TURBULENT FLUX VARIABILITIES OVER THE ARA WATERSHED

Moussa Doukouré, Sandrine Anquetin, Jean-Martial Cohard

Laboratoire d’étude des Transferts en Hydrologie et Environnement (LTHE)

Grenoble, France

INTRODUCTION

The determination of turbulent fluxes is very important for the closure of energy balance equation.

In an agrometeorological point of view :

Assessment of the evapotranspiration term that quantifies water needed by plants

► Evaluate water scarcity and agricultural strategy.

In an hydrological point of view :

Close the water balance at the watershed scale

► Evaluate the water ressources avalaible for both population needs and energy production

Usual technical measurement

- Point measurement

Difficulties in measuring

Surface heterogeneities (temperature, soil humidity, topography) and atmospheric state generate secondary circulation and rolls that make difficult the accurate measurement of turbulent fluxes with conventional measurements (EC)

Simulated water vapour mixing ratio over Hamdallaye watershed (Niger)

Simulated organized turbulent structures

INTRODUCTION

(Steinfeld et al, 2006)

(Lothon et al,2007)

Problem of averaged data representative of the surfaces

Problem of flux sources control for more acurate analyses

Better estimation from the time and space average than from point measurement

Need to characterize the variability below the LAS path, wind direction and stability parameter

►Take into account the 3 dimensionnal (3D) behavior of the turbulent fluxes

► Analyse the footprint

Another concept of measurement: Large Aperture Scintillometer (LAS)

Savannah bushes

Savannah trees

Cultures and/or bare soils

Case Study : The ARA watershed (~12 km2) in Nalohou

(North part of Benin)

INTRODUCTION

Also a problem of representativeness !!!

Topography, atmospheric and ground forcings for a case study of 10/04/2006

►Use Meso-NH model (Lafore et al, 1998)

Use of atmospheric 3D model including Large-Eddy Simulation (LES) approach can resolve part of these problems.

Use of an atmospheric model coupled with land surface scheme

METHODOLOGY

Perform sensitivity studies

► Impact on the turbulent flux variabilities

1.23 2.23

10.36

9.36

1.891.399.53

10.03

1.771.44

9.91

9.58

9.83

9.611.48 1.70

Δx= Δy=18km

Cyclic boundary conditions

Δx= Δy=6km

Open boundary conditions

Δx= Δy=1km

Open boundary conditions

Δx= Δy=2km

Open boundary conditions

Δx= Δy=250m

Open boundary conditions

1.559.72

9.79

1.63

Altitude (m)

MODELING STRATEGY 5 nested domains (Two-way)

Topography - SRTM 90m

ECMWF radiation scheme

SURFEX soil-vegetation-atmospheric-transfer model (Noilhan and Planton, 1989)ECOCLIMAP (Masson et, al 2003) (1km2) for vegetation parameters

LES, sub-grid paramerization of Deardorff

Clear sky conditions

MODELING STRATEGY

Homogeneous sahelian woodland

Spot vegetation at 20m resolution ( Zin et al, 2009)

Can ECOCLIMAP be usefull for our study ?

Initialization : sounding at Parakou,10/04/2006 at 10.30 AM

MODELING STRATEGY

virtual potential temperature at 10.30 day 10/04/2009

393

1393

2393

3393

4393

5393

307 312 317 322 327

Virtual potentiail temperature (°K)

Alt

itu

de

(m)

Vertical profil of v at 10:30, 10/04/2006

10/04/2006

10.30 AM11/04/200

6 10.30 AM

Extraction of data at each time step.

20 minutesSimulation strategy

24h simulation, diurnal cycle, radiation scheme activeradiation scheme

OFF

PRELIMINARY RESULTS: WIND ROTATION

Initial South-Westerly wind forcing Final North and North-West wind

Δx= Δy=18km

Cyclic boundary conditions

Dynamic forcing no maintained

PRELIMINARY RESULTS: FLUX VARIABILITY OVER CATCHMENT SCALE

Turbulent latent heat flux

Turbulent sensible heat flux

► Highest values on the crests and advected in lower zones

W/m2

W/m2

PRELIMINARY RESULTS: IMPACT OF THE TOPOGRAPHY ON THE FLUX VARIABILITIES

m.s-1

m.s-1

Vertical wind over flat terrain

Vertical wind over the « real » topographySame meteorological forcings !

Vertical wind organized as convective rolls

Vertical motion organized according to orographic structures

► Highest values over flat terrain rather than over « real » topography.

► Vertical motion modified by the orography structure

PRELIMINARY RESULTS: SCINTILLOMETER FOOPRINT ANALYSIS

Latent heat flux over flat terrainLatent heat flux with topography

Min : 122 W/m2Max : 137 W/m2Mean : 127 W/m2Std : 4.4 W/m2

Min : 153 W/m2Max :  169 W/m2Mean : 163 W/m2Std : 4.4 W/m2

Latent Heat Flux « seen » by the scintillometer

The local wind has an impact on the shape of the footprint

CONCLUSION AND PRESPECTIVES

Improve the vegetation cover description by using satellite analysis (Zin et al., 2009)

►

- Wind rotation probably due to cyclic boundary condition

- High values of fluxes observed over crests and advected into the lower zones

- Wind circulation influenced by the horizontal gradient of turbulent fluxes

Conclusion

Perspectives

Attempt to improve simulations with OPEN boundary condition that is better to maintain wind direction

ECOCLIMAP Satelite data

Probably use of ECMWF reanalysis as forcing data !!!

Many thanks !