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Triple oxygen isotopes in Texas precipitation reveal variability in the nature and timing of secondary evaporation

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Abstract

Over the past decade, triple oxygen isotopes (Δʹ17O) have provided valuable hydroclimate insights, but their variability in tropical and subtropical regions remains poorly understood. This study examines δD, δ18O, d-excess, and Δʹ17O in monthly precipitation from 2021 to 2023 across four subtropical climate divisions in Texas: 1) humid marine prairie and marsh (Houston, southeast), 2) sub-humid mixed prairie, savanna, and woodland (San Antonio, south-central), 3) arid desert (Odessa, west), and 4) sub-humid mixed savanna and woodland (Jolly, north-central). Isotopic values range from δD: −86.5 to + 12.0 ‰, δ18O: −12.8 to + 0.2 ‰, d-excess: −2.9 to + 25.8 ‰, and Δʹ17O: −6 to + 44 per meg. We identify secondary evaporation as the dominant control on isotopic variability. HYSPLIT analysis reveals that in south-central and southeast Texas, secondary evaporation occurs locally, influenced by fluctuations in humidity (Houston) and seasonal temperature and wind speed variations (San Antonio). In contrast, west and north-central Texas (Odessa and Jolly) experience secondary evaporation during inland moisture transport from oceanic sources. Seasonal δD and δ18O differences were detected only at Odessa, with enriched values corresponding to Gulf of Mexico convection (warm season) and depleted values to frontal stratiform rain-producing systems from the Pacific (cold season). By evaluating multi-year temporal variability of Δ’17O in precipitation across a climate-diverse area, this study expands on an initial Δ’17O investigation of the continental US that was based on opportunistic sampling of tap waters and enhances our understanding of isotopic variability for future paleoclimate studies.

Original languageEnglish (US)
Article number134859
JournalJournal of Hydrology
Volume669
DOIs
StatePublished - Apr 2026

Bibliographical note

Publisher Copyright:
© 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Keywords

  • Climate
  • Hydrologic cycle
  • Mass-dependent fractionation
  • Meteoric water
  • Monthly precipitation
  • d-excess
  • ΔʹO

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