References
- Abrahart, R.J., Heppenstall, A.J., and See, L.M., 2007. Timing error correction procedure applied to neural network rainfall–runoff modelling. Hydrological Sciences Journal, 52 (3), 414–431. doi: 10.1623/hysj.52.3.414
- Antar, A.M., Elassiouti, I., and Allam, M.N., 2005. Rainfall–runoff modelling using artificial neural networks technique: a Blue Nile catchment case study. Hydrological Processes, 20 (5), 1201–1216. doi: 10.1002/hyp.5932
- BCEOM, 1999. Abay Basin integrated master plan study. Main report Ministry of Water Resources, Addis Ababa, Phase two, Volume, Agriculture, 1–2.
- Boucher, M.A., Perreault, L., and Anctil, F., 2009. Tools for the assessment of hydrological ensemble forecasts obtained by neural networks. Journal of Hydroinformatics, 11(3–4), 297–307. doi: 10.2166/hydro.2009.037
- Chang, F.-J., and Chen, Y.C., 2001. A counterpropagation fuzzy-neural network modelling approach to real time streamflow prediction. Journal of Hydrology, 245 (1–4), 153–164. doi: 10.1016/S0022-1694(01)00350-X
- Conway, D. 1997. A water balance model of the Upper Blue Nile in Ethiopia. Hydrological Sciences Journal, 42, 265–286. doi: 10.1080/02626669709492024
- Coulibaly, P., Anctil, F., and Bobée, B., 2000. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach. Journal of Hydrology, 230 (3–4), 244–257. doi: 10.1016/S0022-1694(00)00214-6
- Dawson, C.W., See, L.M., Abrahart, R.J., and Heppenstall, A.J., 2006. Symbiotic adaptive neuro-evolution applied to rainfall–runoff modelling in northern England. Neural Networks, 19 (2), 236–247. doi: 10.1016/j.neunet.2006.01.009
- Dawson, C.W., and Wilby, R.L. 2001. Hydrological modelling using artificial neural networks. Progress in Physical Geography, 25 (1), 80–108. doi: 10.1177/030913330102500104
- Dibike, Y.B., and Solomatine, D.P., 2001. River flow forecasting using artificial neural networks. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26 (1), 1–7. doi: 10.1016/S1464-1909(01)85005-X
- Hebb, D.O., 1949. The organization of behaviour. New York: John Wiley & Sons.
- James, L.D., and Thompson, W.O., 1970. Least squares estimation of constants in a linear recession model. Water Resources Research, 6 (4), 1062–1069. doi: 10.1029/WR006i004p01062
- Maier, H.R., and Dandy, G.C., 2000. Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environmental Modelling & Software, 15, 101–124. doi: 10.1016/S1364-8152(99)00007-9
- McCulloch, W.S., and Pitts, W., 1943. A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 5, 115–133.
- Nash, J.E., and Sutcliffe, J.V., 1970. River flow forecasting through conceptual models. Part 1: a discussion of principles. Journal of Hydrology, 10, 282–290. doi: 10.1016/0022-1694(70)90255-6
- NeuroShell2 Website, 2012. Trading software for stocks, commodities, futures, and forex [online]. Available from: http://wardsystems.com/neuroshell2.asp [Accessed 24 September 2012].
- Pramanik, N., and Panda, R.K., 2009. Application of neural network and adaptive neuro-fuzzy inference systems for river flow prediction. Hydrological Sciences Journal, 54 (2), 247–260. doi: 10.1623/hysj.54.2.247
- Rajurkar, M.P., Kothyari, U.C., and Chaube, U.C., 2004. Modelling of the daily rainfall–runoff relationship with artificial neural network. Journal of Hydrology, 285 (1–4), 96–113. doi: 10.1016/j.jhydrol.2003.08.011
- Shamseldin, A.Y., 1997. Application of neural network technique to rainfall–runoff modelling. Journal of Hydrology, 199, 272–294. doi: 10.1016/S0022-1694(96)03330-6
- Shamseldin, A.Y., 2010. Artificial neural network model for river flow forecasting in a developing country. Journal of Hydroinformatics, 12 (1), 22–35. doi: 10.2166/hydro.2010.027
- Shamseldin, A.Y., Nasr, A.E., and O'Connor, K.M., 2002. Comparison of different forms of the multi-layer feed-forward neural network method used for river flow forecast combination. Hydrology and Earth System Sciences, 6 (4), 671–684. doi: 10.5194/hess-6-671-2002
- Shamseldin, A.Y., O'Connor, K.M., and Nasr, A.E., 2007. A comparative study of three neural network forecast combination methods for river flow forecasting. Hydrological Sciences Journal, 55 (2), 898–916.
- Sughaiyaroun, E., 1968. Regulation Rules for the working of the reservoirs at Roseires and Sennar on the Blue Nile. Ministry of Irrigation and Hydro-electric Power, The Republic of the Sudan, Khartoum, Sudan.
- Sutcliffe, J.V., and Parks, Y.P., 1999. The hydrology of the Nile (IAHS Special publication No.5). Wallingford: IAHS press, Institute of Hydrology.
- Tallaksen, L.M., 1995. A review of baseflow recession analysis. Journal of Hydrology, 165, 349–370. doi: 10.1016/0022-1694(94)02540-R
- Tekleab, S., Uhlenbrook, S., Mohamed1, Y., Savenije, H.H.G., Ayalew, S., Temesgen, M., and Wenninger, J., 2010. Water balance modeling of Upper Blue Nile catchments using a top-down approach. Hydrology and Earth System Sciences, 7, 6851–6886. doi: 10.5194/hessd-7-6851-2010
- Vogel, R.M., and Kroll, C.N., 1996. Estimation of baseflow recession constants. Water Resources Management, 10, 303–320.
- Yilma, S., and Ulrich, Z., 2004. Recent changes in rainfall and rainy days in Ethiopia. International Journal of Climatology, 24, 973–983. doi:10.1002/joc.1052.