Title of article :
Using spatial statistics to identify drought-prone regions (A case study of Khuzestan Province, Iran)
Author/Authors :
Nejadrekabi, Mohsen Department of Civil Engineering - Najafabad Branch - Islamic Azad University - Najafabad, Iran , Eslamian, Saeid Department of Civil Engineering - Najafabad Branch - Islamic Azad University - Najafabad, Iran , Zareian, Mohammad Javad Department of Water Resources Research - Water Research Institute (WRI) - Tehran, Iran
Abstract :
Iran is located in the Earth’s arid zone, and a drought crisis imperils the country
as a result of declining water resources. Khuzestan Province, located in the
south of Iran, is in critical condition due to water shortages; many of its groves
have been destroyed. It also has many respiratory and pulmonary patients due
to the constant presence of dust. The pandemic and this dust have caused
acute problems for those diagnosed with COVID-19. Due to the importance of
water deficit in this province, the present research calculated the Standardized
Precipitation Index (SPI) and Standard Precipitation Evaporation Index (SPEI)
in a thirty-year statistical period from 1984 to 2014; 12 stations were selected
during the months when rainfall was more likely. This study utilized a
geostatistical method to prepare zoning maps of SPI and SPEI. Then, various
spatial statistics techniques in ArcGIS software were used to identify and locate
the exact areas that were the sources of drought with the help of drought hot
spots and strong drought clusters. Anselin Local Moran's maps indicated that
the high-high precipitation clusters were located in the northeastern regions
of Khuzestan. The hot and cold drought spots, which were identified by Getis-
Ord G* spatial statistics based on both SPI and SPEI, showed that the hot spots
were formed in the southern and southwestern regions; the cold spots were
formed in the northwestern regions. Furthermore, the drought hot spots were
identified with a 99% confidence level in places where the total ten-year
precipitation was less than 270 millimeters.
Keywords :
Spatial statistics , Geostatistics , Spatial correlation , Anselin Local Moran index , Hot spots and cold spots
Journal title :
advances in Environmental Technology