On the inclusion of forest exposure pathways into a stylized lake-farm scenario in a geological repository safety analysis

Pohjola, Jari; Turunen, Jari; Lipping, Tarmo; Ikonen, A.T.K.

doi:10.1016/j.jenvrad.2022.107019

Cited by 3 publications

(1 citation statement)

References 30 publications

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“… Sr is not transported as easily as Cs, but plants growing in contaminated soil can take up small doses of both Sr and Cs 8 , 9 . In numerical simulations of groundwater, such as in 10 , 11 , Sr and Cs mainly decay in the transportation phase, while part of the Sr dose will stay in deep sediments and a fraction of both radionuclides could contaminate plants and animals. For example, Cs tends to be absorbed by mushrooms, while Sr tends to be spread to agricultural vegetables 11 .…”

Section: Introductionmentioning

confidence: 99%

Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

Turunen

Lipping

2023

Sci Rep

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In this paper we compare the outputs of neural network metamodels with numerical solutions of differential equation models in modeling cesium-137 transportation in sand. Convolutional neural networks (CNNs) were trained with differential equation simulation results. Training sets of various sizes (from 5120 to 163,840) were used. First order and total order Sobol methods were applied to both models in order to test the feasibility of neural network metamodels for sensitivity analysis of a radionuclide transport model. Convolutional neural networks were found to be capable of emulating the differential equation models with high accuracy when the training set size was 40,960 or higher. Neural network metamodels also gave similar results compared with the numerical solutions of the partial differential equation model in sensitivity analysis.

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Section: Introductionmentioning

confidence: 99%

Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

Turunen

Lipping

2023

Sci Rep

Self Cite

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High-risk nuclide screening and parameter sensitivity analysis based on numerical simulation and machine learning

Zhang,

Zhang

et al. 2024

Journal of Hazardous Materials

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Dynamics of Forest Vegetation in an Urban Agglomeration Based on Landsat Remote Sensing Data for the Period 1990–2022: A Case Study

Yankovich

Yankovich²,

Baranovskiy

2023

Remote Sensing

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In recent years, the vegetation cover in urban agglomerations has been changing very rapidly due to technogenic influence. Satellite images play a huge role in studying the dynamics of forest vegetation. Special programs are used to process satellite images. The purpose of the study is to analyze forest vegetation within the territory of the Tomsk agglomeration based on Landsat remote sensing data for the period from 1990 to 2022. The novelty of the study is explained by the development of a unique program code for the analysis of Landsat satellite data on the previously unexplored territory of the Tomsk agglomeration with the prospect of moving to the scale of the entire state in the future. In this study, the authors present an algorithm implemented in Python to quantify the change in the area of vegetation in an urban agglomeration using Landsat multispectral data. The tool allows you to read space images, calculate spectral indices (NDVI, UI, NDWI), and perform statistical processing of interpretation results. The created tool was applied to study the dynamics of vegetation within the Tomsk urban agglomeration during the period 1990–2022. Key findings and conclusions: (1) The non-forest areas increased from 1990 to 1999 and from 2013 to 2022. It is very likely that this is due to the deterioration of the standard of living in the country during these periods. The first time interval corresponds to the post-Soviet period and the devastation in the economy in the 1990s. The second period corresponds to the implementation and strengthening of sanctions pressure on the Russian Federation. (2) The area of territories inhabited by people has been steadily falling since 1990. This is due to the destruction of collective agriculture in the Russian Federation and the outflow of the population from the surrounding rural settlements to Tomsk and Seversk.

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On the inclusion of forest exposure pathways into a stylized lake-farm scenario in a geological repository safety analysis

Cited by 3 publications

References 30 publications

Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

High-risk nuclide screening and parameter sensitivity analysis based on numerical simulation and machine learning

Dynamics of Forest Vegetation in an Urban Agglomeration Based on Landsat Remote Sensing Data for the Period 1990–2022: A Case Study

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