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.
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References
ASCE (1993) Criteria for evaluation of watershed models. J Irrig Drain Eng 119:422–449
Chang F-J, Chen L (1998) Real-coded genetic algorithm for rule-based flood control reservoir management. Water Resour Manag 12:185–198
Conn AR, Gould NI, Toint PL (2000) Trust region methods. vol 1. Siam
Cooper V, Nguyen V-T-V, Nicell J (2007) Calibration of conceptual rainfall–runoff models using global optimisation methods with hydrologic process-based parameter constraints. J Hydrol 334:455–466
Cunderlik J, Simonovic SP (2004) Calibration, verification and sensitivity analysis of the HEC-HMS hydrologic model. Department of Civil and Environmental Engineering, The University of Western Ontario
Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33:140–158
Fleming M, Neary V (2004) Continuous hydrologic modeling study with the hydrologic modeling system. J Hydrol Eng 9:175–183
Franz KJ, Butcher P, Ajami NK (2010) Addressing snow model uncertainty for hydrologic prediction. Adv Water Resour 33:820–832
Garcia A, Sainz A, Revilla JA, Alvarez C, Juanes JA, Puente A (2008) Surface water resources assessment in scarcely gauged basins in the north of Spain. J Hydrol 356:312–326
Goldberg DE (1989) Genetic algorithms in search, optimization, and, machine learning, 1st edn. Addison-Wesley Professional
Gyawali R, Watkins DW (2013) Continuous hydrologic modeling of snow-affected watersheds in the great lakes basin using HEC-HMS. J Hydrol Eng 18:29–39. doi:10.1061/(ASCE)HE.1943-5584.0000591
Hall M (2001) How well does your model fit the data? J Hydroinf 3:49–55
Hevesi JA, Istok JD, Flint AL (1992) Precipitation estimation in mountainous terrain using multivariate geostatistics part I: structural analysis. J Appl Meteorol 31
Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann Arbor
McEnroe B (2010) Guidelines for continuous simulation of streamflow in Johnson County, Kansas, with HEC-HMS. Department of Civil, Environmental and Architectural Engineering, Univ of Kansas
Melanie M (1999) An introduction to genetic algorithms. Massachusetts Institute of Technology
Nash J, Sutcliffe JV (1970) River flow forecasting through conceptual models part I-A discussion of principles. J Hydrol 10:282–290
O’Reilly U-M, Yu T, Riolo R, Worzel B (2005) Genetic programming theory and practice II. Genetic programming series. Springer Science + Business Media, Inc
Oxley RL, Mays LW (2014) Optimization–simulation model for detention basin system design. Water Resour Manag 28:1157–1171
Raes D (2009) The ETo calculator reference manual version 3.2, food and Agriculture Organization of the United Nations. Land and Water Division, Via delle Terme di Caracalla, p 153
Reshma T, Reddy KV, Pratap D, Ahmedi M, Agilan V (2015) Optimization of calibration parameters for an event based watershed model using genetic algorithm. Water Resour Manag 29:4589–4606
Savic DA, Walters GA, Davidson JW (1999) A genetic programming approach to rainfall-runoff modelling. Water Resour Manag 13:219–231
Saxton KE, Rawls WJ, Romberger JS, Papendick RI (1986) estimating generalized soil-water characteristics fromTexture. Soil Sci Soc Am J 50
Scharffenberg WA, Fleming MJ (2005) Hydrologic Modeling System HEC-HMS user’s Manual vol version 3, Davis
Scharffenberg W, Ely P, Daly S, Fleming M, Pak J (2010) Hydrologic Modeling System (HECHMS): physically-based simulation components. In: 2nd Joint Federal Interagency Conference, Las Vegas, 2010
Shrestha, Solomatine DP (2008) Data-driven approaches for estimating uncertainty in rainfall-runoff modelling. Intl J River Basin Manag 6:109–122
Skahill BE (2006) Potential improvements for HEC-HMS automated parameter estimation. DTIC document
Skahill BE, Doherty J (2006) Efficient accommodation of local minima in watershed model calibration. J Hydrol 329:122–139
USACE USACoE (2000) Hydrologic Modeling System HEC-HMS- technical reference manual. Washington
USACE USACoE (2009) HEC-DSSVue, HEC data storage system visual utility engine-user’s manual, Davis
USACE USACoE (2010) Snowmelt modeling in HEC-HMS
USACE USACoE (2013) Hydrologic Modeling System HEC-HMS, user’s manual, version 4.0
USDA (2007) Hydrologic soil groups. In: Service USDoANRC (ed) National Engineering Handbook (NEH) part 630, hydrology. Hydrologic Soil Groups. The U.S. Department of Agriculture (USDA)
Verdhen A, Chahar B, Sharma O (2013) Snowmelt runoff simulation using HEC HMS in a Himalayan watershed. Paper presented at the World Environmental and Water Resources Congress, Cincinnati
Vos NJ, Rientjes THM, Gupta HV (2010) Diagnostic evaluation of conceptual rainfall–runoff models using temporal clustering. Hydrol Process 24:2840–2850
Wheater H, Sorooshian S, Sharma KD (2008) Hydrological modelling in arid and semi-arid areas. Cambridge University Press
Zhang X, Hörmann G, Fohrer N, Gao J (2012) Parameter calibration and uncertainty estimation of a simple rainfall-runoff model in two case studies. J Hydroinf 14:1061–1074
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Dariane, A.B., Javadianzadeh, M.M. & James, L.D. Developing an Efficient Auto-Calibration Algorithm for HEC-HMS Program. Water Resour Manage 30, 1923–1937 (2016). https://doi.org/10.1007/s11269-016-1260-7
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DOI: https://doi.org/10.1007/s11269-016-1260-7