Forecasting the risk of drought in Zabol synoptic station based on the output of CMIP6 climate models

Drought is one of the most complex natural hazards that affect natural and human systems (Wilhite et al., 2005, Wilhite et al., 2007). Greenhouse gas emission has contributed to climate change in the last century (Van Pelt and Swart, 2011). Climate change has a significant impact on the hydrological cycle and consequently on water resources, and the frequency and severity of droughts and floods. The most reliable tool available for future climate simulation is the output of coupled atmosphere-ocean patterns of atmospheric general circulation (Shakarami and Massahbavani, 2007). The reports of the Intergovernmental Panel on Climate Change show that if the current trend of greenhouse gas production due to the consumption of fossil fuels continues, the concentration of these gases can reach more than 600 ppm before the end of the 21st century (IPCC, 2007). The downscale model, which is a downscale statistical method, uses semi-empirical distributions for simulation and downscale and can generate future climate parameters at the station level. A major application of these data is to monitor and evaluate future droughts (Hosseinabadi et al, 2020). In the occurrence of drought, there are many factors such as changing the course of rivers and draining reservoirs, climate change and warming of the earth. Nowadays, the increasing occurrence of drought has caused the attention of many meteorologists and climatologists around the world. Drought indicators are used to diagnose and classify drought conditions. These indicators include the possibility of evaluating the standardized precipitation evaporation and transpiration index SPEI, the Palmer drought intensity index PDSI, the standard runoff index SRI and the identification drought index RDI. SPI and SPEI are the most common drought indicators.