Meteorological drought using the Precipitation Condition Index in dry northeast Mexico during the 2000-2023 period

Northeast Mexico is well known for having dry climate; nevertheless, agriculture and livestock stand among the top economic activities of the state. For the last 24 years, Tamaulipas has been struck by numerous meteorological droughts which have caused financial losses in the country. This work studied meteorological drought in Tamaulipas through remote sensing techniques and IMERG satellite imagery for accumulated precipitation for 2000-2023 period. Downloaded IMERG images were projected to WGS 84/ UTM14N, cropped in the shape of Tamaulipas and processed to compute the Precipitation Condition Index (PCI). As a method of validating, the Pearson Lineal Correlation was calculated for PCI results and Standardized Precipitation Index for one (SPI-1) and three (SPI-3) months. Six years are clearly identified as meteorological drought years: 2000, 2006, 2009, 2011, 2022 and 2023. Results obtained by PCI show drought events that match the dry years identified by the SPI. Furthermore, dry years are closely related to the low-activity annual tropical cyclone season in the Gulf of Mexico. PCI and SPI-1 in the northern region showed the best correlation between them (r=0.87), while the worst correlation was found between PCI and SPI-3 in the southern region (r=0.44), from which it is concluded that PCI is a meteorological drought index capable and adequate for monitoring meteorological drought in Tamaulipas and in similar weather conditions.

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Publication Details

Journal
Revista de Teledetección
Published
2025-06-30
DOI
https://doi.org/10.4995/raet.2025.22885
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Meteorological drought using the Precipitation Condition Index in dry northeast Mexico during the 2000-2023 period

Wilberth Alfredo Poot-Poot, I. Gutiérrez, Víctor H. Domínguez-Meza, Xóchitl C. Ramírez Campanur
Revista de Teledetección
Hydrology and Drought Analysis
article

Meteorological drought using the Precipitation Condition Index in dry northeast Mexico during the 2000-2023 period

Wilberth Alfredo Poot-Poot, I. Gutiérrez, Víctor H. Domínguez-Meza, Xóchitl C. Ramírez Campanur
article en

Abstract

Northeast Mexico is well known for having dry climate; nevertheless, agriculture and livestock stand among the top economic activities of the state. For the last 24 years, Tamaulipas has been struck by numerous meteorological droughts which have caused financial losses in the country. This work studied meteorological drought in Tamaulipas through remote sensing techniques and IMERG satellite imagery for accumulated precipitation for 2000-2023 period. Downloaded IMERG images were projected to WGS 84/ UTM14N, cropped in the shape of Tamaulipas and processed to compute the Precipitation Condition Index (PCI). As a method of validating, the Pearson Lineal Correlation was calculated for PCI results and Standardized Precipitation Index for one (SPI-1) and three (SPI-3) months. Six years are clearly identified as meteorological drought years: 2000, 2006, 2009, 2011, 2022 and 2023. Results obtained by PCI show drought events that match the dry years identified by the SPI. Furthermore, dry years are closely related to the low-activity annual tropical cyclone season in the Gulf of Mexico. PCI and SPI-1 in the northern region showed the best correlation between them (r=0.87), while the worst correlation was found between PCI and SPI-3 in the southern region (r=0.44), from which it is concluded that PCI is a meteorological drought index capable and adequate for monitoring meteorological drought in Tamaulipas and in similar weather conditions.

Revista de Teledetección(66)
Universidad Michoacana de San Nicolás de Hidalgo (MX), Autonomous University of Tamaulipas (MX)
Universidad Autónoma de Tamaulipas
Openalex Percentile: Top 85%
Hydrology and Drought Analysis
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Meteorological drought using the Precipitation Condition Index in dry northeast Mexico during the 2000-2023 period — Wilberth Alfredo Poot-Poot, I. Gutiérrez, et al. · Revista de Teledetección (2025) | TGRS Research Map | TGRS