Richard Escadafal

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.

Relationships between satellite-based radiometric indices simulated using laboratory reflectance data and typic soil color of an arid environment

Abstract By definition, the color of an object such as soil is highly dependent on its reflectance properties in the visible spectrum. In this study, the relationships between soil color and simulated reflectance values for the Landsat TM and SPOT HRV satellites are examined from a laboratory standpoint. Visible reflectance spectra were acquired for 124 soil samples originated from an arid environment, and selected radiometric indices were worked out for both sensors. All the earlier studies relative to soil color and remote sensing have considered the widely known Munsell method as a reference for soil color quantification. Some characteristics of this system based on a visual comparison of a soil sample with painted color chips may complicate the establishment of simple relationships between reflectance data and soil color. We have applied the CIE 1931 standard method of color measurement which consists in computing color parameters directly from reflectance spectra using colorimetric equations. Color data are expressed according to two polar coordinates called Helmholtz coordinates (dominant wavelength and purity of excitation) and a luminance variable having a similar meaning to the Munsell hue, chroma, and value, respectively. The Munsell system is also employed to estimate soil color. Linear regression analysis between soil color and radiometric indices show a systematic improvement of correlations (r) from about 0.7 to more than 0.9 using Munsell data and Helmoltz data, respectively. Simple radiometric indices (band combinations) calculated from broad blue, green, and red bands are found to be good predictors of each of the soil color components. The increasing availability of spectroradiometers, including in the field, should stimulate the use of Helmholtz coordinates, as a beneficial alternative to the Munsell chart to obtain a precise and reproducible color quantification which may be useful for remote sensing applications. The radiometric indices utilized in this study are potentially helpful to contribute to soil resource and soil degradation cartography using visible satellite data in vast arid regions where soil data are not readily available.

Remote Sensing of Water Resources in Semi-Arid Mediterranean Areas: the joint international laboratory TREMA

Monitoring of water resources and a better understanding of the eco-hydrological processes governing their dynamics are necessary to anticipate and develop measures to adapt to climate and water-use changes. Focusing on this aim, a research project carried out within the framework of French–Moroccan cooperation demonstrated how remote sensing can help improve the monitoring and modelling of water resources in semi-arid Mediterranean regions. The study area is the Tensift Basin located near Marrakech (Morocco) – a typical Southern Mediterranean catchment with water production in the mountains and downstream consumption mainly driven by agriculture. Following a description of the institutional context and the experimental network, the main recent research results are presented: (1) methodological development for the retrieval of key components of the water cycle in a snow-covered area from remote-sensing imagery (disaggregated soil moisture from soil moisture and ocean salinity) at the kilometre scale, based on the Moderate Resolution Imaging Spectroradiometer (MODIS); (2) the use of remote-sensing products together with land-surface modelling for the monitoring of evapotranspiration; and (3) phenomenological modelling based only on time series of remote-sensing data with application to forecasting of cereal yields. Finally, the issue of transfer of research results is also addressed through two remote sensing-based tools developed together with the project partners involved in water management and irrigation planning.

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.

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.