Seyhan Havzasında SWAT Modeli İle Nehir Akış Simülasyonu Ve Değerlendirilmesi

Toprak ve Su Değerlendirme Yazılımı (SWAT) Türkiye'de bulunan Seyhan nehri havzasında hidrolojik işlemleri su bütçesini temel alarak simüle etmek için kullanılmıştır. Model duyarlılık analizi ve otomatik kalibrasyonlar, SWAT-Kalibrasyon paket programında (SWAT-CUP) bulunan, Sıralı Belirsizlik Uygunluğu (SUFI-2), Genelleştirilmiş Olabilir Belirsizlik Tahmini (GLUE) ve Parametre Çözümü (ParaSol) algoritmaları kullanılarak, Üçtepe, Himmetli, Korkun ve Zamantı akarsuları için yapılmıştır. Duyarlılık analizi sonucunda, Baz Akış Alfa Faktörü (ALPHA_BF) ve SCS akış eğri numarasının (CN2) bu havza için akıma etki eden en hassas parametreler olduğunu göstermiştir. Gözlenen akım verilerinde tüm belirsizlik kaynaklarının ParaSol sonucunda Üçtepe (% 57) hariç, SUFI-2 ve ParaSol sonuçlarında %60’dan fazla olduğu görülmüştür. Akış verilerinin kalibrasyonu aylık bazda 2001-2007 dönemi için yapılmıştır. Nash Sutcliffe Katsayısına (NSE) göre ParaSol, SUFI-2 ve GLUE’ye göre daha iyi sonuçlar vermiştir. Kullanılan kalibrasyon algoritmaları arasında en iyi sonuç, (NSE=0.74) Zamanti akış verilerinin Parasol algoritması ile kalibrasyonu sonucu bulunmuştur.

Anahtar Kelimeler:

Hidrolojik modelleme, Seyhan havzası, SWAT modeli, nehir akış simülasyonu

Evaluation of Streamflow Simulation By SWAT Model for The Seyhan River Basin

The Soil and Water Assessment Tool (SWAT) was used to model the hydrological water balance from theSeyhan river basin located in Turkey. The model sensitivity analysis and auto-calibration were conducted atfour sites (i.e., Uctepe, Himmetli, Korkun and Zamanti) using the Sequential Uncertainty Fitting (SUFI-2), theGeneralized Likelihood Uncertainty Estimation (GLUE) and Parameter Solution (ParaSol) algorithms in theSWAT-Calibration Uncertainty Programs (SWAT-CUP) package. The sensitivity analysis showed that thebase-flow alpha factor (ALPHA_BF) and SCS runoff curve number (CN2) are the most sensitive parametersfor this catchment. All sources of uncertainties were captured by bracketing more than 60% of the observedriver discharge when using SUFI-2 and ParaSol except for ParaSol at Uctepe (57%). Streamflow calibrationwas done at a monthly time step for the period of 2001-2007. The results showed that ParaSol gave betterresults than those obtained by SUFI-2 and GLUE with regard to the Nash Sutcliffe Efficiency (NSE). Amongall of the calibrated sites and the various calibration algorithms, the highest NSE (0.74) was obtained when themodel was calibrated at Zamanti using the ParaSol algorithm.

Keywords:

