G. Boulet

Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue.

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997-1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources.

Monitoring irrigation volumes using high-resolution NDVI image time series: calibration and validation in the Kairouan plain (Tunisia)

The increasing availability of high resolution high repetitively VIS-NIR remote sensing, like the forthcoming Sentinel-2 mission to be launched in 2015, offers unprecedented opportunity to improve agricultural monitoring. In this study, regional evapotranspiration and crop water consumption were estimated over an irrigated area located in the Kairouan plain (central Tunisia) using the FAO-56 dual crop coefficient water balance model combined with NDVI image time series providing estimates of the actual basal crop coefficient (Kcb) and vegetation fraction cover. Three time series of high-resolution SPOT5 images have been acquired for the 2008-2009, 2011-2012 and 2012-2013 hydrological years. We also benefited from a SPOT4 time series acquired in the frame of the SPOT4-Take5 experiment. The SPOT5 images were radiometrically corrected, first, using the SMAC6s Algorithm, and then improved using invariant objects located on the scene. The method was first calibrated using ground measurements of evapotranspiration achieved using eddy-correlation devices installed on irrigated wheat and barley plots. For other crops for which no calibration data was available, parameters were taken from bibliography. Then, the model was run to spatialize irrigation over the whole area and a validation was done using cumulated seasonal water volumes obtained from ground survey for three irrigated perimeters. In a subsequent step, evapotranspiration estimates were obtained using a large aperture scintillometer and were used for an additional validation of the model outputs.

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.