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Terra Latinoamericana

On-line version ISSN 2395-8030Print version ISSN 0187-5779

Abstract

MAGALLANES-QUINTANAR, Rafael et al. Negative regional Standardized Precipitation Index trends prevail in the Mexico’s state of Zacatecas. Terra Latinoam [online]. 2019, vol.37, n.4, pp.487-499.  Epub Mar 24, 2020. ISSN 2395-8030.  https://doi.org/10.28940/terra.v37i4.563.

As the earth atmosphere warms, it is unclear how the precipitation will change or how these changes will impact regional rainfall. For the study of spatial and temporal variability of rainfall, several indexes have been developed. The Standardized Precipitation Index (SPI) that only involves recorded rainfall data has been used as a tool for climatic zone classification and a drought indicator. Then, the aims of the present study were: 1) to cluster monthly precipitation time series into groups that represent regions under the basis of similar precipitation regimes, 2) to compute regional SPI’s using all the members (time series) of each cluster, and 3) to estimate trends of the regional SPI’s. The cluster analysis approach was used to identify four groups of monthly precipitation time series that represent regions of similar precipitation regimes. Afterwards, regional SPI’s were estimated using all the members of each cluster. Finally, four regional SPI trends were estimated by means of the Mann-Kendall trend test and Sen’s slope estimator. Estimated decreasing SPI trends imply prevail of negative values at the end of the study period (1964-2014), which indicate less than median precipitation in the entire Zacatecas state territory. For instance, SPI at 12-month time scale Sen’s slope values were -0.17 and -0.18 for the wet and dry seasons, respectively in the Semi-desert region. Thus, the evidenced trends may be having influence on the availability of surface water, groundwater levels and aquifers recharge in the near future. So, it is imperative to adjust inhabitants’ activities according to design planned climate change adaptation strategies.

Keywords : climatic regions; cluster analysis; drought; dry season; wet season.

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