Abdelghani Chehbouni

The use of high-resolution image time series for crop classification and evapotranspiration estimate over an irrigated area in central Morocco

A time series of eight high‐resolution Landsat TM images, ranging over the crop season, has been acquired over an irrigated area in central Morocco. From this time series, a Normalized Difference Vegetation Index (NDVI) profile was generated for each pixel. In order to get significant profiles, the images were radiometrically corrected, first, using invariant objects located on the scene, based on visual observation of the images, and second, using the reflectance of these objects, estimated from a previously corrected image. In the following step, these NDVI profiles were used to identify four main crop types—bare soil, annual crops, trees on bare soil and trees on annual understory—using a decision tree algorithm. The resulting land cover map and the associated NDVI profiles were then used for an evapotranspiration estimate over the whole area, using the Food and Agriculture Organization (FAO) model. Daily outputs of the Moroccan meteorological model Aire Limitée Adaptation Dynamique développement International (ALADIN) were used to generate reference evapotranspiration (ET0) maps and K c estimates were determined using the NDVI profiles.

An integrated modelling and remote sensing approach for hydrological study in arid and semi-arid regions: the SUDMED Programme

Recent efforts have been concentrated in the development of models to understand and predict the impact of environmental changes on hydrological cycle and water resources in arid and semi‐arid regions. In this context, remote sensing data have been widely used to initialize, to force, or to control the simulations of these models. However, for several reasons, including the difficulty in establishing relationships between observational and model variables, the potential offered by satellite data has not been fully used. As a matter of fact, a few hydrological studies that use remote sensing data emanating from different sources (sensors, platforms) have been performed. In this context, the SUDMED programme has been designed in 2002 to address the issue of improving our understanding about the hydrological functioning of the Tensift basin, which is a semi‐arid basin situated in central Morocco. The first goal is model development and/or refinement, for investigating the hydrological responses to future scenario about climate change and human pressure. The second aim is the effective use of remote sensing observations in conjunction with process models, to provide operational prognostics for improving water‐resource management. The objective of this paper is to present the SUDMED programme, its objectives, and its thrust areas, and to provide an overview of the results obtained in the first phase of the programme (2002–2006). Finally, the lessons learned, future objectives, and unsolved issues are presented.

A combined modeling and multispectral/multiresolution remote sensing approach for disaggregation of surface soil moisture: application to SMOS configuration

A new physically based disaggregation method is developed to improve the spatial resolution of the surface soil moisture extracted from the Soil Moisture and Ocean Salinity (SMOS) data. The approach combines the 40-km resolution SMOS multiangular brightness temperatures and 1-km resolution auxiliary data composed of visible, near-infrared, and thermal infrared remote sensing data and all the surface variables involved in the modeling of land surface-atmosphere interaction available at this scale (soil texture, atmospheric forcing, etc.). The method successively estimates a relative spatial distribution of soil moisture with fine-scale auxiliary data, and normalizes this distribution at SMOS resolution with SMOS data. The main assumption relies on the relationship between the radiometric soil temperature inverted from the thermal infrared and the microwave soil moisture. Based on synthetic data generated with a land surface model, it is shown that the radiometric soil temperature can be used as a tracer of the spatial variability of the 0-5 cm soil moisture. A sensitivity analysis shows that the algorithm remains stable for big uncertainties in auxiliary data and that the uncertainty in SMOS observation seems to be the limiting factor. Finally, a simple application to the SGP97/AVHRR data illustrates the usefulness of the approach.

A simple water and energy balance model designed for regionalization and remote sensing data utilization

A simple soil‐vegetation‐atmosphere transfer (SVAT) model designed for scaling applications and remote sensing utilization will be presented. The study is part of the Semi-Arid Land Surface Atmosphere (SALSA) program. The model is built with a single-bucket and single-source representation with a bulk surface of mixed vegetation and soil cover and a single soil reservoir. Classical atmospheric forcing is imposed at a reference level. It uses the concept of infiltration and evaporation capacities to describe water infiltration or exfiltration from a bucket of depth dr corresponding to the average infiltration and evaporation depth. The atmospheric forcing is divided into storm and interstorm periods, and both evaporation and infiltration phenomena are described with the well-known three stages representation: one at potential (energy- or rainfall-limited) rate, one at a rate set by the soil water content and one at a zero rate if the water content reaches one of its range limits, namely saturation or residual values. The analytical simplicity of the model is suitable for the investigation of the spatial variability of the mass and energy water balance, and its one-layer representation allows for the direct use of remote sensing data. The model is satisfactorily evaluated using data acquired in the framework of SALSA and a mechanistic complex SVAT model, Simple Soil-Plant-Atmosphere Transfer (SiSPAT) model.

Estimation of surface sensible heat flux using dual angle observations of radiative surface temperature

Abstract In this study, dual angle observations of radiative surface temperature have been used in conjunction with a two-layer model to derive sensible heat flux over a sparsely vegetated surface. Data collected during the semi-arid-land-surface-atmosphere program (SALSA) over a semi-arid grassland in Mexico were used to assess the performance of the approach. The results showed that this approach led to reasonable estimates of the observed fluxes. The mean average percentage difference (MAPD) between observed and simulated fluxes was about 23%, which is not statistically different from the expected 20% scatter, when different flux measuring devices are compared over the same site. However, the sensitivity analysis indicated that the approach was rather sensitive to uncertainties in both measured radiative temperatures and aerodynamic characteristics of the vegetation. Finally, the issue of using dual angle observations of surface temperature for characterizing the difference between aerodynamic and nadir viewing radiative temperature has been examined. The results showed that this difference is linearly correlated with the difference between nadir and oblique radiative temperatures. Based on this finding, we expressed sensible heat flux in terms of the (nadir) radiative-air temperature gradient and a corrective term involving the nadir–oblique temperature differences. This formulation has been successfully tested. The resulting MAPD was about 33%.

