Methodological estimation to quantify drought intensity based on the NDDI index with Landsat 8 multispectral images in the central zone of the Gulf of Mexico

• Published in: Frontiers in earth science (Lausanne) Vol. 11
• Main Authors: Salas-Martínez, Fernando, Valdés-Rodríguez, Ofelia Andrea, Palacios-Wassenaar, Olivia Margarita, Márquez-Grajales, Aldo, Rodríguez-Hernández, Leonardo Daniel
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 09.05.2023
• Subjects: climate change; drought; Gulf of Mexico; Landsat 8; NDDI index
• ISSN: 2296-6463; 2296-6463
• DOI: 10.3389/feart.2023.1027483

Introduction: Drought is a slow evolution phenomenon drastically affecting the environment and human activities. Nowadays, there are several indices to study drought. They can be based on in-site measurements of meteorological stations or remote perception data. However, Mexico’s number of functioning meteorological stations from the National Meteorological Service (NMS) is steadily decreasing. Nevertheless, the NMS reports drought conditions through the Mexican Drought Monitor (MDM), which uses different methods to estimate drought levels. These reports are provided every 15 days for each municipality. However, the methods the NMS utilizes are unknown to the general public. Thus, in-situ studies which try to estimate drought are limited by the MDM data constrictions. Consequently, remote perception is an alternative to solve the lack of stations and the MDM data restrictions, depending on the region. Therefore, this research aims to: 1) Develop a methodology to quantify drought intensity based on the Normalized Difference Drought Index (NDDI) with Landsat 8 multispectral images in the municipalities of the central zone of the Gulf of Mexico for drought and no drought periods. 2) Analyze and compare the NDDI behavior against the MDM from the NMS during the same periods. Methods: The methodology consisted of estimating the NDDI by using Landsat 8 multispectral images. Further on, NDDI drought values were compared with the MDM. Results: Results showed that NDDI values increase from July to October during a drought period, coinciding with months when precipitation is low, and temperature is high. Additionally, it was found that the NDDI coincides with the MDM data in 46% of the municipalities having drought conditions when temperatures increased 2.1°C and precipitations decreased by 668 mm. Furthermore, the NDDI coincided in 16% of the municipalities during no drought periods with the maximum increases in temperatures at 1.4°C and precipitation reduced by 386 mm. Discussion: The NDDI estimated by Landsat 8 images can determine drought behavior in the study zone during periods with limited reduced precipitation and temperature increases.