Complex relationship between seasonal streamflow forecast skill and value in reservoir operations
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 ri...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/21/4841/2017/hess-21-4841-2017.pdf |
| Summary: | 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. |
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| ISSN: | 1027-5606 1607-7938 |