Groundwater ages in coastal aquifers |
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| Institution: | 1. Water Resources and Environmental Geology, University of Almería, Spain;2. Department of Geology, FCFM, University of Chile, Chile;3. Andean Geothermal Center of Excellence (CEGA), Fondap-Conicyt, Chile;1. Department of Earth Sciences, “Sapienza” University, Roma, Italy;2. Department of Physics and Earth Sciences, University of Ferrara, Ferrara, Italy;1. Department of Civil Engineering, Sharif University of Technology, PO Box 11155-9313, Tehran, Iran;2. National Centre for Groundwater Research and Training and School of the Environment, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia;1. Department of Earth Sciences, “Sapienza” University, Rome, Italy;2. Department of Physics and Earth Sciences, University of Ferrara, Ferrara, Italy;3. CSIRO Land and Water, Private Bag No. 5, Wembley, WA 6913, Australia;4. School of Earth and Environment, University of Western Australia, 35 Stirling Hwy, Nedlands, WA 6009, Australia;5. National Centre for Groundwater Research and Training (NCGRT), Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia;1. Civil Engineering Faculty, K.N. Toosi University of Technology, P.O. Box 15875-4416, Tehran, Iran;2. National Centre for Groundwater Research and Training, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia;3. School of the Environment, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia;4. Civil Engineering Department, The State Polytechnic of Ujung Pandang, P.O. Box 90245, South Sulawesi, Indonesia;1. College of Science and Engineering, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia;2. National Centre for Groundwater Research and Training, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia |
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| Abstract: | The interpretation of groundwater ages in coastal aquifers requires an improved understanding of relationships between age distributions and the processes accompanying dispersive, density-dependent flow and transport. This study uses numerical modeling to examine the influence of mixing and a selection of other hydrogeological factors on steady-state age distributions in coastal aquifers. Three methods of age estimation are compared: the piston flow age, the direct age, and the tracer-based age. These are applied to various forms of the Henry problem, as well as to three variants of a larger, hypothetical coastal aquifer. Circulation of water within the seawater wedge results in markedly higher ages in the transition zone than in the underlying saltwater or overlying freshwater. Piston flow ages show a sharp increase where the freshwater and saltwater systems meet, whereas direct- and tracer-based simulations result in a smoother age distribution, as expected. Greater degrees of mixing result in larger differences between piston flow and direct or tracer-based ages, and bring about lower ages in the saltwater wedge. Tracer-based ages are preferred over direct- and piston flow ages for comparison with field data, especially in cases with wide transition zones. Despite the relatively simple conditions used for the simulations, complex age distributions with depth were obtained. Hence, the assessment of ages in field cases will be difficult, particularly where accurate ages in the transition zone are sought. |
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| Keywords: | Coastal aquifer Groundwater age Numerical model Seawater intrusion |
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