Variance Reduction Analysis

Rouhani, Shahrokh

doi:10.1029/wr021i006p00837

Cited by 118 publications

(68 citation statements)

References 24 publications

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“…Examples can be found in the work of Bras and Rodríguez-Iturbe (1976), Rouhani (1985), Loaiciga (1989), Rouhani and Hall (1988), Pardo-Igúzquiza (1998), van Groenigen et al (1999), van Groenigen and Stein (1998), and Nunes et al (2004a, b).…”

Section: Introductionmentioning

confidence: 99%

Optimal estuarine sediment monitoring network design with simulated annealing

Nunes

Caeiro²,

Cunha

et al. 2006

Journal of Environmental Management

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An objective function based on geostatistical variance reduction, constrained to the reproduction of the probability distribution functions of selected physical and chemical sediment variables, is applied to the selection of the best set of compliance monitoring stations in the Sado river estuary in Portugal. These stations were to be selected from a large set of sampling stations from a prior field campaign. Simulated annealing was chosen to solve the optimisation function model. Both the combinatorial problem structure and the resulting candidate sediment monitoring networks are discussed, and the optimal dimension and spatial distribution are proposed. An optimal network of sixty stations was obtained from an original 153-station sampling campaign. q

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Section: Introductionmentioning

confidence: 99%

Optimal estuarine sediment monitoring network design with simulated annealing

Nunes

Caeiro²,

Cunha

et al. 2006

Journal of Environmental Management

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“…Surrogate objectives are substitutes for ultimate objectives, and are used in many cases to bypass the difficulties posed by the formulation of network design problems in terms of ultimate objectives. Examples of surrogate objectives are the minimization of statistical parameters such as the variance of contaminant concentrations (Rouhani, 1985) or the minimization of the maximum absolute deviation between actual and predicted variables (Loaiciga and Church, 1990).…”

Section: Objective Functionsmentioning

confidence: 99%

Long-term Monitoring Plan for the Central Nevada Test Area

Hassan¹

2003

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EXECUTIVE SUMMARYThe groundwater flow and transport model of the Faultless underground nuclear test conducted at the Central Nevada Test Area (CNTA) was accepted by the state regulator and the environmental remediation efforts at the site have progressed to the stages of model validation and long-term monitoring design. This report discusses the long-term monitoring strategy developed for CNTA. Subsurface monitoring is an expensive and time-consuming process, and the design approach should be based on a solid foundation. As such, a thorough literature review of monitoring network design is first presented. Monitoring well networks can be designed for a number of objectives including aquifer characterization, parameter estimation, compliance monitoring, detection monitoring, ambient monitoring, and research monitoring, to name a few. Design methodologies also range from simple hydrogeologic intuition-based tools to sophisticated statistical-and optimization-based tools.When designing the long-term monitoring well network for CNTA, a number of issues are carefully considered. These are the uncertainty associated with the subsurface environment and its implication for monitoring design, the cost associated with monitoring well installation and operation, the design criteria that should be used to select well locations, and the potential conflict between different objectives such as early detection versus impracticality of placing wells in the vicinity of the test cavity. Given these considerations and the literature review of monitoring design studies, a multi-staged approach for development of the long-term monitoring well network for CNTA is proposed. This multi-staged approach will proceed in parallel with the validation efforts for the groundwater flow and transport model of CNTA. Two main stages are identified as necessary for the development of the final long-term monitoring well network for the site.The first stage is to use hydrogeologic expertise combined with model simulations and probability based approaches to select the first set of monitoring wells that will serve two purposes. The first is to place the wells in areas likely to encounter migration pathways thereby enhancing the probability of detecting radionuclide migration in the long run. The second objective is crucial in the short run and is aimed at using this set of wells to collect validation data for the model. The selection criteria should thus balance these two objectives. Based on the results of the validation process that progresses concurrently with the first monitoring stage, either more wells will be needed in this first stage or the second stage will be initiated. The second monitoring design stage will be based on an optimum design methodology that uses a suitable statistical approach, combined with an optimization approach, to augment the initial set of wells and develop the final long-term monitoring network.The first-stage probabilistic analysis conducted using the CNTA model indicates that the likelihood of migration away from th...

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“…The data worth is evaluated by comparing the reduction of the risk of failure and the cost of data sampling. Rouhani [1985] presented an indirect approach to incorporate the economical implications of FMD into the groundwater management model, where a new methodology was proposed that determines the optimal number of measurements and their locations based on a variance reduction analysis. His analysis was based on the concept that when the number of measurements increases, both the variance of the state variable and the marginal economic gain decrease; the selection of the number and the locations of new measurements were a compromise between modeling purposes and economical budget.…”

Section: Literature Reviewmentioning

confidence: 99%

A methodology to determine optimal transmissivity measurement locations in groundwater quality management models with scarce field information

Criminisi¹,

Tucciarelli²,

Karatzas³

1997

Water Resources Research

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Abstract.A new criterion to determine transmissivity measurement location for groundwater quality management models is proposed. The transmissivity is represented as a random field with known mean and covariance function, conditioned to existing measurements values. The criterion is the minimization of the coefficient of variation of the optimal remediation cost distribution. This distribution is computed numerically by means of Monte Carlo simulations in which each optimal remediation cost is evaluated by solving a deterministic management problem, where the transmissivity is a single realization of the random field. The coefficient of variation is equivalent to the relative error in the prediction of the optimal cost and is shown to be invariant with respect to the actual (unknown) measurement value according to some limiting conditions. In the more general case the coefficient of variation of the optimal cost is less sensitive than the expected optimal cost to the actual measurement value. The proposed criterion becomes a useful tool to determine the "best" transmissivity measurement location when only few measurements have been performed.

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Variance Reduction Analysis

Cited by 118 publications

References 24 publications

Optimal estuarine sediment monitoring network design with simulated annealing

Optimal estuarine sediment monitoring network design with simulated annealing

Long-term Monitoring Plan for the Central Nevada Test Area

A methodology to determine optimal transmissivity measurement locations in groundwater quality management models with scarce field information

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