Monitoring and forecasting nitrate concentration in the groundwater using statistical process control and time series analysis: a case study |
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Authors: | J Carlos Garc��a-D��az |
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Institution: | (1) Centro de Gesti?n de la Calidad y del Cambio, Universidad Polit?cnica de Valencia, Camino de Vera s/n, Building 7A, 46022 Valencia, Spain |
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Abstract: | Contaminated water resources have important implications on health and the environment. Nitrate contamination of the groundwater
is a serious problem in the European Union. A method based on the statistical process control (SPC) and time series analysis
is developed to monitoring and to predict the concentration evolution of nitrate (NO3
−) in groundwater. In many pumping wells the NO3
−concentration (NO3
−]) increases and approaches or even passes the European Community standard of 50 mg l−1. 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 autoregressive integrated moving average (ARIMA) model as a management
tool to monitoring and reduction of the intrusion of nitrate into the groundwater. This tool should help in setting up useful
guidelines for evaluating actual environmental performance against the firm’s 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 concentrations. In doing so, the paper fills an
important gap in the water pollution standards and emerging polices (Water Framework directives). |
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Keywords: | |
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