Assessment of groundwater quality by means of self-organizing maps: application in a semiarid area |
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Authors: | Sanchez-Martos Francisco Aguilera Pedro A Garrido-Frenich Antonia Torres Jose A Pulido-Bosch Antonio |
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Institution: | (1) Department of Hydrogeology, Almería University, 04120 Almería, Spain, ES;(2) Department of Ecology, Almería University, 04120 Almería, Spain, ES;(3) Department of Analytical Chemistry, Almería University, 04120 Almería, Spain, ES;(4) Department of Computer Science, Almería University, 04120 Almería, Spain, ES;(5) Department of Hydrogeology, Almería University, 04120 Almería, Spain, ES |
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Abstract: | The Kohonen neural network was applied to hydrochemical data from the Detritic Aquifer of the Lower Andarax, situated in a
semiarid zone in the southeast of Spain. An activation map was obtained for each of the sampling points, in which the spatial
distribution of the activated neurons indicated different water qualities. To extract the information contained in the activation
maps, they were divided into nine quadrats. Cartesian coordinates were assigned to each quadrant (x, y), and for each sampling point, three derived variables were selected, which were assigned the values x and y of the corresponding quadrat. A classification was defined based on this simple matrix system which allows an easy and rapid
means of evaluating the water quality. This assessment highlights the various processes that affect groundwater quality. The
method generates output that is easier to interpret than from traditional statistical methods. The information is extracted
from the activation maps without significant loss of information. The method is proposed for assessing water quality in hydrogeochemically
complex areas, where large numbers of observations are made. |
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Keywords: | : Self-organizing maps Multivariate analysis Groundwater quality Semiarid area |
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