Understanding lake evaporation and the climate change role in evaporation is paramount for any water resources management system. The prediction of the climate's future changes is a very important step in planning lake future management decisions. This study analyzed Lake Nasser's evaporation in southern Egypt. Meteorological parameters were compiled from Aswan meteorological station near Lake Nasser. Also, CORDEX predicted climatological parameters from 2021 to 2050 were collected. Lake Nasser's evaporation prediction model using artificial neural networks technique was built. Statistics were calculated in the calibration and validation stages to find 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 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 with 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 neurons with 5 input variables were tested to find the best model evaporation estimation of the lake with the least number of neurons. 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, about a 2% increase in lake Nasser evaporation could be predicted in the year 2050. It was noticed that the maximum predicted values of evaporation are in July to August months with a range from 7.04 mm/day to 9.64 mm/day. The peak value, the outlier of maximum evaporation, is about 11.16 mm/day. The minimum predicted values are in December to January months with a range from 3.50 mm/day to 6.81 mm/day. Trend analysis showed that the predicted climatological parameters are slightly higher than historical records.

了解湖泊蒸发及其在蒸发中的气候变化作用对于任何水资源管理系统都是至关重要的。对气候未来变化的预测是规划湖泊未来管理决策中非常重要的一步。这项研究分析了纳赛尔湖在埃及南部的蒸发。气象参数是从纳赛尔湖附近的阿斯旺气象站收集的。此外，还收集了CORDEX预测的2021年至2050年的气候参数。利用人工神经网络技术建立了纳赛尔湖的蒸发量预测模型。在校准和验证阶段计算统计数据，以找到最合适的Lake蒸发量计算模型。使用CORDEX区域气候模型的预测气候数据从模型中提取未来蒸发的预测。进行了趋势分析，以确保气候变化对湖泊的影响。ANN模型已在纳赛尔湖上成功开发并实施，可用于处理纳赛尔湖上的蒸发量计算。测试了具有训练算法的神经网络模型，该算法具有2个，4个，6个，8个，10个，12个，14个，16个，18个，20个，22个具有5个输入变量的神经元，以找到神经元数量最少的湖泊的最佳模型蒸发估计。具有训练算法的神经网络模型具有20个神经元和5个输入变量，对湖泊的蒸发估算效果最佳。根据预测的气候数据，到2050年，纳赛尔湖的蒸发量将增加约2％。注意到最大的蒸发预测值为7月至8月，范围为7.04 mm /天至9.64 mm /天。峰值，即最大蒸发量的异常值，约为11.16毫米/天。最小预测值是在12月到1月之间，范围从3.50毫米/天到6.81毫米/天。趋势分析表明，预测的气候参数略高于历史记录。