Quantitative decision making for a groundwater monitoring and subsurface contamination early warning network

Li, Huishu; Gu, Jianli; Hanif, Asma; Dhanasekar, Ashwin; Carlson, Kenneth

doi:10.1016/j.scitotenv.2019.05.121

Cited by 18 publications

(7 citation statements)

References 12 publications

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“…With the continuous development of my country's market economy, the steel industry has also been rapidly improved, the automation level of the entire industry has been continuously improved, and the high-speed and continuous characteristics of the industry are very prominent, and the importance of equipment operation safety has become increasingly prominent [1][2][3]. Based on the current background, it is urgent to strengthen the application of the rapid and accurate position determination technology of modern multimodal couplings to achieve precise positioning.…”

Section: Introductionmentioning

confidence: 99%

Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Tan

2021

Advances in Multimedia

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During the overhaul and maintenance of the transmission system of the modern rolling mill, a very common problem is the positioning of the motor and the reducer or speed increaser. The operation of the equipment and the service life of the equipment will be significantly affected by the accuracy of the multimodal coupling position determination. Therefore, precise positioning and rapid positioning must be achieved. This article intends to analyze how this type of equipment achieves rapid and accurate positioning and what factors will affect the location determination process.

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Section: Introductionmentioning

confidence: 99%

Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Tan

2021

Advances in Multimedia

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“…Typical statistical models, including multi-criteria decision analysis (MCDA), entropy theory, and principal component analysis (PCA), are involved in quantifying the monitor site selection and performance evaluation. In a recent study by Li, Gu, Hanif, Dhanasekar, and Carlson (2019), MCDA was applied to evaluate the geology, topology, and hydrology. Moreover, MCDA is capable to identify the existing wells and potential adverse effects of nearby oil and gas extraction operation.…”

Section: Groundwater Monitoringmentioning

confidence: 99%

Groundwater quality

Motlagh

Yang

Saba

2020

Water Environment Research

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Groundwater is a vital component of water supply for residential, industrial, and agricultural purposes. However, many groundwater basins are being used unsustainably and groundwater contamination is a growing water quality problem. Although anthropogenic activities and natural processes have been increasing the contamination in this valuable water resource, several remediation techniques have been developed in the last few decades to reduce these contamination levels. This review paper focuses on the recent studies developed on groundwater pollutions, remediation practices, and groundwater quality management.

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“…Information entropy is a measure of the uncertainty degree of a system . With the development of information theory, many different forms of information entropy have been derived, such as conditional entropy, Shannon entropy, and relative entropy, which are often used to measure sampling data worth. − Benefiting from the theoretical rigor and correctness of information entropy, researchers have used information entropy to optimize sampling strategies mainly focused on the design of groundwater monitoring networks. − This study aims to elaborate an information entropy-based site investigation method to optimize a detailed survey design for contaminated sites. Such a procedure is needed, especially for heavy metal sites since these are often large sites with relatively few soil samplings.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Soil Sampling with Information Entropy at Heavy-Metal Sites

et al. 2023

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Knowledge of the spatial distribution of heavy metals is indispensable for successful risk analysis of contaminated sites. The common practice is to obtain soil samples for spatial interpolation through site investigation, which generally involves preliminary and detailed surveys. In this study, we propose an information entropy-based site investigation (IESI) method in which an optimal design step is implemented to guide soil sampling at the detailed survey stage. Two types of information entropy (i.e., relative entropy and Shannon entropy) are used to design the optimal sampling strategy. The results show that, within the IESI method, relative entropy is superior to Shannon entropy in guiding soil sampling. Combined with ordinary kriging, the IESI method outperforms conventional surveys for hypothetical and actual heavy metal-contaminated sites as it can identify new polluted and clean areas. For quantitative comparisons, the IESI method coupled with ordinary kriging, logarithmic ordinary kriging, and universal kriging with linear and quadratic trends can improve the interpolation accuracy by 16–43% at the actual heavy metal-contaminated site. Upon further examination of the IESI method, informative sampling points are mainly distributed around the polluted areas identified by the preliminary survey with soil pollution probabilities between 0.75 and 0.95. This work provides an effective tool for delineating the spatial distribution and valuable insights into identifying encryption areas at heavy-metal sites.

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Quantitative decision making for a groundwater monitoring and subsurface contamination early warning network

Cited by 18 publications

References 12 publications

Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Groundwater quality

Optimizing Soil Sampling with Information Entropy at Heavy-Metal Sites

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