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Using UAV Photogrammetry and Automated Sensors to Assess Aquifer Recharge from a Coastal Wetland

Novel data-acquisition technologies have revolutionized the study of natural systems, allowing the massive collection of information in situ and remotely. Merging these technologies improves the understanding of complex hydrological interactions, such as those of wetland–aquifer systems, and facilit...

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Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-12, Vol.14 (24), p.6185
Main Authors: García-López, Santiago, Vélez-Nicolás, Mercedes, Martínez-López, Javier, Sánchez-Bellón, Angel, Pacheco-Orellana, María Jesús, Ruiz-Ortiz, Verónica, Muñoz-Pérez, Juan José, Barbero, Luis
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Language:English
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Summary:Novel data-acquisition technologies have revolutionized the study of natural systems, allowing the massive collection of information in situ and remotely. Merging these technologies improves the understanding of complex hydrological interactions, such as those of wetland–aquifer systems, and facilitates their conservation and management. This paper presents the combination of UAV technology with water level dataloggers for the study of a coastal temporary wetland linked to an underlying sandy aquifer and influenced by the tidal regime. Wetland morphology was defined using UAV imagery and SfM algorithms during the dry period. The DTM (6.9 cm resolution) was used to generate a flood model, which was subsequently validated with an orthophoto from a wet period. This information was combined with water stage records at 10-min intervals from a network of dataloggers to infer the water balance of the wetland and the transfers to the aquifer. Inflows into the pond were around 6200 m3 (40% direct precipitation over the pond, 60% surface runoff). Outputs equalled the inputs (41% direct evaporation from water surface, 59% transfers into the aquifer). The proposed methodology has demonstrated its suitability to unravel complex wetland–aquifer interactions and to provide reliable estimations of the elements of the water balance.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14246185