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Artisanal and small-scale gold mining (ASGM) is the largest global source of anthropogenic mercury emissions. However, little is known about how effectively mercury released from ASGM is converted into the bioavailable form of methylmercury in ASGM-altered landscapes. Through examination of ASGM-impacted river basins in Peru, we show that lake area in heavily mined watersheds has increased by 670% between 1985 and 2018 and that lakes in this area convert mercury into methylmercury at net rates five to seven times greater than rivers. These results suggest that synergistic increases in lake area and mercury loading associated with ASGM are substantially increasing exposure risk for people and wildlife. Similarly, marked increases in lake area in other ASGM hot spots suggest that “hydroscape” (hydrological landscape) alteration is an important and previously unrecognized component of mercury risk from ASGM.
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Satellites provide a temporally discontinuous record of hydrological conditions along Earth’s rivers (e.g., river width, height, water quality). The degree to which archived satellite data effectively capture the overall population of river flow frequency is unknown. Here, we use the entire archives of Landsat 5, 7, and 8 to determine when a cloud-free image is available over the United States Geological Survey (USGS) river gauges located on Landsat-observable rivers. We compare the flow frequency distribution derived from the daily gauge record to the flow frequency distribution derived from ideally sampling gauged discharge based on the timing of cloud-free Landsat overpasses. Examining the patterns of flow frequency across multiple gauges, we find that there is not a statistically significant difference between the flow frequency distribution associated with observations contained within the Landsat archive and the flow frequency distribution derived from the daily gauge data (α = 0.05), except for hydrological extremes like maximum and minimum flow. At individual gauges, we find that Landsat observations span a wide range of hydrological conditions (97% of total flow variability observed in 90% of the study gauges) but the degree to which the Landsat sample can represent flow frequency distribution varies from location to locationmore »