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A global-scale framework for hydropower development incorporating strict environmental constraints

Nature Water volume 1, pages 113–122 (2023)Cite this article

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Abstract

The benefits of developing the world’s hydropower potential are intensely debated when considering the need to avoid or minimize environmental impacts. However, estimates of global unused profitable hydropower potential with strict environmental constraints have rarely been reported. In this study we performed a global assessment of the unused profitable hydropower potential by developing a unified framework that identifies a subset of hydropower station locations with reduced environmental impacts on the network of 2.89 million rivers worldwide. We found that the global unused profitable hydropower potential is 5.27 PWh yr−1, two-thirds of which is distributed across the Himalayas. Africa’s unused profitable hydropower is 0.60 PWh yr−1, four times larger than its developed hydropower. By contrast, Europe’s hydropower potential is extremely exploited. The estimates, derived from a consistent and transparent framework, are useful for formulating national hydropower development strategies.

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Fig. 1: Spatial distribution and cost–supply curves of unused profitable potential at the global and continental scales.
Fig. 2: National unused profitable potential as a percentage of total electricity generation.
Fig. 3: Extent of hydropower development for each country and continent.

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Data availability

The discharge dataset is available at http://hydrology.princeton.edu/data/mpan/GRFR/discharge/daily/, the river network dataset is available at http://hydrology.princeton.edu/data/mpan/MERIT_Basins/MERIT_Hydro_v07_Basins_v01/, the DEM dataset is available at http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro/, the GRanD database is available at https://www.globaldamwatch.org/grand, the Global Georeferenced Database of Dams (GOODD) dataset is available at https://www.globaldamwatch.org/goodd, Georeferenced global dam and reservoir (GeoDAR) data are available at https://zenodo.org/record/6163413, the latest global reservoir and power-line datasets can be extracted from https://www.openstreetmap.org/, the WDPA database is available at https://www.protectedplanet.net/en, the natural and mixed World Heritage Sites are available at https://www.arcgis.com/home/item.html?id=ef1ecce8fa3e41d89688be6199b5b32c, large lakes are available at https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database, the tropical rainforests dataset is available at https://glad.umd.edu/dataset/primary-forest-humid-tropics, the peatlands dataset is available at https://archive.researchdata.leeds.ac.uk/251/, the population dataset is available at https://landscan.ornl.gov/, the electricity consumption dataset is available at https://www.iea.org/data-and-statistics/data-browser/?country=WORLD&fuel=Energy%20consumption&indicator=TotElecCons, the electricity supply dataset is available at https://www.iea.org/data-and-statistics/data-browser?country=WORLD&fuel=Energy%20supply&indicator=ElecGenByFuel, the global aboveground biomass carbon density maps are available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1763, the IUCN Red List data are available at https://www.iucnredlist.org/resources/other-spatial-downloads, the Global Amphibian and Mammal Species Richness Grids of the ICUN are available at https://sedac.ciesin.columbia.edu/data/set/species-global-amphibian-richness-2015 and https://sedac.ciesin.columbia.edu/data/set/species-global-mammal-richness-2015, the GDP dataset is available at https://datadryad.org/stash/dataset/doi:10.5061/dryad.dk1j0, the Global Seismic Hazard Map is available at http://gmo.gfz-potsdam.de/, global land cover data are available at http://www.esa-landcover-cci.org/?q=node/197 and the global soil dataset is available at http://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/. All datasets are also available from the corresponding author upon request.

Code availability

The scripts used to generate all the results are MATLAB (R2018b). All data and code are available at https://github.com/xurr2020/GlobalHydropower.

References

  1. Gielen, D. et al. The role of renewable energy in the global energy transformation. Energy Strategy Rev. 24, 38–50 (2019).

    Article  Google Scholar 

  2. Hart, E. K. & Jacobson, M. The carbon abatement potential of high penetration intermittent renewables. Energy Environ. Sci. 5, 6592–6601 (2012).

    Article  CAS  Google Scholar 

  3. Jacobson, M. et al. Low-cost solutions to global warming, air pollution, and energy insecurity for 145 countries. Energy Environ. Sci. https://doi.org/10.1039/D2EE00722C (2022).

    Article  Google Scholar 

  4. Global Energy Review 2021 (International Energy Agency, 2021); https://www.iea.org/reports/global-energy-review-2021

  5. Moran, E. et al. Sustainable hydropower in the 21st century. Proc. Natl Acad. Sci. USA 115, 11891–11898 (2018).

    Article  CAS  Google Scholar 

  6. Latrubesse, E. et al. Damming the rivers of the Amazon basin. Nature 546, 363–369 (2017).

    Article  CAS  Google Scholar 

  7. Maavara, T. et al. River dam impacts on biogeochemical cycling. Nat. Rev. Earth Environ. 1, 103–116 (2020).

    Article  Google Scholar 

  8. Best, J. Anthropogenic stresses on the world’s big rivers. Nat. Geosci. 12, 7–21 (2019).

    Article  CAS  Google Scholar 

  9. Lehner, B., Czisch, G. & Vassolo, S. The impact of global change on the hydropower potential of Europe: a model-based analysis. Energy Policy 33, 839–855 (2005).

