اثر توأم نوسانات فصلی دمای سطح آب خلیج فارس و دریای مدیترانه بر پیش‌بینی آبدهی ماهانۀ رودخانۀ کرخه

Araghinejad S. (2014). Data-Deriven Modeling: Using MATLAB in Water Resources and Environmental Engineering. NewYork: Springer.

Borhani Dariane, A. and Fatehi Marj, A. (2008). Application of artificial neural network in stream flow forecasting using climatic indices (Case study: Nazloochay River Basin). Journal of Faculty of Eng, 35 (3) (Civil Eng), 25-36. (In Farsi)

 Bretherton C.S., Smith C. and Wallace J.M. (1992). An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5: 541–560.

Chen, L., Ye, L., Singh, V., Zhou, J. and Guo, S. (2014). Determination of input for artificial neural networks for flood forecasting using the copula entropy method. J. Hydrol. Eng, 19(11), 04014021.

Cigizoglu, H. K. and Alp, M. (2004). Rainfall-runoff modelling using three neural network methods. ‌J. Artificial Intelligence and Soft Computing,‌‌ 3070, 166-171.

Cigizoglu, H. K. (2005). Generalized regression neural network in monthly flow forecasting. ‌J. Civil Engineering and Environmental Systems, ‌22 (2), 71-81.

Gray Robert.M. (2013). Entropy and Information Theory. NewYork: Springer-Verlag.

 Kassomenos P. A. and McGregor G. R. (2006). The interannual variability and trend of Precipitable Water over Southern Greece. J. Hydrometeorol, 7: 271-284.

Kişi, Ö. (2008). River flow forecasting and estimation using different artificial neural network techniques. Hydrol. Res, 39(1), 27–40.

Kutiel, H., Hirsch-Eshkol, T. R. and Turkes, M. (2001). Sea level pressure patterns associated with dry and wet monthly rainfall conditions in Turkey. Theor. Appl. Climatol., 69, 39-67.

Meidani E., and Araghinejad S. (2014). Long-lead streamflow forecasting in southwest of Iran by the Sea Surface Temperature of Mediterranean Sea. J. Hydrol.Eng,19(8), 05014005.

Nazemosadat  M.J.  (1998). The Persian Gulf Sea Surface Temperature as a drought diagnostic for southern parts of Iran. Drought News Network, 10:12-14.

Nazemosadat, M. J.  (2008). Improving neural network models for forecasting seasonal precipitation in southwestern Iran: The evaluation of oceanic-atmospheric indices. Advances in Geosciences, 16, 133-145.

Nazemosadat, M.J., Ghasemi, A.R., Amin, S.A. and Soltani, A.R. (2008). The simultaneous effect of ENSO and Persian Gulf SSTs on the occurrence of the drought and wet condition over the western and northwestern parts of Iran. Journal of Agricultural Science (University of Tabriz), 18(3), 1-17. (In Farsi)

NOAA_OI_SST_V2 data Available at

http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.oisst.v2.html)(visited 26 May 2015).

Mahab Ghodss Consulting Engineering Company. (2010). Report of water resources planning and management for Karkheh basin. (In Farsi)

Rezayi Banafsheh, M., Jahanbakhsh, S., Bayati Khatibi, M. and Zeinali, B. (2010). Forecast of autumn and winter precipitation of west Iran by use from summer and autumn Mediterranean sea surface temprature. Physycal Geography Research Quarterly, 24, 47-62. (In Farsi)

Rowell D. P.  (2003). The impact of Mediterranean SSTs on the Sahelian rainfall seasonal. J. Climate, 16(5): 849–862.

 Soukup T.L., Aziz O.A., Tootle G.A., Piechota T.C., and Wulff, S.S. (2009). Long lead-time streamflow forecasting of the North Platte River incorporating ocean-atmospheric climate variability.  J.  Hydrology, 368: 131-142.

Uvo C.B., Repelli C.A., Zebiak S.E., and Kushnir Y. (1998). The relationship between tropical Pacific and Atlantic SST and northeast Brazil monthly precipitation. J. Climate, 11:551-562.

 Wallace J.M., Smith C., and Bretherton C.S. (1992). Singular value decomposition of wintertime sea surface temperature and 500-mb height anomalies. J. Climate, 5:561-576.

Wang, W.C., Chau, K.W., Cheng, C.T. and Qui, L. (2009). A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series. ‌J. Hydrology, ‌374, 294-306.

Wu, C. L., Chau, K.W. and Fan, C. (2010). Prediction of rainfall time series using modular artificial neural networks coupled with data preprocessing techniques. ‌J. Hydrology, ‌389, 146-167.