PREMHYCE: An operational tool for low-flow forecasting
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Published:2020-09-16
Issue:
Volume:383
Page:381-389
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ISSN:2199-899X
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Container-title:Proceedings of the International Association of Hydrological Sciences
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language:en
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Short-container-title:Proc. IAHS
Author:
Nicolle PierreORCID, Besson François, Delaigue OlivierORCID, Etchevers PierreORCID, François Didier, Le Lay Matthieu, Perrin Charles, Rousset Fabienne, Thiéry Dominique, Tilmant François, Magand Claire, Leurent Timothée, Jacob Élise
Abstract
Abstract. In many countries, rivers are the primary supply of
water. A number of uses are concerned (drinking water, irrigation,
hydropower, etc.) and they can be strongly affected by water
shortages. Therefore, there is a need for the early anticipation of low-flow
periods to improve water management. This is strengthened by the perspective
of having more severe summer low flows in the context of climate change.
Several French institutions (Inrae, BRGM, Météo-France, EDF and
Lorraine University) have been collaborating over the last years to develop
an operational tool for low-flow forecasting, called PREMHYCE. It was tested
in real time on 70 catchments in continental France in 2017, and on 48 additional catchments in 2018. PREMHYCE includes five hydrological models:
one uncalibrated physically-based model and four storage-type models of
various complexity, which are calibrated on gauged catchments. The models
assimilate flow observations or implement post-processing techniques.
Low-flow forecasts can be issued up to 90 d ahead, based on ensemble
streamflow prediction (ESP) using historical climatic data as ensembles of
future input scenarios. These climatic data (precipitation, potential
evapotranspiration and temperature) are provided by Météo-France
with the daily gridded SAFRAN reanalysis over the 1958–2017 period, which
includes a wide range of conditions. The tool provides numerical and
graphical outputs, including the forecasted ranges of low flows, and the
probability to be under low-flow warning thresholds provided by the users.
Outputs from the different hydrological models can be combined through a
simple multi-model approach to improve the robustness of forecasts. Results
are illustrated for the Ill River at Didenheim (northeastern France) where
the 2017 low-flow period was particularly severe and for which PREMHYCE
provided useful forecasts.
Publisher
Copernicus GmbH
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