Document Type : Research Paper
Authors
1 Department of Arid and Mountainous Areas Restoration, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2 Assistant professor, Department of reclamation of arid and mountainous regions Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
Abstract
Meteorological drought is one of the major hazards and anomalies in the country, especially in arid and semi-arid regions. In the context of comprehensive watershed management, accurate and timely drought forecasting is of great importance. This is a necessity, especially in sensitive and vulnerable areas such as Khuzestan Province, for the optimal use of water resources, consumption management, and increasing the resilience of natural and human ecosystems. Therefore, drought prediction can increase resistance to possible environmental crises to the desired extent. In the present study, the analysis and prediction of meteorological drought in Khuzestan Province was investigated with the individual FCMR model and the dual FCMR-GOW and FCMR-ACOR models during a 30-year statistical period (1989 to 2020). To assess drought conditions, the Standardized Precipitation Index (SPI) derived from rainfall data from eight synoptic stations was used. Then, the modeling results were compared with the aforementioned models using goodness-of-fit indices. The results indicated that the GOW catalyst improved the FCMR model and the ACOR catalyst reduced the accuracy of the FCMR model. At all eight stations, the dual hybrid FCMR-GOW model ranked first with the highest accuracy in predicting SPI. Also, long-term SPI time windows had higher accuracy than short-term time windows. In general, it can be concluded that combining individual models with meta-heuristic algorithms does not necessarily mean increasing accuracy in SPI modeling.
Keywords
)