Drought Forecasting for Future Periods Using LARS-WG Model: The Case Study of Kermanshah City

Document Type : Research Paper

Authors

1 PhD Student of Water Resources Engineering, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran

2 Associate Professor, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran

Abstract

The prediction of climactic changes is of great importance due to their destructive effects on aquatic, environmental, economic, and social resources. Accordingly, the purpose of this study was to predict the climactic changes of Kermanshah city using micro-scale general atmospheric circulation models accessible in LARS-WG6 (GFDL-CM3, MPI-ESM-MR, MIROC5) model in scenarios RCP4.5 and RCP8.5 for the 2020 to 2100 period based on the benchmark period of 1980-2010. In order to evaluate the data forecasted in LARS-WG model, the error rate of the observed and predicted data was addressed using R2, RMSE, MSE, and MAD criteria. The results showed that LARS-WG model had the needed capability to predict climactic data in future. In the secondary models, the MPI-ESM-MR model in scenario RCP4.5 showed a higher reliability rate compared to other secondary models evaluated in the study. Moreover, all models indicated increases in the average minimum and maximum temperature and forecasted changes in rainfall pattern in future periods in the studied area. Then, the SPI and De Martonne indices were calculated for all models. According to SPI index, all evaluated climactic models demonstrated that by the year 2100, the years with normal index would decrease while the years with dry conditions would increase. Moreover, based on De Martonne index, the GFDL model in RCP8.5 scenario estimated the climactic changes level more than other models, and predicted that dry and semi-dry years will be more than wet years. Contrarily, the MIRO model in RCP45 scenario acted more optimistically and predicted less climactic changes.

Keywords


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