Investigating the Effects of Climate Change on Temperature and Precipitation Using Neural Network and CMIP6 (Case Study: Aleshtar and Khorramabad Stations)

Document Type : Research Paper

Authors

1 Department of Water Science and Engineering, Faculty of Agriculture, Bu Ali Sina University, Hamadan, Iran.

2 Planning Deputy of the Regional Water Company of Lorestan Province, Iran.

3 Department of Water Resources Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran,

4 Department of Environmental Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.

Abstract

The purpose of this research is to evaluate the effects of climate change on temperature, precipitation, and future droughts in Al-Shatar and Khorramabad stations, for this purpose, the output of the general circulation model MRI-ESM2 according to the latest IPCC report (sixth report) and the emission scenarios SSP 1.2.6, SSP 2.4 5, SSP 3.7.0 and SSP 5.8.5 were used in these study areas. Using the decision tree model (M5 Tree), the most dominant predictor variables of the MRI-ESM2 model were selected. Next, the predictor variables were included as input in the advanced artificial neural network (FFNN) statistical microscale model and with the firefly optimization algorithm (FFA), the process The exponential micro-scale of precipitation parameters, maximum temperature, and minimum temperature for the base period (1970-2014) was carried out with favorable results in the studied stations. After proving the capability of the neural network model, forecasting the average temperature and monthly precipitation changes during the near future periods (2062 2023-2023) and the distant future (2063-2100) were carried out under the scenarios of the joint socio-economic trajectories (SSP) related to the coupled model of the sixth phase (CMIP6). In general, the results showed that these variables in both future periods On a monthly scale will have several fluctuations, so that in the two stations of Aleshtar and Khorramabad, during the periods of the near future and the distant future, the maximum temperature, and the minimum temperature will have an increasing trend compared to the observation period in all SSP scenarios, and the minimum temperature changes compared to The maximum temperature will be higher in the near future The annual rainfall of Elshtar station will decrease between 0.3 Percent and 16 Percent and Khorramabad station between Seven percent and 12 Percent under SSP scenarios. In the distant future, the average annual precipitation of Aleshatar station will decrease between 10-20 Percent and Khorramabad station between 12-24% under SSP scenarios.

Keywords

Main Subjects

References

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Water and Irrigation Management
Volume 12, Issue 4
January 2023
Pages 821-845

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