Tracking Sediment Provenance Applying a Linear Mixing Model Approach Using R’s FingerPro Package, in the Mining-Influenced Ocoña Watershed, Southern Peru

Jorge Crespo (), Elizabeth Holley, Madeleine Guillen, Ivan Lizaga, Sergio Ticona, Isaac Simon, Pablo A. Garcia-Chevesich and Gisella Martínez
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Jorge Crespo: Department of Mining Engineering, Colorado School of Mines, Golden, CO 80401, USA
Elizabeth Holley: Department of Mining Engineering, Colorado School of Mines, Golden, CO 80401, USA
Madeleine Guillen: Department of Geology and Geophysics, Universidad Nacional de San Agustín de Arequipa, Av. Independencia and Paucarpata Street s/n, Arequipa 04001, Peru
Ivan Lizaga: Isotope Bioscience Laboratory—ISOFYS, Department of Green Chemistry and Technology, Ghent University, Coupure Links 653, 9000 Gent, Belgium
Sergio Ticona: Department of Geology and Geophysics, Universidad Nacional de San Agustín de Arequipa, Av. Independencia and Paucarpata Street s/n, Arequipa 04001, Peru
Isaac Simon: Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO 80401, USA
Pablo A. Garcia-Chevesich: Department of Civil and Environmental Engineering, Colorado School of Mines, Golden, CO 80401, USA
Gisella Martínez: Department of Geology and Geophysics, Universidad Nacional de San Agustín de Arequipa, Av. Independencia and Paucarpata Street s/n, Arequipa 04001, Peru

Sustainability, 2023, vol. 15, issue 15, 1-17

Abstract: Stream sediments record water–rock interactions in tributaries followed by fluid mixing in larger downstream catchments, but it can be difficult to determine the relative contributions of each tributary. A good way to analyze this problem is sediment fingerprinting, which allows researchers to identify the source of sediments within a basin and to estimate the contribution of each source to the watershed. Herein, we developed a workflow using the frequentist model FingerPro v1.3 to quantify the sediment source contribution in a semiarid watershed. We applied an unmixing model algorithm to an ICP-MS geochemical database containing information on 32 elements in 362 stream sediment samples. By modeling the source contributions to these mixed samples, we infer that the main sediment contribution comes from the upper portion of the catchment (61–70%), followed by the middle (21–29%) and lower (8–10%) parts, with geochemical anomalies (As and Cu) being closely related to mining sites. Results from this study can be helpful for future management decisions to ensure a better environment in this semiarid watershed.

Keywords: mining; linear mixing model; sediments provenance; FingerPro; southern Peru (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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