Abstract

Multivariate statistical techniques, including discriminant function analysis (DFA), cluster analysis (CA),principal component analysis (PCA), absolute principal component score (APCS), and radial basis function neural network(RBF-NN), were applied to a data set formed by 905 samples and 15 parameters, including pH, electrical conductivity(EC), total dissolved solids (TDS), dissolved oxygen (O2), chemical oxygen demand (COD), Na+, Ca2+, Mg2+, K+, Cl-,NO3-, SO42-, HCO3, and vital organism at 22°C and 36°C, of groundwater samples collected in the Apulia region (southernItaly). Among all collected samples, only samples showing values for all parameters were used to compose the data set onwhich the multivariate statistical techniques were applied. PCA and APCS allowed us to identify, for each province as wellas the sites diverging from the main cluster, the pollution sources pressuring the sampling sites investigated: they wereidentified as fertilizer applications, the use of unpurified irrigation water, marine water intrusion, and calcareous characteristicsof the soil. We found that the groundwater pollution sources pressuring the sites were similar among the five Apulianprovinces (Foggia, Bari, Brindisi, Lecce, and Taranto). Moreover, for each province, marine water intrusion showedthe highest contribution. The application of DFA to the data set allowed us to obtain good results in discriminating amongfour provinces, with the exception of Taranto. The model also gave good performance results in forecasting. However,RBF-NN provided more accurate results than DFA and confirmed that EC had the greatest relative importance. This isprobably due to the different salinity among the sites (Na+ also showed good discriminant importance). In fact, with PCAand APCS, it was possible to observe that EC, together with Na+, Cl-, and TDS, was the parameter that most often showedhigh loading values, and the scattered samples with these loading values were collected at sites in which marine waterintrusion had been hypothesized. The results obtained by multivariate statistical methods can be useful both in guidingstakeholders and in providing a valid tool to authorities for assessing and managing groundwater resources.

Autore Pugliese

• Uricchio Vito Felice , Ielpo Pierina

Tutti gli autori

• P. Ielpo; D. Cassano; V. F. Uricchio; A. Lopez; G. Pappagallo; L. Trizio; G. de Gennaro

Titolo volume/Rivista

Transactions of the ASABE

Anno di pubblicazione

2013

ISSN

2151-0032

ISBN

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Numero di citazioni Wos

Nessuna citazione

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Numero di citazioni Scopus

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Settori ERC

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Codici ASJC

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