Using Remote Sensing to Assess the Vegetation Cover of a Protected Salt Marsh Subjected to Artificial Recharge and Groundwater Abstractions during the Period 1925–2022 (Alicante, SE Spain)

José Marín Salcedo, Iván Alhama, Manuel Alcaraz, José Álvarez-Rogel and José Antonio Jiménez-Valera ()
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José Marín Salcedo: Mining and Civil Engineering Department, Technical University of Cartagena, Paseo de Alfonso XIII 52, 30203 Cartagena, Spain
Iván Alhama: Mining and Civil Engineering Department, Technical University of Cartagena, Paseo de Alfonso XIII 52, 30203 Cartagena, Spain
Manuel Alcaraz: Mining and Civil Engineering Department, Technical University of Cartagena, Paseo de Alfonso XIII 52, 30203 Cartagena, Spain
José Álvarez-Rogel: Department of Agricultural Engineering of the E.T.S.I.A., Soil Ecology and Biotechnology Unit of the Institute of Plant Biotechnology, Technical University of Cartagena, 30203 Cartagena, Spain
José Antonio Jiménez-Valera: Mining and Civil Engineering Department, Technical University of Cartagena, Paseo de Alfonso XIII 52, 30203 Cartagena, Spain

Sustainability, 2024, vol. 16, issue 3, 1-21

Abstract: The Agua Amarga salt marsh has been subjected to artificial seawater recharge on its surface during the period 1925–1969 for industrial purposes (saltwork activity) and from 2008 to present to compensate for coastal groundwater abstraction to supply Alicante desalination plants. This groundwater abstraction has caused piezometric depletion in the coastal aquifer connected to the protected salt marsh. The seawater recharge program also involved vegetation monitoring to control the impact on the salt marsh ecosystem, allowing data to be collected about the halophyte vegetation species growing in the salt marsh ( Arthrocnemum macrostachyum , Sarcocornia fruticosa , and Ruppia maritima , among others) from spring and autumn field surveys. In this work, vegetation development is assessed with remote sensing for the period 1929–2022 using images with visible and near-infrared spectral resolution. Different spectral indices (NDVI, BI, and NDWI) and classification algorithms (random forest) are used to calculate the vegetation cover. Field data are employed to evaluate the protocols and compare the results, showing a 46% decrease caused by the salt works and a 50% increase as a result of natural evolution and artificial recharge. The spread of Phragmites australis is also addressed by comparing LiDAR data with field monitoring, showing an increase of 12% during the period 2005–2023. The advantages and complementarity of field monitoring and remote sensing information are explained.

Keywords: coastal aquifer; artificial recharge; vegetation cover; remote sensing; GIS; reedbed (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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