Unit hydrograph identification based on fuzzy regression analysis

A methodology has been developed to treat the uncertainties of the unit hydrograph rainfall-runoff transformation based on the fuzzy linear regression model. The components of the unit hydrograph are proposed to be symmetric triangular fuzzy numbers. The main idea is to develop a fuzzified version of the widely-used unit hydrograph. The input of the model is the effective rainfall (which is a set of crisp numbers) and the output is the runoff (which is a set of fuzzy numbers). The problem of determining the fuzzy components of the unit hydrograph is transformed into a linear optimization approach based on the fuzzy linear regression of Tanaka. The condition applied is that the data must be included in the fuzzy band of discharge produced by the fuzzy unit hydrograph. However, some modifications of the widely-used fuzzy regression are proposed in order to be compatible with the unit hydrograph implementation. The model was tested based on twenty real rainfall-runoff events, the conclusion being that it works well in the case of an individual storm event. However, the consideration of many storms seems to be required in order to increase the applicability of the produced fuzzy hydrograph to other storms in such a way that the fuzziness is increased. Several measures of suitability are proposed in order to check the efficiency of the proposed method. Several other useful comments according to the comparison with other unit hydrograph considerations are made.

Automated summary

A methodology using fuzzy linear regression model was developed to handle uncertainties in unit hydrograph rainfall-runoff transformation. The model showed promising results in individual storm events, but further consideration of multiple storms is needed to increase its applicability.