Cargando…
Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province
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 temperatu...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799989/ https://www.ncbi.nlm.nih.gov/pubmed/35126565 http://dx.doi.org/10.1007/s13762-021-03852-8 |
_version_ | 1784642167733485568 |
---|---|
author | Nejadrekabi, M. Eslamian, S. Zareian, M. J. |
author_facet | Nejadrekabi, M. Eslamian, S. Zareian, M. J. |
author_sort | Nejadrekabi, M. |
collection | PubMed |
description | 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%. |
format | Online Article Text |
id | pubmed-8799989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87999892022-01-31 Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province Nejadrekabi, M. Eslamian, S. Zareian, M. J. Int J Environ Sci Technol (Tehran) Original Paper 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%. Springer Berlin Heidelberg 2022-01-29 2022 /pmc/articles/PMC8799989/ /pubmed/35126565 http://dx.doi.org/10.1007/s13762-021-03852-8 Text en © Islamic Azad University (IAU) 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Nejadrekabi, M. Eslamian, S. Zareian, M. J. Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title | Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title_full | Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title_fullStr | Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title_full_unstemmed | Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title_short | Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province |
title_sort | spatial statistics techniques for spei and ndvi drought indices: a case study of khuzestan province |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8799989/ https://www.ncbi.nlm.nih.gov/pubmed/35126565 http://dx.doi.org/10.1007/s13762-021-03852-8 |
work_keys_str_mv | AT nejadrekabim spatialstatisticstechniquesforspeiandndvidroughtindicesacasestudyofkhuzestanprovince AT eslamians spatialstatisticstechniquesforspeiandndvidroughtindicesacasestudyofkhuzestanprovince AT zareianmj spatialstatisticstechniquesforspeiandndvidroughtindicesacasestudyofkhuzestanprovince |