Search

Climate change raises important issues concerning hydrological engineering. The impact of climate change on important river basins should be investigated rigorously. Extreme temperature variability has a direct impact on the hydrological cycle, especially the evaporation component. In this paper, spatial and temporal patterns of changes in extreme temperatures were investigated using 10 meteorological stations' data for the period 1950–2018 in the Blue Nile Basin. Long-term trends in the Blue Nile Basin annual and monthly temperatures were investigated. The statistical significance of the trend was calculated by applying the Mann–Kendall (MK) test. The analysis of data was performed using the coefficient of variance and anomaly index. The results showed that the annual maximum and minimum temperatures were increasing significantly with a magnitude of 0.037 and 0.025 ∘ C per decade respectively in the period from 1950 to 2018. The result of the Mann–Kendall analysis test revealed a marked increase in the mean maximum and minimum temperature trends over time during the study period (the minimum temperature rate is more evident than the maximum). The long-term anomalies of mean annual minimum temperature revealed the interannual variability while the trend after 1977 was higher than the long-term average, which is proof of the warming trend's existence during the last two decades of the 20th century. [ABSTRACT FROM AUTHOR]

In this paper, spatial and temporal patterns of changes in extreme temperatures are investigated using 10 meteorological stations data for the period 1950-2018 in the Blue Nile basin. Monthly temperature data for the basin were used in the study. Long-term trends in the Blue Nile Basin annual and monthly temperatures were investigated. The statistical significance of the trend is calculated by applying the Mann-Kendall (MK) test. The analysis of data was performed using the coefficient of variance, anomaly index. The results showed that the annual maximum and minimum temperature is increasing significantly with a magnitude of 0.037° and 0.025 °C per decade respectively in the period from 1950-2018. The result of the Mann-Kendall analysis test revealed a marked increase in mean maximum and minimum temperatures trend over time significantly during the study period (the minimum temperature rate is more evident than the maximum). The long-term anomalies of mean annual minimum temperature revealed the inter-annual variability while the trend after 1977 was higher than the long-term average that is proof of the warming trend existence since the last two decades of the 20th century. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • This paper developed Artificial Neural Network model to assess Lake Nasser evaporation. • The developed model is calibrated and validated for Lake Nasser. • The paper assessed the impact of climate change using the developed model on Lake Nasser. • The model could be tested for other dry regions with a good degree of trust. • The most influential meteorological parameters on Lake Nasser projected evaporation. [ABSTRACT FROM AUTHOR]