volume 19 issue 7 pages 6573-6594

Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province

Publication typeJournal Article
Publication date2022-01-29
scimago Q1
wos Q2
SJR0.736
CiteScore7.2
Impact factor3.4
ISSN17351472, 17352630
General Agricultural and Biological Sciences
Environmental Chemistry
Environmental Engineering
Abstract
Drought is a major water resources management issue in Iran. Khuzestan Province is in a drought state due to water shortage. Therefore, identifying areas at high risk of drought and when drought occurs is essential for drought management. For this purpose, this study used precipitation and temperature data of 12 selected stations and MODIS sensor images from the United States Geological Survey database in 2000–2017. The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Normalized Difference Vegetation Index (NDVI) were calculated using the Hargreaves–Samani method and ENVI software. Moreover, different spatial statistics techniques were used in the ArcGIS environment to analyze the results. Also, time series diagrams were drawn, and the trend was evaluated using the Mann–Kendall test. Finally, the distribution of NDVI values was investigated using EasyFit software, and the amount of drought damage was determined using NDVI. The investigation of the cluster maps of the Anselin Local Moran’s Index along with hot and cold spots formed for both SPEI and NDVI showed that drought severity was higher at the southern stations than at the semi-northern and northwestern ones in the province. Moreover, the survey results using the EasyFit software showed that the southern stations, including the Ahvaz, Mahshahr, and Omidiyeh-Aghajari stations, were more at risk of drought than the other stations due to the drought threshold. Furthermore, the total damage caused by drought for the Ahvaz and Abadan stations showed a damage rate of 50%.
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GOST Copy
Nejadrekabi M. et al. Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province // International Journal of Environmental Science and Technology. 2022. Vol. 19. No. 7. pp. 6573-6594.
GOST all authors (up to 50) Copy
Nejadrekabi M., Eslamian S., Zareian M. J. Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province // International Journal of Environmental Science and Technology. 2022. Vol. 19. No. 7. pp. 6573-6594.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1007/s13762-021-03852-8
UR - https://doi.org/10.1007/s13762-021-03852-8
TI - Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province
T2 - International Journal of Environmental Science and Technology
AU - Nejadrekabi, M
AU - Eslamian, S
AU - Zareian, M J
PY - 2022
DA - 2022/01/29
PB - Springer Nature
SP - 6573-6594
IS - 7
VL - 19
PMID - 35126565
SN - 1735-1472
SN - 1735-2630
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2022_Nejadrekabi,
author = {M Nejadrekabi and S Eslamian and M J Zareian},
title = {Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province},
journal = {International Journal of Environmental Science and Technology},
year = {2022},
volume = {19},
publisher = {Springer Nature},
month = {jan},
url = {https://doi.org/10.1007/s13762-021-03852-8},
number = {7},
pages = {6573--6594},
doi = {10.1007/s13762-021-03852-8}
}
MLA
Cite this
MLA Copy
Nejadrekabi, M., et al. “Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province.” International Journal of Environmental Science and Technology, vol. 19, no. 7, Jan. 2022, pp. 6573-6594. https://doi.org/10.1007/s13762-021-03852-8.