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Advances in Meteorology
Volume 2018, Article ID 1098942, 16 pages
https://doi.org/10.1155/2018/1098942
Research Article

Identification of Variations in the Climatic Conditions of the Lerma-Chapala-Santiago Watershed by Comparative Analysis of Time Series

1Facultad de Geografía, Universidad Autónoma del Estado de México, Toluca, MEX, Mexico
2Centro Interamericano de Recursos del Agua, Facultad de Ingeniería, Universidad Autónoma del Estado de México, Toluca, MEX, Mexico

Correspondence should be addressed to Miguel A. Gómez-Albores; xm.xemeau@azemogam

Received 14 December 2017; Accepted 10 April 2018; Published 9 May 2018

Academic Editor: Enrico Ferrero

Copyright © 2018 Luis Ricardo Manzano-Solís et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The current study presents a method for automating the Köppen–Garcia climate classification using a GIS module. This method was then applied in a case study of the Lerma-Chapala-Santiago watershed to compare time series data on climate from 1960 to 1989, 1981 to 2010, and 1960 to 2010. The kappa statistic indicated that the climate classifications of the generated model had a perfect degree of agreement with those of a prior nonautomated study. The climate data from the period 1960 to 2010 were used to create a climate map for the watershed. Overall, the dominant climates were dry, semiarid, temperate, and semiwarm temperate with a summer rainfall pattern. A comparative analysis of climate behavior between 1960 and 1989 and between 1981 and 2010 showed changes in temperature and extreme temperatures over 13.6% and 9.9%, respectively, of the watershed; the presence or absence of mid-summer drought also changed over 0.8% of the watershed. The module developed herein can be used to classify climates across all of Mexico, and data of varying spatial resolution and coverage can be inputted to the module. Finally, this module can be used to automate the creation of climate maps or to update climate maps at diverse spatial-temporal scales.