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UAV-based land surface temperatures and vegetation indices explain and predict spatial patterns of soil water isotopes in a tropical dry forest
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  • Beyer Matthias,
  • Alberto Iraheta,
  • Malkin Gerchow,
  • Katrin Kühnhammer,
  • Ana Claudia Callau-Beyer,
  • Paul Koeniger,
  • David Dubbert,
  • Maren Dubbert,
  • Ricardo Sánchez-Murillo,
  • Christian Birkel
Beyer Matthias
Institute of Geoecology, Technische Universität Braunschweig

Corresponding Author:matthias.beyer@tu-bs.de

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Alberto Iraheta
Institute of Geoecology, Technische Universität Braunschweig
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Malkin Gerchow
Institute of Geoecology, Technische Universität Braunschweig
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Katrin Kühnhammer
Institute of Geoecology, Technische Universität Braunschweig
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Ana Claudia Callau-Beyer
Institute of Horticultural Production Systems, Leibniz Universität Hannover
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Paul Koeniger
BGR
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David Dubbert
Isotope Biogeochemistry and Gas Fluxes, Landscape Functioning (ZALF)
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Maren Dubbert
Isotope Biogeochemistry and Gas Fluxes, Landscape Functioning (ZALF)
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Ricardo Sánchez-Murillo
Department of Earth and Environmental Sciences, University of Texas at Arlington
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Christian Birkel
University of Costa Rica
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Abstract

The spatial variation of soil water isotopes (SWI) - representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques - has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between soil water content and isotope patterns with canopy status.
We carried out a spatial sampling of ten SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm to 5 m). Best relationships were used for generating soil water isoscapes for the entire study area.
Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R² of 0.65 for δ18O and 0.57 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU. Supporting spatial analyses of SWI with UAV-based approaches might be a future avenue for improving the spatial representation and credibility of such studies.