تهدف هذه الدراسة إلى تحديد العناصر المناخية الأكثر تأثيرا على علاقة الهطل - جريان لنهر الكبير الشمالي, باستخدام الشبكات العصبية الاصطناعية. حيث احتوت مدخلات الشبكات العصبية على الهطل المطري و التدفق في النهر, وفق تأخرات زمنية مختلفة, بالإضافة إلى هنصر من العناصر المناخية في كل نموذج من النماذج, لتحديد النموذج الأفضل و الأكثر دقة.
the aim of this study is
determination of the most influential climatic factors in the rainfall
runoff relationship in Al-Kabir Al-shimalee river using artificial
neural networks. The inputs included Precipitation, runoff, in
different delays, in addition on لاclimate factor in each network, to
determinate the best model.
References used
ANTAR, M. A; ELASSIOUTI, I; ALLAM, M. N. Rainfallrunoff modelling using artificial neural networks technique: a Blue Nile catchment case study. Hydrol. Process. 20, 1201– 1216, 2006
KALTEH, A. M. 2008 - Rainfall-runoff modelling using artificial neural networks (ANNs): modelling and understanding. Caspian J. Eng. Sci. Vol. 6 No.1. 53-58
KUMAR, M; RAGHUWANSHI, N. S; SINGH, R; WALLENDER, W. W; PRUITT, W. O, 2002. Estimating Evapotranspiration using Artificial Neural Network. Journal of Irrigation and Drainage Engineering
Al-Kabeer Al-Shemale river rises from Aqraa Mountain and coastal mountains, it is considered one of the largest rivers in the coastal area.Its catchment area is 1097 km2, and empties into the sea to the southern of Lattakia.The study aims to determin
The relationship between precipitation and surface runoff is one of
the fundamental components of the hydrological cycle of water in
nature and is one of the most complex and difficult to understand
because of the large number of parameters involv
This study deals with the determination of total mercury concentration in the water
taken from three sites on Al-Kabeer Al-Shemaly River ( near the industrial area and Al-
Damat Lake, and 16 Tishreen Lake), also the effect of some physio-chemical p
Study of the general characteristics of Fractures in the central part of
the AL-Kabir AL- Shimali river basin showed the presence of
several main groups of Fractures with directions NE-SW _ NNESSW,
NW-SE , E-W.and showed increased fracture rate in
This study has reached to that ANN (5-9-1) (five neurons in input
layer_nine neurons in hidden layer _ one neuron in output layer) is the
optimum artificial network that hybrid system has reached to it with
mean squared error equals (1*10^-4) (0.7