The study of groundwater hydrogeochemistry of the sedimentary rock shallow aquifer system in the
Yarmouk Basin of north Jordan produced a large geochemical dataset. Groundwater samples were collected at 36
sites in October 2009 (dry season) and in May 2010 (wet season) over a 1426 km2 study area and analyzed for major
and minor ions. The large number of data can lead to difficulties in the integration, interpretation and representation
of the results. Two multivariate statistical methods, Hierarchical Cluster Analysis (HCA) and Principal Components
Analysis (PCA), were applied to a subgroup of the dataset to evaluate their usefulness to classify the groundwater
samples and to identify geochemical processes controlling groundwater geochemistry. This subgroup consisted of
36 samples and 28 parameters (Ca2+, Na+, Mg2+, K+, Cl-, HCO3
2-, Al, B, Ba2+, Be, Bi, Cd, Co, Cr, Cu,
Fe2+, Li, Mn2+, Ni, Pb, Sb, Se, Zn, P, Sr, V). Seven geochemically distinct clusters, C1-C7, resulted from the HCA.
Calcium and magnesium are the dominant ions in the groundwater of the basin (clusters C1, C5 and C7), while
bicarbonate is the most abundant of the anions (clusters C2 and C3). A total of five PCA components were extracted
for dry and wet seasons, where it accounts 68.6 and 72.6% of the total variance in the dataset, respectively. For dry
and wet season water samples characteristic loadings, two components were defined as the salinity and hardness
components, while the other components were related to more local and geologic effects.