    Article  Google Scholar 

  10. Fekete, B. et al. Millennium ecosystem assessment scenario drivers (1970–2050): climate and hydrological alterations. Global Biogeochem. Cycles 24, GB0A12 (2010).

    Article  Google Scholar 

  11. Zhou, Y. et al. A comprehensive view of global potential for hydro-generated electricity. Energy Environ. Sci. 8, 2622–2633 (2015).

    Article  Google Scholar 

  12. Gernaat, D. et al. High-resolution assessment of global technical and economic hydropower potential. Nat. Energy 2, 821–828 (2017).

    Article  Google Scholar 

  13. Hoes, O. C. et al. Systematic high-resolution assessment of global hydropower potential. PLoS ONE 2, e0171844 (2017).

    Article  Google Scholar 

  14. Ziv, G. et al. Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin. Proc. Natl Acad. Sci. USA 109, 5609–5614 (2013).

    Article  Google Scholar 

  15. Pastor, A. V. et al. Accounting for environmental flow requirements in global water assessments. Hydrol. Earth Syst. Sci. 18, 5041–5059 (2014).

    Article  Google Scholar 

  16. Jacobson, M. et al. Low-cost solution to the grid reliability problem with 100% penetration of intermittent wind, water, and solar for all purposes. Proc. Natl Acad. Sci. USA 112, 15060–15065 (2015).

    Article  CAS  Google Scholar 

  17. An Assessment of Energy Potential at Non-Powered Dams in the United States (US Department of Energy, 2021); https://www.energy.gov/eere/water/downloads/assessment-energy-potential-non-powered-dams-united-states

  18. Kareiva, P. Dam choices: analyses for multiple needs. Proc. Natl Acad. Sci. USA 109, 5553–5554 (2012).

    Article  CAS  Google Scholar 

  19. Poff, N. & Schmidt, J. How dams can go with the flow. Science 353, 1099–1100 (2016).

    Article  CAS  Google Scholar 

  20. Poff, N. & Olden, J. Can dams be designed for sustainability? Science 358, 1252–1253 (2017).

    Article  CAS  Google Scholar 

  21. Lin, P. et al. Global reconstruction of naturalized river flows at 2.94 million reaches. Water Resour. Res. 55, 6499–6516 (2019).

    Article  Google Scholar 

  22. OpenStreetMap (OSMF, 2021); www.openstreetmap.org

  23. Lehner, B. et al. High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Front. Ecol. Environ. 9, 494–502 (2011).

    Article  Google Scholar 

  24. Mulligan, M., Soesbergen, A. & Sáenz, L. GOODD, a global dataset of more than 38,000 georeferenced dams. Sci. Data 7, 31 (2020).

    Article  Google Scholar 

  25. Wang, J. et al. GeoDAR: georeferenced global dam and reservoir dataset for bridging attributes and geolocations. Earth Syst. Sci. Data 14, 1869–1899 (2022).

    Article  Google Scholar 

  26. IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  27. Li, D. et al. High mountain Asia hydropower systems threatened by climate-driven landscape instability. Nat. Geosci. https://doi.org/10.1038/s41561-022-00953-y (2022).

    Article  Google Scholar 

  28. Cáceres, A. et al. Potential hydropower contribution to mitigate climate risk and build resilience in Africa. Nat. Clim. Change 12, 719–727 (2022).

    Article  Google Scholar 

  29. Bertassoli, D. J. Jr et al. How green can Amazon hydropower be? Net carbon emission from the largest hydropower plant in Amazonia. Sci. Adv. 7, eabe1470 (2021).

    Article  CAS  Google Scholar 

  30. Millstein, D. et al. Solar and wind grid system value in the United States: the effect of transmission congestion, generation profiles, and curtailment. Joule 21, 1749–1775 (2021).

    Article  Google Scholar 

  31. Rehman, S., Al-Hadhrami, L. M. & Alam, Md. M. Pumped hydro energy storage system: a technological review. Renew. Sustain. Energy Rev. 44, 586–598 (2015).

    Article  Google Scholar 

  32. Stocks, M. et al. Global atlas of closed-loop pumped hydro energy storage. Joule 5, 270–281 (2021).

    Article  Google Scholar 

  33. Hunt, J. et al. Global resource potential of seasonal pumped hydropower storage for energy and water storage. Nat. Commun. 11, 947 (2020).

