Preprints
https://doi.org/10.5194/essd-2025-306
https://doi.org/10.5194/essd-2025-306
05 Aug 2025
 | 05 Aug 2025
Status: this preprint is currently under review for the journal ESSD.

The first rainfall erosivity database in Mexico: facing challenges of leveraging legacy climate data

Viviana Marcela Varón-Ramírez, Douglas Andrés Gómez-Latorre, Carlos Eduardo Arroyo-Cruz, Alberto Gómez-Tagle, Blanca Lucía Prado Pano, Ronald Roger Gutierrez Llantoy, Deyanira Lobo-Luján, and Mario Guevara

Abstract. Soil water erosion (SWE) is the dominant soil degradation driver on a global scale. For quantifying SWE, erosivity is an index that reflects the potential (i.e., the energy) of rainfall to cause SWE. To support large-scale SWE studies and the assessment of the SWE process at the national scale in Mexico, the objectives of this research are a) to develop the first Mexican rainfall time series database for three climate normals CNs (1968–1997, 1978–2007, and 1988–2017) leveraging legacy climate data, and b) to estimate rainfall erosivity across continental Mexico by using daily rainfall time series. The workflow has three methodological moments: 1) development of the daily rainfall time series database, 2) identification of the best empirical relationship to estimate daily rainfall erosivity, and 3) estimation of the rainfall erosivity across Mexican territory. We compiled and harmonized 5410 rainfall time series (RTS) well distributed across the Mexican territory. We perform quality control and assurance, homogeneity analysis (using the normal homogeneity test), and the data gap-filling process (using the proportion method). Then, we tested three combinations of the α and β coefficients, proposed by three authors, in a power model to estimate rainfall erosivity; in this step, we used three validation databases (global, national, and local scales). Finally, we estimated the annual rainfall erosivity for all three CNs with multiple combinations of α and β coefficients. As principal results, the new database includes 1370, 1678, and 1676 RTS for each CN and its corresponding rainfall erosivity. The best parameter combination is the one proposed by Richardson et al. (1983) for all three validation databases. For the global and national databases, we observe a positive bias (Mean error of 956 and 324 MJ mm ha-1 h-1 yr-1, respectively); in contrast, for the local database, results show a negative and higher bias (Mean error of -3699 MJ mm ha-1 h-1 yr-1). About the erosivity estimation across the Mexican territory, the median values for rainfall erosivity for the three CNs were 3245, 3070, and 3327 MJ mm ha-1 h-1 yr-1, respectively. The statistical distribution of the erosivity values was right-skewed for the three CNs, with high erosivity values reaching >12000 MJ mm ha-1 h-1 yr-1 in all three CNs. The behavior throughout the year of the rainfall erosivity was similar for the three CNs. However, September had the highest contribution to the rainfall erosivity. The new database provides daily climatological data and analysis across Mexican territory through a multi-year period (1968 to 2017). Rainfall erosivity results support the study of SWE at the national scale by identifying areas with higher susceptibility to soil loss due to rainfall action and providing a more spatially dense and well-documented rainfall erosivity database. Following the FAIR principles (Findability, Availability, Interoperability, and Reproducibility) for scientific data, this database is available from a scholarly accepted repository https://doi.org/10.6073/pasta/e0dc8bd3501f8c19bb750e853c3289cb (Varón-Ramírez et al., 2025) for public consultation.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Viviana Marcela Varón-Ramírez, Douglas Andrés Gómez-Latorre, Carlos Eduardo Arroyo-Cruz, Alberto Gómez-Tagle, Blanca Lucía Prado Pano, Ronald Roger Gutierrez Llantoy, Deyanira Lobo-Luján, and Mario Guevara

Status: open (until 11 Sep 2025)

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Viviana Marcela Varón-Ramírez, Douglas Andrés Gómez-Latorre, Carlos Eduardo Arroyo-Cruz, Alberto Gómez-Tagle, Blanca Lucía Prado Pano, Ronald Roger Gutierrez Llantoy, Deyanira Lobo-Luján, and Mario Guevara

Data sets

Daily rainfall series and rainfall erosivity in Mexico for three climatic normals (1968-1997, 1978-2007, and 1988-2017) V. M. Varón-Ramírez et al. https://doi.org/10.6073/pasta/e0dc8bd3501f8c19bb750e853c3289cb

Model code and software

Rainfall-Erosivity-Mexico: Rainfall- Erosivity-Mexico V. M. Varón-Ramírez https://doi.org/10.5281/zenodo.15468097

Viviana Marcela Varón-Ramírez, Douglas Andrés Gómez-Latorre, Carlos Eduardo Arroyo-Cruz, Alberto Gómez-Tagle, Blanca Lucía Prado Pano, Ronald Roger Gutierrez Llantoy, Deyanira Lobo-Luján, and Mario Guevara
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Latest update: 05 Aug 2025
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Short summary
This research focuses on Mexico's soil water erosion (SWE) using rainfall data to estimate erosivity. A database of daily rainfall series was developed for three climate normals –CNs– (1968–1997, 1978–2007, 1988–2017) with over 5,000 series. We found median erosivity values of 3245, 3070, and 3327 MJ mm ha-1 h-1 yr-1 for the three CNs. The resulting publicly available datasets of rainfall series and erosivity help better understand SWE and rainfall patterns across Mexico.
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