On SEBI-SEBS validation in France, Italy, Spain, USA and China

Transcription

1 On SEBI-SEBS validation in France, Italy, Spain, USA and China Massimo Menenti Li Jia 2 and ZongBo Su 2 - Laboratoire des Sciences de l Image, de l Informatique et de la Télédétection (LSIIT), Strasbourg, France -Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFoM), National Research Council (CNR), Italy 2 ALTERRA Green World Research, Wageningen University and Research Centre, 6700 AA Wageningen, The Netherlands; September 17th ICID RS ET - Montpellier 1

2 land evaporation: processes and observations evaporation land potential actual heat balance surface water balance soil water balance air Rn+ G+ H+ LE=0 P + I + Q + δm + δw + E = 0 δv δt + div q September 17th ICID RS ET - Montpellier 2 v = E P

3 Actual evaporation: a history of methods heat balance land surface linear relationship [1] SVAT [4] local maximum ET [6] linear relationship B, n variable [2] SVAT + PBL [5] improved observations [7] NDVI vs. Trad [3] Menenti, 2001 September 17th ICID RS ET - Montpellier 3

4 RS flux-algorithms albedo LE 0 SEBAL (Bastiaanssen, 1995) H 0 temperature pbl-temp SEBI (Menenti & Choudhury, 1993; Su et al, 2000) obs Dual - view angle measurements of surface temperature (Menenti et al, 2001) September 17th ICID RS ET - Montpellier 4

5 SEBI: theory and definitions Menenti and Choudhury (1993) SEBI = (T 0 - T re (T 0 - T ( re ) a d a ) (T 0 - T a ) - ( re ) w ) d (T 0 - T a ) - ( re ) w w w Λ r H λe = λ E wet λe =1- SEBI Λ= R G n ( )( R G) = 1 Λ n Reference height = PBL top or blending height T a = potential air temperature θ max H ρ a max c u p * = 1 ln κ h z 0h C h L max θ min H ρ c u a min p * = 1 ln κ h z 0h C h L min H max = Q* G H min : s( Q G) + ρc / r ( e e) September 17th ICID RS ET - Montpellier 5 λe wet = * a p s+γ a sat

6 Case studies France, DAISEX 1999 at Colmar and Hartheim (Jia et al., 2001) Italy, Pian di Rosia 1997 (Roerink et al., 2000). Spain (Jia et al., 2003) USA SGP 97 (Su et al., 2002) China (Su et al., 2003) September 17th ICID RS ET - Montpellier 6

7 DAISEXL Overview of data collected - DAIS (Digital Airborne Imaging Spectrometer) - HYMAP (Hyperspectral Mapper) - ROSIS (Reflective Optics System Imaging Spectrometer) - POLDER (POLarized and Directional Earth's Reflectances) -WAAC (Wide Angle Airborne Camera) - LEANDRE LIDAR (aerosols lidar) - ARAT (in-situ atmospheric sensors) - ERS-1/ERS-2 Tandem SAR - Landsat TM / SPOT data (for the dates of campaigns) THREE YEARS OF CAMPAIGNS: Barrax: 1998, 1999 and 2000; Alsace: 1999 September 17th ICID RS ET - Montpellier 7

8 SEBI from field measurements SEBI Normorlized (T0 - Ta) (K / (s m-1)) 0.6 Wet condition 0.4 Actual Dry condition albedo Energy flux ( W m-2) :00 09:20 09:32 09:40 12:00 12:20 12:48 16:14 17:00 Hour(UTC) Rn G H_obs H_s ebi LE_obs LE_s ebi Flux densities 350 Colmar, sugar beet: SEBI estimates vs. field measurements RMSD = 17.4 Wm -2 LE estimation by SEBI ( W m-2 ) RMSD = 17.4 W m LE obsevation ( W m-2 ) September 17th ICID RS ET - Montpellier 8

9 Dry and Wet reference vs. Observations September 17th ICID RS ET - Montpellier 9

10 From SEBI to LE - map Normalized (T0-Ta) ( K/(s m-1) ) Colmar sugarbeet Wet boundary Actual Dry boundary normalized (T 0 T a ) versus surface albedo; airborne HYMAP, DAIS, Colmar albedo LE Sugar beet Bare soil Distribution of LE at Colmar sub-site; cross indicates location of field measurements Fallow maiz Wm -2 September 17th ICID RS ET - Montpellier 10

