Assessment of climate change parameters impact on long-term sediment transport trend case study: Azam River basin

Abstract

At the turn of the new decade, climate change is one of the key issues that has affected all social, economic and other human's activities. In this study, the effects of changes in precipitation and temperature parameters on sediment changes in the Azam River located in Yazd province of Iran were investigated. The Mann-Kendall test was used to identify the changes in sediment parameters. Subsequently, in order to predict the sediment changes the artificial neural network (ANN) was considered. In order to use the ANN model for predicting the sediment amount, firstly, the model was trained by temperature and precipitation data as input parameters, in the next step the ANN model sensitivity analysis was done by changing the layers and the neuron numbers, finally the most suitable model with 25 layers and 30 neurons was chosen. The final trained ANN model was used forecasting the sediment amount over 2015-2044.