4.6 Article

Estimating groundwater recharge and precipitation sources of the Zamora River Basin, southeastern Ecuador, using GIS and stable isotopes

Journal

ENVIRONMENTAL EARTH SCIENCES
Volume 82, Issue 17, Pages -

Publisher

SPRINGER
DOI: 10.1007/s12665-023-11097-6

Keywords

Groundwater recharge; GIS; Water balance; Stable isotopes; Conceptual model

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The correct management of groundwater depends on understanding its evolutionary processes and spatial variability of recharge mechanisms. GIS-based index models provide a reliable and adaptable solution for mapping and interpreting recharge models. Stable isotopes of hydrogen and oxygen in water help determine the origin and monitoring of water in the hydrological cycle.
The correct management of groundwater depends on information regarding the evolutionary processes of groundwater and the characterization of spatial variability of recharge mechanisms. GIS-based index models have become a reliable alternative for mapping and interpreting recharge models due to their adaptability and reliability in estimating recharge. Furthermore, stable isotopes of hydrogen and oxygen in water (& delta;H-2 and & delta;O-18) help determine the origin and monitoring of water in the hydrological cycle. This paper aims to contribute to the knowledge of groundwater recharge by developing a conceptual recharge model using stable isotopes and estimating the recharge amount using a spatially distributed water balance model based on GIS for the Zamora River Basin (ZRB) in Ecuadorian Amazon. Due to the basin's size and geography, it was necessary to divide it into six precipitation blocks. The high precipitation rates resulted in high (18.22%) and moderate (30.93%) recharge zones across the basin. The analysis of stable isotopes in water indicates that precipitation water comes from the east, from the Amazon plain. In the valleys, precipitation enriched in & delta;O-18 suggests that it has undergone a recycling process in the basin; groundwater recharge comes from these precipitations. This analysis provides a simplified representation of reality that can assist in predicting the impacts of human activities on the basin.

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