Dominique Courault 1 et al

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1 Dominique Courault 1 et al 1 AVIGNON 2 Toulouse UMR TETIS Montpellier UMR Innovation CEEP réserve Crau Fondation Tour du Valat 1 1

2 SPOT4 on the mediterranean region biodiversity orchard A wide variety of landscapes, natural ecosystems, crops Urban areas Orange forests Lubéron Montpellier La Crau Camargue Martigues rice Wet areas SPOT4 14/4/2013 Irrigated grasslands LAI fcover swamps Dry pasture CNR1 flux measur ts

3 SPOT4 acquisitions over the SE site from 3/02 to 18/06/ /2 08/2 13/2 18/2 23/2 28/2 Feb Mar 15/3 25/3 30/3 Apr 04/4 09/4 14/4 19/4 24/4 May 04/5 09/5 14/5 19/5 24/5 Jun 03/6 13/6 18/6 22 images 12 without clouds!

4 EMMAH research questions 1- What interactions between agricultural surfaces and practices and ground water recharge? irrigation of grasslands in Crau impact of flooding with fresh water in rice fields on the saline transfers to the superficial groundtable in Camargue forests 2- How production is impacted by the global changes (water restriction, ITK modifications)? Remote sensing data SVAT models assimilation Evapotranspiration

5 detection of agricultural practices (cut, irrigation, rice flooding, ) 15/3 14/4 14/6 13/2 3/6 DOY (14/2-18/6/2013)

6 Estimation of biophysical variables (BV-net tool developped by EMMAH (Baret, Weiss et al)

7 Validation: ground measurements during SPOT4 acquisitions - Continuous measurements on various surfaces: albedo (CNR1), LAI, surface fluxes pastis57 pastispar CNR1-flux -Punctual measurements: vegetation height, hemispheric photos (LAI,fcover), ITK obs grassland 11/04 28/02 Rice 6/05 6/05 Dry Crau 6/05

8 Questions for CEN PACA Pôle Crau (réserve naturelle pôle Crau St Martin de Crau) jun2006 rain=160mm jun2013 rain=300mm SPOT4 3/6/2013 FORMOSAT2 2/6/2006 NDVI Evolution of the steppe area? biotope protection (biomass estimation) sheep path & pasture production maps of ecological habitats

9 SPOT4 13/2 Questions Fondation Tour du Valat - saline transfers between lakes, ponds and sea? - regulation of water levels for the biodiversity? Regulation of natural ecosystems - use of hydrological models

10 Questions UMR innovation Montpellier 14/4 13/6 18/6 - detection of dates of water flooding for rice - Identify an optimum land use (combination of agricultural activities) - Typology of farm (f(itk)) Bio-economic modeling Sylvestre Delmotte

11 Subject of thesis Monitoring of soil water balance and vegetation for management of irrigation systems SPOT4 14/4 Presented by: Mohamad El Hajj Director: Nicolas Baghdadi (UMR TETIS) Co-director : Gilles Belaud (UMR G-EAU)

12 Objectives Remote sensing: Characterize the physical parameters of the soil and vegetation Improve the hydro-agricultural models with information derived from remote sensing data (soil moisture, Biomass, LAI,...) Hydraulic modeling: Assimilate the spatial data in the hydro-agricultural models monitoring the water balance at different spatial scales

13 Further work by Emmah Unit Study site dry pasture Irrigated fields Irrigation network parcels Monoculture system (Plaine de la Crau) Experimental field of SupAgro (Support: F. Charron) Known rules of irrigation (IRD-GEAU Study, Thesis A. Mérot 2007) Irrigation system already studied in several works

14 Dates of acquisition of spatial data and field works

15 Field measurements of the physical parameters of the soil and vegetation Soil moisture Is the total amount of water present in the unsaturated zone Soil roughness: Standard deviation of heights rms2 = (z(x) zmean )2 Vegetation Water Content (VWC) Vegetation height Leaf area index ( LAI) Biomass Sec weight (g/ 50 cm x 50 cm) Top-layer(1-5 cm) soil moisture : radar sensitive to this depth 300 y = 0,2088x R² = 0, Wet weight (g/ 50 cm x 50 cm)

16 Radar signal (db) at X-band ( TerraSAR-X et Cosmo) 27/03/2013 Radar signal as a function of the surface soil moisture 16/04/ /05/ /05/ /06/ /07/ /07/ /08/ /09/ /09/2013 Surface soil moisture (%) Irrigation date HH- X band (db) Soil moisture (%)

17 Temporal variation of the physical parameters of the vegetation 6i_6j

18 Future Work Remote Sensing section : Analyze the potential of radar data to estimate the physical parameters of the soil and vegetation. Synergy between optical and radar data for: 1- Calibrate radar scattering models using physical parameters of the vegetation, estimated from optical data. 2- Inversion of models to estimate surface soil moisture and physical parameters of the vegetation at plot and intra-plot scale Hydrological section : Integration of spatial information in the management of an irrigation system at different spatial scale (field scale, large-network scale)

19 Thanks to the CNES team Olivier et al!

20 Teams involved UMR EMMAH Avignon: impact of ITK modifications on water and productions, interaction groundtable recharge- surface-atmosphere (tool development: BV-net-EVASPA) (Projects: Hymex, SIRRIMED, TOSCA, PNTS ) //www4.paca.inra.fr/emmah/ UMR TETIS Montpellier: Monitoring of irrigation combining radar + SPOT4 (PhD M El Hajj) UMR Geau and Innovation Montpellier: crop and water management (ScenaRice project) UR ECODEV INRA Avignon: urban development- impact of landuse modifications on ecosystemic services La fondation de la Tour du Valat : natural ecosystem monitoring (water, biodiversity)

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