Analysis of the meteorological drought in four agricultural locations of Venezuela by the combination of multivariate methods.

On a global scale, agriculture is considered the most vulnerable to drought, representing one of the most devastating climate threats. For this reason, the objective of this work was to analyze the occurrence of meteorological drought by means of time series of the Normalized Precipitation Index dur...

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Bibliographic Details
Authors: Orlando Olivares, Barlin, Zingaretti, M. L.
Format: article
Status:Published version
Publication Date:2018
Country:Costa Rica
Institution:Universidad Estatal a Distancia
Repository:Portal de Revistas UNED
Language:Spanish
OAI Identifier:oai:revistas.investiga.uned.ac.cr:article/2026
Online Access:https://revistas.uned.ac.cr/index.php/cuadernos/article/view/2026
Access Level:Open access
Keyword:agriculture
climate
precipitation
water deficit
drought
agricultura
clima
precipitación
déficit hídrico
sequía
Description
Summary:On a global scale, agriculture is considered the most vulnerable to drought, representing one of the most devastating climate threats. For this reason, the objective of this work was to analyze the occurrence of meteorological drought by means of time series of the Normalized Precipitation Index during the period (1980-2014) for four Venezuelan agricultural sites. For the analysis, we used the combination of two multivariate methods: the Principal Coordinate Analysis of the data matrices using Euclidean Distance and the Cluster Analysis. The results of the analysis revealed three groups of years for the localities El Tigre and Banco de San Pedro, represented by the wet years, normal or intermediate conditions and years with significant water deficit; while for the rest of the localities (Tapipa-Padrón and El Guayabo) only two groups of years are distinguished (humid and dry). The statistical methodology based on the multivariate analysis allowed delineating groups of years that showed similar patterns of the index of meteorological drought as a function of the time series. The study is the backbone for space planning and the strengthening of strategies for food security in those localities.