Tailoring groundwater quality monitoring to vulnerability: a GIS procedure for network design

Combining natural background levels (NBLs) assessment with indicator kriging analysis to improve groundwater quality data interpretation and management

The natural background level (NBL) concept is revisited and combined with indicator kriging method to analyze the spatial distribution of groundwater quality within a groundwater body (GWB). The aim is to provide a methodology to easily identify areas with the same probability of exceeding a given threshold (which may be a groundwater quality criteria, standards, or recommended limits for selected properties and constituents). Three case studies with different hydrogeological settings and located in two countries (Portugal and Italy) are used to derive NBL using the preselection method and validate the proposed methodology illustrating its main advantages over conventional statistical water quality analysis. Indicator kriging analysis was used to create probability maps of the three potential groundwater contaminants. The results clearly indicate the areas within a groundwater body that are potentially contaminated because the concentrations exceed the drinking water standards or even the local NBL, and cannot be justified by geogenic origin. The combined methodology developed facilitates the management of groundwater quality because it allows for the spatial interpretation of NBL values.

Optimization of the monitoring network on the River Tisza (Central Europe, Hungary) using combined cluster and discriminant analysis, taking seasonality into account

The most essential requirement for water management is efficient and informative monitoring. Operating water quality monitoring networks is a challenge from both the scientific and economic points of view, especially in the case of river sections ranging over hundreds of kilometers. Therefore, spatio-temporal optimization is vital. In the present study, the optimization of the monitoring system of the River Tisza, the second largest river in Central Europe, is presented using a generally applicable and novel method, combined cluster and discriminant analysis (CCDA). This area for the study was chosen because, spatial inhomogeneity of a river's monitoring network can more easily be studied in a mostly natural watershed - as in the case of the River Tisza - since the effects of man-made obstacles: e.g water barrage systems, hydroelectric power plants, artificial lakes, etc. are more pronounced. Furthermore, since the temporal sampling frequency was bi-weekly, the opportunity of optimizing the monitoring system on a temporal (monthly) scale arose. In the research, 15 water quality parameters measured at 14 sampling sites in the Hungarian section of the River Tisza were assessed for the time period 1975-2005. First, four within-year sections ("hydrochemical seasons") were determined, characterized with unequal lengths, namely 2, 4, 2, and 4 months long starting with spring. Homogeneous groups of sampling sites were determined in space for every season, with the main separating factors being the tributaries and man-made obstacles. Similarly, an overall pattern of homogeneity was determined. As an overall result, the 14 sampling sites could be grouped into 11 homogeneous groups leading to the possibility of reducing the number of sampling locations and thus making the monitoring system more cost-efficient.

Groundwater geochemistry and microbial community structure in the aquifer transition from volcanic to alluvial areas

Groundwaters may act as sinks or sources of organic and inorganic solutes, depending on the relative magnitude of biochemical mobilizing processes and groundwater-surface water exchanges. The objective of this study was to link the lithological and hydrogeological gradients to the aquatic microbial community structure in the transition from aquifer recharge (volcanic formations) to discharge areas (alluvial deposits). A field-scale analysis was performed along a water table aquifer in which volcanic products decreased in thickness and areal extension, while alluvial deposits became increasingly important. We measured the main groundwater physical parameters and the concentrations of major and trace elements. In addition, the microbial community structure was assessed by estimating the occurrence of total coliforms and Escherichia coli, the prokaryotic abundance, the cytometric and phylogenetic community composition. The overall biogeochemical asset differed along the aquifer flow path. The concentration of total and live prokaryotic cells significantly increased in alluvial waters, together with the percentages of Beta- and Delta-Proteobacteria. The microbial propagation over a theoretical groundwater travel time allowed for the identification of microbial groups shifting significantly in the transition between the two different hydrogeochemical facies. The microbial community structure was intimately associated with geochemical changes, thus it should be further considered in view of a better understanding of groundwater ecology and sustainable management strategies.