Maliko Tanguy email: maliko.tanguy@upct.es

http://www.upct.es

ESTIMATION OF EVAPOTRANSPIRATION FROM REMOTE SENSING DATA: VALIDATION AND APPLICATION AT BONTIOLI, BURKINA FASO

M. Tanguy1, A. Baille1, M. Gonzalez-Real1, V. Martínez1

1 Departamento de Ing. de los Alimentos y del Equip. Agrícola. Área Agroforestal. Universidad Politécnica de Cartagena. Paseo Alfonso XIII nº48, 30203 Cartagena, Murcia, Spain2 IMK-IFU, Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, FRG

1. INTRODUCTION

Evapotranspiration (ET), or latent energy flux, is an important element of surface energy balance, and its knowledge is of high interest as it represents the main component of the water balance at the earth surface. In agriculture, estimating ET is especially valuable for irrigation scheduling and for improving irrigation as well as crop water use efficiency. In sparsely-vegetated semi-arid regions, latent energy flux may exhibit high spatial variability, which can be more or less reliably estimated by remote sensing, depending of the amount and quality of both satellite and ground data .

The main objectives of this study were (i) to evaluate several algorithms for retrieval of ET from satellite data (MODIS Terra), using tower-based flux measurements obtained at a subsahelian site (Bontioli, Burkina Faso) during the 2005 and 2006 African Monsoon season and (ii) to derive and compare the maps of spatially distributed fluxes (evapotranspiration and sensible heat flux) over a 85km x 85 km window around Bontioli.

2. MATERIALS AND METHODS

Ground weather and flux data measured during the 2005 and 2006 Monsoon season at Bontioli (Burkina Faso) were used to evaluate the performances of five evapotranspiration (ET)-retrieval algorithms. Remote sensing data were land surface temperature, LST, surface reflectance, and vegetation index, VI, from MODIS-TERRA satellite. Three algorithms (SM, SEBAL and TSEB) derive ET as the residual term of the surface energy balance, while the other two (JIC and S-SEBI) are “self-constrained” methods which directly derive the evaporative fraction (EF) from the graphical analysis of the LST-VI space.

3. RESULTS

The evaluation reveals that the JIC model proposed by Jiang and co-workers (Jiang et al., 2004) is the most robust and accurate, while the other methods are under-performing (Fig.1).

The estimation of sensible flux Hs was further analyzed, pointing out the necessity to develop adequate algorithms that enable a more accurate estimation of the soil heat flux.

Spatialization of ET using the JIC algorithm and available MODIS images was carried out on a window of 85 km x 85 km whose centre coincides with the flux measurements site. The differences in ET between the dry season and the African Monsoon season were quantified over the whole area, evidencing the rapid and drastic increase of ET and NDVI at the onset of the Monsoon season (Fig.2). The results showed a similar distribution pattern of vegetation index NDVI and ET, both significantly higher in the southern and south-western than in the northern part of the area. Spatial differences could be ascribed mainly to the precipitation and NDVI gradients between north and south (Fig.3.).

Fig.2: Evolution of ET spatial distribution, Dano (Burkina Faso), year 2005.

4. CONCLUSION

This study showed that the tested ET-retrieval algorithms performed rather distinctly, some of them overestimating or underestimating largely the ground observations. Therefore, care must be taken in selecting the appropriate retrieval method. From the validation test presented in this study, it appears that the self constrained methods supply the best agreement with the ground data, especially the JIC approach. The residual methods suffer from errors due to the estimation of the sensible flux. In particular, it appears necessary to develop a better parameterization of the soil heat flux, G.

Fig.3: Maps of ET and NDVI of the studied area, DOY 124 year 2005.

MAIN REFERENCES

Carlson, T.N., William, J.C., Gillies, R.R. (1995). A new look at the simplified method for remove sensing of daily evapotranspiration. Remote Sens. Environ., 54, 161-167.

Bastiaanssen, W.G.M., Menenti, M., Feddes, R. A., Holtslag, A.A.M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. J. Hydrol., 212/213, 198-212.

Jiang, L., Islam, S., Carlson, T.N. (2004). Uncertainties in latent heat flux measurements and estimation: implications for using a simplified approach with remote sensing data. Can. J. Remote Sensing, 30, 769-787.

Melesse, A.M., Nangia, V. (2005). Estimation of spacially distributed surface energy fluxes using remotely-sensed data for agricultural fields. Hydrological Processes, 19, 2653-2670.

Roerink, G.L., Su, Z., Menenti, N. (2000). S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance. Phys. Chem. Earth (B), 25, 147-157.

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