CASE STUDIES
May 23, 2011

Accuracy of HEC-HMS and LBRM Models in Simulating Snow Runoffs in Upper Euphrates Basin

Publication: Journal of Hydrologic Engineering
Volume 17, Issue 2

Abstract

Forecasting streamflow is extremely significant in hydrological studies to optimize the operation of water resources systems. Upper Euphrates Basin, which is located in eastern Turkey, is a snow-dominated basin and its runoff is largely affected by snowmelt. Snowmelt is an important water resource to many aspects of hydrology, including water supply, flood control, and erosion. Selection of a suitable tool was necessary to assess potential impacts of climate change on the hydrological cycle of this region. Hydrologic models are useful tools for the prediction of runoffs and interactions among hydrological variables within the hydrologic cycle. Because of limited data availability, lumped conceptual hydrological models are often used instead of distributed hydrological models. To assess the accuracy of lumped conceptual hydrological models, this paper presents simulation results of snowmelt runoffs of Upper Euphrates Basin by using two models that use the temperature index approach to calculate snowmelt process. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Large Basin Runoff Model (LBRM) were used for this purpose.

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References

Abudu, S., King, J. P., and Bawazir, A. S. (2011). “Forecasting monthly streamflow of spring-summer runoff season in rio grande headwaters basin using stochastic hybrid modeling approach.” J. Hydrol. Eng., 16(4), 384–390.
Akhtar, M. K., Corzo, G. A., van Andel, S. J., and Jonoski, A. (2009). “River flow forecasting with artificial neural networks using satellite observed precipitation pre-processed with flow length and travel time information: case study of the Ganges river basin.” Hydrol. Earth Syst. Sci., 13(9), 1607–1618.
Aqil, M., Kita, I., Yano, A., and Nishiyama, S. (2007). “A comparative study of artificial neural networks and neuro-fuzzy in continuous modelling of the daily and hourly behaviour of runoff.” J. Hydrol. (Amsterdam), 337(1-2), 22–34.
Charbonneau, R., and Lardeau, J. P. (1981). “Problems of modelling a high mountainousdrainage basin with predominant snow yields.” Hydrol. Sci. Bull., 26(4), 345–361.
Croley, T. E. (2002). “Large basin runoff model.” Mathematical models in watershed hydrology, V. Singh, D. Frevert, and S. Meyer, eds., Water Resources, Littleton, CO, 717–770.
Croley, T. E., and He, C. (2005). “Distributed-parameter large basin runoff model I: Model development.” J. Hydrol. Eng., 10(3), 173–181.
Croley, T. E., He, C., and Lee, D. H. (2005). “Distributed-parameter large basin runoff model II: Application.” J. Hydrol. Eng., 10(3), 182–191.
Croley, T. E., Quinn, F. H., Kunkel, K. E., and Changnon, S. J. (1998). “Great Lakes hydrology under transposed climates.” Clim. Change, 38(4), 405–433.
Dressler, K. A., Leavesley, G. H., Bales, R. C., and Fassnacht, S. R. (2006). “Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model.” Hydrol. Process, 20(4), 673–688.
He, C., and Croley, T. E. (2007). “Application of a distributed large basin runoff model in the Great Lakes Basin.” Control Eng. Pract., 15(8), 1001–1011.
Hock, R. (2003). “Temperature index melt modelling in mountain areas.” J. Hydrol. (Amsterdam), 282(1-4), 104–115.
Hu, H. H., Kreymborg, L. R., Doeing, B. J., Baron, K. S., and Jutila, S. A. (2006). “Gridded snowmelt and rainfall-runoff CWMS hydrologic modeling of the red river of the north basin.” J. Hydrol. Eng., 11(2), 91–100.
Karunanithi, N., Grenney, W. J., Whitley, D., and Bovee, K. (1994). “Neural networks for river flow prediction.” J. Comput. Civ. Eng., ASCE, 8(2), 201–220.
Liston, G. E., and Elder, K. (2006). “A distributed snow-evolution modeling system (snowmodel).” J. Hydrometeorol., 7(6), 1259–1276.
