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Mid-latitude freshwater availability reduced by projected vegetation responses to climate change

Nature Geoscience volume 12, pages 983–988 (2019)Cite this article

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Abstract

Plants are expected to generate more global-scale runoff under increasing atmospheric carbon dioxide concentrations through their influence on surface resistance to evapotranspiration. Recent studies using Earth System Models from phase 5 of the Coupled Model Intercomparison Project ostensibly reaffirm this result, further suggesting that plants will ameliorate the dire reductions in water availability projected by other studies that use aridity metrics. Here we complicate this narrative by analysing the change in precipitation partitioning to plants, runoff and storage in multiple Earth system models under both high carbon dioxide concentrations and warming. We show that projected plant responses directly reduce future runoff across vast swaths of North America, Europe and Asia because bulk canopy water demands increase with additional vegetation growth and longer and warmer growing seasons. These runoff declines occur despite increased surface resistance to evapotranspiration and vegetation total water use efficiency, even in regions with increasing or unchanging precipitation. We demonstrate that constraining the large uncertainty in the multimodel ensemble with regional-scale observations of evapotranspiration partitioning strengthens these results. We conclude that terrestrial vegetation plays a large and unresolved role in shaping future regional freshwater availability, one that will not ubiquitously ameliorate future warming-driven surface drying.

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Fig. 1: Vegetation and water availability projections.
Fig. 2: Relative changes in the hydrological budget at the land surface.
Fig. 3: Absolute changes in the hydrological budget at the land surface.
Fig. 4: The relationship between relative and absolute hydrological changes.

Data availability

All data supporting the findings of this study are freely available from the following locations: CMIP5 model data: https://pcmdi.llnl.gov.

Code availability

All code to reproduce the results of this study are available on reasonable request from the corresponding author.

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Acknowledgements

We thank the Earth System Grid Federation and their archiving of the Coupled Model Intercomparison Project (phase 5) data and N. Henderson and H. Liu for the data serving and computing support in the Division of Ocean and Climate Physics at Lamont-Doherty Earth Observatory of Columbia University. We also greatly appreciate Z. Wei for kindly sharing his ET partitioning data29. J.S.M. was funded by the Burke Research Initiation Award and the National Science Foundation award AGS‐1243204, which also supported R.S. and J.E.S. Additional support for R.S. and J.E.S. was provided by National Science Foundation awards GS‐1401400, AGS‐1805490, AGS-1602581 and OISE-1743738. B.I.C. was supported by the NASA Modeling, Analysis, and Prediction. A.P.W. was supported by National Science Foundation award AGS-1703029 and NASA award 16-MAP16-0081. Lamont contribution #8359.

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Authors and Affiliations

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

    Justin S. Mankin

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

    Justin S. Mankin

  3. Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA

    Justin S. Mankin, Richard Seager, Jason E. Smerdon, Benjamin I. Cook & A. Park Williams

  4. NASA Goddard Institute for Space Studies, New York, NY, USA

    Benjamin I. Cook

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Contributions

J.S.M., R.S., J.E.S., B.I.C. and A.P.W. conceived the study. J.S.M. designed and performed the analysis. All authors interpreted the results. J.S.M. wrote the manuscript with all authors providing critical input.

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Correspondence to Justin S. Mankin.

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Extended data

Extended Data Fig. 1 Precipitation partitioning in the present and future.

a., WY partitioning [mm/yr] of precipitation (P) among the canopy (C/P, green), runoff (Q/P, blue), and soil + storage (S/P, red), shown as fluxes in the current climate. All else equal, high [CO2] and warming-induced VPD could close stomata, decreasing transpiration and increasing soil water and runoff, as in b. Soil water and runoff could alternatively decrease as longer and warmer growing seasons and CO2 fertilization increase ecosystem water demands, leading to reductions in soil water and runoff, as in c.

Extended Data Fig. 2 Precipitation and leaf area index (LAI) changes.

End-of-century changes in average a., WY precipitation (mm mo-1) and b., annual-scale leaf area index (LAI, unitless) for the ensemble mean. Red hatching indicates insignificant change based on a K-S test of the historical period (1976–2005) versus the future (2070–2099) and that at least 80% of the models agree on the direction of mean change at that point.

