Abstract
Jordan is suffering a chronicle water resources shortage. Rainfall is the real input for all water resources in the country. Acceptable accuracy of rainfall prediction is of great importance in order to manage water resources and climate change issues. The actual study include the analysis of time series trends of climate change regards to rainfall parameter. Available rainfall data for five stations from central Jordan where obtained from the Ministry of water and irrigation that cover the interval 1938- 2018. Data have been analyzed using Nonlinear Autoregressive Artificial Neural Networks NAR-ANN) based on Levenberg-Marquardt algorithm. The NAR model tested the rainfall data using one input layer, one hidden layer and one output layer with a different combinations of number of neuron in hidden layer and epochs. The best combination was using 25 neurons and 12 epochs. The classification performance or the quality of result is measured by mean square error (MSE). For all the meteorological stations, the MSE values were negligible ranging between 4.32*10-4 and 1.83*10-5. The rainfall prediction result show that forecasting rainfall values in the base of calendar year are almost identical with those estimated for seasonal year when dealing with long record of years. The average predicted rainfall values for the coming ten-year in comparison with long-term rainfall average show; strong decline for Dana station, some decrees for Rashadia station, huge increase in Abur station, and relatively limited change between predicted and long-term average for Busira and Muhai Stations.
Highlights
Climate change is becoming a reality rather than hypothesis
One of the good examples that show these supposed climatic changes is the murals in the Umayyad palaces scattered in the Jordanian deserts
The Dead Sea is another example of the supposed climate change
Summary
Climate change is becoming a reality rather than hypothesis. Over the last few decades, the atmospheric concentration of carbon dioxide has increase significantly [1]. Water resources related issues are always present a source of concern and at the same time a source of interest Among these issues, we could specify the climate change, groundwater over abstraction, water quality deterioration. It should be noted that in addition to climate change, the large and irregular increase in population, whether due to natural reproduction or migrations from neighboring countries, complicates the water resources management efforts in Jordan. Climate change and related issues are of great concern to government agencies, scientific entities and even public masses. There has been an increasing interest in the scientific literature regarding accurate prediction in the case of linear and nonlinear systems using artificial neural networks. There are many practical applications in this field In this scientific paper, the possibility of obtaining annual forecasts of precipitation quantities through neural networks is studied and analyzed. Prediction results showed a high degree of accuracy of long-term forecasts
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