Unspecified Carlos Cohen-Manrique Profile

Carlos Cohen-Manrique

at Univ. Tecnológica de Bolívar

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Proceedings Article | 10 June 2024 Presentation + Paper

Impact of land cover variations on the Morroa aquifer (Colombia) static and dynamic levels through remote sensing analysis

Carlos Cohen-Manrique, Yady Solano-Correa, Jose Villa-Ramírez, Alex Alvarez-Month

Proceedings Volume 13037, 1303704 (2024) https://doi.org/10.1117/12.3014190

KEYWORDS: Vegetation, Land cover, Remote sensing, Rain, Artificial neural networks, Water, Random forests, Machine learning, Data modeling

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The Morroa aquifer plays a crucial role supplying drinking water to around one million residents across Sucre, Córdoba, and Bolívar departments in Colombia. However, it faces severe water stress, ranking as the second most overexploited aquifer globally according to recent research using the Groundwater Footprint (GF) indicator. This situation threatens the sustainability of the aquifer and the well-being of the region's inhabitants who rely on it. To tackle this challenge, CARSUCRE, the entity responsible for aquifer management, has implemented various strategies. These include establishing a monitoring network with piezometers to track static and dynamic aquifer levels and conducting civil works to redirect rainfall runoff towards artificial recharge projects. Yet, the impact of vegetation variations in the recharge areas of the aquifer levels remains uncertain due to many different factors like drought, heavy rainfall, and economic changes. This research introduces a methodology that leverages remote sensing data, particularly high-resolution images from the Planet platform (3m), combined with land cover analysis in piezometer influence areas. The primary aim is to assess how changes in vegetation affect both static and dynamic levels of the Morroa Aquifer and then identify strategies to enhance land cover and improve water capture. The results obtained show a significant correlation between NDVI, EVI, and LULC for the aquifer recharge zone, with an average of 0.858 for all applied tools. These findings provide valuable information for the management and preservation of this vital water resource in the region.

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