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An Analysis of MLR and NLP for Use in River Flood Routing and Comparison with the Muskingum Method

Author(s): Mohammad Zare; Manfred Koch

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Keywords: Flood wave routing; Muskingum; Nonlinear programming; Multiple linear regression

Abstract: The development of precise and simple methods for flood simulation has greatly reduced financial damages and life losses in many flood-prone regions of the world. Most of the flood simulation techniques and procedures implemented up-to-date are based on the Saint-Venant's one-dimensional equation governing unsteady flows. In the present study, two new approaches for tackling the problem of optimal calibration of a flood model have been introduced. The first method is based on nonlinear programming (NLP), which permits to determine the optimum values of the routing coefficients in the diffusion wave or Muskingum method by minimizing a misfit function under the constraint of satisfying the continuity equation. The second method is based on Multiple Linear Regression (MLR) of in- and output variables in the Muskingum equations, which allows the direct computation of the routing coefficients. To calibrate and verify the two new routing models as well as of the traditional Muskingum method three (one for calibration and two for verification) observed flood hydrographs in a limited reach of Mehranrood River in northwest Iran are used. The results obtained by these two new methods are compared with those of the classical Muskingum method. It is found that the NLP- and the MLR- routed hydrographs come as close, if not better, to the observed output hydrographs as those of the Muskingum method. This is also corroborated by similar high values for the coefficient of determination R2 of the adjustment of the simulated to observed hydrographs for the three routing methods. However, limitations of all three kinematic-wave type routing methods become clear during the verification routing simulation for one flood even with a sharply rising input hydrograph, in the case of which, the application of full dynamic wave routing gives much better results. In spite of these restrictions - typical for kinematic wave routing methods - the two new parameter optimization methods proposed here for the automatic calibration of the routing coefficients in the widely used Muskingum method are powerful and reliable procedures for flood routing in rivers, not to the least due to the fact that they are convenient to use.

DOI:

Year: 2013

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