Automated Simulation of Basin Characteristics Using HEC-HMS, Genetic Algorithm, and AutoIt on Observed Hydrograph Properties

Document Type : Original Article

Authors

1 M. Sc. student, Dept. of Water Structure Engineering, Tarbiat Modares University, Tehran, Iran

2 Professor, Dept. of Water Structure Engineering, Tarbiat Modares University, Tehran, Iran.

Abstract

The main objective in calibration of conceptual Rainfall-Runoff models is to find a set of optimal model parameters that provide the best fitness between the observed and the estimated flow hydrographs. These models are general, but when there is a lack of data, their application will be too difficult. In basins without data using the synthetic unit hydrograph for calculation of design flood is inevitable. Recently, it is shown that the use of the heuristic algorithms in combinational optimization problems is very suitable. In this research, two different algorithms, Univariate-Gradient as a classic optimizer, and Genetic Algorithm as a throughout optimizer, were used for calibrating snyder, Clark, and SCS unit hydrograph models in HEC-HMS software. The flood of Bahman 14-18, 1371 (Shamsi Calendar) in Dejgan station, MehranRiver, Hormozgan Province, was used in this study. Results showed that the combination of GA and Snyder method is appropriate for forecasting the basin characteristics. The basin characteristic can be obtained using this method, observed hydrograph, and fitness function. “AutoIt” software was used for automated running of simulation and optimization.

Keywords

References

خلقی، پ. (1387)، "استفاده از روشهای الگوریتم ژنتیک و بهینه‌سازی دسته ذرات در حل معکوس مدل‌سازی آلودگی آب زیرزمینی"، هفتمین کنفرانس هیدرولیک ایران.
قدمی، س. م.، قهرمان، ب.، شریفی، م. ب. و رجبی، ح. (1388)، "بهینه­سازی بهره­برداری از سیستم­های چند مخزنی منابع آب با استفاده از الگوریتم ژنتیک"، مجله تحقیقات منابع آب ایران، شماره 2، ص15-1.
علیزاده، ا. (1383)، "اصول هیدرولوژی کاربردی"، دانشگاه فردوسی مشهد، 631ص. 
Tang, Y., Reed, P. M. and Kollat, J. B. (2007), "Parallalezation Strategies for Rapid and Robust Evolutionary Multi-objective Optimization in Water Resources Applications", Adv. Water resource, pp. 335-353.

Files

History

  • Receive Date: 04 July 2009
  • Accept Date: 28 September 2010

Share

How to cite

Statistics