  Groundwater flow model accuracy is often limited by the uncertainty in model
parameters that characterize aquifer properties and aquifer recharge. Aquifer
properties such as hydraulic conductivity can have an uncertainty spanning
orders of magnitude. Meanwhile, parameters used to configure model boundary
conditions can introduce additional uncertainty. In this study, the Morris
Method sensitivity analysis is performed on multiple quantities of interest to
assess the sensitivity of a steady-state groundwater flow model to uncertain
input parameters. The Morris Method determines which of these parameters are
less influential on model outputs. Uninfluential parameters can be set constant
during subsequent parameter optimization to reduce computational expense.
Combining multiple quantities of interest (e.g., RMSE, groundwater fluxes) when
performing both the Morris Method and parameter optimization offers a more
complete assessment of groundwater models, providing a more reliable and
physically consistent estimate of uncertain parameters. The parameter
optimization procedure also provides us an estimate of the residual uncertainty
in the parameter values, resulting in a more complete estimate of the remaining
uncertainty. By employing such techniques, the current study was able to
estimate the aquifer hydraulic conductivity and recharge rate due to rice field
irrigation in a groundwater basin in Northern Italy, revealing that a
significant proportion of surficial aquifer recharge (approximately 81-94%)
during the later summer is due to the flood irrigation practices applied to
these fields.
