalized Extreme Value (GEV) distributions were found to be the best distributions for Indiana data. Because of the requirement that Log Pearson (3) (LP(3)) distribution must be used in federally-funded projects it was retained in the study.

Relationships were developed for the flood frequencies to be estimated by the LP(3) distributions. The State of Indiana has been divided into regions, seven of which are homogeneous and one heterogeneous. The floods of specific return periods were related to watershed characteristics which are relatively easy to measure by the generalized least squares (GLS) method.

The regional flood estimates based on L-moments have been developed and presented for all the eight regions. These are based on P(3), GEV and LP(3) distributions. The GLS based regional regression analysis was used to relate the flood magnitudes based on these distributions and watershed parameters. The L-moment based methods and the regional regression relationships are compared to each other by split sample tests.

The following conclusions are presented based on this study. (1) Identifying homogeneous regions prior to development of flood frequency relationships substantially reduce the prediction errors. (2) The L-moment based flood frequency relationships are more accurate than those developed by regional regression analysis (3) The Pearson (3) and GEV distributions give more accurate flood flow estimates than the LP(3) distribution.

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flood frequency analysis, watersheds, generalized least squares, SPR-2858

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Performing Organization

Joint Transportation Research Program

Publisher Place

West Lafayette, IN

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