Machine learning model as a tool for decision making in the Ariporo river basin.

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Mariana Alejandra Rodriguez
https://orcid.org/0000-0002-4480-3898
María Fernanda López Romero
https://orcid.org/0000-0001-6877-0480
Luisa María Tejada Henríquez
https://orcid.org/0000-0001-8728-4437
Gonzalo Alberto Forero Buitrago
https://orcid.org/0000-0002-9739-4741

Abstract

The Ariporo river basin is located in the eastern country, in the department of Casanare where there have been ecological disasters such as a high mortality of animals, an example of this, the one that occurred in 2014 caused by a severe drought registered in the media. communication. In accordance with the above, a methodological design has been developed in three phases listed below: Hydrological diagnosis of the basin using data science and remote sensors, elaboration of a mathematical model using a material balance so that visualize the mechanics between the rainfall and flow data from the (IDEAM) station, and finally, recommend strategies against land use for the basin according to the information collected.


 


When obtaining in the model, it can be contemplated how the contribution of groundwater is essential in the dry season, which is why it is concluded that the infiltration of rainwater in the excess season for the months of April, May, June, August in order for the aquifers to recharge to provide water to the river in the dry season in the period corresponding to November, December, January, February and March, where the use of the land is essential in planning the region. which requires deforestation to establish pastures for livestock through production strategies, and in the same way, the use of reservoirs as strategic areas to maximize the infiltration of rainwater into the aquifers.

References

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