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A global rise in alluvial mining increases sediment load in tropical rivers

Nature volume 620, pages 787–793 (2023)Cite this article

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Abstract

Increasing gold and mineral mining activity in rivers across the global tropics has degraded ecosystems and threatened human health1,2. Such river mineral mining involves intensive excavation and sediment processing in river corridors, altering river form and releasing excess sediment downstream2. Increased suspended sediment loads can reduce water clarity and cause siltation to levels that may result in disease and mortality in fish3,4, poor water quality5 and damage to human infrastructure6. Although river mining has been investigated at local scales, no global synthesis of its physical footprint and impacts on hydrologic systems exists, leaving its full environmental consequences unknown. We assemble and analyse a 37-year satellite database showing pervasive, increasing river mineral mining worldwide. We identify 396 mining districts in 49 countries, concentrated in tropical waterways that are almost universally altered by mining-derived sediment. Of 173 mining-affected rivers, 80% have suspended sediment concentrations (SSCs) more than double pre-mining levels. In 30 countries in which mining affects large (>50 m wide) rivers, 23 ± 19% of large river length is altered by mining-derived sediment, a globe-spanning effect representing 35,000 river kilometres, 6% (±1% s.e.) of all large tropical river reaches. Our findings highlight the ubiquity and intensity of mining-associated degradation in tropical river systems.

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Fig. 1: Overview of global river mineral mining.
Fig. 2: Rivers respond rapidly after mining begins.
Fig. 3: River lengths affected by river mineral mining.
Fig. 4: Fraction of total river length affected by mining in each country.

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Data availability

The available data include KML files of all mining site locations and river profiles, as well as unprocessed remote-sensing data. All data are archived at https://zenodo.org/record/7699122#.ZE9Hey-B3RY.

Code availability

All code necessary for accessing the unprocessed data used for this study and reproducing our results is available at https://zenodo.org/record/7699122#.ZE9Hey-B3RY and https://github.com/evandethier/global-alluvial-mining.

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Acknowledgements

This research was funded by NASA Land-Cover and Land-Use Change Program award 80NSSC21K0309 and NASA Terrestrial Hydrology Program award 80NSSC23K1293.

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Author notes

  1. Evan N. Dethier

    Present address: Department of Geology, Occidental College, Los Angeles, CA, USA

Authors and Affiliations

  1. Department of Environmental Studies, Dartmouth College, Hanover, NH, USA

    Evan N. Dethier & David A. Lutz

  2. Department of Earth Sciences, Dartmouth College, Hanover, NH, USA

    Evan N. Dethier & Carl E. Renshaw

  3. Department of Earth and Oceanographic Science, Bowdoin College, Brunswick, ME, USA

    Evan N. Dethier & Peter Tomhave

  4. Department of Biology, Wake Forest University, Winston-Salem, NC, USA

    Miles Silman & Luis E. Fernandez

  5. Center for Energy, Environment, and Sustainability, Wake Forest University, Winston-Salem, NC, USA

    Miles Silman, Sarra Alqahtani & Paúl Pauca

  6. Center for Environmental Health, Oakland, CA, USA

    Jimena Díaz Leiva

  7. Department of Computer Science, Wake Forest University, Winston-Salem, NC, USA

    Sarra Alqahtani, Paúl Pauca & Seda Çamalan

  8. Centro de Innovación Científica Amazónica (CINCIA), Puerto Maldonado, Peru

    Luis E. Fernandez

  9. Department of Geography, Dartmouth College, Hanover, NH, USA

    Francis J. Magilligan

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Contributions

E.N.D., M.S., D.A.L., F.J.M. and C.E.R. devised the project. E.N.D., D.A.L., C.E.R. and F.J.M. obtained project funding. E.N.D. and P.T. generated and analysed the data. E.N.D. drafted the manuscript and all authors contributed to the final version and revisions.

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Correspondence to Evan N. Dethier.

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Extended data figures and tables

Extended Data Fig. 1 Chronology of river mineral mining impacts by river.

Post-mining change in SSC, as measured by Z-scores, relative to pre-mining conditions or an unmined analogue in each river system affected by river mineral mining. Z-scores are computed on a 3-year running average basis to dampen outlier effects from individual years, particularly those with sparse data. No data for a year is indicated by dark-grey cells. Numbers on the right correspond with the river profile id number in the Supplementary Data 2.