Hydrologic modelling, Seyhan river basin, SWAT model, streamflow simulation,

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Abbaspour, K.C., Faramarzi, M., Ghasemi, S.S.& Yang H., (2009). Assessing the impact of climate change on water resources in Iran. Water Resour. Res. 45, 1-16.
Abbaspour, K.C., Vejdani, M. & Haghighat, S., (2007a). SWATCUP calibration and uncertainty programs for SWAT. In Proc. Intl. Congress on Modelling and Simulation (MODSIM’07), 1603-1609. L. Oxley and D. Kulasiri, eds. Melbourne, Australia: Modelling and Simulation Society of Australia and New Zealand.
Abbaspour, K.C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J. & Srinivasan, R., (2007b). Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT., J. Hydrol.333, 413–430.
Acar, A. & Dincer, I., (2005). Left upstream slope design for the Catalan Dam, Adana, Turkey and its behavior under actual earthquake loading. Eng. Geol. 82, 1– 11.
Akiner, M.E. & Akkoyunlu, A., (2012). Modeling and forecasting river flow rate from the Melen Watershed, Turkey. J. Hydrol. 456–457,121–129.
Allen, R.G., (1997). Self-Calibrating Method for Estimat¬ing Solar Radiation from Air Temperature. J. Hydrol. Eng. 2(2), 56-67.
Allen, R.G., Walter, I.A., Elliot, R.L. & Howell, T.A., (2005). The ASCE Standardized Reference Evapotranspiration Equation. Reston, VA: American Society of Civil Engineers.
Arnold, J.G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., Santhi, C., Harmel, R. D., van Griensven, A., M. W., Van Liew, Kannan, N., & Jha, M. K., (2012). SWAT: model use, calibration and validation. Trans. ASABE,55(4),1491-1508.
Arnold, J.G., Srinivasan, R., Muttiah, R.S. & Williams, J.R., (1998). Large area hydrologic modeling and assessment. Part I: Model development. J. Am. Water Resour. As. 34 (1), 73-89.
Beven, K. & Binley A., (1992). The future of distributed models – Model calibration and uncertainty prediction. Hydrol. Process. 6(3), 279–298.
Beven, K.J., Lamb, R., Quinn, P.F., Romanowicz, R. & Freer, J., (1995). Chapter 18: TOPMODEL. In: Computer Models of Watershed Hydrology (V.P. Singh, ed.), Water Resources Publications, Colorado, pp. 627-668.
Cao, W.Z., Bowden, W.B., Davie, T. & Fenemor, A., (2006). Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability. Hydrol. Process.20,1057-1073.
Cho, J., Bosch, D., Vellidis, G., Lowrance, R. & Strickland, T., (2013). Multi-site evaluation of hydrology component of SWAT in the coastal plain of southwest Georgia. Hydrol. Process.27, 1691-1700.
Crawfod, N.H. & Linsley, R.K. Jr., (1966). Digital simulation in hydrology: Stanford Watershed Model IV. In: Technical Report No. 39. Department of Civil Engineering, Stanford University. Stanford (California)
Di Luzio, M., Srinivasan, R., & Arnold, J.G., (2001). ArcView Interface for SWAT2000 - User’s Guide, Blackland Research Center, Texas Agricultural Experiment Station and Grassland, Soil and Water Research Laboratory, USDA Agricultural Research Service, Temple, Texas.
Douglas-Mankin, K.R., Srinivasan, R. & Arnold, J.G., (2010). Soil and Water Assessment Tool (SWAT) model: Current development and applications. Trans. ASABE 53(5): 1423-1431.
Duan, Q.Y., Sorooshian, S., Gupta, V., (1992). Effective and efficient global optimization for conceptual rainfall–runoff models. Water Resour. Res. 28 (4), 1015–1031.
Duffie, J.A. & Beckman, W.A., (1993). Solar Engineering of Thermal Processes, Wiley, New York, as summarized in Maidment, Handbook of Hydrology, pp 919.Eckhardt, K., Fohrer, N. & Frede, H.G., (2005). Automatic model calibration. Hydrol. Process. 19, 651–658.
Engel, B. A., Srinivasan, R., Arnold, J. G., Rewerts, C. & Brown, S. J., (1993). Nonpoint-source (NPS) pollution modeling using models integrated with geographic information systems (GIS). Water Sci. Tech.28 (3-5), 685-690.
Tanaka, K., Watanabe, T., Nagano, T. & Kojiri, T., (2008). Assessing the impacts of climate change on the water resources of the Seyhan River Basin in Turkey: Use of dynamically downscaled data for hydrologic simulations. J. Hydrol. 353, 33– 48.
Graham, D.N. & Butts, M.B., (2006). Flexible, integrated watershed modelling with MIKE-SHE. In: Watershed Models (Singh, V.P. &Frevert, D.K. eds.), CRC press, pp. 245-272.
Hargreaves, G.H. & Samani, Z.A., (1982). Estimating Potential Evapotranspiration. J. Irrig. Drain. Eng. 108(3), 223-230.
