Seasonal and isotopic precipitation patterns in the semi-arid and high mountain areas

Abstract

Precipitation plays a crucial role in the natural hydrological cycle. Understanding the spatial and temporal variations of precipitation isotopes is essential for identifying hydrological, meteorological, and ecological processes. In high mountain areas with arid and semi-arid conditions, especially in regions with endorheic basins, the portion of precipitation that infiltrates the groundwater as the primary source of water recharge. However, estimating this recharge is challenging and prone to high uncertainty. The main objective of this study was to implement a robust and detailed methodology to analyze the influence of meteorological variables and the origin of moisture sources on the stable isotopic composition (δ18O and δ2H) of precipitation. As an illustrative case, we focused on the Los Pozuelos Basin, an endorheic basin in the Altiplano-Puna region of the Andes. The analysis incorporated precipitation samples collected over a 3-year period (January 2020 to April 2023) along with comprehensive monitoring of local atmospheric variables, satellite imagery, and HYSPLIT backward trajectory models. The examination involved a multivariate analysis of meteorological and stable isotope data and atmospheric transport pattern. Precipitation characteristics exhibited seasonal variability, with summer precipitation being depleted in heavy isotopes due to its extended continental journey and the recycling it undergoes while crossing the Amazon basin with convective activity. Another moisture path from the Atlantic Ocean, via the Río de la Plata or Gran Chaco basin, represented an intermediate isotopic stage. La Niña events intensified westerly winds, drawing moist air masses from the Pacific Ocean and causing rainfall in the study area. In winter, precipitation comes from the Pacific Ocean and isotopically enriched due to the low amount of precipitation and lower convective activity. By employing a meticulous methodology and multivariate statistical analysis, the study contributes positively to the broader discourse on water resource management and conservation in arid and semi-arid environments.