    Article  CAS  Google Scholar 

  34. Winemiller, K. O. et al. Balancing hydropower and biodiversity in the Amazon, Congo, and Mekong. Science 351, 128–129 (2016).

    Article  CAS  Google Scholar 

  35. Tamba, J. et al. Carbon dioxide emissions from thermal power plants in Cameroon: a case study in Dibamba Power Development Company. Low Carbon Econ. 4, 35–40 (2013).

    Article  Google Scholar 

  36. Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).

    Article  Google Scholar 

  37. Hwang, S., Cao, Y. & Xi, J. The short-term impact of involuntary migration in China’s Three Gorges: a prospective study. Social Indic. Res. 101, 73–92 (2011).

    Article  Google Scholar 

  38. Belletti, B. et al. More than one million barriers fragment Europe’s rivers. Nature 588, 436–441 (2020).

    Article  CAS  Google Scholar 

  39. Schiermeier, Q. Europe is demolishing its dams to restore ecosystems. Nature 557, 290–291 (2018).

    Article  CAS  Google Scholar 

  40. Sharma, S., Waldman, J., Afshari, S. & Fekete, B. Status, trends and significance of American hydropower in the changing energy landscape. Renew. Sustain. Energy Rev. 101, 112–122 (2019).

    Article  Google Scholar 

  41. Arbuckle, E. et al. Insights for Canadian electricity generation planning from an integrated assessment model: should we be more cautious about hydropower cost overruns. Energy Policy 150, 112138 (2021).

    Article  Google Scholar 

  42. Nazareno, A. & Lovejoy, T. Giant dam threatens Brazilian rainforest. Nature 478, 37 (2011).

    Article  CAS  Google Scholar 

  43. Pritchard, H. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654 (2019).

    Article  CAS  Google Scholar 

  44. Ran, L. & Lu, X. X. Cooperation is key to Asian hydropower. Nature 473, 452 (2011).

    Article  CAS  Google Scholar 

  45. Hugonnet, R., McNabb, R. & Berthier, E. Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726–731 (2021).

    Article  CAS  Google Scholar 

  46. Farinotti, D., Pistocchi, A. & Huss, M. From dwindling ice to headwater lakes: could dams replace glaciers in the European Alps? Environ. Res. Lett. 11, 054022 (2016).

    Article  Google Scholar 

  47. Shukla, T. & Sen, I. Preparing for floods on the Third Pole. Science 372, 232–234 (2021).

    Article  CAS  Google Scholar 

  48. Jacobson, M. et al. 100% clean and renewable wind, water, and sunlight all-sector energy roadmaps for 139 countries of the world. Joule 1, 15–17 (2017).

    Article  Google Scholar 

  49. Yamazaki, D. et al. A high-accuracy map of global terrain elevations. Geophys. Res. Lett. 44, 5844–5853 (2017).

    Article  Google Scholar 

  50. Yamazaki, D., Ikeshima, D. & Sosa, J. MERIT Hydro: a high-resolution global hydrography map based on latest topography dataset. Water Resour. Res. 55, 5053–5073 (2019).

    Article  Google Scholar 

  51. Beck, H. et al. MSWEP V2 global 3-hourly 0.1° precipitation: methodology and quantitative assessment. Bull. Am. Meteorol. Soc. 100, 473–500 (2019).

    Article  Google Scholar 

  52. The World Database on Protected Areas (WDPA) (UNEP-WCMC, 2015)

  53. KML Layer of Natural and Mixed World Heritage Sites as Recorded in the World Database on Protected Areas (WDPA) (IUCN and UNEP-WCMC, 2013); https://www.arcgis.com/home/item.html?id=ef1ecce8fa3e41d89688be6199b5b32c

  54. Lehner, B. & Dölla, P. Development and validation of a global database of lakes, reservoirs and wetlands. J. Hydrol. 296, 1–22 (2004).

    Article  Google Scholar 

  55. Turubanova, S., Potapov, P. & Tyukavina, A. Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environ. Res. Lett. 13, 074028 (2018).

    Article  Google Scholar 

  56. Xu, J., Morris, P., Liu, J. & Holden, J. PEATMAP: refining estimates of global peatland distribution based on a meta-analysis. Catena 160, 134–140 (2018).

    Article  Google Scholar 

  57. LandScan 2019 Global Population Database (Oak Ridge National Laboratory, 2020); https://landscan.ornl.gov/

  58. Fischer G. et al. Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008) (IIASA, Laxenburg, Austria and FAO, 2008); https://pure.iiasa.ac.at/id/eprint/6182/1/IR-00-064.pdf

  59. Shedlock, K. M., Giardini, D., Grunthal, G. & Zhang, P. The GSHAP Global Seismic Hazard Map. Seismol. Res. Lett. 71, 679–686 (2000).

