UAV-based land surface temperatures and vegetation indices explain and
predict spatial patterns of soil water isotopes in a tropical dry forest
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.