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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-486
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-486
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 07 Oct 2019

Submitted as: research article | 07 Oct 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

Sean W. D. Turner1, Wenwei Xu1, and Nathalie Voisin1,2 Sean W. D. Turner et al.
  • 1Pacific Northwest National Laboratory, Seattle, WA, USA
  • 2University of Washington, Seattle, WA, USA

Abstract. Medium to long-range forecasts often guide reservoir release decisions to support water management objectives, including mitigating flood and drought risks. While there is a burgeoning field of science targeted at improving forecast products and associated decision support models, data describing how and when forecasts are applied in practice remains undeveloped. This lack of knowledge may prevent hydrological modelers from developing accurate reservoir release schemes for large-scale, distributed hydrology models that are increasingly used to assess the vulnerabilities of large regions to hydrological stress. We address this issue by estimating seasonally-varying, regulated inflow forecast horizons used in the operations of more than 300 dams throughout the Conterminous United States. For each dam, we take actual forward observed inflows (perfect foresight) as a proxy for forecasted flows available to the operator, and then identify for each week of the year the forward horizon that best explains the release decisions taken. Resulting horizon curves specify for each dam the inferred horizon as a function of the week of the water year. These curves are analyzed for strength of evidence for contribution of medium to long-range forecasts in decision making. We use random forest classification to estimate that approximately 80 % of large dams and reservoirs in the US (1553 ± 50 out of 1927 dams with at least 10 Mm3 storage capacity) adopt medium to long-range inflow forecasts to inform release decisions during at least part of the water year. Long-range forecast horizons (more than six weeks ahead) are detected in the operations of reservoirs located in high elevation regions of the Western US, where snowpack information likely guides the release. A simulation exercise conducted on a selection of key reservoirs demonstrates that forecast-informed models of reservoir operations outperform models that neglect the horizon curve – including during flood and drought conditions.

Sean W. D. Turner et al.
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Sean W. D. Turner et al.
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Short summary
To understand human vulnerability to flood and drought risk, researchers increasingly use hydrology models that convert precipitation to river flows at global or regional spatial scales. State-of-the-art models include the effects of river regulation by dams. These models currently lack representation dam operators' use of water forecasts to mitigate risk. This research provides a dataset of estimated forecast horizons to guide more realistic water release schemes in large-scale hydrology models.
To understand human vulnerability to flood and drought risk, researchers increasingly use...
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