Combining noisy well data and expert knowledge in a Bayesian calibration of a flow model under uncertainties: an application to solute transport in the Ticino basin

Groundwater flow modeling is commonly used to calculate groundwater heads, estimate groundwater flow paths and travel times, and provide insights into solute transport processes within an aquifer. However, the values of input parameters that drive groundwater flow models are often highly uncertain due to subsurface heterogeneity and geologic complexity in combination with lack of measurements/unreliable measurements. This uncertainty affects the accuracy and reliability of model outputs. Therefore, parameters' uncertainty must be quantified before adopting the model as an engineering tool. In this study, we model the uncertain parameters as random variables and use a Bayesian inversion approach to obtain a posterior,data-informed, probability density function (pdf) for them: in particular, the likelihood function we consider takes into account both well measurements and our prior knowledge about the extent of the springs in the domain under study. To keep the modelistic and computational complexities under control, we assume Gaussianity of the posterior pdf of the parameters. To corroborate this assumption, we run an identifiability analysis of the model: we apply the inversion procedure to several sets of synthetic data polluted by increasing levels of noise, and we determine at which levels of noise we can effectively recover the "true value" of the parameters. We then move to real well data (coming from the Ticino River basin, in northern Italy, and spanning a month in summer 2014), and use the posterior pdf of the parameters as a starting point to perform an Uncertainty Quantification analysis on groundwater travel-time distributions.Comment: First submissio

Combining the Morris Method and Multiple Error Metrics to Assess Aquifer Characteristics and Recharge in the Lower Ticino Basin, in Italy

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.Comment: second submission after minor revision

Narrowband, mid-infrared, seeded optical parametric generator based on non-critical CdSiP2 pumped by 120-ps, single longitudinal mode 1,064 nm pulses

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Sub-nanosecond, 1-10 kHz, low-threshold, non-critical OPOs based on periodically poled KTP crystal pumped at 1,064 nm

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Diode-pumped Nd: BaY 2 F 8 picosecond laser mode-locked with carbon nanotube saturable absorbers

Picosecond pulse generation near 1-m wavelength has been achieved with a Nd: BaY 2 F 8 (Nd:BaYF) laser mode-locked using a single-walled carbon nanotube saturable absorber (SWCNT-SA). The laser was operated at its main 1049-nm transition, generating 8.5-ps pulses with Ϸ70-mW output power for Ϸ570-mW absorbed pump power. This is the first demonstration of cw mode-locking in the picosecond regime with Nd-doped crystals and SWCNT-SAs. The requirements on the SWCNT-SA for successful mode-locking in relatively narrowband neodymium lasers are reviewed and their implications are discussed

Diode-pumped solid state lasers: resonators for the 2000

Overview of laser resonators for solid-state (and fiber) lasers, operating in different regimes and power levels

Passive and self-Q-switching of phase-conjugation Nd:YAG laser oscillators

Self-Q-switching with stimulated Brillouin scattering by an intracavity liquid cell was achieved in a Nd:YAG laser. A numerical model was developed