Abstract

One of the impacts related to mining dam failures is the change in water quality downstream of the rupture and a knowledge gap is observed in terms of methodologies aimed at the prognosis of impact in water abstractions, a vulnerability that can be identified before a rupture event. Thus, the present work aims to describe a novel methodological proposal, not currently considered by control agencies, of a standard protocol that enables a comprehensive prognosis of the impacts on water quality impact in scenarios of dam failure. Initially, extensive bibliographic research was carried out on the main disruptions events since 1965 intended to better comprehend the impacts on water quality and to identify mitigatory actions proposed by the time. The information provided a framework to propose a conceptual model for the prognosis of water abstractions, with the suggestion of software and studies to comprehend the different scenarios in the event of dam failure. A protocol was prepared to obtain information on potentially affected inhabitants and a multicriteria analysis was developed using the Geographic Information System (GIS) to suggest the employment of preventive and corrective actions. The methodology was demonstrated in the Velhas River basin considering a hypothetical scenario of tailing dam failure. Changes in water quality would be observed in 274 km of its extension, mainly related to alterations in solids, metals, and metalloids’ concentration, in addition to the impact on important water treatment plants. The map algebra and the results suggest the need for structuring actions in cases where the water abstraction is intended for human supply and in populations greater than 100,000 inhabitants. Populations smaller than these, or usages other than human supply, could be supplied by water tank trucks or mixed alternatives. The methodology pointed out the necessity for structuring supply actions with due notice, with the potential to prevent water shortages in scenarios of tailing dam failure and to complement the enterprise resource planning of mining companies.

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