  Periodic monitoring of groundwater quality at industrial and commercial sites
generates large volumes of spatiotemporal concentration data. Data modelling is
typically restricted to either the analysis of monotonic trends in individual
wells, or independent fitting of spatial concentration distributions (e.g.
Kriging) to separate monitoring time periods. Neither of these techniques
satisfactorily elucidate the interaction between spatial and temporal
components of the data. Potential negative consequences include an incomplete
understanding of groundwater plume dynamics, which can lead to the selection of
inappropriate remedial strategies. The GroundWater Spatiotemporal Data Analysis
Tool (GWSDAT) is a user friendly, open source, decision support tool that has
been developed to address these issues. Uniquely, GWSDAT applies a
spatiotemporal model for a more coherent and smooth interpretation of the
interaction in spatial and time-series components of groundwater solute
concentrations. GWSDAT has been designed to work with standard groundwater
monitoring data sets, and has no special data requirements. Data entry is via a
standardised Microsoft Excel input template. The underlying statistical
modelling and graphical output are generated using R. This paper describes in
detail the various plotting options available and how the graphical user
interface can be used for rapid, rigorous and interactive trend analysis with
facilitated report generation. GWSDAT has been used extensively in the
assessment of soil and groundwater conditions at Shell's downstream assets and
the discussion section describes the benefits of its applied use. These include
rapid interpretation of complex data sets, early identification of new spills,
detection of off-site plume migration and simplified preparation of groundwater
monitoring reports - all of which facilitate expedited risk assessment and
remediation.
