Automatic Calibration of HEC-HMS Model Using Multi-Objective Fuzzy Optimal Models

Document Type : Research Papers

Authors

1 PhD. Student, College of Civil and Environmental Engineering, Amirkabir University of Technology, P.O. Box: 15875-4413, Tehran, Iran.

2 Associate Professor, College of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran. P.O. Box: 15875-4413, Tehran, Iran.

Abstract

Estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. This study aimed to use the particle swarm optimization (PSO) algorithm for automatic calibration of the HEC-HMS hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff process. Since a flood hydrograph has different characteristics such as time to peak, peak discharge and total runoff volume, the calibration process is addressed using a single-objective or multi-objective optimization model. In this context, the fuzzy set theory can be used to combine different objective functions and convert the multi-objective model to a single-objective one. In this research, the Tamar basin, a sub-basin of the Golestan-Dam Basin in north of Iran, was selected as the case study with four reliable measured flood events. The first three events were used for calibration and the fourth one for verification. As most of the models built in the HEC-HMS software were event-based, the concept of recalibration of parameters related to a basin initial condition was also introduced. The comparison of results obtained from the single and multi-objective scenarios showed the efficiency of the proposed HMS-PSO simulation-optimization approach in the multi-objective calibration of event-based hydrologic models.

Keywords

References

Bekele, E.G. and Nicklow, J.W. (2007). Multi-objective automatic calibration of SWAT using NSGA-II, Journal of Hydrology, 341(3-4), 165-176.
Cheng, C.T., Oub, C.P. and Chauc, K.W. (2002). “Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration”, Journal of Hydrology,26(1-4), 72-86.
Chow V.T., Maidment D.R. and Mays L.W. (1988). Applied Hydrology, McGraw, Inc., ISBN-10: 0070108102, New York, USA. Pages 502. Table 15.1.2 SCS lag Equation.
Duan, Q., Sorooshian, S. and Gupta, H.V. (1994). “Optimal use of the SCE-UA global optimization method for calibrating watershed models”, Journal of Hydrology, 158, 265-284.
Eberhart, R.C. and Kennedy, J. (1995). “A new optimizer using particle swarm theory”, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, Piscataway, NJ: IEEE Service Center, 39-43. 
Iran Water Research Institute (IWRI). (2008). Report on hydrologic model calibration: Gorganroud flood warning system project, Water Resources Department, Tehran, Iran.
Kamali, B., Mousavi, S.J. and Abbaspour, K. (2013). “Automatic calibration of HEC-HMS using single-objective and multi-objective PSO algorithms”, Hydrological Processes, 27(26), 4028-4042.
Liu, H. and Abraham A. (2007). “A fuzzy adaptive turbulent particle swarm optimization”, International Journal of Innovative Computing and Applications, 1(1), 39-47.
Madsen, H. (2000). “Automatic calibration of a conceptual rainfall–runoff model using multiple objectives”, Journal of Hydrology, 235, 276–288.
Moussa, R. and Chahinian, N. (2009). “Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events”, Journal of hydrology and Earth System Sciences, 13, 519-535.
Parsopoulos, K.E. and Vrahatis, M.N. (2002). “Recent approaches to global optimization problems through particle swarm optimization”, Natural Computing, 1(1-2), 235-306.
Reddy, M.J. and Kumar, D.N. (2007). “An efficient multi-objective optimization algorithm based on swarm intelligence for engineering design”, Engineering Optimization, 39, 49-68.
Scharffenberger, W.A. and Fleming, M.J. (2008). Hydrologic modeling system HEC-HMS user’s manual, US Army Corps of Engineers, 1-290.
Timothy D.S., Charles S.M. and Kyle E.K. (2000). “Equations for estimating Clark unit hydrograph parameters for small rural watersheds in Illinois”, Water Resources Investigations Report. Cooperation with the Illinois Department of Natural Resources, Office of Water Resources Urbana, Illinoise,
USACE. (2008). Hydrologic modeling system HEC-HMS applications guide. US. Army Corps of Engineers, Hydrologic Engineering Center (HEC), Washington, DC.
Yapo, P., Gupta, H.V. and Sorooshian, S. (1998). “Multi-objective global optimization of hydrologic models”, Journal of Hydrology, 204, 83-97.

Files

History

  • Receive Date: 14 September 2011
  • Revise Date: 02 December 2012
  • Accept Date: 30 December 2012

Share

How to cite

Statistics