Methodological approach for the analysis of groundwater quality in the framework of the Groundwater Directive

Abstract

All countries of the European Union are required to determine the evolution of groundwater quality, including trend assessment. With this aim, the Water Framework Directive advises using standardized statistical analysis, like least squares regression. But this methodology is not applicable to all situations and what’s more, does not offer a sound methodological framework. There are many statistical procedures to evaluate temporal behaviour of environmental data but, when applied unconnectedly, erroneous conclusions can be reached due to bias of assuming partial or particular conducts. In this paper, a methodology for studying such information is proposed, integrating most common methods for time series analysis. To provide a sound scientific basis to the methodology, statistic intervals combined with trend assessment are proposed, after adjusting a regression curve and applying smoothing techniques to select the baseline level. Confidence intervals have been used when a threshold value does exist. Whether it is not fixed or the baseline level exceeds the standard, prediction intervals were employed. The approach has been analysed at Plana de Vinaroz Groundwater Body (PV). As a result, PV is classed of poor chemical status in regard to diffuse pollution and sea water intrusion, and consequently a programme of measures is necessary. In relation with marine intrusion, a regional downward trend has been found, showing no further deterioration. An additional outcome of the procedure is a methodological framework for the systematic review of the relevant information for evaluation of Groundwater Body chemical status, which includes additional steps to check the effectiveness of the programme of measures and update the baseline level periodically. The proposed methodology, based on procedures usually applied separately, provides a comprehensive framework for groundwater quality data analysis. It will allow more rigorous implementation objectives of the Directive. Results obtained for the developed case are more robust from the statistical point of view, because all hypotheses have been contemplated.