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Dinamik Su Bütçesi Modeli

Year 2015, Volume: 17 Issue: 1, 70 - 82, 01.06.2015

Abstract

Sunulan çalışmada, aylık yağış-akış ilişkisini tanımlamak amacıyla Budyko yaklaşımına dayanan dinamik su bütçesi modeli kullanılmıştır. Önerilen 5 parametreli model girdi olarak sadece aylık alansal ortalama yağış ve potansiyel evapotranspirasyon verilerine ihtiyaç duymaktadır. Çalışma sahası Gediz Havzası’ndaki Medar Çayı’nı kapsamaktadır. Modelin performansını sınamak maksadıyla farklı ölçütler değerlendirilmiştir. Çalışmadan elde edilen bulgular, dinamik su bütçesi modelinin aylık akış serilerini modellemede başarılı olduğunu göstermiştir

References

  • [1]. Okkan, U., İklim değişikliğinin akarsu akışları üzerindeki etkilerinin değerlendirilmesi, Doktora Tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü, İzmir, Türkiye. (2013).
  • [2]. Okkan, U. ve Fıstıkoğlu, O., PMS ve GR2M Aylık Yağış-Akış Modelleri, VII. Ulusal Hidroloji Kongresi, 26-27 Eylül 2013, Süleyman Demirel Üniversitesi, Isparta, 167-176, (2013).
  • [3]. Okkan, U. ve Fistikoglu, O., Evaluating Climate Change Effects on Runoff by Statistical Downscaling and Hydrological Model GR2M. Theoretical and Applied Climatology, 117(1-2), 343-361, (2014).
  • [4]. Budyko, M.I., The Heat Balance of the Earth’s Surface. US Department of Commerce, Washington, DC. (1958).
  • [5]. Milly, P.C.D., Climate, soil water storage, and the average annual water balance. Water Resour. Res. 30, 2143–2156, (1994).
  • [6]. Koster, R.D., Suarez, M.J., A simple framework for examining the interannual variability of land surface moisture fluxes. J. Clim. 12, 1911–1917, (1999).
  • [7]. Zhang, L., Dawes, W.R., Walker, G.R., Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37, 701–708, (2001).
  • [8]. Zhang, L., Potter, N., Hickel, K., Zhang, Y.Q., Shao, Q.X., Water balance modeling over variable time scales based on the Budyko framework – model development and testing. J. Hydrol. 360 (1–4), 117–131, (2008).
  • [9]. Atkinson, S.E., Woods, R.A., Sivapalan, M., Climate and landscape controls on water balance model complexity over changing timescales. Water Resour. Res. 38 (12), 1314. doi:10.1029/2002WR00148, (2002).
  • [10]. Fu, B.P., On the calculation of the evaporation from land surface. Sci. Atmos. Sin., 23–31, (1981) (in Chinese).
  • [11]. Moriassi DN, Arnold JG, Van LiewMW, Bingner RL, Harmel RD, Veith TL., Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE, 50, 885–900, (2007).
  • [12]. Thornthwaite, C. W., An Approach toward a Rational Classification of Climate, Geographical Review, 38, 55-94, (1948).
  • [13]. Haan, C.T., Statistical Methods in Hydrology (2nd. ed.). John Wiley & Sons, UK. (2002).
  • [14]. McCuen, R. The role of sensitivity analysis in hydrologic modelling. Journal of Hydrology, 18, 37-53, (1973).

Dynamic Water Budget Model

Year 2015, Volume: 17 Issue: 1, 70 - 82, 01.06.2015

Abstract

In the study presented, to define monthly rainfall-runoff relation, dynamic water budget model based on Budyko approach was used. Proposed model having 5- parameter requires only monthly areal precipitation and potential evapotranspiration data as input. The study region covers the Medar River which is located at the Gediz Basin. To validate the model performance, different measures were assessed. The results derived from the study show that dynamic water budget model is successful in modeling of monthly runoff series

