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![Page 1: Description and validation of a streamflow assimilation system for a distributed hydrometeorological model over France. Impacts on the ensemble streamflow.](https://reader036.fdocuments.net/reader036/viewer/2022070305/5513ec845503466f748b59eb/html5/thumbnails/1.jpg)
Description and validation of a streamflow assimilation system for a distributed
hydrometeorological model over France. Impacts on the ensemble streamflow
forecasts
G. Thirel, E. Martin, J.-F. Mahfouf (CNRM/Météo-France),
S. Massart, S. Ricci (CERFACS),
F. Regimbeau (DCLIMHYDRO/Météo-France),
F. Habets (UMR Sisyphe Mines ParisTech)
![Page 2: Description and validation of a streamflow assimilation system for a distributed hydrometeorological model over France. Impacts on the ensemble streamflow.](https://reader036.fdocuments.net/reader036/viewer/2022070305/5513ec845503466f748b59eb/html5/thumbnails/2.jpg)
Introduction
2 ensemble streamflow prediction systems (ESPS) at a short- and mid-term range at Météo-France– Based on the distributed hydrometeorological model SIM
– ECMWF EPS-based ESPS (10-day range, 1.5°, 51 members)
– PEARP-based ESPS (60-h range, 0.25°, 11 members)
Need to improve the initial states by an assimilation system– Use of observed discharges
– Description
– Validation over 18 months
Impacts of the assimilation system on the ECMWF EPS-based ESPS
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ISBA
Physiographic data for soil and vegetation
+
MODCOU
QrQi
E
H
G
Aquifer
DailyStreamflow
Surface scheme
Snow
SAFRANObservations + NWP modelsPPrecipitation, temperature, humidity, wind, radiations
Hydrological modelPoor
Weak to moderate
Good
Nash
Habets et al. (2008)
Meteorological analysis
The SIM hydro-meteorological model
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The SIM based ESPS
ObservationsMeteor. models
ANALYSIS RUN (daily)
SAFRAN10-year
climatology Wind, Rad.,
Humidity
SOIL WAT. TABLES
RIVERS FINAL STATE
ECMWF/PEARP Ensemble forecasts51/11 members, 11/2-day forecasts
ENSEMBLE FORECASTS
T+ Precip Spatial
DESAGGREGATION
ISBA MODCOU
ENSEMBLE FORECAST
SOIL WAT. TABLES
RIVERS FINAL STATES
ISBA MODCOU
SOIL WAT. TABLES
RIVERS STATE
Initial states of ESPS : need for improvement
Adjusted by BLUE
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Strategy
186 stations assimilated over France– Low human influence
– Good quality of observations
– Not too bad results given by SIM
Aim : to use observed discharges in
order to improve streamflow simulation,
by adjusting the ISBA soil moisture
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The BLUE equations
Analysed state
Background state
Innovation vector
Jacobian H :
H determines the sensitivity of streamflows to soil moisture variations
Hypothesis : linearity of the model
-> H is computed with SIM runs initialized by perturbed soil moisture states (perturbation around 0.1%)
Observed streamflows
streamflows
x : control variable
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Jacobian matrix filling
3 gauging stations Q1, Q2 et Q3.
w1, w2 et w3 moderated sums of soil moistures on the basins
Jacobian matrix :
0
0 0
0
basins
stations
186 stations
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Principle of the assimilation system
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Experiments (10 March 2005 / 30 September 2006, 186 stations)
6 experiments : 3 variable states * 2 physics of the model
Daily assimilation, daily observations
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IS2 (and IS1) will be retained
IS2 combines the best Nash and rmse scores, and the lowest increments
The Doubs at Besançon
Scores for a selection of 148 stations
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An exemple of the impacts on the ESPS
IS2
IS1
No assimilation
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Some statistical scores
Scores for a selection of 148 assimilated stations, for the 10-day SIM-ECMWF
Spread of the ensemble
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RMSE
Scores computed against observed streamflows
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Brier Skill Score day 1 and day 10
Day 1
Day 10
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Conclusions and perspectives
A streamflow assimilation system has been implemented and validated for the SIM suite
– Better simulation of flows and initial states for the ESPSs (Thirel et al., submitted to the Journal of Hydrology)
Significative improvement of ensemble streamflow forecasts when initialized by the assimilated SIM suite
– Lower RMSE, better BSS and RPSS (due to the assimilation for the first days, then due to the exponential profile)
– Few differences between SIM-PEARP and SIM-ECMWF, difficult to conclude– It is the first time that the ensemblist SIM is compared to observations, not a
reference run
Perspectives : – Optimizing computing costs and the quality of the assimilation system (R and B
matrices to better estimate)– Using another operator (EnKF?)– Implementing the assimilation system into the SIM-ECMWF operational suite
(2012?)
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Thank you for your attention!