Precipitation, pH and metal load in AMD river basins: an application of fuzzy clustering algorithms to the process characterization

Abstract

In the present work, Acid Mine Drainage (AMD) processes in the Chorrito Stream, which flows into the Cobica River (Iberian Pyrite Belt, Southwest Spain) are characterized by means of clustering techniques based on fuzzy logic. Also, pH behavior in contrast to precipitation is clearly explained, proving that the influence of rainfall inputs on the acidity and, as a result, on the metal load of a riverbed undergoing AMD processes highly depends on the moment when it occurs. In general, the riverbed dynamic behavior is the response to the sum of instant stimuli produced by isolated rainfall, the seasonal memory depending on the moment of the target hydrological year and, finally, the own inertia of the river basin, as a result of an accumulation process caused by age-long mining activity.

Time Evolution of an AMD-Affected River Chemical Makeup

“…Previous studies by different authors (Borrego 1992;Borrego et al 2002;Braungardt et al 1998;Davis et al 2000;Elbaz-Poulichet et al 1999, 2001Leblanc et al 2000;Sáinz 1999;Sáinz et al 2002Sáinz et al , 2003aGrande et al 2000Grande et al , 2003aGrande et al , b, 2005a and, more specifically, that by Grande et al (2005b) (where the authors characterise AMD and ARD processes in the same area of study, taking samples from the Chorrito Stream and from another stream called Higuereta, which flows into the Cobica and has no acid contributions), are useful as a reference for the discussion and for obtaining the conclusions of our study. It is evident that there are different responses at each sampling point, although all of them are framed within the general characteristics of AMD processes.…”

Fuzzy Modeling of the Spatial Evolution of the Chemistry in the Tinto River (SW Spain)

“…When the water reaches Niebla the average sulfate concentration values have dropped to 370.5 mg l −1 and the Medium-concentrated Negligible-occasionally medium-low values variance, just as happened with the pH and unlike the metals, is 575 times lower in the receiving milieu. Figures 4 and 5 show the fuzzy rules (seven for each of the sampling sites) obtained by applying the fuzzy logic tools used previously in the qualitative modeling of water pollution processes by Grande et al (2005a) Tables 3 and 4. Equally, Figs. 6 and 7 display the Redox Potential as consequent and their summarized explanation appears in Tables 5 and 6.…”

“…The high number of samples analyzed, indispensable for observing cause-and-effect relationships in AMD processes in view of the immediacy of certain reactions following episodes of rainfall (Grande et al 2005a), suggest the use of fuzzy logic as an advanced tool for interpreting this type of phenomena and especially for attempting to model the process correctly.…”

“…The main objective of this work is to characterize the behavior of As conditioned by the presence of other elements which are characteristic of AMD pollution, both in the generating milieu, and in the receiving milieu of the Tinto river, and thus to be able to establish the differences in behavior at both sites by using a fuzzy computer tool, PreFuRGe (Grande et al 2005a), which allows qualitative interpretation of the data recorded in a database relating to the chemistry of water. Specifically, we aim to find information, apparently hidden and not likely to be detected by means of classical statistical techniques, which can help to characterize and interpret the behavior of As in a complex system.…”

Hydrochemical characterization of an acid mine drainage-affected reservoir: the Sancho Reservoir, Huelva, southwest Spain

“…The IPB is one of the largest metallogenic regions of the world, with numerous giant and supergiant massive sulphide ore deposits (Sáez et al 1999), comprising 1700 Mt of sulphide reserves (Pinedo-Vara 1963). Consequently, the regional drainage network is strongly affected by AMD and acid rock drainage (ARD), as described by several authors: Elbaz-Poulichet et al (1999,2000,2001), Davis et al (2000), Grande et al (2003aGrande et al ( , 2003bGrande et al ( , 2005aGrande et al ( , 2005bGrande et al ( , 2010aGrande et al ( , 2010bGrande et al ( , 2010cGrande et al ( , 2010dGrande et al ( , 2010e, 2011aGrande et al ( , 2011b, Leblanc et al (2000), Borrego et al (2002), Sáinz et al (2002Sáinz et al ( , 2003aSáinz et al ( , 2003bSáinz et al ( , 2004Sáinz et al ( , 2005, Olıás et al (2004Olıás et al ( , 2005aOlıás et al ( , 2005bOlıás et al ( , 2006, Aroba et al (2007), Jiménez et al (2009), de la Torre et al (2009, Carro et al (2011) and Grande (2011).…”