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Vojtěch Svoboda, Martin Hanel, Petr Máca and Jan Kyselý

-010-0808-0. Dunkerley, D., 2008. Identifying individual rain events from pluviograph records: a review with analysis of data from an Australian dryland site. Hydrol. Process., 22, 26, 5024–5036, doi: 10.1002/hyp.7122. Fiener, P., Neuhaus, P., Botschek, J., 2013. Long-term trends in rainfall erosivity – analysis of high resolution precipitation time series (1937–2007) from Western Germany. Agr. Forest Meteorol., 171–172, 115–123. doi: 10.1016/j.agrformet.2012.11.011. Frei, C., Schöll, R., Fukutome, S., Schmidli, J., Vidale, P.L., 2006. Future change of precipitation

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Pratibha Warwade, Shalini Tiwari, Sunil Ranjan, Surendra K. Chandniha and Jan Adamowski

REFERENCES A kinremi O.O., M c G inn S.M., C utforth H.W. 2001. Seasonal and spatial patterns of rainfall trends on the Canadian prairies. Journal of Climate. Vol. 14. No. 9 p. 2177–2182. A raghi A., M ousavi baygi M., A damowski J., M a -L ard J., N alley D., H asheminia H. 2015. Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data. Journal of Atmospheric Research. Vol. 11 p. 52–72. A yalew D., T esfaye K., M amo G., Y itaferu B., B ayu W. 2012

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Lily Montarcih Limantara, Donny H. Harisuseno and Vita A.K. Dewi

REFERENCES C how V.T., M aidment D.R., M ays L.W. 1988. Applied hydrology. Singapore. McGraw-Hill Book Company. ISBN 0070108102 pp. 572. H adisusanto N. 2010. Aplikasi hidrologi [Applied hydrology]. Malang. Jogja Mediautama. ISBN 978-602-1936-03-06 pp. 300. H idayat A. 2013. Transformasi data [Transformation of data] [online]. [Access 24.09.2014]. Available at: http://www.statistikian.com/2013/01/transformasi-data.html H oybye J., R osbjerg D. 1999. Effect of input and parameter uncertainties in rainfall-runoff simulations. Journal

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Dounia Mrad, Yassine Djebbar and Yahia Hammar

REFERENCES A dler R.F., H uffman G.J., B olvin D.T., C urtis S., N elkin E.J. 2000. Tropical rainfall distributions determined using TRMM combined with other satellite and rain gauge information. Journal of Applied Meteorology. Vol. 39 p. 2007–2023. B alah B., A marchi H. 2016. Variabilité des séries pluviométriques du bassin versant de la Seybouse du Nord Est-Algérien [Variability of rainfall series of Seybouse watershed of North-East of Algeria]. Revue Sciences Technologies, Synthèse. Vol. 32 p. 86–97. B enkhaled A., B ouziane M.T., A

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Zeineddine Nouaceur, Ovidiu Murărescu and George Murătoreanu

., YeKutieli D., Clacino M., Diodata L., Ramis C., Hmaor V. et al. (2002). The paradoxical increase of Mediterranean extreme daily rainfall in spite of decrease in total value, Geophysical Research Letters, vol. 29, Issue 11, 31-1 – 31-4, DOI: 1029/2001GL013554. Bogdan O. (1980). Potenţialul climatic al Bărăganului [Climatic potential of Bărăgan] . Bucureşti, Editura Academiei Române, 175 p. Bojariu R., Georgi F. (2005). The North-Atlantic oscilation signal in a regional climate simulation for the European region. Tellus , 57 (4), 641-653, DOI: 10.1111/j.1600

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Mojca Šraj, Luka Dirnbek and Mitja Brilly

discharges in ungauged basins. Global NEST Journal, 7 , 3, 296-305. DEVRIES J. J., 1982: Hydrologic Analysis of ungaged water-sheds using HEC-1. US Army Corps of Engineers, Davis, CA. DIRNBEK L., 2009: The effect of precipitation excess on runoff hydrograph. Unpublished diploma, University of Ljubljana. EL-JABI N., SARRAF S., 1991: Effect of maximum rainfall position on rainfall-runoff relationship, ASCE Publ., 117 , 5, 681-685. FAURES J. M, GOODRICH D. C., WOOLHISER D

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Grzegorz Janik, Wojciech Skierucha, Marek Błaś, Mieczysław Sobik, Małgorzata Albert, Michał Dubicki and Anna Zawada

information on variability of selected physical properties of soil. Int.Agrophysics, 22, 35-43. Janik G., Szpila M., S³owiñska J., Brej G., Turkiewicz M., Skierucha W., and Pastuszka T., 2011. Method for the determination of the sensitivity zone of TDR probe. Acta Agrophysica, 183, 269-286. Kaseke F.K., Mills A.J., Brown R., Esler K.J., Henschel R., and Seely M.K., 2011. A method for direct assessment of the ‘non rainfall’ atmospheric water cycle: input and evaporation from the soil. Pure Appl. Geophys., 169(5-6), 847

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Mexoese Nyatuame and Sampson K. Agodzo

REFERENCES A bdul -A ziz A., A nokye M., K wame A., M unyakazi L., N sowah -N uamah N. 2013. Modeling and forecasting rainfall pattern in Ghana as a seasonal ARIMA process: The case of Ashanti region. International Journal of Humanities and Social Science. Vol. 3. No. 3 p. 224–233. A frifa -Y amoah E. 2015. Application of ARIMA models in forecasting monthly average surface temperature of Brong Ahafo Region of Ghana. International Journal of Statistics and Applications. Vol. 5. No. 5 p. 237–246. A frifa -Y amoah E., S aeed B.I., K arim A

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Cristian Dinu, Radu Drobot, Claudiu Pricop and Tudor Viorel Blidaru

-0699(2000)5:2(124) [3] Hsu, K., Vijai Gupta, H., & Sorooshian, S. (1995), Artificial neural network modeling of the rainfall-runoff process. Water Resources Research. 31(10), 2517-2530. DOI: 10.1029/95WR01955 [4] Minns, A. W. & Hall, M. J. (1996). Artificial neural networks as rainfall-runoff models. Hydrological Sciences Journal, 41(3), 399-417. [5] Dawson, C. W. & Wilby, R. (1998), An artificial neural network approach to rainfall-runoff modelling. Hydrological Sciences Journal. 43(1), 47-66. DOI: 10.1080/02626669809492102 [6

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Cristian Dinu, Radu Drobot, Claudiu Pricop and Tudor Viorel Blidaru

References [1] Solomatine, D. P. & Ostfeld, A. (2008), Data-driven modelling: Some past experiences and new approaches. Journal of Hydroinformatics. 10(1), 3-22. DOI: 10.2166/hydro.2008.015; [2] Hsu, K., Vijai Gupta, H., & Sorooshian, S. (1995), Artificial neural network modeling of the rainfall-runoff process. Water Resources Research. 31(10), 2517-2530. DOI: 10.1029/95WR01955; [3] Abrahart, R. J. & See, L. M. (2007), Neural network modelling of non-linear hydrological relationships. Hydrology and Earth System