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Monitoring and forecasting nitrate concentration in the groundwater using statistical process control and time series analysis

  • Autores: Juan Carlos García Díaz Árbol académico
  • Localización: XXX Congreso Nacional de Estadística e Investigación Operativa y de las IV Jornadas de Estadística Pública: actas, 2007, ISBN 978-84-690-7249-3
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • A method based on the statistical process control (SPC) and time series analysis (ARIMA model) is developed to monitoring and to predict the con- centration distribution of nitrate in groundwater. In many pumping wells the -concentration increases and approaches or even passes the European Commu- nity standard of 50 mg . The objective of this paper is to show the application of statistical process control as a monitoring tool for groundwater pollution from agricultural practices. We propose the ARIMA model as a management tool to monitoring and reduction of the intrusion of nitrate into the groundwa- ter. This tool should help in setting up useful guidelines for evaluating actual environmental performance against the ¯rm^aÄA^os environmental objectives and targets and regulatory requirements. We concluded that the statistical process control method may be a potentially important way of monitoring groundwater quality that also permits rapid response to serious increases in pollutants con- centrations. In doing so, the paper ¯lls an important gap in the water pollution standards and emerging polices (Water Framework directives).


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