Moment-based metrics for global sensitivity analysis of hydrological systems

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 output, y. These include the expected value of y, the spread around the mean and the degree of symmetry and tailedness of the pdf of y. Since reliable assessment of higher order statistical moments can be computationally demanding, we couple our GSA approach with a surrogate model, approximating the full model response at a reduced computational cost. Here, we consider the generalized Polynomial Chaos Expansion (gPCE), other model reduction techniques being fully compatible with our theoretical framework. We demonstrate our approach through three test cases, including an analytical benchmark, a simplified scenario mimicking pumping in a coastal aquifer, and a laboratory-scale conservative transport experiment. Our results allow ascertaining which parameters can impact some moments of the model output pdf while being uninfluential to others. We also investigate the error associated with the evaluation of our sensitivity metrics by replacing the original system model through a gPCE. Our results indicate that the construction of a surrogate model with increasing level of accuracy might be required depending on the statistical moment considered in the GSA. Our approach is fully compatible with (and can assist the development of) analysis techniques employed in the context of reduction of model complexity, model calibration, design of experiment, uncertainty quantification and risk assessment

Probabilistic assessment of seawater intrusion under multiple sources of uncertainty

Coastal aquifers are affected by seawater intrusion (SWI) on a worldwide scale. The Henry's problem has been often used as a benchmark to analyze this phenomenon. Here, we investigate the way an incomplete knowledge of the system properties impacts the assessment of global quantities (GQs) describing key characteristics of the saltwater wedge in the dispersive Henry's problem. We recast the problem in dimensionless form and consider four dimensionless quantities characterizing the SWI process, i.e., the gravity number, the permeability anisotropy ratio, and the transverse and longitudinal Peclet numbers. These quantities are affected by uncertainty due to the lack of exhaustive characterization of the subsurface. We rely on the Sobol indices to quantify the relative contribution of each of these uncertain terms to the total variance of each of the global descriptors considered. Such indices are evaluated upon representing the target GQs through a generalized Polynomial Chaos Expansion (gPCE) approximation. The latter also serves as a surrogate model of the global system behavior. It allows (a) computing and analyzing the joint and marginal probability density function (pdf) of each GQ in a Monte Carlo framework at an affordable computational cost, and (b) exploring the way the uncertainty associated with the prediction of these global descriptors can be reduced by conditioning of the joint pdf on available information. Corresponding analytical expressions of the marginal pdfs of the variables of interest are derived and analyzed. (C) 2014 Elsevier Ltd. All rights reserved

Probabilistic assessment of failure of infiltration structures under model and parametric uncertainty

We focus on the quantification of the probability of failure (PF) of an infiltration structure, of the kind that is typically employed for the implementation of low impact development strategies in urban settings. Our approach embeds various sources of uncertainty. These include (a) the mathematical models rendering key hydrological traits of the system and the ensuing model parametrization as well as (b) design variables related to the drainage structure. As such, we leverage on a rigorous multi-model Global Sensitivity Analysis framework. We consider a collection of commonly used alternative models to represent our knowledge about the conceptualization of the system functioning. Each model is characterized by a set of uncertain parameters. As an original aspect, the sensitivity metrics we consider are related to a single- and a multi-model context. The former provides information about the relative importance that model parameters conditional to the choice of a given model can have on PF. The latter yields the importance that the selection of a given model has on PF and enables one to consider at the same time all of the alternative models analyzed. We demonstrate our approach through an exemplary application focused on the preliminary design phase of infiltration structures serving a region in the northern part of Italy. Results stemming from a multi-model context suggest that the contribution arising from the adoption of a given model is key to the quantification of the degree of importance associated with each uncertain parameter.Project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of December 16, 2021, rectified by Decree n.3175 of December 18, 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Project code CN_00000033, Concession Decree No. 1034 of June 17, 2022 adopted by the Italian Ministry of University and Research, CUP D43C22001250001, Project title “National Biodiversity Future Center - NBFC”. Aronne Dell’Oca acknowledges funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie [Grant Agreement No. 895152, MixUQ].Peer reviewe

Solute dispersion for stable density-driven flow in randomly heterogeneous porous media

We present a theoretical investigation on the processes underpinning the reduced longitudinal spreading documented in stable variable density flows, as opposed to constant density settings, within heterogeneous porous media. We do so by decomposing velocity and pressure in terms of stationary and dynamic components. The former corresponds to the solution of the constant density flow problem, while the latter accounts for the effects induced by density variability. We focus on a stable flow configuration and analyze the longitudinal spread of saltwater injected from the bottom of a column formed by a heterogeneous porous medium initially fully saturated by freshwater. We adopt a perturbation expansion approach and derive the equations satisfied by section-averaged concentrations and their ensemble mean values. These formulations are respectively characterized by a single realization and an ensemble dispersive flux, which we determine through appropriate closure equations. The latter are solved via semi-analytical and numerical approaches. Our formulations and associated results enable us to discriminate the relative impact on the density-driven solute displacement of (a) covariance of the permeability of the porous medium, (b) cross-covariance between permeability and concentration, which is in turn linked to the coupling of flow and transport problems, and (c) cross-covariance between the dynamic and stationary velocities.MIUR (Italian ministry of Education, University and Research); CICYT (Project MEDISTRAES)24 month embargo; published online: 1 November 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Ecological indicators and bioindicator plant species for biomonitoring industrial pollution : eco-based environmental assessment

Industrial pollution remains a driving force to ecosystem alteration. Pollutants are released in the atmosphere interacting in turn with other components of earth system such as plant species. Despite the long-term exposition of vegetation cover to pollution is drastically devastating, less is known about the contribution of ecological indicators for its monitoring. The aims of this study are (i) to introduce the ecological indicators in assessing the cement dust impact on plant species and its biomonitoring and (ii) to screen new indicator species for phytoremediation studies. Floristic surveys were conducted in the cement plant closeness following quadrat method. Vegetation indicators such as total plant cover, perennial and annual species densities and diversity were assessed. Bioindicator species were identified using the bioaccumulation factor (BF) and translocation factor (TF). A decrease of perennial species richness and a decline of total vegetation cover by 7 times as well as a diversity decrease ranging from 2.99 to 2.31 were found pertinent indicators of land degradation in the industrial area. Annual species densities were significantly affected by cement pollution. Species like Lygeum spartum, Atractylis serratuloides and Gymnocarpos decander arise as indicators of heavy metals pollution. Pollution in the cement plant vicinity excluded sensitive species like Helianthemum kahiricum, Stipa tenassissima, Plantago coronopus. This study allowed the identification of indicator species of potential use in phytoremediation applications and emphasized the possibility of relaying on the vegetation indicators to assess the impact of cement pollution