Predicting Climate Change Scenarios Using Artificial Neural Networks

Climate change, by causing changes in temperature and precipitation, causes changes in river discharge. Therefore, river flow simulation is of great importance as a prerequisite for planning and managing water resources and uses. Precipitation is one of the most important climatic parameters affecting the hydrological regime of watersheds. Various methods have been proposed to predict precipitation, including time series models and artificial neural networks. These models predict climatic parameters without considering the issue of global warming and climate change. Considering climate change, global warming and recent droughts, predicting maximum temperatures as one of the most important climate parameters provides planners with a good opportunity to plan and provide necessary measures. Investigating and analyzing maximum temperatures as one of the climate parameters is of great importance in the management of water and natural resources, agriculture, the spread of pests and diseases, snowmelt and flooding, evaporation and transpiration, drought, etc.

Autorentext

Dr. Shahide Dehghan, Ph.D., Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran. Technical Skills are Climatology, Statistical Analysis, Geography, Geo-Natural Hazards, Geomorphology, Factor Analysis, Data Analysis, Climate Change, Atmosphere, Global Warming, Climate Sciences, Insurance Investment, Water Resources.