Drought forecasting using Group Method of Data Handling (GMDH) and Adaptive Neural-Fuzzy Inference System (ANFIS) in different climates

The results of model evaluation during training and testing demonstrated significant accuracy differences between various models. Results showed that in the ANFIS, minimum of R2 in SPI-3 was 0.59, in hyper-humid climates (Ramsar and Bandar-e-Anzali) and maximum of R2 in SPI-3 was 0.78, in hyper-arid climate (Zahedan) and humid climate (Yasuj). Also minimum of R2 in SPI-6 was 0.75, in semi-arid climate (Hamedan) and maximum of R2 in SPI-6 was 0.87, in hyper-arid and arid climates (Zahedan and Mashhad). In SPI-12, minimum of R2 was 0.88, in hype-arid and semi-arid climates (Zahedan and Hamedan) and minimum of R2 was 0.97 in arid climates (Mashhad). Also, results of ANFIS showed that membership functions type and climates type don't have effect on ANFIS performance and when model is using precipitation in two delay step and SPI in 3 delay step, it has acceptable and high accuracy results. In the GMDH, R2 is between 0.91-0.99 in all three SPI scales (SPI-3, SPI-6 and SPI-12) and in all climates which it indicates the acceptable accuracy of this model. In order to evaluate the results of GMDH models, the best models related to M4 and M9 that input variables are {SPI(t-1), SPI(t-2), SPI(t-3), SPI(t-4), SPI(t-5)} and {SPI(t-1), SPI(t-2), SPI(t-3), SPI(t-4), SPI(t-5), P(t-1), P(t-2)}. RMSE values indicated that it increases when climate type is changing. Hyper-humid and humid climates have RMSE more than other climates. It related to precipitation effect in models performance. M5 and M6 models that use just precipitation in the previous months have low performance in drought forecasting. Also results indicate that SPI is appropriate for 12-month scale. In fact, the performance of the models has direct relationship with the increasing of the SPI time scale. Finally, The results of the comparison of observed and calculated values of three SPI scales (SPI-3, SPI-6 and SPI-12) using the GMDH model in all climates showed that drought forecasting is reliable when this method used and it'll use possibility for future drought forecasting. In general, the results are accurate when using ANFIS and GMDH but the performance of the GMDH model is better than other model. Also, execution speed and GMDH calculations are far more than the ANFIS. Finally, in this study, GMDH propose as the best model for drought forecasting