Malikov, M. (2004). “The importance of snowmelt runoff modelling for sustainable development and disaster prevention.” Regional Workshop on the Use of Space Technology for Environmental Security, Disaster Rehabilitation and Sustainable Development, Islamic Republic of Iran.
Marim, G., Sensoy, A., and Sorman, A. U. (2009). “Applications of snowmelt runoff model for Upper Euphrates Basin using snow depletion curves derived from optical satellites.” EGU2009-1086, Geophysical Research Abstracts, 11.
Mernild, S. H., Liston, G. E., Steffen, K., van den Broeke, M., and Hasholt, B. (2010). “Runoff and mass-balance simulations from the greenland ice sheetat Kangerlussuaq (Søndre Strømfjord) in a 30-year perspective, 1979-2008.” The Cryosphere, 4(2), 232–241.
Nagler, T., Rott, H., Malcher, P., and Muller, F. (2008). “Assimilation of meteorological and remote sensing data for snowmelt runoff forecasting.” Remote Sens. Environ., 112(4), 1408–1420.
Ohara, N., Kavvas, M. L., Easton, D., Dogrul, E. C., Yoon, J. Y., and Chen, Z. Q. (2010). “The role of snow in runoff processes in a sub-alpine hillslope: Field study in the Ward Creek watershed, Lake Tahoe, California during 2000 and 2001 water years.” J. Hydrol. Eng., 16(6), 521–533.
Parajka, J., and Bloschl, G. (2008). “The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models.” J. Hydrol. (Amsterdam), 358(4 March), 240–258.
Prasad, V. H., and Roy, P. S. (2005). “Estimation of snowmelt runoff in Beas Basin, India.” Geocarto International, 20(2), 41–47.
Sensoy, A. (2005). “Physically based point snowmelt modeling and its distribution in Upper Euphrates Basin.” Middle East Technical Univ., Ankara, Turkey.
Sorman, A. A., Sensoy, A., Tekeli, A. E., Sorman, A. U., and Akyurek, Z. (2009). “Modelling and forecasting snowmelt runoff process using the HBV model in the eastern part of Turkey.” Hydrol. Process., 23(7), 1031–1040.
Tarboton, D. G., and Luce, C. H. (1996). “Utah energy balance snow accumulation and melt model (UEB): Computer model technical description and users guide.” 〈http://www.fs.fed.us/rm/boise/publications/watershed/rmrs_1996_tarbotond001.pdf〉 (July 10, 2010).
Tekeli, A. E., Akyurek, Z., Sorman, A. A., Sensoy, A., and Sorman, A. U. (2005). “Using MODIS snow cover maps in modeling snowmelt runoff process in the eastern part of Turkey.” Remote Sens. Environ., 97(2), 216–230.
Turan, M. E., and Yurdusev, M. A. (2009). “River flow estimation from upstream flow records by artificial intelligence methods.” J. Hydrol. (Amsterdam), 369(1-2), 71–77.
US Army Corps of Engineers Hydrologic Engineering Center (USACE). (2009). “Hydrologic modeling system HEC-HMS user’s manual.” 〈http://www.hec.usace.army.mil/software/hec-hms/〉 (January 5, 2012).
Yoshitani, J., Chen, Z. Q., Kavvas, M. L., and Fukami, K. (2009). “Atmospheric model-based streamflow forecasting at small, mountainous watersheds by a distributed hydrologic model: Application to a watershed in Japan.” J. Hydrol. Eng., 14(10), 1107–1118.

Information & Authors

Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 17Issue 2February 2012
Pages: 342 - 347

History

Received: Aug 17, 2010
Accepted: May 20, 2011
Published online: May 23, 2011
Published in print: Feb 1, 2012

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Authors

Affiliations

Abdullah Gokhan Yilmaz [email protected]
Heriot-Watt Univ., School of the Built Environment, Civil Engineering Dept., PO Box: 294345, Dubai, UAE (corresponding author). E-mail: [email protected]
Monzur Alam Imteaz
Faculty of Engineering and Industrial Sciences, Swinburne Univ. of Technology, Hawthorn, Melbourne, Victoria 3122, Australia.
Olisanwendu Ogwuda
Heriot-Watt Univ., School of the Built Environment, Civil Engineering Dept., PO Box: 294345, Dubai, UAE.

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