Extended Data Fig. 3 Relative change in the Blue Water Tradeoff.

As in Fig. 2a, but expressed as a fraction of historical WY runoff.

Extended Data Fig. 4 Accounting for interannual variation in precipitation partitioning in the present and future.

Performance of a statistical model of model- and region-based interannual WY (a) canopy partitioning, C/P, (b) runoff partitioning (Q/P), (c) and soil + storage partitioning (S/P). In each panel, the partitioning predicted by the statistical model (x-axis) is plotted against its actual value as simulated by the CMIP5 models for each grid point in each region. Historical years (1976–2005) and future years (2070–2099) are shown. The statistical model for each partitioning ratio and period is the same: Y = β0 + β1*(WY P) + β2*(WY T) + β3*( < X > ), where Y is either WY C/P, WY Q/P, WY S/P and < X > is a set of model and region control variables. The 1:1 line is shown in each panel.

Extended Data Fig. 5 Model-by-model correlations among partitioning, temperature, and precipitation.

Model- and region-based Spearman’s rank correlation of historical (1976–2005) partitioning ratios with historical precipitation (a-c) and temperature (d-f).

Extended Data Fig. 6 Regional-scale blue water tradeoff time series.

Ensemble mean time series in the runoff loss to the canopy, the blue water tradeoff (BWT) for the five regions as an anomaly from the 1976–2005 baseline. Positive (brown) values indicate the amount of WY precipitation going to the canopies to the sacrifice of runoff; negative (blue) values show the opposite. Bolded lines in each regional time series panel signify signal emergence ( > 1) of the ensemble mean (μ/σ) in that year from the baseline (1976–2005).

Extended Data Fig. 7 BWT accounts for runoff changes.

Performance of a statistical model of model- and region-based centennial-scale changes in WY runoff (∆Q) without (a) and with (b) the canopy-runoff tradeoff (blue water tradeoff, BWT) metric. The model and region based ∆Q predicted by the statistical model (x-axis) is plotted against its actual value as simulated by the CMIP5 models for each region. The statistical model for (a) includes temperature and precipitation and their interaction: ∆Q = β0 + β1*(∆P) + β2*(∆T) + β3*(∆T*∆P). The statistical model for (b) adds the BWT value for each model and region. The 1:1 line is shown in each panel.

Extended Data Fig. 8 Accounting for regional canopy partitioning changes.

Performance of a statistical model of model- and region-based centennial-scale changes in WY C/P (∆(C/P)). The ∆(C/P) predicted by the statistical model (x-axis) is plotted against its actual value as simulated by the CMIP5 models for each region. The statistical model includes temperature and precipitation and their interaction: ∆Q = β0 + β1*(∆LAI) + β2*(∆C/ET) + β3*(∆P) + β4*(∆T) + β5*(∆P*∆T). The 1:1 line is shown. In the standardized version of this model (that is, (X-μX)/σX), the coefficient of ∆(C/ET) is largest, twice that of ∆P.

Extended Data Fig. 9 Observational constraint for the blue water tradeoff.

Constraining the runoff loss to vegetation (blue water tradeoff, BWT) and changes in runoff, ∆Q. Because ∆C/ET dominates changes in C/P (see Fig. S8), we show the relationship between historical (observed period, 1982–2014) C/ET and future C/P in (a) across models and regions. For each region, we show the observational range ( + /− 1σ) of C/ET, derived from the sum of interception and transpiration from Wei et al. GRL (2017) as colored bars mapping to the x-axis, with colors corresponding to the inset map. (b) Bar plot of unconstrained (raw) versus constrained BWT and ∆Q for each region. Whiskers show 1 standard error of the mean.

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Mankin, J.S., Seager, R., Smerdon, J.E. et al. Mid-latitude freshwater availability reduced by projected vegetation responses to climate change. Nat. Geosci. 12, 983–988 (2019). https://doi.org/10.1038/s41561-019-0480-x

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