  Proximal gamma-ray spectroscopy recently emerged as a promising technique for
non-stop monitoring of soil water content with possible applications in the
field of precision farming. The potentialities of the method are investigated
by means of Monte Carlo simulations applied to the reconstruction of gamma-ray
spectra collected by a NaI scintillation detector permanently installed at an
agricultural experimental site. A two steps simulation strategy based on a
geometrical translational invariance is developed. The strengths of this
approach are the reduction of computational time with respect to a direct
source-detector simulation, the reconstruction of $^{40}K$, $^{232}Th$ and
$^{238}U$ fundamental spectra, the customization in relation to different
experimental scenarios and the investigation of effects due to individual
variables for sensitivity studies. The reliability of the simulation is
effectively validated against an experimental measurement with known soil water
content and radionuclides abundances. The relation between soil water content
and gamma signal is theoretically derived and applied to a Monte Carlo
synthetic calibration performed with the specific soil composition of the
experimental site. Ready to use general formulae and simulated coefficients for
the estimation of soil water content are also provided adopting standard soil
compositions. Linear regressions between input and output soil water contents,
inferred from simulated $^{40}K$ and $^{208}Tl$ gamma signals, provide
excellent results demonstrating the capability of the proposed method in
estimating soil water content with an average uncertainty <1%.
