Zobrazeno 1 - 10
of 3 499
pro vyhledávání: '"A. Guadagnini"'
Publikováno v:
Hydrology and Earth System Sciences, Vol 28, Pp 2661-2682 (2024)
We introduce a comprehensive and robust theoretical framework and operational workflow that can be employed to enhance our understanding, modeling and management capability of complex heterogeneous large-scale groundwater systems. Our framework encap
Externí odkaz:
https://doaj.org/article/76795540a2f64ec795da7e509f6690e2
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 16, Pp n/a-n/a (2024)
Abstract We present an innovative approach that combines a unique real‐time data set documenting absolute dissolution rates of a calcite crystal with an original reactive transport model tailored to the analysis of the dynamics of nano‐scale mine
Externí odkaz:
https://doaj.org/article/24924ca156c34acba154ece97b6faaf1
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 5905-5915 (2021)
Our study investigates interplays between dissolution, precipitation, and transport processes taking place across randomly heterogeneous conductivity domains and the ensuing spatial distribution of preferential pathways. We do so by relying on a coll
Externí odkaz:
https://doaj.org/article/553ee3ffc99a41fa9ed38531102d9c32
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 3539-3553 (2021)
This work explores a probabilistic modeling workflow and its implementation targeting CO2 generation rate and CO2 source location by the occurrence of carbonate–clay reactions (CCRs) in three-dimensional realistic sedimentary basins. We ground our
Externí odkaz:
https://doaj.org/article/0fcffee296674b05a64a3294d5908186
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 1689-1709 (2021)
We employ an approach based on the ensemble Kalman filter coupled with stochastic moment equations (MEs-EnKF) of groundwater flow to explore the dependence of conductivity estimates on the type of available information about hydraulic heads in a thre
Externí odkaz:
https://doaj.org/article/e750bdf776144aa6b9b068ea35d1721d
We provide an approach enabling one to employ physics-informed neural networks (PINNs) for uncertainty quantification. Our approach is applicable to systems where observations are scarce (or even lacking), these being typical situations associated wi
Externí odkaz:
http://arxiv.org/abs/2408.04690
Providing a sound appraisal of the nature of the relationship between flow $(Q)$ and pressure drop $(\Delta P)$ for porous media is a long-standing fundamental research challenge. A wide variety of environmental, societal and industrial issues, rangi
Externí odkaz:
http://arxiv.org/abs/2406.03246
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 3097-3109 (2020)
We employ elements of information theory to quantify (i) the information content related to data collected at given measurement scales within the same porous medium domain and (ii) the relationships among information contents of datasets associated w
Externí odkaz:
https://doaj.org/article/e1cde8230e844843a4534863361ecc04
Publikováno v:
Hydrology and Earth System Sciences, Vol 21, Pp 6219-6234 (2017)
We propose new metrics to assist global sensitivity analysis, GSA, of hydrological and Earth systems. Our approach allows assessing the impact of uncertain parameters on main features of the probability density function, pdf, of a target model out
Externí odkaz:
https://doaj.org/article/048507fac63f4df78dbb13cfe5135252
Publikováno v:
Hydrology and Earth System Sciences, Vol 19, Iss 2, Pp 729-745 (2015)
We analyze scale-dependent statistics of correlated random hydrogeological variables and their extremes using neutron porosity data from six deep boreholes, in three diverse depositional environments, as example. We show that key statistics of porosi
Externí odkaz:
https://doaj.org/article/fbe12f425559438499a98fb65ea34643