Summary and
Conclusion
Isotope tagging of ground level water vapor is very important to
understand hydrological processes in different geographical regions
having varied eco-hydrological, agro-climatic and water resource
situations.
There are limitations and constraints in obtaining reliable isotopic
signatures of ground level water vapor, related to infrastructure and
analytical capabilities for ground based or remotely sensed
observations. In this study a simple, cost efficient and novel
methodology is discussed in which ambient water vapor is collected by
liquid condensation on ice-cooled metallic surface, and using a
non-linear regression model true isotopic composition of ground level
water vapor is computed from measured isotopic composition of liquid
condensate.
The non-linear regression model in this study is based on a known
kinetic fractionation process during solid and liquid condensation under
supersaturated environment, discussed respectively by Jouzel and
Merlivat (1984) and R. D. Deshpande et al. (2013). This non-linear
regression model is necessary because the physical parameters involved
during kinetic fractionation, namely, effective degree of
supersaturation, actual condensation temperature and diffusivity
coefficients for heavier and lighter isotopologues cannot be determined
precisely for the liquid condensation. Therefore, without the proposed
non-linear regression model it is not possible to correctly estimate the
true isotopic composition of ambient water vapor from that of liquid
condensate, using the known theory of kinetic fractionation under
supersaturated environment.
The non-linear regression model can estimate the isotopic composition of
ground level water vapor far more accurately (±1.8308‰ for
δ18O at Ahmedabad) compared to the best available
remotely sensed data. Moreover, the method of non-linear regression is
successful for samples collected from three different climate zones
assuring that it is geographically invariant. The ground level water
vapor sampling method of liquid condensation on ice-cooled surface can
be easily adopted anywhere and at a very low cost. This paves the way
for a cheap and yet reliable method of sampling ground level water vapor
which can be extensively carried out at any location with limited
infrastructure and resources. The data obtained can be further used to
calibrate and strengthen the remotely sensed data as well as to verify
the input and output from isotope enabled atmospheric general
circulation models. This method can be particularly useful for
developing nations with limited infrastructure and resources for
fundamental research.