  Since the seventies, several reconstruction techniques have been proposed,
and are currently used, to extrapolate and quantify eruptive parameters from
sampled deposit datasets. Discrete numbers of tephra ground loadings or
stratigraphic records are usually processed to estimate source eruptive values.
Reconstruction techniques like Pyle, Power law and Weibull are adopted as
standard to quantify the erupted mass (or volume) whereas Voronoi for
reconstructing the granulometry. Reconstructed values can be affected by large
uncertainty due to complexities occurring within the atmospheric dispersion and
deposition of volcanic particles. Here we want to quantify the sensitivity of
reconstruction techniques, and to quantify how much estimated values of mass
and grain size differ from emitted and deposited ones. We adopted a numerical
approach simulating with a dispersal code a mild explosive event occurring at
Mt. Etna, with eruptive parameters similar to those estimated for eruptions
occurred in the last decade. Then we created a synthetic deposit by integrating
the mass on the ground computed by the model over the computational domain
(>50000 km2). Multiple samplings of the simulated deposit are used for
generating a large dataset of sampling tests afterwards processed with standard
reconstruction techniques. Results are then compared and evaluated through a
statistical analysis, based on 2000 sampling tests of 100 samplings points. On
average, all the used techniques underestimate deposited and emitted mass. A
similar analysis, carried on Voronoi results, shows that information on the
total grain size distribution is strongly deteriorated. Here we present a new
method allowing an estimate of the deficiency in deposited mass for each
simulated class. Finally a sensitivity study on eruptive parameters is
presented in order to generalize our results to a wider range of eruptive
conditions.