References

  • [1]. Okkan, U., İklim değişikliğinin akarsu akışları üzerindeki etkilerinin değerlendirilmesi, Doktora Tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü, İzmir, Türkiye. (2013).
  • [2]. Okkan, U. ve Fıstıkoğlu, O., PMS ve GR2M Aylık Yağış-Akış Modelleri, VII. Ulusal Hidroloji Kongresi, 26-27 Eylül 2013, Süleyman Demirel Üniversitesi, Isparta, 167-176, (2013).
  • [3]. Okkan, U. ve Fistikoglu, O., Evaluating Climate Change Effects on Runoff by Statistical Downscaling and Hydrological Model GR2M. Theoretical and Applied Climatology, 117(1-2), 343-361, (2014).
  • [4]. Budyko, M.I., The Heat Balance of the Earth’s Surface. US Department of Commerce, Washington, DC. (1958).
  • [5]. Milly, P.C.D., Climate, soil water storage, and the average annual water balance. Water Resour. Res. 30, 2143–2156, (1994).
  • [6]. Koster, R.D., Suarez, M.J., A simple framework for examining the interannual variability of land surface moisture fluxes. J. Clim. 12, 1911–1917, (1999).
  • [7]. Zhang, L., Dawes, W.R., Walker, G.R., Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37, 701–708, (2001).
  • [8]. Zhang, L., Potter, N., Hickel, K., Zhang, Y.Q., Shao, Q.X., Water balance modeling over variable time scales based on the Budyko framework – model development and testing. J. Hydrol. 360 (1–4), 117–131, (2008).
  • [9]. Atkinson, S.E., Woods, R.A., Sivapalan, M., Climate and landscape controls on water balance model complexity over changing timescales. Water Resour. Res. 38 (12), 1314. doi:10.1029/2002WR00148, (2002).
  • [10]. Fu, B.P., On the calculation of the evaporation from land surface. Sci. Atmos. Sin., 23–31, (1981) (in Chinese).
  • [11]. Moriassi DN, Arnold JG, Van LiewMW, Bingner RL, Harmel RD, Veith TL., Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE, 50, 885–900, (2007).
  • [12]. Thornthwaite, C. W., An Approach toward a Rational Classification of Climate, Geographical Review, 38, 55-94, (1948).
  • [13]. Haan, C.T., Statistical Methods in Hydrology (2nd. ed.). John Wiley & Sons, UK. (2002).
  • [14]. McCuen, R. The role of sensitivity analysis in hydrologic modelling. Journal of Hydrology, 18, 37-53, (1973).
There are 14 citations in total.

Details

Other ID JA22CV88FJ
Journal Section Research Articles
Authors

Umut Okkan This is me

Publication Date June 1, 2015
Submission Date June 1, 2015
Published in Issue Year 2015 Volume: 17 Issue: 1

Cite

APA Okkan, U. (2015). Dinamik Su Bütçesi Modeli. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 17(1), 70-82.
AMA Okkan U. Dinamik Su Bütçesi Modeli. BAUN Fen. Bil. Enst. Dergisi. June 2015;17(1):70-82.
Chicago Okkan, Umut. “Dinamik Su Bütçesi Modeli”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 17, no. 1 (June 2015): 70-82.
EndNote Okkan U (June 1, 2015) Dinamik Su Bütçesi Modeli. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 17 1 70–82.
IEEE U. Okkan, “Dinamik Su Bütçesi Modeli”, BAUN Fen. Bil. Enst. Dergisi, vol. 17, no. 1, pp. 70–82, 2015.
ISNAD Okkan, Umut. “Dinamik Su Bütçesi Modeli”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 17/1 (June 2015), 70-82.
JAMA Okkan U. Dinamik Su Bütçesi Modeli. BAUN Fen. Bil. Enst. Dergisi. 2015;17:70–82.
MLA Okkan, Umut. “Dinamik Su Bütçesi Modeli”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 17, no. 1, 2015, pp. 70-82.
Vancouver Okkan U. Dinamik Su Bütçesi Modeli. BAUN Fen. Bil. Enst. Dergisi. 2015;17(1):70-82.