Sulafa Salah | King Saud University (original) (raw)
Address: Saudi Arabia
less
Uploads
Papers by Sulafa Salah
Alexandria Engineering Journal, 2014
Sudan is a large country and the Nile, which is one of the most remarkable and the second longest... more Sudan is a large country and the Nile, which is one of the most remarkable and the second longest river in the world, runs a long distance from south of the country to the north. The Nile is known for its marked seasonal and manual variations. The variation in discharge is illustrated by the fact that more than 80% of its manual flow occurs from August to October. It is interesting to note that manual discharge of the Nile for the year 1913-1914 was 41 milliard cubic meters as compared to 151 milliard cubic meters in 1878-1879. Due to the history of the Nile in the Sudan, many surrounding areas were damaged during periods of floods, causing many economical problems for the inhabitants of the flood plains. This study for the high discharge across the Nile and its effects to the surrounding areas according to the topography. The study was carried for the upper reach of Dongola station, where continuous record for the period 1960-1990 will be used together with the topography of the ar...
Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. ... more Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. The floods destroy houses, crops, roads, and basic infrastructure, resulting in the displacement of people. This study aimed to forecast the River Nile flow at Dongola Station in Sudan using an Artificial Neural Network (ANN) as a modeling tool and validated the accuracy of the model against actual flow. The ANN model was formulated to simulate flows at a certain location in the river reach, based on flow at upstream locations. Different procedures were applied to predict flooding by the ANN. Readings from stations along the Blue Nile, White Nile, Main Nile, and River Atbara between 1965 and 2003 were used to predict the likelihood of flooding at Dongola Station. The analysis indicated that the ANN provides a reliable means of detecting the flood hazard in the River Nile.
Alexandria Engineering Journal, 2014
Sudan is a large country and the Nile, which is one of the most remarkable and the second longest... more Sudan is a large country and the Nile, which is one of the most remarkable and the second longest river in the world, runs a long distance from south of the country to the north. The Nile is known for its marked seasonal and manual variations. The variation in discharge is illustrated by the fact that more than 80% of its manual flow occurs from August to October. It is interesting to note that manual discharge of the Nile for the year 1913-1914 was 41 milliard cubic meters as compared to 151 milliard cubic meters in 1878-1879. Due to the history of the Nile in the Sudan, many surrounding areas were damaged during periods of floods, causing many economical problems for the inhabitants of the flood plains. This study for the high discharge across the Nile and its effects to the surrounding areas according to the topography. The study was carried for the upper reach of Dongola station, where continuous record for the period 1960-1990 will be used together with the topography of the ar...
Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. ... more Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. The floods destroy houses, crops, roads, and basic infrastructure, resulting in the displacement of people. This study aimed to forecast the River Nile flow at Dongola Station in Sudan using an Artificial Neural Network (ANN) as a modeling tool and validated the accuracy of the model against actual flow. The ANN model was formulated to simulate flows at a certain location in the river reach, based on flow at upstream locations. Different procedures were applied to predict flooding by the ANN. Readings from stations along the Blue Nile, White Nile, Main Nile, and River Atbara between 1965 and 2003 were used to predict the likelihood of flooding at Dongola Station. The analysis indicated that the ANN provides a reliable means of detecting the flood hazard in the River Nile.