Journal of Applied Research in Geographical Sciences

en A Comparative Evaluation of Drought Indices Using CMIP6 Climate Model Simulations: A Case Study of Semnan Province, Iran A Comparative Evaluation of Drought Indices Using CMIP6 Climate Model Simulations: A Case Study of Semnan Province, Iran اب و هواشناسی climatology پژوهشي Research <div style="text-align: justify;">In recent years, the world has experienced more frequent droughts, largely due to climate change. This study monitors and projects drought conditions in Semnan Province, Iran, using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). It also evaluates drought characteristics under future climate scenarios. Projections of temperature and precipitation from 12 CMIP6 climate models were downscaled using Quantile Mapping. To reduce uncertainty, a Bayesian Model Averaging (BMA) ensemble was created. These projections were then used to calculate 12-month SPI and SPEI values for both the baseline and near-future period (2031–2054). Drought characteristics—such as duration, intensity, and magnitude—were analyzed using Run theory and compared across two periods. Ensemble model projections suggest that mean temperatures in the province will rise by approximately 1.1-1.2 °C relative to the baseline period under both scenarios. Furthermore, annual average precipitation is expected to increase by 3-8% at most stations in the province, except for Shahrud station. The SPI and SPEI indices exhibited a significant positive correlation, demonstrating relatively similar performance despite minor differences. Based on both indices, drought characteristics such as duration and intensity are projected to increase significantly during the latter years of the 2031–2054 horizon compared to the baseline period. The most notable increase was observed for the SPEI index under the SSP585 scenario, where drought duration rose from 6.6 months during the baseline period to 8.9 months under the SSP245 scenario and 16 months under the SSP585 scenario. For the SPI index, drought duration decreased from 6.3 months in the baseline period to 5.6 months under the SSP245 scenario, then increased to 7.8 months under the SSP585 scenario.  </div> In recent years, the world has experienced more frequent droughts, largely due to climate change. This study monitors and projects drought conditions in Semnan Province, Iran, using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). It also evaluates drought characteristics under future climate scenarios. Projections of temperature and precipitation from 12 CMIP6 climate models were downscaled using Quantile Mapping. To reduce uncertainty, a Bayesian Model Averaging (BMA) ensemble was created. These projections were then used to calculate 12-month SPI and SPEI values for both the baseline and near-future period (2031–2054). Drought characteristics—such as duration, intensity, and magnitude—were analyzed using Run theory and compared across two periods. Ensemble model projections suggest that mean temperatures in the province will rise by approximately 1.1-1.2 °C relative to the baseline period under both scenarios. Furthermore, annual average precipitation is expected to increase by 3-8% at most stations in the province, except for Shahrud station. The SPI and SPEI indices exhibited a significant positive correlation, demonstrating relatively similar performance despite minor differences. Based on both indices, drought characteristics such as duration and intensity are projected to increase significantly during the latter years of the 2031–2054 horizon compared to the baseline period. The most notable increase was observed for the SPEI index under the SSP585 scenario, where drought duration rose from 6.6 months during the baseline period to 8.9 months under the SSP245 scenario and 16 months under the SSP585 scenario. For the SPI index, drought duration decreased from 6.3 months in the baseline period to 5.6 months under the SSP245 scenario, then increased to 7.8 months under the SSP585 scenario.   میانگین‌گیری مدل بیزن, نگاشت چندک, تئوری ران, استان سمنان Bayesian Model Averaging, Quantile Mapping, Run Theory, Semnan Province 0 0 http://jgs.khu.ac.ir/browse.php?a_code=A-10-1232-4&slc_lang=en&sid=1 Hossein Ghorbani Hossein Ghorbani armanneshin@gmail.com 100319475328460025201 100319475328460025201 No Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Mohammad baaghideh Mohammad baaghideh m.baaghideh@hsu.ac.ir 100319475328460025202 100319475328460025202 Yes Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar alireza entezari alireza entezari entezari2005@gmail.com 100319475328460025203 100319475328460025203 No Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Elaheh Asgari Asgari elaheh.asgari2011@gmail.com elaheh.asgari2011@gmail.com 100319475328460025204 100319475328460025204 No Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar