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Stochastic model on the mobility of petroleum in the soils of the Ecuadorian Amazon
Marco Heredia 1 , Maria de Decker 2 , Valeria Villalta 3 , Mayra Vargas 3
1  Universidad Estatal Amazónica,Universidad Politécnica de Madrid
2  Universidad Estatal Amazónica,Johann Heinrich von Thünen-Institut
3  Universidad Estatal Amazónica

Published: 27 October 2017 by MDPI AG in Proceedings of MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition in MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition session MODEC-02: Workshop on Natural Products and Agro-Industrial Procesess in Amazon, UEA, Puyo, Ecuador, 2017
MDPI AG, 10.3390/mol2net-03-04634

The Ecuadorian Amazon has an area of ​​1,23 x 107 ha, due to its mega biodiversity and its distribution is classified as a hot spot in the world. The overlap in its territory by oil activities, protected areas, ancestral territories and intangible zones generates a series of environmental conflicts. The oil spills have generated negative impacts on the soil, plants and animals, promoting an increase in the quality of the soils in the region. The objective of this study was to evaluate the oil contamination process in soils of the Northern Region of the Ecuadorian Amazon. Netlogo 3D software version 5.2.1 was used to simulate the evolution during 24 hours of oil percolation. The simulation scenarios were recorded according to the porosity (%) of the soils of the Northern Region of the Ecuadorian Amazon. The temporal evolution of the occupation of the soil by the oil particles is conditioned by the variables: texture, dynamic pressure, volume, gravity, vegetation cover. The dynamics of oil percolation in the simulations is directly proportional to the existence of porous spaces in the Ecuadorian Amazonian soil. The understanding of this phenomenon allows to define strategies of prevention and to mitigate the potential risks for the ecosystems.

Keywords: contamination, evolution, model, percolation, soils, territories, Ecuadorian Amazon
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