Abstract
Adequate water resources management includes understanding patterns and spatiotemporal variability of precipitation, as this variable is determinant for ecosystems’ stability, food security, and most human activities. Based on satellite estimations validated through ground measurements from 59 meteorological stations, the objective of this study is to evaluate the long-term spatiotemporal variability and trends of the average monthly precipitation in the Magdalena Department, Colombia, for the 1981–2018 period. This heterogeneous region comprises many different ecoregions in its 23,188 km2 area. The analysis of spatial variability allowed for the determination of four different subregions based on the differences in the average values of precipitation and the degree of rainfall variability. The trend analysis indicates that the current rainfall patterns contradict previous estimates of a progressive decrease in annual averages due to climate change in the study region, as most of the department does not exhibit statistically significant trends, except for the Sierra Nevada de Santa Marta area, where this study found reductions between 10 mm yr−1 and 30 mm yr−1. The findings of this study also suggest the existence of some links between precipitation patterns with regional phenomena of climate variability and solar activity.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
This paper aims to evaluate the long-term spatiotemporal variability and trends of average monthly precipitation in the Magdalena Department based on satellite estimations, using ground measurements to validate these datasets
Subregion 2 corresponds to a low-precipitation (< 1500 mm yr−1 ) and low-variability (CV < 20) zone, and it covers the central region of the department in a longitudinal gradient
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The analysis of the spatial distribution of rainfall and its temporal trends is crucial for water resources management, farming productivity, and climate change mitigation [1]. The yearly and seasonal precipitation trends analysis offers intuitive information about the soil humidity dynamic in the non-irrigated land systems [2]. Spatial pattern estimation of rainfall is the key for designing mitigation and response actions
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