Thesis (M.Sc.) - Cairo University - Faculty of African Postgraduate Studies - Department of Natural Resources

Water budget and energy balance of lakes are very sensitive to lake evaporation. Understanding lake evaporation and the climate change role in evaporation is paramount for any water resources management system. The prediction of the climate future changes is a very important step in planning lake future management decisions. This study introduces an inclusive analysis of Lake Nasser evaporation in the most southern part of Egypt. Meteorological parameters were compiled from Aswan meteorological station near Lake Nasser. In addition to that, CORDEX predicted climatological parameters from 2021 to 2050 were collected. Lake Nasser evaporation predicition model using Artificial Neural Networks (ANN) technique has been built. Statistics were calculated in the calibration and validation stages to find out the most adequate model of the Lake evaporation calculation. The predictions of future evaporation were extracted from the model using predicted climatological data from CORDEX regional climate models. Trend analysis was done to assure the impacts of the climate change on the lake. ANN model was developed and implemented successfully on Lake Nasser, which could be used to handle evaporation calculation over Lake Nasser. ANN model with training algorithm using 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 neurons with 5 input variables was tested to find the best model evaporation estimation of the lake with least number of neurons. Results showed that, ANN model with training algorithm with 20 neurons with 5 input variables performed the best for evaporation estimation of the lake. According to predicted climate data a slight increase in lake Nasser evaporation could be predicted

Issued also as CD