Quantitative microbial risk assessment of a non-membrane based indirect potable water reuse system using Bayesian networks

Zhiteneva, V.; Carvajal, Gustavo; Shehata, Omar M.; Hübner, Uwe; Drewes, Jörg E.

doi:10.1016/j.scitotenv.2021.146462

Cited by 15 publications

(4 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, economic evaluation and public acceptance will be considered to ensure the wide distribution of this technology in the Middle East and North African countries (arid and semi-arid regions). Electro-agric technology also proposes the mandatory treatment of industrial wastewater within the factories to decrease the burden of wastewater reuse that is currently accepted worldwide [82]. In addition, E-AT proposes the integration of water, soil, organic matter, plants, and other factors to ensure the sustainability of such processes.…”

Section: Electro-agric Technology (E-at)mentioning

confidence: 99%

A Critical Review of Innovations and Perspectives for Providing Adequate Water for Sustainable Irrigation

Abou-Shady,

Siddique,

2023

Water

View full text Add to dashboard Cite

Global climatic change intensifies the water crisis, particularly in arid and semi-arid regions. In this regard, the provision of enough water for irrigation is a serious dilemma because the agricultural sector consumes the largest amount of water (70% withdrawal and 90% consumption). In this review, we have summarized recent innovations that have emerged as unconventional techniques to supply adequate water for irrigation purposes. We present the principles and basics of seven approaches: the Sahara Forest Project (SFP), water extraction from the air (WEA), aquifer recharge, the treatment of marginal water using a magnetic field, desalination and wastewater treatment (DWT), electro-agric technology (E-AT), and the Toshka Project. The SFP is currently being utilized in Aqaba, Jordan, and DWT is considered a common practice worldwide, whereas some of these innovations are still under investigation to ensure their feasibility for large-scale applications, such as E-AT. The Toshka Project is considered a wonderful idea that utilizes the water stored behind the High Dam in Lake Nasser, Egypt. Several approaches have been adopted to reduce the amount of water being used for irrigation, as the current amount of freshwater is insufficient for the requirements of increased agricultural consumption, particularly in hot, arid, and semi-arid regions.

show abstract

Section: Electro-agric Technology (E-at)mentioning

confidence: 99%

A Critical Review of Innovations and Perspectives for Providing Adequate Water for Sustainable Irrigation

Abou-Shady,

Siddique,

2023

Water

View full text Add to dashboard Cite

show abstract

“…Bayesian optimization algorithm [37] (BOA) is an approximate approximation algorithm based on probability distribution, which uses an agent function to fit the relationship between tuning hyperparameters and model evaluation, establishes an initial set of candidate solutions, finds the next point that is likely to be the extreme value according to the points in the set, and adds that point to the set, repeats the steps until the iteration terminates, and the combination of hyperparameters that works best is obtained by the iteration results, and can therefore be seen mathematically as a globally optimal solution to an unknown objective function, and is mostly suitable for optimization of algorithms with a large number of tuning hyperparameters.…”

Section: Optimization Algorithms Boa Algorithmmentioning

confidence: 99%

A Rice Security Risk Assessment Method Based on the Fusion of Multiple Machine Learning Models

Wang

Zhang

et al. 2022

Agriculture

View full text Add to dashboard Cite

With the accelerated digital transformation, food security data is exponentially growing, making it difficult to process and analyze data as the primary challenge for food security risk regulation. The promotion of “big data + food” safety supervision can effectively reduce supervision costs and improve the efficiency of risk detection and response. In order to improve the utilization of testing data and achieve rapid risk assessment, this paper proposes a rice security risk assessment method based on the fusion of multiple machine learning models, and conducts experimental validation based on rice hazard detection data from 31 provinces in China excluding Hong Kong, Macao and Taiwan in 2018. The model comparison verifies that the risk assessment model shows better performance than other mainstream machine learning algorithms, and its evaluation accuracy is as high as 99.54%, which verifies that the model proposed in this paper is more stable and accurate, and can provide accurate and efficient decision-making basis for regulatory authorities.

show abstract

“…42 BNs can be applied to a wide range of application domains such as environmental modelling 43 and artificial intelligence, 44 and as mentioned above to quantitative microbial risk assessment (for a review, see Beaudequin et al (2015) 45 ), and water reuse and QMRA. 41,42,[46][47][48] While QMRAs are often constrained by the availability of required data (for example, in dose-response assessments), system models based on BNs are an effective framework that tackle the lack of data. As all data in the network contribute to the whole, accurate predictions can be made with incomplete data or a quite small sample size.…”

Section: Introductionmentioning

confidence: 99%

“…As all data in the network contribute to the whole, accurate predictions can be made with incomplete data or a quite small sample size. 48 BNs were also used for scenario assessment, 46 risk minimisation 36 and work with uncertainty and variability as a probabilistic tool. 41,49 One of the objectives of this paper is the combination of a general Bayesian network (GBN) and QMRA.…”

Section: Introductionmentioning

confidence: 99%

Monitoring the risk ofLegionellainfection using a general Bayesian network updated from temporal measurements in agricultural irrigation with reclaimed wastewater

Massiot

Courault

Jacob

et al. 2023

Environ. Sci.: Water Res. Technol.

View full text Add to dashboard Cite

show abstract

Quantitative microbial risk assessment of a non-membrane based indirect potable water reuse system using Bayesian networks

Cited by 15 publications

References 44 publications

A Critical Review of Innovations and Perspectives for Providing Adequate Water for Sustainable Irrigation

A Critical Review of Innovations and Perspectives for Providing Adequate Water for Sustainable Irrigation

A Rice Security Risk Assessment Method Based on the Fusion of Multiple Machine Learning Models

Monitoring the risk ofLegionellainfection using a general Bayesian network updated from temporal measurements in agricultural irrigation with reclaimed wastewater

Contact Info

Product

Resources

About