Assessing environmental risks through fuzzy parameterized probabilistic analysis

Abstract

A fuzzy parameterized probabilistic analysis (FPPA) method was developed in this study to assess risks associated with environmental pollution-control problems. FPPA integrated environmental transport modeling, fuzzy transformation, probabilistic risk assessment, fuzzy risk quantification into a general risk assessment framework, and was capable of handling uncertainties expressed as fuzzy-parameterized stochastic distributions. The proposed method was applied to two environmental pollution problems, with one being about the point-source pollution in a river system with uncertain water quality parameters and the other being concerned with groundwater contaminant plume from waste landfill site with poorly known contaminant physical properties. The study results indicated that the complex uncertain features had significant impacts on modeling and risk-assessment outputs; the degree of impacts of modeling parameters were highly dependent on the level of imprecision of these parameters. The results also implied that FPPA was capable of addressing vagueness or imprecision associated with probabilistic risk evaluation, and help generate risk outputs that could be elucidated under different possibilistic levels. The proposed method could be used by environmental managers to evaluate trade-offs involving risks and costs, as well as identify management solutions that sufficiently hedge against dual uncertainties.

Multivariate flood risk analysis for Wei River

“…Owing to the development of copula methods, amounts of research efforts have been proposed for multivariate hydrologic risk analysis (Zhang and Singh 2006;Xu et al 2010;Fan et al 2012Fan et al , 2015aZhang et al 2013, Cantet andArnaud 2014;Sraj et al 2014;Kong et al 2015;Ming et al 2015;Saad et al 2015). The main advantage of copula functions over classical multivariate hydrologic modelling is that the marginal distributions and multivariate dependence modelling can be determined in two separate processes, giving additional flexibility to the practitioner in choosing different marginal and joint probability functions (Zhang and Singh 2006;Genest and Favre 2007;Qin 2012;Sraj et al 2014;Fan et al 2015b). …”

An Integrated Simulation, Inference and Optimization Approach for Groundwater Remediation with Two-Stage Health-Risk Assessment

“…For example, Qin (2012) developed a fuzzy parameterized probabilistic analysis (FPPA) method to assess risks associated with environmental pollution-control problems. The results indicated that complex uncertain features had significant impacts on modeling and risk-assessment outputs [25]. Li et al (2015) presented an integrated optimal groundwater remediation design approach that incorporated numerical simulation, health-risk assessment, uncertainty analysis, and non-linear optimization within a general framework [3].…”

An Inexact Credibility Chance-Constrained Integer Programming for Greenhouse Gas Mitigation Management in Regional Electric Power System under Uncertainty

“…To reflect such uncertainties in EPS, inexact system-analysis techniques can be used (Gong et al, 2016;Lin et al, 2016;Tong et al, 2016). Examples are interval parameter programming (IPP) (Huang et al, 1992(Huang et al, , 2011Grosfeld-Nir and Tishler, 1993;Lin and Huang, 2008;Li et al, , 2013, stochastic mathematical programming (SMP) (Grosfeld-Nir et al, 1993;Darby-Dowman et al, 2000;Xie et al, 2010;Pousinho et al, 2011;Svensson et al, 2011;Qin, 2012;Wang et al, 2012) and fuzzy linear programming (FLP) (Huang et al, 1993;Huang et al, 1996;Yin et al, 1999;Chanas and Zielinski, 2000;Li et al, 2007;Muela et al, 2007;Lu et al, 2008).…”