Scope and limitations of drought management within complex human–natural systems

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Abstract

Growing evidence suggests that drought risk is increasing due to climate change. Evaluation of potential policy responses involves understanding complex economic tradeoffs, hydrologic and social feedbacks, and recognizing how combinations of interventions may have complementary or conflicting effects. This paper explores the potential that coupled human–natural system models have to address these questions. We employ a detailed model of the Willamette River Basin, Oregon, to evaluate the effectiveness of a variety of potential drought policy interventions to conserve or reallocate water during a simulated near-term drought year. The drought year is characterized by early-season low flows that make it impossible to meet water demands. The results indicate that while the policies are effective at conserving water, they have limited ability to mitigate the shortages because the timing and location of conservation responses do not match the timing and location of the shortages.

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Fig. 1: The Willamette Basin WRB covers 29,730 km2 (11,480 square miles), approximately 12% of Oregon’s land area.
Fig. 2: Diagram of the Willamette River Basin model.
Fig. 3: Hydrographs of Willamette River flows.
Fig. 4: Conservation and mitigation potential of policies.
Fig. 5: Hydrographs of drought mitigation.

Data availability

Details of the Willamette Envision models and scenarios used for the analysis described in this paper can be found at http://inr.oregonstate.edu/ww2100/data.

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Acknowledgements

This project was supported by the National Science Foundation (grant Nos. 1039192 (Oregon State University), 1038925 (Portland State University) and 1038899 (University of Oregon)). We also acknowledge support from NOAA’s Climate Program Office under cooperative agreement No. NA15OAR4310145.

Author information

All authors contributed equally.

Correspondence to William K. Jaeger.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Methods, References 1–26, Tables 1–7 and Figs. 1–4.

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