Assessing the effects of climate change on droughts in the coming decades in aras watershed under the CMIP6 model | ||
| مهندسی و مدیریت آبخیز | ||
| Article 4, Volume 17, Issue 1, April 2025, Pages 44-63 PDF (1.77 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/ijwmse.2024.364619.2040 | ||
| Authors | ||
| Fatemeh Vatanparast Ghaleh Juq1; Bromand Salahi* 2 | ||
| 1Ph.D. Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| 2Professor of climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| Abstract | ||
| Introduction Human life is constantly affected by various natural hazards, some of which result from climate events and global warming. This issue is so significant that the Intergovernmental Panel on Climate Change (IPCC) was established to study climate change on a global scale and assess the role of human activity in this matter. One of the consequences of climate change is the occurrence of extreme events such as drought. In fact, with climate change, the intensity and frequency of droughts are becoming more complex. Given the vital role of water in human life, agricultural production, and the environment, it is crucial to assess its adverse effects on the occurrence and severity of droughts. The primary cause of droughts is fluctuations in climatic components, such as decreased precipitation and increased temperature. Materials and methods This study aimed to predict drought conditions in Ardabil, Ahar, Parsabad, Jolfa, Khoi, and Maku stations, located within the Aras River watershed. To achieve this, the accuracy of the General Circulation Models (GCMs) from the IPCC’s CMIP6 dataset was evaluated. The climate models used for forecasting precipitation in the future period (2024–2043) include CanESM5, NorESM2-MM, and MPI-ESM1-2-HR under both optimistic (SSP1-2.6) and pessimistic (SSP5-8.5) emission scenarios. Then, using the Standardized Precipitation Index (SPI), drought characteristics on an annual scale during the historical period (1985–2014) were compared with those in the future period. Model validation was performed using R², RMSE, and NSE parameters. Finally, the SPI drought index was analyzed in terms of intensity and frequency based on the generated precipitation data. Results and discussion Model evaluation using different error metrics indicated that the CanESM5 model outperformed the others in simulating precipitation for the studied stations. A comparison of the models and scenarios revealed that, according to the MPI-ESM1-2-HR model, drought severity is projected to increase, while the CanESM5 model suggests a rise in drought frequency. The results also indicate that under the most pessimistic scenario, both the number and intensity of dry periods will increase compared to the optimistic scenario. Furthermore, normal conditions are expected to decrease, while the number and frequency of dry periods will rise due to the consequences of climate change in the study area. Additionally, the frequency and intensity of wet years have shown a slight increase compared to the historical period. Overall, climate change is expected to have a significant impact on the future drought conditions in the Aras River watershed. Conclusion In summary, understanding changes in precipitation and water resources is crucial due to their various applications in agriculture, drinking water supply, and industry. The accuracy of future climate models varies depending on the climate of each region, the month, and the predicted climate variable. The Aras River Basin is facing a decline in water resources due to agricultural activities exceeding capacity and high water consumption in different agricultural sectors. This study aimed to assess the impact of climate change on drought severity and frequency in the Aras River Basin, providing insights for developing intelligent policies for sustainable water and land resource management. The findings confirm the occurrence of climate change and, in particular, the recurrence of droughts in the studied stations. Using multiple climate models, as the most reliable tool for generating climate scenarios, not only allows for more accurate forecasts but also helps evaluate uncertainties in future climate conditions. These insights assist planners and decision-makers in better monitoring the adverse effects of drought on water resources and agriculture, enabling proactive planning to mitigate regional losses before a crisis occurs. | ||
| Keywords | ||
| Aras River Valley; Climate; GCM Models; Global Warming; SPI Drought Index | ||
| References | ||
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