Inferred inflow forecast horizons guiding reservoir release decisions across the United States
Abstract
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 remain 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 (CONUS). 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 inflow forecast 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 approximatelymore »
- Authors:
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1605466
- Alternate Identifier(s):
- OSTI ID: 1616683
- Report Number(s):
- PNNL-SA-142797
Journal ID: ISSN 1607-7938
- Grant/Contract Number:
- 59534; AC05-76RL01830
- Resource Type:
- Published Article
- Journal Name:
- Hydrology and Earth System Sciences (Online)
- Additional Journal Information:
- Journal Name: Hydrology and Earth System Sciences (Online) Journal Volume: 24 Journal Issue: 3; Journal ID: ISSN 1607-7938
- Publisher:
- European Geosciences Union (EGU)
- Country of Publication:
- Germany
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Turner, Sean W. D., Xu, Wenwei, and Voisin, Nathalie. Inferred inflow forecast horizons guiding reservoir release decisions across the United States. Germany: N. p., 2020.
Web. doi:10.5194/hess-24-1275-2020.
Turner, Sean W. D., Xu, Wenwei, & Voisin, Nathalie. Inferred inflow forecast horizons guiding reservoir release decisions across the United States. Germany. https://doi.org/10.5194/hess-24-1275-2020
Turner, Sean W. D., Xu, Wenwei, and Voisin, Nathalie. Thu .
"Inferred inflow forecast horizons guiding reservoir release decisions across the United States". Germany. https://doi.org/10.5194/hess-24-1275-2020.
@article{osti_1605466,
title = {Inferred inflow forecast horizons guiding reservoir release decisions across the United States},
author = {Turner, Sean W. D. and Xu, Wenwei and Voisin, Nathalie},
abstractNote = {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 remain 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 (CONUS). 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 inflow forecast 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 6 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 four key western US reservoirs indicates that forecast-informed models of reservoir operations may outperform models that neglect the horizon curve – including during flood and drought conditions.},
doi = {10.5194/hess-24-1275-2020},
journal = {Hydrology and Earth System Sciences (Online)},
number = 3,
volume = 24,
place = {Germany},
year = {2020},
month = {3}
}
https://doi.org/10.5194/hess-24-1275-2020
Web of Science
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