Use of Artificial Neural Networks as a Predictive Tool of Dissolved Oxygen Present in Surface Water Discharged in the Coastal Lagoon of the Mar Menor (Murcia, Spain)

The Mar Menor is a Mediterranean coastal saltwater lagoon (Murcia, Spain) that represents a unique ecosystem of vital importance for the area, from both an economic and ecological point of view. During the last decades, the intense agricultural activity has caused episodes of eutrophication due to the contribution of inorganic nutrients, especially nitrates. For this reason, it is important to control the quality of the water discharged into the Mar Menor lagoon, which can be performed through the measurement of dissolved oxygen (DO). Therefore, this article aimed to predict the DO in the water discharged into this lagoon through the El Albujon watercourse, for which two theoretical models consisting of a multiple linear regression (MLR) and a back-propagation neural network (RPROP) were developed. Data of temperature, pH, nitrates, chlorides, sulphates, electrical conductivity, phosphates and DO at the mouth of this watercourse, between January 2014 and January 2021, were used. A preliminary statistical study was performed to discard the variables with the lowest influence on DO. Finally, both theoretical models were compared by means of the coefficient of determination (R-2), the root mean square errors (RMSE) and the mean absolute error (MAE), concluding that the neural network made a more accurate prediction of DO.

Datos y Recursos

Cite como

Garcia del Toro E.M. Francisco Mateo L. Garcia-Salgado S. Isabel Mas-Lopez M. y Angeles Quijano M. Use of Artificial Neural Networks as a Predictive Tool of Dissolved Oxygen Present in Surface Water Discharged in the Coastal Lagoon of the Mar Menor (Murcia Spain). MDPI, 2022. https://doi.org/10.3390/ijerph19084531

Clipboard Icon
Recuperado: 20 Jan 2025 15:51:35

Metadatos

Información básica
Tipo de recurso Artículo
Fecha de creación 05-11-2024
Fecha de última modificación 20-01-2025
Mostrar histórico de cambios
Identificador de los metadatos 21a5f10f-1a8f-577d-b2fe-58d73522632e
Idioma de los metadatos Español
Temáticas (NTI-RISP)
Categoría del conjunto de alto valor (HVD) Observación de la Tierra y medio ambiente
Categoría temática ISO 19115
URI de palabras clave
Información bibliográfica
Nombre del autor Garcia del Toro, E.M., Francisco Mateo, L., Garcia-Salgado, S., Isabel Mas-Lopez, M. y Angeles Quijano, M.
Nombre del editor MDPI
Identificador alternativo DOI: 10.3390/ijerph19084531
Identificador del autor
Email del autor evamaria.garcia@upm.es
Web del autor
Procedencia
Declaración de linaje
Perfil de Metadatos
Notas sobre la versión
Versión