Abstract
Patterns of δ18O and
δ2H in Earth’s precipitation provide essential
scientific data for use in hydrological, climatological, ecological and
forensic research. Insufficient global spatial data coverage promulgated
the use of gridded datasets employing geostatistical techniques
(isoscapes) for spatiotemporally coherent isotope predictions.
Cluster-based isoscape regionalization combines the advantages of local
or regional prediction calibrations into a global framework. Here we
present a revision of a Regionalized Cluster-Based Water Isotope
Prediction model (RCWIP2) incorporating new isotope data having
extensive spatial coverage and a wider array of predictor variables
combined with high-resolution gridded climatic data. We introduced
coupling of δ18O and
δ2H (e.g. d-excess constrained) in the
model predictions to prevent runaway isoscapes when each isotope is
modelled separately. We validated RCWIP2 isoscape performance by
cross-checking observed versus modelled d-excess values. We
improved model error quantification by adopting full uncertainty
propagation in all calculations. RCWIP2 improved the RMSE over previous
isoscape models by ca. 0.6 ‰ for δ18O and 5 ‰
for δ2H with an uncertainty <1.0 ‰
for δ18O and <8 ‰ for
δ2H for most regions of the world. The improved
RCWIP2 isoscape grids and maps (season, monthly, annual, regional) are
available for download at https://isotopehydrologynetwork.iaea.org.