Multifractal Analysis of Monthly Precipitation in a Semi-Arid Region of Central Mexico: Guanajuato, 1981–2016

This study characterizes the multifractal structure of monthly precipitation in the semi-arid state of Guanajuato, Mexico, using Multifractal Detrended Fluctuation Analysis with quadratic detrending (MFDFA-2). We analyze 65 quality-controlled meteorological stations covering the period 1981–2016. All series exhibit multifractality, with generalized Hurst exponents h(2)=0.568±0.065 indicating predominantly persistent dynamics and long-term positive autocorrelation (64.6% of stations). The multifractal spectrum width (Δα) ranges from 0.15 to 0.72 (mean = 0.2423), revealing substantial spatial variability in scaling complexity. K-means clustering based on multifractal features identifies the following four hydroclimatic groups: one random cluster (29.2% of stations) and three persistence-dominated clusters (70.8%), with coherent spatial organization. These findings provide new insights into the temporal scaling properties of precipitation in semi-arid regions and have important implications for water resource management and regionalized drought-risk assessment.

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Journal
Water
Published
2026-04-11
DOI
https://doi.org/10.3390/w18080911
Primary Topic
Complex Systems and Time Series Analysis
Type
article
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article

Multifractal Analysis of Monthly Precipitation in a Semi-Arid Region of Central Mexico: Guanajuato, 1981–2016

Jorge Luis Morales Martínez, Guillermo Sosa-Gómez, Víctor Manuel Ortega Chávez, Juan Manuel Navarro Céspedes et al.
Water
Complex Systems and Time Series Analysis
article

Multifractal Analysis of Monthly Precipitation in a Semi-Arid Region of Central Mexico: Guanajuato, 1981–2016

Jorge Luis Morales Martínez, Guillermo Sosa-Gómez, Víctor Manuel Ortega Chávez, Juan Manuel Navarro Céspedes, Juana Edith Lozano Hernández, Xitlali Delgado-Galván
article en

Abstract

This study characterizes the multifractal structure of monthly precipitation in the semi-arid state of Guanajuato, Mexico, using Multifractal Detrended Fluctuation Analysis with quadratic detrending (MFDFA-2). We analyze 65 quality-controlled meteorological stations covering the period 1981–2016. All series exhibit multifractality, with generalized Hurst exponents h(2)=0.568±0.065 indicating predominantly persistent dynamics and long-term positive autocorrelation (64.6% of stations). The multifractal spectrum width (Δα) ranges from 0.15 to 0.72 (mean = 0.2423), revealing substantial spatial variability in scaling complexity. K-means clustering based on multifractal features identifies the following four hydroclimatic groups: one random cluster (29.2% of stations) and three persistence-dominated clusters (70.8%), with coherent spatial organization. These findings provide new insights into the temporal scaling properties of precipitation in semi-arid regions and have important implications for water resource management and regionalized drought-risk assessment.

WaterVol. 18(8)
National Research University Higher School of Economics (RU), Universidad de Guanajuato (MX), Saint Petersburg State University of Aerospace and Instrumentation (RU), Tecnológico Nacional de México (MX), Universidad Panamericana (MX)
Clean water and sanitation
Openalex Percentile: Top 14%
Complex Systems and Time Series Analysis
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