S. Khabba

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.

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.

Agrometerological study of semi-arid areas: an experiment for analysing the potential of time series of FORMOSAT-2 images (Tensift-Marrakech plain)

Earth Observing Systems designed to provide both high spatial resolution (10 m) and high capacity of time revisit (a few days) offer strong opportunities for the management of agricultural water resources. The FORMOSAT‐2 satellite is the first and only satellite with the ability to provide daily high‐resolution images over a particular area with constant viewing angles. As part of the SudMed project, one of the first time series of FORMOSAT‐2 images has been acquired over the semi‐arid Tensift‐Marrakech plain. Along with these acquisitions, an experimental data set has been collected to monitor land‐cover/land‐use, soil characteristics, vegetation dynamics and surface fluxes. This paper presents a first analysis of the potential of these data for agrometerological study of semi‐arid areas.

Automatic unmixing of MODIS multitemporal data for inter-annual monitoring of land use at a regional scale (Tensift, Morocco)

The objective of this study is to develop an approach for monitoring land use over the semi-arid Tensift–Marrakech plain, a 3000 km2 intensively cropped area in Morocco. In this objective, the linear unmixing method is adapted to process a 6-year archive of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 16-day composite data at 250 m spatial resolution. The result of the processing is a description of land use in terms of fractions of three predominant classes: orchard, non-cultivated area and annual crop. The typical signatures of land classes – endmembers – are retrieved on a yearly basis using an automated algorithm that detects the most pure pixels in the study area. The algorithm first extracts typical NDVI profiles as potential endmembers, then selects the profiles that have the best ability to reproduce the variability of MODIS NDVI time series over the study area. The endmembers appear stable over the 6 years of study and coherent with the vegetation seasonality of the three targeted land classes. Validation data allow us to quantify the error on land-use fractions to about 0.10 at 1 km resolution. Land-use estimates are consistent in space and time: the orchard class is stable, and differences in water availability (irrigation and rainfall) partly explain a part of the inter-annual variations observed for the annual crop class. The advantages and drawbacks of the approach are discussed.

Data assimilation of surface soil moisture, temperature, and evapotranspiration estimates in a SVAT model over irrigated areas in semi-arid regions: what’s best to constraint evapotranspiration predictions?

This study presents a strategy to improve the evapotranspiration estimates in semi arid areas using data assimilation in a SVAT (Soil Vegetation Atmosphere Transfer) modeling, the ISBA scheme (Interaction Soil Biosphere Atmosphere). In the perspective to use remote sensing products, the overall objective of this work is to identify the best combination of data (surface soil moisture / surface temperature / evapotranspiration), the temporal repetitiveness of acquisition (daily / tri-daily / weekly / bi-monthly / monthly) and the kind of data assimilation technique (two dimensional variational method / Extended Kalman filter) to constraint evapotranspiration predictions. Within this preliminary study, synthetic data referring to a wheat crops experimental site located in the Haouz Plain, part of the Tensift basin near Marrakesh in Morocco have been used (from January to May 2003). The results show that in order to improve the evapotranspiration through the analysis of the root zone soil moisture, the surface soil moisture is the most informative observation to use in the assimilation process (roughly 40% improvement in evapotranspiration RMSE). Combinations of observations improve the results but not significantly (few % improvement in evapotranspiration RMSE). Assimilation is very efficient for short assimilation windows. It is also shown that the propagation of the background error matrix done through the Extended Kalman filter doesn’t represent a significant added value with regards to the constant matrix used with two dimensional variational method.