Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad; Simmons, Craig T.

doi:10.1016/j.jhydrol.2014.11.020

Cited by 104 publications

(48 citation statements)

References 89 publications

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“…Such situations are common in multi-disciplinary modeling applications that link multiple, complex components [78]. Therefore, a research frontier in designing useful DSS for water-resource managers involves the rigorous assessment of uncertainty associated with each dataset and model component, coupled with state-of-the-art computational techniques for propagating uncertainty through complex hierarchical systems (e.g., [79,80]). …”

Section: Challenges and Opportunitiesmentioning

confidence: 99%

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

Cartwright

Caldwell

Nebiker

et al. 2017

Water

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This paper presents a conceptual framework to operationalize flow-ecology relationships into decision-support systems of practical use to water-resource managers, who are commonly tasked with balancing multiple competing socioeconomic and environmental priorities. We illustrate this framework with a case study, whereby fish community responses to various water-management scenarios were predicted in a partially regulated river system at a local watershed scale. This case study simulates management scenarios based on interactive effects of dam operation protocols, withdrawals for municipal water supply, effluent discharges from wastewater treatment, and inter-basin water transfers. Modeled streamflow was integrated with flow-ecology relationships relating hydrologic departure from reference conditions to fish species richness, stratified by trophic, reproductive, and habitat characteristics. Adding a hypothetical new water-withdrawal site was predicted to increase the frequency of low-flow conditions with adverse effects for several fish groups. Imposition of new reservoir release requirements was predicted to enhance flow and fish species richness immediately downstream of the reservoir, but these effects were dissipated further downstream. The framework presented here can be used to translate flow-ecology relationships into evidence-based management by developing decision-support systems for conservation of riverine biodiversity while optimizing water availability for human use.

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Section: Challenges and Opportunitiesmentioning

confidence: 99%

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

Cartwright

Caldwell

Nebiker

et al. 2017

Water

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“…Since PCE reduces the computational expense of uncertainty propagation, it has been widely applied in complex environmental problems including water quality modeling (Moreau et al 2013), large scale socio-hydrologic modeling coupled with Agent-Based Models (Hu et al 2015), groundwater hydrogeological modeling (Deman et al 2016) and in other dynamic modeling examples such as crop modeling (Lamboni et al 2009) and seawater intrusion (Rajabi et al 2015). Moreover, an extensive review of basic principles and applications of PCE in computational fluid dynamics was conducted by Najm (2009).…”

Section: Sleuth For Urban Growth and Land-use Change Modelingmentioning

confidence: 99%

A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model

Şalap-Ayça

Jankowski

Clarke

et al. 2017

International Journal of Geographical Information Science

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The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models. ARTICLE HISTORY

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“…Some existing methods, namely, Monte Carlo simulation (MCS) [11][12][13], Taylor expansion-based method [14,15], reliability-based method [16][17][18], polynomial chaos expansion (PCE) [19][20][21] and numerical integration-based method [1,22,23] have already contributed to UP. The MCS method was first used in simulating a neutron chain reaction.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty propagation analysis by an extended sparse grid technique

Jia

Jiang

et al. 2018

Front. Mech. Eng.

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In this paper, an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle, aiming at improving the solving accuracy of the high-order moments and hence the fitting accuracy of the probability density function (PDF) of the system response. The proposed method incorporates the extended Gauss integration into the uncertainty propagation analysis. Moreover, assisted by the Rosenblatt transformation, the various types of extended integration points are transformed into the extended Gauss-Hermite integration points, which makes the method suitable for any type of continuous distribution. Subsequently, within the sparse grid numerical integration framework, the statistical moments of the system response are obtained based on the transformed points. Furthermore, based on the maximum entropy principle, the obtained first four-order statistical moments are used to fit the PDF of the system response. Finally, three numerical examples are investigated to demonstrate the effectiveness of the proposed method, which includes two mathematical problems with explicit expressions and an engineering application with a black-box model.

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Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations

Cited by 104 publications

References 89 publications

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model

Uncertainty propagation analysis by an extended sparse grid technique

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