A. Chehbouni

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.

Assessment of Equity and Adequacy of Water Delivery in Irrigation Systems Using Remote Sensing-Based Indicators in Semi-Arid Region, Morocco

The irrigation performance criteria of equity and adequacy are of primary concern for irrigation managers. The input data required at various scales to assess irrigation performance, often not available, need costly intensive field campaigns. Remote sensing techniques, used to directly estimate crop evapotranspiration (ETc), became recently an attractive option to assess irrigation performance from individual fields to irrigation scheme or river basin scale. In this study, ETc maps were obtained by combining the FAO-56 dual approach with relationships between crop biophysical variables and NDVI (Normalized Difference Vegetation Index), using high spatial resolution time series of SPOT and Landsat images. This approach was applied for 2002/2003 growing season in Haouz plain, Morocco. Remote sensing-based indicators, reflecting equity and adequacy of the irrigation water delivery were estimated. Adequacy was determined according to Relative Irrigation supply (RIS), Depleted Fraction (DF) and Relative Evapotranspiration (RET) and equity according to the coefficient of variation of ETc. The analysis of these indicators exhibits a great variability among fields. Variability in irrigation performance at all levels, associated factors and possible improvements are discussed. This study demonstrates how remote sensing-based estimates of water consumption provide better estimates of irrigation performance at different scales than the traditional field survey methods.

Integrated modelling of the water cycle in semi arid watersheds based on ground and satellite data: the SudMed project

The SudMed project aims since 2002 at modelling the hydrological cycle in the Tensift semi arid watershed located in central Morocco. To reach these modelling objectives, emphasis is put on the use of high and low resolution remote sensing data, in the visible, near infrared, thermal, and microwave domains, to initialize, to force or to control the implementation of the process models. Fundamental studies have been conducted on Soil-Vegetation-Atmosphere Transfer modelling (SVAT), especially related to the various means of incorporating both ground and remote sensing observation into them. Satellite data have been used for monitoring the snow dynamic which is a major contribution to runoff issued from the mountains. Remote sensing image time series have also been used to map the land cover, based on NDVI time profiles analysis or temporal unmixing of low resolution pixels. Subsequently, remote sensing time series proved to be very valuable for monitoring the development of vegetation and the crop water status, in order to estimate of evapotranspiration, key information for irrigation management.