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Potential hydropower contribution to mitigate climate risk and build resilience in Africa

Abstract

Hydropower will play an essential role in meeting the growing energy needs in Africa but will be affected by climate change. We assess future annual usable capacity and variability of supply for 87 existing hydropower plants in Africa on the basis of a multimodel ensemble of 21 global climate models and two emissions scenarios (representative concentration pathways RCP 4.5 and 8.5). We estimate near-future, mid-century and end-of-the-century impacts and assess the potential for connections within and across power pools to reduce changes in usable capacity and variability. We evaluate the potential synergies between hydropower, wind and solar resources in each power pool. We find that regional interconnection could mitigate some of the climate impacts on hydropower. Furthermore, variable renewable energy, especially solar power, could potentially compensate for usable hydropower capacity losses. Our work contributes to a better understanding of the climate-induced impacts on hydropower resources in Africa and potential risk mitigation opportunities.

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Fig. 1: Hydropower plants in the COMELEC, CAPP, WAPP, EAPP and SAPP included in the analysis.
Fig. 2: Mean relative changes in annual normalized usable capacity for RCP 4.5 and RCP 8.5.
Fig. 3: Mean relative changes in annual normalized usable capacity for RCP 4.5 and RCP 8.5 at the power-pool level.

Data availability

We use open-access datasets to perform all calculations and analyses. Supplementary Table 13 summarizes the datasets collected for their application in the streamflow and hydropower formulations. We present the locations and characteristics of the power plants in Supplementary Table 1. We provide the individual time series in our online repository78. Finally, we present the complete list of GCMs used in Supplementary Table 14. The datasets generated and analysed during the current study are available in the zenodo repository (https://doi.org/10.5281/zenodo.5020878)80.

Code availability

R and Python codes used in the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This study was supported by the Rockefeller Foundation through a subcontract with the University of Massachusetts at Amherst (subaward no. 19-10766 A 00). This article was prepared while C.S. was affiliated with Carnegie Mellon University. The opinions expressed in this article are the authors’ own and do not reflect the view of the US government or any other organization.

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A.L.C., P.J., H.S.M., C.S. and B.N. conceived and designed the study. A.L.C. collected the data, developed the model, developed the results and led the manuscript preparation. All authors interpreted the results and contributed to the manuscript writing.

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Correspondence to Ana Lucía Cáceres.

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Competing interests

C.S. declares a potentially perceived non-financial competing interest. After the completion of this paper, C.S. began a temporary mobility employment assignment with the US government through the Intergovernmental Personnel Act. C.S. is on Public Service Leave and this article was prepared while he was employed at Carnegie Mellon University. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Aggregated usable capacity for the COMELEC, CAPP, EAPP, SAPP, and WAPP.

The boxplots present the results from the multimodel ensemble of 21 GCM experiments for the 1970–2005 historical reference (wheat), RCP 4.5 (orange), and RCP 8.5 (purple). Each column presents the time frame of the analysis: near-future (2010–2039), mid-century (2040–2069), and end-of-century (2070–2099). The scales of each of the panels are different depending on the power pool.

Extended Data Fig. 2 Probability Density Function of Aggregated Multi-Model Ensemble Power Pool Usable Capacity Time Series.

The Y axis of the plot represents the probability for a usable capacity (MW) value for the power pool. We include all five power pools in the analysis (COMELEC, WAPP, CAPP, EAPP, and SAPP). We present three scenarios (historical reference, RCP 4.5, and RCP 8.5) and three time frames (early century – 2010–2039, mid-century – 2040–2069, and end of the century – 2070–2099). We present the historical reference in “wheat” colour, RCP 4.5 in “orange” colour, and RCP 8.5 in “purple” colour.

Extended Data Fig. 3 Exceedance Probability of Aggregated Multi-Model Ensemble Power Pool Usable Capacity Time Series.

The Y axis of the plot represents the exceedance probability of usable capacity (MW) for the power pool. We include all five power pools in the analysis (COMELEC, WAPP, CAPP, EAPP, and SAPP). We present three scenarios (historical reference, RCP 4.5, and RCP 8.5) and three time frames (early century – 2010–2039, mid-century – 2040–2069, and end of the century – 2070–2099). We present the historical reference in “wheat” colour, RCP 4.5 in “orange” colour, and RCP 8.5 in “purple” colour.

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Supplementary Notes 1–3, Figs. 1–22, Tables 1–14 and references.

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Cáceres, A.L., Jaramillo, P., Matthews, H.S. et al. Potential hydropower contribution to mitigate climate risk and build resilience in Africa. Nat. Clim. Chang. 12, 719–727 (2022). https://doi.org/10.1038/s41558-022-01413-6

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