11 The Simplified Surface Energy Balance Index ( SEBI ) Surface temperature ( o C) T H T λe T 0 H max (r 0 ) λe max (r 0 ) mean temperature H [measured] (W/m2) eddy correlation bowen ratio scintillometer Surface reflectance (-) H [S-SEBI] (W/m2) Menenti and Choudhury, 1993; Roerink et al., 1999 September 17th ICID RS ET - Montpellier 11

12 SEBS - The Surface Energy Balance System Input SEBS Core Modules Output Meteorological Data Boundary Layer Variables Remote Sensing Data Boundary Layer Similarity Theory Roughness for Heat Transfer Turbulence Heat Fluxes Evaporative Fraction NIR VIS TIR Surface Energy Balance Index Actual Evaporation September 17th ICID RS ET - Montpellier 12

13 Spain: validation with scintillometers Location of scintillometer measurements sites Location and characteristics of scintillometer experimental sites in Spain. Site Tomelloso Lleida Badajoz Transmitter Receiver Distance between Surface Location transmitter and receiver (m) Characteristics Location N W N E N W Height (m) N W N E N W Height (m) Dry vineyard Small scale irrigation area with fruit trees, alfalfa Large scale irrigation area with wheat, corn, alfalfa, lettuce, olives, beans, tomatoes. September 17th ICID RS ET - Montpellier 13

14 Surface temperature (K) Surface albedo ( ) NDVI ( ) Fractional vegetation cover ( ) PBL depth (m) PBL pressure (Pa) PBL potential temperature (K) PBL speci.c humidity (%) PBL wind speed (m/s) Channel SEBS Data Requirements ATSR ATSR ATSR ATSR NWP-RACMO RACMO RACMO RACMO RACMO Central wavelength 50% band wid (mm) (mm) 1 * * * * ATSR channels September 17th ICID RS ET - Montpellier 14

15 Sensible heat flux: SEBI vs. scintillometers H estimated by SEBS (W m -2 ) Tomelloso Lleida Badajoz SEBI (SEBS version) ATSR-2: surface temperature, albedo and NDVI vertical error bars = standard deviation over pixels along path horizontal error bars = error LAS measurements H observed by LAS (W m -2 ) September 17th ICID RS ET - Montpellier 15

16 SEBI: Forward and nadir T 0 USA: Southern Great Plain 1997 Hydrology Experiment (SGP 97) (Nadir View) (Forward View) Colour from red to yellow, green, blue indicates increasing evaporative fraction forward view = higher fraction of foliage, lower surface brightness temperature higher estimate of evaporative fraction September 17th ICID RS ET - Montpellier 16

17 China: Monitoring Droughts July 1, 2000 July 8, 2000 September 17th ICID RS ET - Montpellier 17

18 Comparison with Soil Moisture Measurements China: Relative evaporation vs relative soil moisture April 2000 April 2000 April 2000 Relative Soil Moisture (at10 cm depth) Relative Evaporation (%) SOIL MOISTURE (at10 cm depth) Predicted Average Relative Soil Moisture Avergae Relative Soil Moisture up to 20 cm Depth (%) Relative Evaporation (%) Average Relative Soil Moisture up to Depth of 20 cm Predicted Average Relative Soil Moisture Average Relative Soil Moisture up to depth of 50cm (%) Relative Evaporation (%) 6 Average Relative Soil Moisture up to Depth of 50 cm Predicted Average Relative Soil Moisture Time Series of Drought Severity Index September 17th ICID RS ET - Montpellier 18

19 Development related changes in land cover and Colour composite of multitemporal images of the Soil Adjusted Vegetation Index (SAVI) calculated with AVHRR Ch1 and Ch2 reflectance at 1 km spatial resolution, Aral Sea Basin 1992: SAVI (April)= red; SAVI (june)= green; SAVI (august)= blue; area is 1568 km x 1232 km; greenish areas = irrigated lands water balance September 17th ICID RS ET - Montpellier 19

20 Concluding Remarks Method performs well under different conditions Use of NWP models to determine PBL variables makes large area applications feasible Error budgets give significantly higher error estimates SEBS will be further developed by integrating generic algorithms to process TOA radiometric data Case studies should be expanded to time series September 17th ICID RS ET - Montpellier 20