Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran

• Published in: Journal of arid land 2020-03, Vol.12 (2), p.318-330
• Main Authors: Dehghan, Sheida, Salehnia, Nasrin, Sayari, Nasrin, Bakhtiari, Bahram
• Format: Article
• Language: English
• Subjects: Arid regions; Arid zones; Climate change and its impact on water resources in arid regions; Climate prediction; Climatic data; Computer simulation; Data analysis; Data processing; Disasters; Drought; Drought index; Earth and Environmental Science; Environmental monitoring; General circulation models; Geography; History; Mathematical models; Meteorological data; Physical Geography; Plant Ecology; Root-mean-square errors; Semi arid areas; Semiarid zones; Statistical models; Sustainable Development; Weather stations
• ISSN: 1674-6767; 2194-7783
• DOI: 10.1007/s40333-020-0095-5

Drought is one of the most significant environmental disasters, especially in arid and semi-arid regions. Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world. One of these indicators is the Palmer drought severity index (PDSI), which is used in many parts of the world to assess the drought situation and continuation. In this study, the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995–2014 according to meteorological data from six weather stations in the province. A statistical downscaling model (SDSM) was used to apply the output results of the general circulation model in Fars Province. To implement data processing and prediction of climate data, a statistical period 1995–2014 was considered as the monitoring period, and a statistical period 2019–2048 was for the prediction period. The results revealed that there is a good agreement between the simulated precipitation ( R 2 >0.63; R 2 , determination coefficient; MAE