Abstract
Environmental data sets are often multidimensional and consequently display complex structure. This article shows the limitations of principal component analysis (PCA) for the study of such three-dimensional (3D) data sets. These limitations can be resolved by the use of the statistical tool STATIS. The inlet (a swallow hole) and the outlet (a spring) of a karst system of the Western Paris basin were sampled during three rain events of various intensities. These 3D geochemical data sets (variables x sites x dates) for a karst system were analyzed by STATIS method to identify hydrological processes. STATIS proceeds in three steps (interstructure, compromise, and intrastructure), which allows us to focus the analysis of hydrologic systems at different temporal and spatial scales. Compromise plane shows that suspended matter and flood are not simultaneous and highlights a rapid flow, characterized by turbidity and phosphate, which represents a point source contamination, and a ground water flow contaminated by nitrate. Intrastructure plane allows us to compare hydrochemical variations between the swallow hole and the spring lead. By this way, hydrological processes such as direct transfer and resuspension of intrakarstic sediments before and after the flood were identified what cannot be realized by comparison of inlet and outlet breakthrough curves. Finally, results obtained from the same data set by STATIS and a coupled study using PCA and normalized hysteresis curves were compared. This comparison shows the efficiency of STATIS at the identification of transport processes and vulnerability of karst system and its potential for hydrological applications.
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