Abstract. Construction and abandonment of mine tailings deposits in river floodplains have created environmental risks associated with the release of toxic substances during floods. Assessment tools are needed to understand levels of risk and to prioritize sites for management. These tools need to be computationally efficient over wide areas, potentially whole river basins, which generally excludes reliance on 2D hydrodynamic models. This research evaluates the applicability of a terrain-based floodplain delineation tool (GFPLAIN) to assess flood exposure of tailings deposits by comparing its results against a 2D hydrodynamic model, the Shallow Water Integrated Flood Tool (SWIFT). For this compassion, the case study area of Copiapó River Basin (Atacama, Chile) was used to model two flood scenarios, the extreme flood event of March 2015, and a hypothetical flood with a 100-year return period. Overall, the GFPLAIN flood maps showed limitations in reproducing the list of tailings deposits identified as exposed by SWIFT, with some agreement between some of the top 10 deposits prioritized by these tools. We conclude that GFPLAIN, while fast to apply and potentially able to prioritize sites at risk, has limitations in providing an accurate and complete assessment due to its limited consideration of local terrain and flood dynamics.

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Minimizing environmental pollution from Tailings Storage Facilities (TSFs) is one of the key goals of the mining sector. While much attention is given to risks from potential catastrophic failures of large TSFs, there is also a need to assess risks due to noncatastrophic but more frequent releases of contaminants. In response to this need, this article proposes a method for prioritizing TSFs in terms of flood exposure, based on flood maps produced by the Shallow Water Integrated Flood Tool. The method was implemented using a case study of a flood event in the Copiap o city region (Atacama, Chile). A sensitivity analysis was carried out to evaluate the influence of different model configurations and input parameters. The results showed that 10% of all the TSFs in the case study region were exposed to flood waters due to the fluvial dynamics of the Copiapo River. Additionally, the sensitivity analysis revealed that in the event of extreme local precipitation, capable of generating runoff, up to 88% of all the TSFs could have some degree of flood exposure. The results also suggest that flood simulations using satellite-derived terrain data at moderate resolution can be used for a preliminary large-scale assessment of TSF flood exposure. K E Y W O R D Scontaminated land, extreme events, mapping of flood hazards, SWIFT, TSFs