The aim of this study is to discretize precipitation through interpolation utilizing the inverse square of distance and elevation as weighting elements to represent the spatial and temporal variation of rainfall. This technique has proven to be highly effective in capturing precipitation variability by integrating distance and elevation data from 15 stations built from a network of 39 rain gauges clustered by subbasins, generating continuous time series from 2006 to 2022. Validation through the double mass method has confirmed the accuracy of these time series, all exhibiting a coefficient of determination greater than R2 = 0.99. This approach has provided a detailed representation of rainfall patterns across the entire region, significantly advancing our understanding of spatial hydrological dynamics.
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Costa et al. (2024) studied this question.