1. Bengio Y. and LeCun Y., 2007. Scaling learning algorithms towards AI1-41. In Bottou L., Chapelle O., DeCoste D., Weston J. Large-scale kernel machines. MIT Press.
2. Camici S., Palazzi E., Pier, A., Brocca L., Moramarco T., and Provenzale A. 2015. Comparison between dynamical and stochastic downscaling methods in central Italy. In EGU General Assembly Conference Abstracts, 10270.. 10270.
3. Chanda K., and Maity R. 2018. Global Climate Pattern Behind Hydrological Extremes in Central India. In Climate Change Impacts (pp. 71-89). Springer, Singapore.
4. Chen H., CY X., and Guo S.L. 2012. Comparison and evaluation of multiple GCMs, statistical downscaling and hydrologicalmodels in the study of climate change impacts on runoff.Journal of hydrology, 434, 36-45.
5. Chen J., Brissette F.P., and LeconteR. 2011. Uncertainty of downscaling meth- od in quantifying the impact of climate change on hydrology. Journal of Hydrology.401:190–202.
6. Devak M., Dhanya C.T., and Gosain A.K. 2015. Dynamic coupling of support vector machine and K-nearest neighbour for downscaling daily rainfall. Journal of Hydrology, 525:286-301.
7. Draper N.R., Smith H., and Pownell E. 1966. Applied regression analysis. 3: 217-220. New York: Wiley.
8. Fisher R.A. 1958. Statistical Methods for Research Workers, 13th Ed., Hafner.
9. Fistikoglu O., and Okkan U. 2011. Statistical Downscaling of Monthly Precipitation Using NCEP / NCAR Reanalysis Data for Tahtali River Basin in Turkey, Journal of Hydrologic Engineering.16, 157–164.
10. Gaitan C. F., Hsieh W. W., and Cannon A. J. 2014. Comparison of statistically downscaled precipitation in terms of future climate indices and daily variability for southern Ontario and Quebec, Canada. Climate Dynamics, 43(12):3201–3217.
11. Hammami D., Lee T.S., Ouarda T.B. M.J., and Le J. 2012. Predictor selection for downscaling GCMs data with LASSO. Journal of Geophysical Research Atmospheres, 117(17):1–11.
12. Harpham C., and Wilby R.L. 2005. Multi-site downscaling of heavy daily precipitation occurrence and amounts. Journal of Hydrology, 312(1):235-255.
13. Hassan Z., Shamsudin S., and Harun S. 2014. Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temper- ature. Theoretical and Applied Climatology. 116:243–257.
14. Hessami M., Gachon P., Ouarda T., and St-Hilaire A. 2008. Automated regression-based statistical downscaling tool. Environmental Modelling & Software, 23:813–834.
15. Huth R. 1999. Statistical downscaling in central Europe: evaluation of methods and potential predictors. Climate Research, 13:91–1011. IPCC (2001) Climate change 2001: impacts, adaptation and vulner- ability. In: McCarthy JJ., Canziani oF, Leary NA., Dokken DJ., White KS (eds) Contribution of working group II to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
16. IPCC (2001) Climate change 2001: impacts, adaptation and vulner- ability. In: McCarthy JJ., Canziani oF, Leary NA., Dokken DJ., White KS (eds) Contribution of working group II to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
17. IPCC (2007) Summary for policymakers. Climate change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 1–18
18. Jafarzadeh A., Pourreza-Bilondi M., Khashei-Siuki A., A. Aghakhani A., and Yaghoobzadeh M. 2017. Reliability estimation of rainwater catchment system using future GCMs output data (case study: Birjand City). In 10th World Congress On Water Resources And Environment (pp. 536–541).
19. Kaviani M., and MirRokni S.M. 2014. Application of principal component analysis to meteorological data in ANN input selection. Geophysics Journal of IRAN, 9(1):71-84.
20. Khan M.S., Coulibaly P., and Dibike Y. 2006. Uncertainty analysis of statistical downscaling methods. Journal of Hydrology, 319(1–4):357–382. https://doi.org/10.1016/j.jhydrol.2005.06.035.
21. Khashei-Suiki A., Shahidi A., Pourreza-Bilondi M., Amirabdizadeh M., and Jafarzadeh A. 2018. Performance Assessment of ANN and SVM for downscaling of daily rainfall in dry regions. Iranian journal of Soil and Water Research. (in Persian)
22.Krause P., Boyle D.P., and Bäse F. 2005. Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5:89–97.
23. McCulloch W.S., and Pitts W. 1943. A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Biophysics, 5(4):115-133.
24. Meenu R., Rehana S., and Mujumdar P.P. 2013. Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM. Hydrological Processes, 27(11):1572–1589.
25. Najafi M.R., Moradkhani H., and Wherry S.A. 2011. Statistical Downscaling of Precipitation Using Machine Learning with Optimal Predictor Selection. Journal of Hydrologic Engineering, 16(8): 650–664.
26. Nasseri M., and Zahraie B. 2013. Performance Assessment of Different Data Mining Methods in Statistical Downscaling of Daily Precipitation. Journal of Hydrology, 492, 1–14.
27. PervezM.S., HenebryG.M. 2014. Projections of the Ganges–Brahmaputra precipitation downscaled from GCMs predictors. Journal of Hydrology 517:120–134.
28. Raje D., Mujumdar P.P. 2011. A comparison of three methods for downscaling daily precipitation in the Punjab region. Hydrology Process, 25(23):3575–3589.
29. Rumelhart D.E., Hinton G.E., and Williams R.J. 1986. Learning representations by back-propagating errors. Nature, 323(6088):533-536.
30. Salathe E.P., Mote P.W., and Wiley M.W. 2007. Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States Pacific Northwest. International Journal of Climatology, 27(12):1611-1621.
31. Semenov M. 2002. LARS-WG A Stochastic Weather Generator for Use in Climate Impact Studies. In Version 3, ed. R. Research.
32. Vousoughi1 F., Dinpashoh Y., and Aalami M. 2010. Effect of Drought on Groundwater Level in the Past Two Decades (Case study: Ardebil Plain). Water and Soil Science, 21(4):165-179. (in Persian)
33. Wilby R.L., and Wigley T.M.L. 2000. Precipitation predictors for downscaling: observed and general circulation model relationships. International Journal of Climatology, 20(6):641-661.
34. Wilby R.L., Dawson C.W., and Barrow E.M. 2002. SDSM—a decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software, 17(2):145-157.
35. Wilks D.S., 1995. Statisistical Methods in the Atmospheric Sciences. Academic Press, San Diego, California
36. Wood A.W., Leung L.R., Sridhar V., and Lettenmaier D.P. 2004. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change 62: 189–216.
37. Yang C. 2016. Performance comparison of three predictor selection methods for statistical downscaling of daily precipitation. Theoretical and Applied Climatology. 131(1-2):43-54.