Climate Change Prediction under Shared Socioeconomic Pathways (SSP) Scenarios in the Bakhtegan-Maharloo Watershed

Introduction and Goal
Climate change means long-term, irreversible changes in average climate conditions caused by natural and human factors. Climate change is causing global temperature increases, melting of polar ice caps, rising sea levels, and extreme weather events. The significant impact of these changes on meteorological variables such as temperature and precipitation, which disrupt hydrological order. By using general atmospheric circulation models as advanced and comprehensive tools for simulating and predict climate changes, dynamic and thermodynamic atmospheric processes can be modeled. Therefore, this study aimed to predict climate change under the Sixth Report models in the Bakhtegan-Maharloo watershed.
Materials amd Methods
In this study, daily precipitation and minimum and maximum temperature data from five synoptic stations of Arsanjan, Neyriz, Safashar, Shiraz and Takht Jamshid were used. Climatic parameters were downscaled using the models of the Sixth Report of the Intergovernmental Panel on Climate Change using the LARS-WG model. The selection of station type was selected based on data adequacy, dispersion and climatic diversity in the watershed. In this study, using three scenarios SSP126, SSP245 and SSP585, the output of three models ACCESS-ESM1-5, CNRM-CM6-1, and MRI-ESM2-0 was used. Using the LARS-WG8 statistical model, downscaling and correction of precipitation and minimum and maximum temperature data were performed to increase the accuracy of the predictions. Finally, the climate projection was calculated for the period 2026 to 2045. Then, daily precipitation and temperature data from the Bakhtegan-Maharloo synoptic stations were processed and compared them with the base period. 
Results and Discussion
The results of the ACCESS-ESM1-5 model showed that the difference between the average precipitation of the base period and the future was significant at the 95% confidence level, and predicted higher precipitation compared to the other two models was related to the ACCESS-ESM1 models, and the estimated magnitude of the CNRM-CM6-1 and MRI-ESM2-0 models was closer to the baseline values. The trend of predicted maximum temperature at all stations and scenarios was increased compared to the observational data and was estimated to be significant and upward at the 95% confidence level. The average annual maximum temperature increased from 24.8°C to 26.9°C. The highest predicted maximum temperature was for the CNRM-CM6-1 model. Shiraz and Persepolis have the highest temperatures. The trend of minimum temperature was increasing in all station. The watershed average minimum temperature increased from 9.7°C to 11.5°C (in the SSP585 scenario), indicating warmer nights and a decrease in nighttime cold. The highest predicted minimum temperature compared to other models was for the CNRM-CM6-1 model. The range of predicted changes in watershed precipitation was from 248.9 to 288.7 mm, and the range of predicted changes in maximum and minimum temperature was from 26 to 26.9 and 11 to 11.9 °C, respectively.
Conclusion and Suggestion
Based on the results of this study, the increasing trend in precipitation and temperature (maximum and minimum) was consistent with the severity of greenhouse gas emission intensity scenarios, indicating that the Bakhtegan-Maharlu region will become warmer and relatively wetter in the future. The differences between the models indicates the lack of certainty in the projections, which necessitates the use of multiple models and scenarios to reduce decision-making risk. These changes require careful planning and adaptation for water resource management, agriculture, and public health in the region. Based on the results of this research in the Bakhtegan-Maharloo watershed, it is suggested that the cultivation pattern be changed towards low-water-intensive crops in order to reduce water consumption and increase climate resilience. In addition, the use of smart irrigation and the implementation of watershed and aquifer management plans are also recommended. To improve the sustainability of underground resources, participatory resource management, operator training, and monitoring of unauthorized wells are recommended. Also, for effective adaptation to climate change, it is suggested to diversify rural livelihoods by developing green and sustainable jobs.