skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

Abstract

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short–term and long–term guarantees as to how much water or energymore » they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. In conclusion, the issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real–world perspective and needs a suitable institutional environment.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [3]
  1. Hong Kong Univ. of Science and Technology, Hong Kong SAR (China); Columbia Univ., New York, NY (United States)
  2. Columbia Univ., New York, NY (United States); Columbia Univ., Palisades, NY (United States)
  3. Columbia Univ., Palisades, NY (United States)
Publication Date:
Research Org.:
Columbia Univ., New York, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1466032
Alternate Identifier(s):
OSTI ID: 1402145
Grant/Contract Number:  
SC0006616
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Water Resources Research
Additional Journal Information:
Journal Volume: 53; Journal Issue: 3; Journal ID: ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; market-based reliable and insurable contracts; climate‐informed water management; hierarchical multitime scales ensemble forecasts; prescribed reliability for supplies; dynamic flood control storage allocation; nonlinear global optimization

Citation Formats

Lu, Mengqian, Lall, Upmanu, Robertson, Andrew W., and Cook, Edward. Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts. United States: N. p., 2017. Web. doi:10.1002/2016WR019552.
Lu, Mengqian, Lall, Upmanu, Robertson, Andrew W., & Cook, Edward. Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts. United States. doi:10.1002/2016WR019552.
Lu, Mengqian, Lall, Upmanu, Robertson, Andrew W., and Cook, Edward. Tue . "Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts". United States. doi:10.1002/2016WR019552. https://www.osti.gov/servlets/purl/1466032.
@article{osti_1466032,
title = {Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts},
author = {Lu, Mengqian and Lall, Upmanu and Robertson, Andrew W. and Cook, Edward},
abstractNote = {Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short–term and long–term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. In conclusion, the issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real–world perspective and needs a suitable institutional environment.},
doi = {10.1002/2016WR019552},
journal = {Water Resources Research},
number = 3,
volume = 53,
place = {United States},
year = {Tue Feb 21 00:00:00 EST 2017},
month = {Tue Feb 21 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 1 work
Citation information provided by
Web of Science

Save / Share: