Droughts present a series of significant problems that affect both the environment and society. Problems arise in diferents intensity, scope, type of impact by region, for example water scarcity affects supply of water for human consumption, agriculture, industry and the environment. To address these problems, it is crucial to implement water management strategies and a continuous monitoring are essential to predict and mitigate the effects of droughts. The Standardized Precipitation Index (SPI), tells us if it has rained normally in a region during a certain time range. The SPEI allows assessing the severity of drought on different time scales. Guanajuato state, nestled in central Mexico, have a semi-arid climate, with an average annual rainfall of 650mm. This work uses data analysis techniques to conduct an initial drought assessment for state of Guanajuato. The Python informatic language was used to generate a web plataform, data visualization, generating interactive maps, informative graphs, and comprehensive data tables, we uded the information of 29 climate monitoring stations, and we analyzed data spanning from January 2000 to November 2023, resulting in a final dataset of 8,294 entries. Preliminary results from our ongoing work presents time series of SPI records helped visualize key characteristics such as trend, seasonality, and cyclicity. Each station's SPI is visualized by a heat map, where vibrant colors paint the picture of their values over time, across different years.

Authors:
JoseDeJesus Sandoval-Palomares, TECNM-LEON, Mexico
Oscar Manuel Rodriguez-Narvaez, CIATEC, Mexico

About the Presenter(s)
Professor JoseDeJesus Sandoval-Palomares is a University Professor/Principal Lecturer at CIATEC,A.C in Mexico

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