Huffman, G.J., Bolvin, D.T., Nelkin, E.J. & Wolff, D.B., (2007). The TRMM Multisatellite precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. J. Hydrometeorol.8, 38-55.
Hydrologic Engineering Center (HEC-1)., 1981. Development of a knowledge-based expert system for water resource problems. Final report, SRI project 1619, SRI international, California.
Irvem, A., Topaloglu, F. & Uygur, V., (2007). Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. J. Hydrol.336, 30– 37.
Lin, Z. & Radcliffe, D.E., (2006). Automatic calibration and predictive uncertainty analysis of a semi distributed watershed model. Vadose Zone J. 5:248-260.
Luo, P., Takara, K., He, B., Cao, W., Yamashiki, Y. & Nover, D., (2011). Calibration and uncertainty analysis of SWAT model in a Japanese river catchment. J. Jpn. Soc. Civil Eng., Ser.B1 Hydraulic Engineering, Vol. 67, No. 4, I:61-I:66
Moriasi, D.N., Arnold, J.G., van Liew, M.W., Bingner, R.L., Harmel, R.D. & Veith, T.L., (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE, 50(3), 885–900.
Nash, J.E., Sutcliffe, J.V., (1970). River flow forecasting through conceptual models. Part 1: discussion of principles. J. Hydrol. 10: 282–290.
Niraula, R., Norman, L.M., Meixner, T. & Callegary, J.B., (2012). Multi-gauge Calibration for modeling the Semi-Arid Santa Cruz Watershed in Arizona-Mexico Border Area Using SWAT. Air, Soil Water Res. 5, 41–57
Qi, C. & Grunwald, S., (2005). GIS-based hydrologic modeling in the Sandusky watershed using SWAT. Trans. ASAE, 48, 1,169-180.
Rostamiani, R., Jaleh, A., Afyuni, M., Mousavi, S.F., Heidarpour, M., Jalalian, A. & Abbaspour K.C., (2008). Application of a SWAT model for estimating runoff and sediment in two mountainous basins in central Iran. Hydrol. Sci. J. 53(5), 977-988.
Schuol, J., Abbaspour, K.C., Yang, H., Srinivasan, R. & Zhender A.J.B., (2008). Modeling blue and green water availability in Africa. Water Resour. Res. 44(W07406), 1-18
Setegn, S.G., Srinivasan, R., Melesse, A.M. & Dargahi, B., (2010). SWAT model application and prediction uncertainty analysis in the Lake Tana basin, Ethiopia. Hydrol. Process. 24,357-367.
Singh V., Bankar, N., Salunkhe, S.S., Bera, A.K. & Sharma J.R., (2013). Hydrological stream flow modelling on Tungabhadra catchment: parameterization and uncertainty analysis using SWAT CUP. Curr. Sci.104 (9), 1187-1199.
Sugawara, M., Ozaki, E., Watanabe, I. & Katsuyama, Y., (1974). Tank model and its application to Bird Creek, Wollombi Brook, Bikin River, Kitsu River, Sanga River. Research Note, National Research Centre for Disease Prevention, No. 11, Kyoto, Japan, 1-64.
Tuppad, P., Douglas-Mankin K. R., Lee T, Srinivasan R, & Arnold J.G., (2011). Soil and Water Assessment Tool (SWAT) hydrologic/water quality model: Extended capability and wider adoption. Trans. ASABE 54(5): 1677-1684.
van Griensven, A. & Bauwens, W., (2003). Multiobjective autocalibration for semidistributed water quality models. Water Resour. Res., 39(12), 1348, doi:10.1029/2003WR002284.
van Griensven, A. & Meixner, T., (2006). Methods to quantify and identify the sources of uncertainty for river basin water quality models. Water Sci.Technol., 53(1), 51–59.
Van Liew, M.W., Veith, T.L., Bosch, D.D. & Arnold J.G., (2007). Suitability of SWAT for the Conservation Effects Assessment Project: Comparison on USDA Agricultural Research Service Watersheds. J. Hydrol. Eng.12 (2), 173-189.
Vrugt, J.A., Gupta, H.V., Bouten, W. & Sorooshian, S., (2003). A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters. Water Resour. Res., 39(8), 1201, doi: 10.1029/2002WR001642.
White, K.L. & Chaubey, I., (2005). Sensitivity analysis, calibration, and validations for a multisite and multivariable SWAT model. J.Am.Water Resour. Ass.41, 1077-1089.
Winchell, M., Srinivasan, R., Di Luzio, M. & Arnold, J.G., (2007). Arc-SWAT interface for SWAT2005 - User’s guide, Blackland Research Center, Texas Agricultural Experiment Station and Grassland, Soil and Water Research Laboratory, USDA Agricultural Research Service, Temple, Texas.
Yang, J., Reichert, P., Abbaspour, K.C., Xia, J. & Yang, H., (2008). Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. J. Hydrol. 358, 1– 23
Zhang, X., Srinivasan, R., Van Liew, M., (2008). Multi-site calibration of the SWAT model for hydrologic modeling. Trans. ASABE, 51, 2039-2049.