Extended Data Fig. 2 Comparisons of changes in suspended sediment transport in watersheds affected by oil palm cultivation and river mineral mining.

a, Estimated SSC for a 10-km reach of the Tabir River, a tributary to the Batang Hari River in Indonesia. Rapid increase in SSC following mining onset was followed by a lull in mining, during which suspended sediment declined despite continuing palm oil cultivation. Resumption of mining in the 2010s was followed by another increase in SSC. b, Average standardized SSC anomaly for 30 sites increased throughout the satellite record on average, both before and after river mineral mining began. However, the rate of SSC increase quickened after mining begins, with a clear break point at the year of mining onset. c, Average SSC rate of increase before mining begins is 7 mg l−1 year−1. After mining, the average rate of increase is 47 mg l−1 year−1, indicating the relatively higher impact of river mineral mining despite its smaller footprint in these watersheds. Grey shading in a and b indicates pre-mining oil palm cultivation period.

Extended Data Fig. 3 Length of river profiles affected by mining.

a, The average number of river kilometres at active mining sites affected by river mineral mining with >3 s.d. increase in SSC relative to the reference period. b, The average percentage of river kilometres in a given mining-affected profile with a >3 s.d. increase in SSC relative to the reference period. Error bars indicate the standard error in the mean.

Extended Data Fig. 4 Reference and post-mining monthly average SSC on some rivers in Africa.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 5 Reference and post-mining monthly average SSC on the remaining rivers in Africa.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 6 Reference and post-mining monthly average SSC on rivers in Asia.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 7 Reference and post-mining monthly average SSC on rivers in North America and Oceania.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 8 Reference and post-mining monthly average SSC on some rivers in South America.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 9 Reference and post-mining monthly average SSC on the remaining rivers in South America.

Error bars indicate the standard error in the mean, computed for that month across all years and river reaches in the satellite record for reference reaches (no mining, blue) and active mining reaches (along stream or downstream of active mining, yellow).

Extended Data Fig. 10 Avulsion downstream of mining areas in the Democratic Republic of the Congo.

a, Image from 2 years before the avulsion, which occurred in 2019. b, Image from after the avulsion, showing the new river course. River flow is from east to west (right to left on the images). Some evidence, including abandoned oxbows, suggests that the river occupied the approximate avulsion path in the past, but the pre-avulsion channel and dashed line in the lower panel has been the stable, primary channel since at least the 1980s. Imagery is from Planet Labs © 2022 Planet Labs PBC, centred at [−4.692102°, 28.559496°].

Extended Data Table 1 River reaches with SSC elevated by 2, 5 and 10 times above the pre-mining mean
Full size table

Supplementary information

Supplementary Figures

This file contains Supplementary Figs. 1–21 and one further reference. In this Supplementary Information document, we: (1) plot the number of mining areas per country (Supplementary Fig. 1); (2) provide further details about satellite image availability for rivers included in our analysis (Supplementary Figs. 2–8); (3) illustrate the methodology for mapping small streams that are altered by river mineral mining (Supplementary Fig. 9) and the quantitative results of that analysis (Supplementary Fig. 10); (4) plot distributions of SSC for reference and active mining periods on affected rivers—these comparison distributions show each individual river and are organized by main landmass (Supplementary Figs. 11–16); (5) plot aggregate time series of mining for all rivers relative to the price of gold (Supplementary Fig. 17) and for each individual country with mappable river mineral mining (Supplementary Fig. 18); (6) provide photographs illustrating how mining operations look on the ground (Supplementary Figs. 19–21).

Peer Review File

Supplementary Data 1

Mining areas mapped in this study (zipped KML file).

Supplementary Data 2

River profiles mapped in this study near and downstream of mining areas (zipped KML file).

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Dethier, E.N., Silman, M., Leiva, J.D. et al. A global rise in alluvial mining increases sediment load in tropical rivers. Nature 620, 787–793 (2023). https://doi.org/10.1038/s41586-023-06309-9

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  • DOI: https://doi.org/10.1038/s41586-023-06309-9

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