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. 2012 May 2;6 Suppl 2(Suppl 2):S5.
doi: 10.1186/1752-153X-6-S2-S5.

Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province

Pierina Ielpo  1 , Daniela Cassano, Antonio Lopez, Giuseppe Pappagallo, Vito Felice Uricchio, Pasquale Abbruzzese De Napoli
Affiliations

Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province

Pierina Ielpo et al. Chem Cent J. .

Abstract

Background: Ground waters are an important resource of water supply for human health and activities. Groundwater uses and applications are often related to its composition, which is increasingly influenced by human activities.In fact the water quality of groundwater is affected by many factors including precipitation, surface runoff, groundwater flow, and the characteristics of the catchment area. During the years 2004-2007 the Agricultural and Food Authority of Apulia Region has implemented the project "Expansion of regional agro-meteorological network" in order to assess, monitor and manage of regional groundwater quality. The total wells monitored during this activity amounted to 473, and the water samples analyzed were 1021. This resulted in a huge and complex data matrix comprised of a large number of physical-chemical parameters, which are often difficult to interpret and draw meaningful conclusions. The application of different multivariate statistical techniques such as Cluster Analysis (CA), Principal Component Analysis (PCA), Absolute Principal Component Scores (APCS) for interpretation of the complex databases offers a better understanding of water quality in the study region.

Results: Form results obtained by Principal Component and Cluster Analysis applied to data set of Foggia province it's evident that some sampling sites investigated show dissimilarities, mostly due to the location of the site, the land use and management techniques and groundwater overuse. By APCS method it's been possible to identify three pollutant sources: Agricultural pollution 1 due to fertilizer applications, Agricultural pollution 2 due to microelements for agriculture and groundwater overuse and a third source that can be identified as soil run off and rock tracer mining.

Conclusions: Multivariate statistical methods represent a valid tool to understand complex nature of groundwater quality issues, determine priorities in the use of ground waters as irrigation water and suggest interactions between land use and irrigation water quality.

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Figures

Figure 1
Figure 1
Water quality monitoring sites in Apulia region.
Figure 2
Figure 2
Foggia province with monitored wells.
Figure 3
Figure 3
Principal component analysis loading plot.
Figure 4
Figure 4
Principal component analysis score plot.
Figure 5
Figure 5
Cluster analysis tree diagram obtained from data set. On the x axis the sample numbers are displayed, while on the y axis the ratio Dlinkage/Dmax *100 is shown.
Figure 6
Figure 6
Cluster analysis tree diagram obtained from the first two component’s scores.
Figure 7
Figure 7
7a Orthophoto showing the sampling site located close to the sea in Mattinata village (Foggia province); 7b Orthophoto showing the sampling site close to La Contessa channel (Foggia province).
Figure 8
Figure 8
Percentage of source’s contribution to each parameters.
See this image and copyright information in PMC

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