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Item type:Publication, Agricultural land degradation in Peru and Bolivia(Springer Nature, 2022-01-01)Soil erosion is the most prominent evidence of soil degradation and is regarded as the main type of agricultural land degradation worldwide. The objective of this contribution is to assess soil degradation associated with agricultural lands in Peru and Bolivia. The assessment is mainly based on a recent soil erosion survey; maps describing soil erosion rates across 5 km grids for the years 1990, 2000, 2010, and 2020; and global observations of agricultural land areas. We observe that soil erosion rates in agricultural lands from Peru and Bolivia are steadily growing. We also observe that (1) the highest quantities of soil erosion are found in the Andean highlands and the largest areas of soil denudation in the Amazonian sections, and (2) there is a positive relation between erosion degree and soil organic carbon stock. The main drivers of soil erosion are the intensive agriculture production and fertilizer use that have increased in Peru and Bolivia. This land use intensification in both countries is also the driver of other land degradation factors such as soil salinization and soil pollution. The use of sewage (e.g., gray water) in urban and peri-urban agricultural areas increases the risk to soil health by inducing the dispersion of microplastics assisted by soil erosion. Overgrazing affects a large portion of the highlands from both countries. Very limited information of the extent of slash-and-burn fire agriculture exists; however, this practice is mostly observed in the Department of Santa Cruz (Bolivia). To prevent or minimize the pressure on soil resources associated with soil erosion or soil pollution, we highlight the need to support sustainable soil management practices and responsible use of fertilizers in agricultural land. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The first rainfall erosivity database in Mexico: facing challenges of leveraging legacy climate data(2025-08-05)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.3