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Title: Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

Abstract

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance ifmore » a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.« less

Authors:
 [1]; ORCiD logo [2];  [3]; ORCiD logo [4]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Singapore Univ. of Technology and Design (Singapore). SUTD-MIT International Design Centre
  2. CSIRO, Melbourne, Clayton, Vic (Australia); Univ. of Tasmania, Hobart, TAS (Australia). Inst. for Marine and Antarctic Studies
  3. CSIRO, Melbourne, Clayton, Vic (Australia)
  4. Singapore Univ. of Technology and Design (Singapore). Pillar of Engineering Systems and Design
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1398219
Report Number(s):
PNNL-SA-126975
Journal ID: ISSN 1607-7938
Grant/Contract Number:  
AC05-76RL01830; IDG 21400101
Resource Type:
Accepted Manuscript
Journal Name:
Hydrology and Earth System Sciences (Online)
Additional Journal Information:
Journal Name: Hydrology and Earth System Sciences (Online); Journal Volume: 21; Journal Issue: 9; Journal ID: ISSN 1607-7938
Publisher:
European Geosciences Union (EGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 42 ENGINEERING; dams; seasonal forecasts; reservoir operations; optimization

Citation Formats

Turner, Sean W. D., Bennett, James C., Robertson, David E., and Galelli, Stefano. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations. United States: N. p., 2017. Web. doi:10.5194/hess-21-4841-2017.
Turner, Sean W. D., Bennett, James C., Robertson, David E., & Galelli, Stefano. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations. United States. doi:10.5194/hess-21-4841-2017.
Turner, Sean W. D., Bennett, James C., Robertson, David E., and Galelli, Stefano. Thu . "Complex relationship between seasonal streamflow forecast skill and value in reservoir operations". United States. doi:10.5194/hess-21-4841-2017. https://www.osti.gov/servlets/purl/1398219.
@article{osti_1398219,
title = {Complex relationship between seasonal streamflow forecast skill and value in reservoir operations},
author = {Turner, Sean W. D. and Bennett, James C. and Robertson, David E. and Galelli, Stefano},
abstractNote = {Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.},
doi = {10.5194/hess-21-4841-2017},
journal = {Hydrology and Earth System Sciences (Online)},
number = 9,
volume = 21,
place = {United States},
year = {2017},
month = {9}
}

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    Works referencing / citing this record:

    Spatio-temporal changes and their relationship in water resources and agricultural disasters across China
    journal, March 2019


    Prediction of Reservoir Storage Anomalies in India
    journal, April 2019

    • Tiwari, Amar Deep; Mishra, Vimal
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    Prediction of Reservoir Storage Anomalies in India
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