Level below which soil or rock is saturated with water, in the well and at the time the level has been measured, expressed in m above the sea level. Groundwater levels measured are interpolated / extrapolated to obtain groundwater level on every cell of the hydrogeological unit raster. Surfer and ArcGis are the software usually used to create groundwater level raster. The dataset designates a raster with a groundwater level, for each cell of the hydrogeological unit.

Groundwater flow is the movement of water in an aquifer or hydrogeological unit. The dataset shows groundwater flow rate and direction in the hydrogeological unit. Groundwater flow is establish from piezometric surface map. The method used to create the dataset is described in the metadata associated with the dataset. The dataset represents a description of the flow, including rate in m/d, direction, date and source. Typically, the data provided will not be in the form of a shapefile with linked properties but in the form of an image that sketches the groundwater flow. The image could also represent a cross section of the hydrogeologic units showing the regional trends of the groundwater flow.

Water composition is defined by measuring the amounts of its various constituents; these are often expressed as milligrams of substance per litre of water (mg/L). Sampling methods vary according to the types of analysis. Dataset point: The dataset represents a general description of the sample, including name, ID, type of analysis and lab. It includes numbers describing the results of the analysis and physical properties of groundwater. Time series: The dataset represents a general description of the sample, including name, ID, type of analysis and lab. It includes series of numbers describing the results of the analysis and physical properties of groundwater with associated date. Dynamic values over time at the same sites provides temporal variation data of groundwater composition.

Level below which soil or rock is saturated with water, in the well and at the time the level has been measured, expressed in m above the sea level. Groundwater depth is measured on the field, using a water level meters. The depth is then subtracted from the elevation of the measurement site to obtain the water level elevation. The dataset is a general description of the measurement site including location and well elevation. It features a series of points of the surface elevation of the groundwater body.

Hydraulic properties characterize a hydrogeological unit. The hydraulic properties considered for this dataset are the transmissivity, the hydraulic conductivity, the storage coefficient, the specific storage coefficient and the porosity. Hydraulic properties are estimated by performing aquifer tests (pumping tests, slug tests). The hydraulic tests and their duration are managed in this dataset. The methods used to create the dataset are described in the metadata associated with the dataset. The dataset exhibits a general description of hydraulic properties of the hydrogeological unit, including hydraulic test, total test duration, method and date. It includes numbers and/or ranges describing the aquifer tests results. Note that an alternate raster representation could be used in complement to the discrete point-based representation.

A measure of the intrinsic susceptibility of an aquifer representing the tendency or likelihood for contaminants to reach a specified position in the groundwater system after introduction at some location above the uppermost aquifer. The method used to create the dataset is described in the metadata associated with the dataset. The dataset is a general assessment of the vulnerability of the hydrogeological unit considered as a whole. It features the local and regional qualifiers in a controlled vocabulary list referring to the extent where the vulnerability value is valid. Because the vulnerability is assessed using contextual indices linked to the regional hydrogeological settings, it is very unlikely to have an homogeneous range of data throughout the various hydrogeologic units across the country for this dataset. Hence, the vulnerability dataset will not qualify as an homogeneous dataset. A more generic reclassification using for examples three vulnerability classes could then be used to solve this problem. Each sub layers used to create the global vulnerability index can be provided along with the final vulnerability index map.