Directional effect on radiative surface temperature measurements over a semiarid grassland site

In this study, an experimental design was conceived, as part of the Semi-Arid-Land-Surface-Atmosphere (SALSA) program, to document the effect of view angle variation on surface radiative temperature measurements. The results indicated differences between nadir and off-nadir radiative temperature of up to 5 K. The data also illustrated that, under clear sky and constant vegetation conditions, this difference is well correlated with surface soil moisture. However, the correlation decreased when the same comparison was made under changing vegetation conditions. To investigate the possibility of deriving component surface temperatures (soil and vegetation) using dual-angle observations of directional radiative temperature, two radiative transfer models (RTM) with different degrees of complexity were used. The results showed that despite their differences, the two models performed similarly in predicting the directional radiative temperature at a third angle. In contrast to other investigations, our study indicated that the impact of ignoring the cavity effect term is not very significant. However, omitting the contribution of the incoming long-wave radiation on measured directional radiance seemed to have a much larger impact. Finally, sensitivity analysis showed that an accuracy of better than 10% on the plant area index (PAI) was required for achieving a precision of 1 K for inverted vegetation temperature. An error of 1 K in measured directional radiative temperature can lead to an error of about 1 K in the soil and vegetation temperatures derived by inverting the RTM.

Methods to aggregate turbulent fluxes over heterogeneous surfaces: application to SALSA data set in Mexico

The issue of using remotely sensed surface temperature to estimate the area-average sensible heat flux over surfaces made up of different vegetated patches has been investigated. The performance of three aggregation procedures, ranging from physically based through semi-empirical, to entirely empirical has been assessed by comparing measured and simulated area-average sensible heat flux. The results show that the physically based scheme perform very well. The performance of the entirely empirical scheme was reasonable but that of the semi-empirical scheme, which actually takes full advantage of remotely sensed data, was very poor. This result suggests that unlike the case of surface fluxes, it is not appropriate to use relationships between model and observational variables (here radiative and aerodynamic surface temperature) that were developed and calibrated at a local/patch scale, for an application at a larger/grid scale just by scaling the parameters. Therefore, future research should be directed towards building robust relationships between model and observational variables directly at the large-scale.

Combining satellite remote sensing data with the FAO-56 dual approach for water use mapping in irrigated wheat fields of a semi-arid region.

The aim of this study was to combine the FAO-56 dual approach and remotely-sensed data for mapping water use (ETc) in irrigated wheat crops of a semi-arid region. The method is based on the relationships established between Normalized Difference Vegetation Index (NDVI) and crop biophysical variables such as basal crop coefficient, cover fraction and soil evaporation. A time series of high spatial resolution SPOT and Landsat images acquired during the 2002/2003 agricultural season has been used to generate the profiles of NDVI in each pixel that have been related to crop biophysical parameters which were used in conjunction with FAO-56 dual source approach. The obtained results showed that the spatial distribution of seasonal ETc varied between 200 and 450 mm depending to sowing date and the development of the vegetation. The validation of spatial results showed that the ETc estimated by FAO-56 corresponded well with actual ET measured by eddy covariance system over test sites of wheat, especially when soil evaporation and plant water stress are not encountered.

Citrus orchard evapotranspiration : comparison between eddy covariance measurements and the FAO-56 approach estimates

Abstract The aim of this study was to use the FAO-56 single and dual crop coefficient approaches to estimate actual evapotranspiration (ETa) over an irrigated citrus orchard under drip and flood irrigations in Marrakech, Morocco. The results showed that, by using crop coefficients suggested in the FAO-56 paper, the performance of both approaches was poor for two irrigation treatments. The Root Mean Squared Error (RMSE) between measured and simulated ETa values over the citrus orchard under drip irrigation was about 1.43 and 1.27 mm/day for the single and dual approaches, respectively, while the corresponding statistics for the orchard irrigated by the flooding technique was 1.87 and 2.48 mm/day. After determination of the appropriate values of the crop coefficient (Kc) based on eddy covariance measurements of ETa, the performance of both approaches greatly improved. The obtained Kc values were lower than the FAO-56 values by about 20%. The low Kc values obtained reflect the practice of drip irrigation for one field and the low value of cover fraction for the other field. Additionally, the efficiency of the irrigation practices was investigated by comparing the measured Kc for two fields. The results showed that a considerable amount of water was lost by direct soil evaporation from the citrus orchard irrigated by flooding technique.

Monitoring of irrigated wheat in a semi‐arid climate using crop modelling and remote sensing data: Impact of satellite revisit time frequency

The rationale of this research is to investigate approaches based on modelling and remote sensing data for estimating the spatial distribution of yield and irrigation of wheat in semi‐arid areas. The specific objective is to compare the performances of two approaches to test the STICS crop model using remotely sensed estimates of leaf area index (LAI). An experimental study of phenology, yield and water balance of irrigated wheat was made in the Marrakech‐Haouz plain during year 2003. Experimental data was allowed to run STICS using two approaches: (1) Calibration of the parameters that control the time course of LAI; (2) driving from LAI time series interpolated with a simple model. The results show the accuracy of STICS to simulate actual evapotranspiration and yield for both approaches. Finally, the two approaches were compared using remotely sensed estimates of LAI upon four scenarios of satellite time revisit frequency. The simulations we obtained always show acceptable results. However, differences appear between the variables, between the approaches and between the frequencies.