پیش بینی زمان تاخیر با استفاده از روابطی بر مبنای رگررسیون فازی

نوع مقاله : Original Articles

نویسندگان

1 دانشجوی دکترای آبخیزداری، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد

2 دانشیار گروه، دانشکده علوم و فنون نوین، دانشگاه تهران، تهران

3 دانشیار گروه آبخیزداری، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد

چکیده

زمان تاخیر حوزه آبخیز یک فاکتور مهم در مدلسازی واکنش حوزه آبخیز است. در این مطالعه مدلسازی زمان تاخیر با استفاده از رگررسیون فازی انجام شده است. برای این منظور، داده های بارش - رواناب حوزه آبخیز خانمیرزا جمع آوری و تحلیل شدند. سپس وقایع (9 واقعه) به دو گروه شامل یک گروه برای ساخت روابطی برمبنای رگرسیون فازی و گروه دیگر برای ارزیابی این روابط تقسیم شدند. نتایج بدست آمده از این تحقیق برمبنای معیارهای آماری خطای نسبی و ریشه میانگین مربع خطا نشان دادند که روابط جدید توسعه یافته برمبنای رگررسیون فازی نسبت به دیگر روابط موجود برای محاسبه زمان تاخیر مناسب تر هستند.

کلیدواژه‌ها


عنوان مقاله [English]

Lag Time Forecasting Using Fuzzy Regression Based Formulae

نویسندگان [English]

  • Moslem Heydari 1
  • Seyed Javad Sadatinejad 2
  • Afshin Honarbakhsh 3
1 PHD. Student of watershed management, Faculty of Natural Resources and Earth Sciences, University of Shahrekord
2 Associate Professor, Department of, Faculty of New Sciences and Technologies, University of Tehran
3 Associate Professor, Department of watershed management, Faculty of Natural Resources and Earth Sciences, University of Shahrekord
چکیده [English]

River basin lag time is an important factor in the linear modelling of river basin response. In this study, the modelling of lag time using fuzzy regression is applied. For this purpose, the data for rainfall-runoff events of Khanmirza basin (nine events) were collected and analysed. Following on, events were divided into two groups: one for formulas based on fuzzy regression and another for the validation of these formulas. The results obtained from this study, based on RE and RMSE statistical measures, showed that the efficiency of newly developed formulas based on fuzzy regression methods is higher than for other formulas used for the calculation of time of concentration.

کلیدواژه‌ها [English]

