Morocco - Tensift

Specific Project Objectives & Deliverables

Main research axes

Based on a lot of work done by the team since 2002 regarding crop hydrological functioning, the research in 2016 focused on the surface evapotranspiration and soil moisture retrieval (both surface and root zone) using microwave and thermal data, using disaggregation. This type of information is potentially used directly by irrigation managers, and also to feed land surface models.

Besides, work is done on the fractioning between vegetation transpiration and soil evaporation, as a key knowledge to assess crop water use efficiency and to suggest irrigation management improvement.

Also we are still working on yield assessment which is a key variable for decision makers.

6.1       Soil moisture retrieval

Currently, the soil moisture data sets available at global scale have a spatial resolution much coarser than the typical size (several ha) of fields. Especially, the soil moisture retrieved from passive microwave observations such as C-band AMSR-E and L-band SMOS data have a spatial resolution of about 60 km and 40 km, respectively. The recent SMAP mission, launched in 2015, ensures continuity of L-band derived soil moisture products with similar resolutions. In this context, downscaling methodologies have been developed to improve the spatial resolution of readily available passive microwave-derived soil moisture data. DISPATCH (DISaggregation based on Physical And Theoretical scale CHange, Merlin et al. 2013) estimates the soil moisture variability within a 40 km resolution SMOS/SMAP pixel at the target 1 km resolution using MODIS data and the target 100 m resolution using Landsat data.

V. Stefan (PhD UPS 2013-2016) improved DISPATCH by integrating a physically-based energy balance model forced by meteorological data available within irrigated perimeters. The approach was validated over the Agues Segarra-Garrigues site in Spain (Stefan et al. 2017).

B. Ait Hssaine (PhD thesis, UCAM/UPS, 201--2018) is working on the retrieval of surface soil moisture at multiple scales by developing synergies between Sentinel-1 radar and 1 km resolution DISPATCH (disaggregated from SMOS using MODIS) data.

Y. Malbéteau (PhD UPS 2013-2016) improved the temporal resolution of DISPATCH data by assimilating the disaggregated soil moisture in a dynamic surface soil water balance model. The approach was tested on a daily basis over the Haouz plain (Malbéteau et al. 2017b). Being based on global scale SMOS, MODIS and ECMWF reanalysis data, it is easily transferable to other semi-arid areas. Moreover, the method has potential for retrieving irrigation amounts at the perimeter scale.

A. Mohamed (PhD isardSAT 2015-2018, seconded to UCAM during 9 months) is developing synergies between 1 km resolution DISPATCH (SMOS disaggregated using MODIS) and Sentinel-1 radar data to derive an enhanced soil moisture product at multiple resolutions.

A. Amazirh (PhD thesis, UCAM/UPS 2016-2018) is developing synergies between Sentinel-1 radar and thermal/optical Landsat-7, 8 data to retrieve the surface soil moisture at high spatio-temporal resolution (crop field scale) without any prior knowledge of soil roughness parameters.

Fig. 8: Image of the mean volumetric soil moisture in 2014 over Tensift Haouz region. Black lines represent the irrigated areas (extracted from Malbéteau et al. 2017b).


6.2       Partition between evaporation and transpiration

The purpose is, beyond the estimates of evapotranspiration, to separate soil evaporation from plant transpiration. This would allow the assessment of irrigation efficiency, considering the objective is to minimize evaporation, and this a major stake in the area were water is scarce.

B. Aït Hssaine (PhD UCAM/UPS 2016-2018) is developing a calibration strategy to integrate both land surface temperature and near-surface soil moisture data in a two-source energy budget model. State-of-the-art evapotranspiration models are generally based on thermal/visible data only and rely on ad hoc assumptions to represent the evaporation/transpiration components. The new approach integrates microwave-derived surface soil moisture as additional constraint on soil evaporation, and subsequently on vegetation water status.

Y. Malbéteau (PhD UPS 2013-2016) developed a method for correcting the remotely sensed land surface temperature for topographic effects. Thermal-based evapotranspiration models could now be applied to hilly and mountainous agricultural areas (Malbéteau et al. 2017a).