    Article  Google Scholar 

  60. Dijkstra, E. W. A note on two problems in connexion with graphs. Numer. Math. 1, 269–271 (1959).

    Article  Google Scholar 

  61. Farinotti, D. et al. Large hydropower and water-storage potential in future glacier-free basins. Nature 575, 341–344 (2019).

    Article  CAS  Google Scholar 

  62. Kummu, M., Taka, M. & Guillaume, J. Gridded global datasets for Gross Domestic Product and Human Development Index over 1990–2015. Sci. Data 5, 180004 (2018).

    Article  Google Scholar 

  63. UK National Ecosystem Assessment Technical Report (UNEP-WCMC, 2011); http://uknea.unep-wcmc.org/

  64. Land Values 2020 Summary (United States Department of Agriculture, 2020); https://www.nass.usda.gov/Publications/Todays_Reports/reports/land0820.pdf#:~:text=4%20Land%20Values%202020%20Summary%20%28August%202020%29%20USDA%2C,per%20acre%20for%202020%2C%20no%20change%20from%202019

  65. Spawn, S., Sullivan, C., Lark, T. & Gibbs, H. Harmonized global maps of above and belowground biomass carbon density in the year 2010. Sci. Data 7, 112 (2020).

    Article  Google Scholar 

  66. IUCN and CIESIN, Global Amphibian Richness Grids, 2015 Release (2013) (NASA and SEDAC, 2015); https://doi.org/10.7927/H4RR1W66

  67. National Inventory of Dams (Federal Emergency Management Agency, 2022); https://www.fema.gov/emergency-managers/risk-management/dam-safety/national-inventory-dams

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Z.Z., grant nos. 42071022 and 72173058), the start-up fund of the Southern University of Science and Technology (Z.Z., 29/Y01296122), the UK Natural Environment Research Council’s Integrated Catchment Solutions Programme (J.H., grant no. NE/P011160/1), the innovation programme under the Marie Skłodowska-Curie grant agreement (D.V.S., grant no. 765553) and the Euro-FLOW project (a European training and research network for environmental flow management in river basins), which received funding from the European Union’s Horizon 2020 research programme and innovation programme under the Marie Skłodowska-Curie grant agreement No 765553 (L.E.B). We thank the Terrestrial Hydrology Research Group at Princeton University for providing the state-of-the-art global run-off dataset. We are grateful to P. R. Elsen for insightful comments and valuable discussions on the manuscript.

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Author notes

  1. Deceased: Eric. F. Wood.

Authors and Affiliations

  1. School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China

    Rongrong Xu, Zhenzhong Zeng, Xinyue He, Bin Ye, Chunmiao Zheng, Junguo Liu, Junyu Zou & Dashan Wang

  2. Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA

    Ming Pan & Eric. F. Wood

  3. Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA

    Ming Pan & Yuan Yang

  4. Faculty of Fisheries Technology and Aquatic Resources, Mae Jo University, Chiang Mai, Thailand

    Alan D. Ziegler

  5. School of Geography & water@leeds, University of Leeds, Leeds, UK

    Joseph Holden & Lee E. Brown

  6. School of Earth and Environment, University of Leeds, Leeds, UK

    Dominick V. Spracklen & Xinyue He

  7. Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden

    Deliang Chen

  8. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, China

    Haiwei Xu

  9. Department of Physics, University of Murcia, Murcia, Spain

    Sonia Jerez

  10. School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, China

    Junguo Liu

  11. Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing, China

    Peirong Lin

  12. State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing, China

    Yuan Yang

  13. School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China

    Mingyi Gu

  14. Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA

    Zongliang Yang

  15. Department of Geography, National University of Singapore, Kent Ridge, Singapore

    Dongfeng Li

  16. International Clean Energy Research Office, China Three Gorges Corporation, Beijing, China

    Junling Huang

  17. Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA

    Venkataraman Lakshmi

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  1. Rongrong Xu
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Contributions

Conceptualization: R.X. and Z.Z. Methodology: R.X., Z.Z., A.D.Z., L.E.B., J.H. and D.V.S. Investigation: R.X. Visualization: R.X. Funding acquisition: Z.Z., L.E.B. and J.H. Project administration: Z.Z. Supervision: Z.Z. Writing—original draft: R.X. Writing—review and editing: all authors contributed to interpreting results, and writing and editing the manuscript.

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Correspondence to Zhenzhong Zeng.

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Xu, R., Zeng, Z., Pan, M. et al. A global-scale framework for hydropower development incorporating strict environmental constraints. Nat Water 1, 113–122 (2023). https://doi.org/10.1038/s44221-022-00004-1

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