Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK
<p>Improved skill of long-range weather forecasts has motivated an increasing effort towards developing seasonal hydrological forecasting systems across Europe. Among other purposes, such forecasting systems are expected to support better water management decisions. In this paper we evaluate t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-12-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://hess.copernicus.org/articles/24/6059/2020/hess-24-6059-2020.pdf |
| Summary: | <p>Improved skill of long-range weather forecasts has
motivated an increasing effort towards developing seasonal hydrological
forecasting systems across Europe. Among other purposes, such forecasting
systems are expected to support better water management decisions. In this
paper we evaluate the potential use of a real-time optimization system
(RTOS) informed by seasonal forecasts in a water supply system in the UK.
For this purpose, we simulate the performances of the RTOS fed by ECMWF
seasonal forecasting systems (SEAS5) over the past 10 years, and we compare
them to a benchmark operation that mimics the common practices for reservoir
operation in the UK. We also attempt to link the improvement of system
performances, i.e. the forecast value, to the forecast skill (measured by
the mean error and the continuous ranked probability skill score) as well as
to the bias correction of the meteorological forcing, the decision maker
priorities, the hydrological conditions and the forecast ensemble size. We find
that in particular the decision maker priorities and the hydrological
conditions exert a strong influence on the forecast skill–value
relationship. For the (realistic) scenario where the decision maker
prioritizes the water resource availability over energy cost reductions, we
identify clear operational benefits from using seasonal forecasts, provided
that forecast uncertainty is explicitly considered by optimizing against an
ensemble of 25 equiprobable forecasts. These operational benefits are also
observed when the ensemble size is reduced up to a certain limit. However,
when comparing the use of ECMWF-SEAS5 products to ensemble streamflow
prediction (ESP), which is more easily derived from historical weather
data, we find that ESP remains a hard-to-beat reference, not only in terms of
skill but also in terms of value.</p> |
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| ISSN: | 1027-5606 1607-7938 |