Developing an Efficient Auto-Calibration Algorithm for HEC-HMS Program

Alireza B. Dariane (), M. M. Javadianzadeh and L. Douglas James
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Alireza B. Dariane: K.N. Toosi University of Technology
M. M. Javadianzadeh: K.N. Toosi University of Technology
L. Douglas James: Utah State University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 6, No 4, 1923-1937

Abstract: Abstract Two auto-calibration methods, namely Nelder-Mead (NM) and Univariate-Gradient (UG) and a manual approach are available for calibrating the HEC-HMS program. However, their being either inefficient or time consuming makes it difficult to work with HEC-HMS especially when using a snowmelt module in a continuous mode. The main objective of this paper is to develop an efficient Genetic Algorithm (GA) based auto-calibration method for HEC-HMS model (HMS-GA) for continuous snowmelt simulation. A general novel procedure is presented in the absence of the HMS source code to link a heuristic algorithm with the HEC program through Jython programming language. The models are developed and evaluated using daily data from basins in Ajichai, northwestern Iran. A comparison of results for a verification period indicates a substantial improvement by applying the HMS-GA over the other available methods. Moreover, it is shown that neither NM nor UG is able to improve the results obtained by either the manual or HMS-GA. Furthermore, the proposed method significantly improves the calibrations of the HMS model found by the three other methods.

Keywords: HEC-HMS; Heuristic algorithm; Auto-calibration; Jython; Soil moisture accounting; Continuous model (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11269-016-1260-7

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