  • Keywords:Lag time
  • Fuzzy Regression
  • Hydrology
  1. Abeb, A. J., Solomatine, D. P. and Vennerker, R. G. W. (2000) Application of adaptive fuzzy rule based methods for reconstruction of missing precipitation events. Hydrological Science Journal, 45(3):425-436.
  2. Anderson, D. G. (2001) Effects of Urban Development on Flood in Northern Virginia. U.S.G.S Water Supply Paper C.
  3. Gray, D.M. (1961) Synthetic unit hydrographs for small watersheds. Journal of the Hydraulics Division, Proceedings of the American Society of Civil Engineers, (4):33-54.
  4. Gutierres Estrada, J. C., Pulido Valvo, I., Rosa, I. and Marchini, B. (2011) Modelling inflow rates for the water exchange management in semi-intensive aquaculture ponds. Aquacultural Engineering, (48):19-30.
  5. Heydari, M.( 2010) Revision of Some Empirical Models for Estimation of Time of Concentration and Survey the Efficiency of Fuzzy Regression Model to Estimate the Time of Concentration in North Karoon River Basin. Msc. Thesis, Shahrekord University (in Persian).
  6. http://www.emsi.com/wmshelp/Hydrologic_Models/Calculators/Computing_Travel_Times/Using_Basin_Data/Equations/Overview_of_Basin_Data_Equations.htm, (assessed: March 31, 2010).
  7. Laenen, A. (1980) Storm Runoff as Related to Urbanization in the Portland, Oregon- Vancouver, Washington Area. U.S.G.S, Water Resource Investigations Open File Report, pp. 80-689.
  8. Laureson, E. M. (1964) A catchment storage model for runoff routing. Journal of Hydrology, (2):141-163.
  9. Leopold, L. B. (1968) Hydrology for Urban Land Planning. A Guidebook on the Hydrologic Effect of Urban Land Use. U.S.G.S Circular, at p. 554.
  10. Lohani, A. K., Goel, N. K. and Bhatia, K.S. (2006) Takagi-Sugeno Fuzzy Inference System for Modelling Stage-Discharge Relationship. Journal of Hydrology, 333:146-160.
  11. Matreja, K.N. (1990) Applied Hydrology. JaTa McGraw Hill Publishing Company Limited, at p. 204.
  12. Ragan, R. M. and Duru, J O. (1972) Kinematic wave nomograph for time of concentration. Journal of the Hydraulics Division, Proceedings of the American Society of Civil Engineers, 98(10):1765-1771.
  13. Ramirez, J. A. (2000) Prediction and Modelling of flood Hydrology and Hydraulics. Chapter 11 of Inland Flood Hazards: Human, Riparian and Aquatic Communities Ed. Ellen Wohl. Cambridge University Press at p. 307.
  14. Rao, A. R. and Delleur, J. W. (1974) Instantaneous unit hydrograph, peak discharges and time lags in urban areas. Hydrological Sciences Bulletin, 19(2):185-198.
  15. Rastogi, R.A. and Jones, B.A. (1969) Simulation and hydrologic response of a drainage net of a small agricultural drainage basin. Transactions of the American Society of Agricultural Engineers, (12): 899-908.
  16. Roussel, M. C., Thompson, D. B., Fang, X., Cleverland, T. G. and Garcia, C. A. (2005) Time Parameters Estimation for Applicable Texas Watersheds. Department of Civil Engineering, Lamar University, Beaumont, TX: Research Project Summary Report 0-4696-s.
  17. Sadatinejad, S. J. and Shayannejad, M. and Honarbakhsh, A. (2009) Investigation of the Efficiency of the Fuzzy Regression Method in Reconstructig Monthly discharge Data of Hydrometric Stations in Great Karoon River Basin. J. Agr. Sci. Tech, (11):111-119.
  18. Sanchez, J.D. and Gomez A.T. (2003) Applications of fuzzy regression in actuarial analysis. Journal of Risk and Insurance, 70(4):797-802.
  19. Saneifard, R. and Ahmadianrad, H. (2012) On the overflow alert system based on fuzzy models. Current research journal of biological sciences, 4(2): 198-201.
  20. Schulz, E.F. and Lopez, O.G. (1974) Determination of urban watershed response time. Hydrology Paper No. 71, Colorado State University, Fort Collins, CO.
  21. Shamskia, N., Rahmati, S. H., Haleh, H. and Rahmati, S.H. (2011) A new approach of fuzzy methods for evaluating of hydrological data. World Academy of Science, Engineering and Technology, 5(5): 1051-1059.
  22. Singh, V. P. and Agiralioglu, N. (1982) Lag time for diverging overland flow. Nordic Hydrology, (13):39-48.
  23. Sudharsanan, R. M., Krishnaveni, R., and Karunakaran, K. (2010) Derivation of Instantaneous Unit Hydrograph for a sub- basin using Linear Geomorphological Model and Geographic Information Systems 77710. Journal of Spatial Hydrology, 10(1): 30-40.
  24. Tanaka, H., Uejima, S. and Asai, K. (1982) Linear regression analysis with fuzzy model. IEEE Transactions on Systems Man, Cybern, 12(6):903-907.
  25. Thompson, D.B., Fang, X. and Cleverland, T.G. (2004) Literature Review on Time Parameters for Hydrographs. Department of Civil Engineering, Lamar University, Beaumont, TX.