L. Olivera (PhD UPS 2016-2019) is investigating different coupling schemes between the FAO-based water budget model and remote sensing data available in the shortwave, thermal infrared and microwave bands to estimate the root zone soil moisture and crop water needs at the daily/field scale.

G. Aouade is combining the isotopic approach (oxygen stable isotopes) and the physically-based modelling of water and energy exchange at the soil-vegetation-atmosphere interface to monitor and predict evapotranspiration partition. She has evaluated, in particular, the domain of validity and the performances of a double energy budget SVAT model recently developed by meteo-france on the main crops of the region based on the Tensift observatory database.

6.3       Stress detection

Z. Rafi (PhD UCAM 2017-2019) is testing the usefulness of (1) thermal, (2) “PRI” shortwaves reflectances (531 nm, 570 nm and between 680-690 nm) and (3) C-band microwave data to characterize the water status of crops. He is also evaluating the complementarity of those wavelengths to better represent the non-stomatal (evaporation) and stomatal (transpiration) fluxes in land surface models.

6.4       Remote sensing for irrigated crops water budget monitoring

A. Diarra evaluated the performance and the domain of validity of the two-source energy balance model (TSEB) for the monitoring of actual evapotranspiration ( ) as a first step towards its use for irrigation planning. Secondary objectives are to analyse the evapotranspiration partition between evaporation (E) and transpiration (T) and the ability to detect water stress over irrigated annual crops. Within this context, TSEB was compared to the calibrated FAO-56 dual approach, taken as a reference tool for the monitoring of plant water consumption. TSEB computes  as the residual of a double component energy balance driven by the radiative surface temperature ( ) used as a proxy of crop hydric conditions; the FAO-56 dual crop coefficient approach uses the Normalized Difference Vegetation Index (NDVI) as a proxy of Basal Crop Coefficient ( ) and assesses the hydric status directly by solving a two layer soil water budget. Both approaches are evaluated using in situ forcings measured over four plots of wheat and sugar beet located in the Haouz plain (Marrakech, Morocco) that were instrumented with eddy covariance systems during the 2012 and 2013 growing seasons. Both models offer fair performances compared to observations with Root Mean Square Error (RMSE) lower than 1 mm day-1 apart from the FAO-56 dual approach on the sugar beet plot because of uncertain irrigation inputs. This highlights a major weakness of this model when water inputs are uncertain; a very likely case at the plot scale. By contrast, the TSEB model offers smoother performances in all cases. Finally, the partition of  between soil evaporation and plant transpiration is estimated indirectly by confrontation between simulated soil evaporation and surface (0–5 cm) soil moisture acquired spatially with ThetaProbe sensors and taken as a proxy of soil evaporation. TSEB evaporation is well correlated to surface soil moisture (r=0.82) for low Leaf Area Index (LAI) values (<1.5 m² m-²). In addition, TSEB predicted partition compares well to snapshot measurements based on the stable isotope method. This in-depth comparison of two simple tools to monitor  leads us to the conclusion that, if thermal images were available at high repetivity (as planned in future High spatial resolution thermal mission), the TSEB model could reasonably be used to map  and possibly for the decision-making process of irrigation scheduling.

Besides the thermal approach, we develop a simple SVAT approach based on NDVI forcing to monitor the crop water budget. The Sat-Irr tool ( is an on-line software based on the FAO-56 approach aiming to help irrigation scheduling at the plot scale. All the technical processing step (data downloading, image correction, data processing, etc...) are totally transparent to the users. An experiment designed to evaluate the tool in terms of both the quality of irrigation advise and of the way the farmers perceived this new information is actually carried out in the Tensift region. To this objective, about 8 farmers in different irrigated sectors have been trained to the use of Sat-Irr and receive their customized advises of irrigation schedule. Surveys are carried out in parallel to evaluate the difference between what has been scheduled by the tool and what was done by the farmers and also to understand the main reasons of the gaps. In addition, a network of low cost soil moisture sensor has been installed on the monitored fields with the objective of testing the assimilation of soil moisture data to improve the performance of the SatIrr tool. 

©2015 Joint Experiment for Crop Assessment and Monitoring