Generación de un modelo espacial de dispersión de contaminantes y calidad del agua aplicando el modelo de Kriging en la Microcuenca de la Quebrada Ortega - cantón Quito.
Understanding the process of dispersion of pollutants in rivers from the activities of human beings is of vital importance for the environmental engineer. The characterization and understanding of the different parameters are key to the generation of different ways to measure the quality indices. T...
| Autor Principal: | Arcos Vargas, Cristian Rodrigo |
|---|---|
| Formato: | bachelorThesis |
| Idioma: | spa |
| Publicado: |
2015
|
| Materias: | |
| Acceso en línea: |
http://dspace.ups.edu.ec/handle/123456789/10080 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: |
Understanding the process of dispersion of pollutants in rivers from the activities of human beings is of vital importance for the environmental engineer. The characterization and understanding of the different parameters are key to the generation of different ways to measure the quality indices.
The use encryption allowed Pfafstetter understand and comprehend the encoding process and delineation of the watershed with an appropriate sampling plan in the watershed was generated.
Data collected in the study are the most common, that is, they are associated with pollution of water resources to make a comparative analysis of water quality indicators and to unite it with the geostatistical modeling. With this methodology an approach to the reality of the body of water of the creek watershed Ortega, located in the Metropolitan District of Quito southern sector was obtained. For this, the method of the water quality index (IQA) and simultaneous water quality index (ISCA) was used, both methods used to check 10 points and 5 points for the model validation process.
In this paper, the fundamental elements of geostatistics and different interpolators in order to infer the data along the watershed not sampled were presented.
After presenting the different interpolators modeling results that met or interpolated closer to reality were Moving Average and Moving Surface. |
|---|