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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. [ABSTRACT FROM PUBLISHER]

Abstract: Irrigation scheduling has become an important tool that significantly influences growth, development and production of crops, especially in arid and semi-arid regions of the South Mediterranean. In these regions, most of the irrigation scheduling of the gravity irrigation networks are not optimized in terms of timing and water quantity. In this paper, we present a way of characterizing the irrigation distribution by the extensively used irrigation systems through a new irrigation index: the “irrigation priority index” (IPI). This normalized indicator takes into account the water stress coefficient and the time of irrigation with regard to the duration of an irrigation round. The IPI ranges between −1 and 1 and decreases with irrigation priority. The IPI was used to evaluate the actual irrigation scheduling in an irrigated perimeter of 2800ha of Tensift Al Haouz plain close to Marrakech in Morocco during the 2002–2003 winter wheat season. The obtained results showed that about 32% of the R3 zone plots receive late irrigation, when the stress was maximum (IPI less than −0.3). The sensitivity of grain yield to the IPI values was evaluated on a data set of wheat yields acquired on the 2008–2009 season. The spatial yield was simply calculated using a linear relationship between wheat yields and the spatial accumulated NDVI (Normalized Difference Vegetation Index) of the last 10 days of March (R 2 =0.84). The result showed a clear relationship between grain yield and IPI. Indeed, with significantly positive IPI [0.37, 0.63], production ranged from 3.8 to 4.7t/ha, whereas, it was less than 2.6t/ha when the IPI values are ranged from −0.52 to −0.16. [Copyright &y& Elsevier]

The present work aims to develop a simple approach relating normalized daily sap flow (liters per unit of leaf area) and daily reference evapotranspiration (ET 0 ) (mm/day). Two methods (FAO-Penman-Monteith (FAO-PM) and Hargreaves-Samani (HARG)) of the calculation of ET 0 were tested in order to examine their impact on the established relationships. The data sets used for developing this approach are taken over well irrigated orchards from three experimental sites (olive trees, cv. “ Olea europaea L .”, olive trees, cv. “ Arbequino ” and citrus trees cv. “ Clementine Afourar ”) conducted in the Tensift region around Marrakech (center of Morocco) and one experimental site (pecan orchard, cv. “ Carya illinoinensis, Wangenh. K. Koch” ) conducted in the Yaqui Valley, northwest of Mexico). The results showed that the normalized daily sap flow was linearly correlated with ET 0 (mm per day) calculated by FAO-PM method. The coefficient of determination (R 2 ) and the slope of this linear regression varied between 0.71 and 0.97 and between 0.30 and 0.35, respectively, depending on the type of orchards. For HARG method, the relationship between both terms is also linear but with more discrepancy (R 2 = 0.7). This was somehow expected since this method is known to underestimate ET 0 values in the semi-arid areas. Afterward, the validation of the developed linear relationship was performed over an olive orchard (“ Olea europaea L .”) where the measurements of sap flow were available for another cropping season (2004). The scatter plot between the normalized measured and estimated sap flow based on FAO-PM method reveals a very good agreement (slope = 1, and RMSE = 0.14 L/m 2 leaf area). However, for the estimation of normalized sap flow based on HARG method, the correlation is relatively more scattered (slope = 0.95, and RMSE = 0.35 L/m 2 leaf area). A further validation was performed using the measurements of evapotranspiration (ET) by eddy correlation system and the results showed that the correlation between normalized measured ET and estimated normalized sap flow is best when using FAO-PM method (RMSE = 0.33 L/m 2 leaf area) for estimating ET 0 than when using HARG method (RMSE = 0.51 L/m 2 leaf area). Finally, the performance of the developed approach was compared to the traditional dual crop coefficient scheme for estimating plant transpiration. Cross-comparison of these two approaches with the measurements data gave satisfactory results with an average value of RMSE equal to about 0.37 mm/day for both approaches. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the performance of three empirical methods for estimating reference evapotranspiration (ET0): Makkink (Mak) and Priestley–Taylor (PT) (radiation-based) and Hargreaves–Samani (HARG) (temperature-based) were assessed in semi-arid regions. The values of ET0 derived using these three methods were compared to those estimated using the reference FAO Penman–Monteith (FAO-PM) method under semi-arid conditions of the Tensift basin (central of Morocco) and the Yaqui Valley (Northwest Mexico). The results showed that the HARG method is the best one to estimate ET0 over both semi-arid test sites. Conversely, the performance of the other two empirical methods was poor except under humid conditions. However when the parameters α and C m figurate in the PT and Mak equations are locally calibrated, the performance of these two methods greatly improved. Additionally, this study showed that, when measurements of meteorological parameters needed for estimating ET0 (which are not always available especially in developing countries) are lacking, the climatic data generated with numerical weather prediction models provide an alternative and effective solution to estimate ET0. In this regard, data generated using a weather forecast model (ALADIN) over the Tensift basin showed that the HARG model is the most accurate one for estimating the spatio-temporal variability of ET0. [ABSTRACT FROM AUTHOR]

High spatial and temporal resolution surface soil moisture is required for most hydrological and agricultural applications. The recently developed Disaggregation based on Physical and Theoretical Scale Change (DisPATCh) algorithm provides 1-km-resolution surface soil moisture by downscaling the 40-km SoilMoisture Ocean Salinity (SMOS) soil moisture using Moderate Resolution Imaging Spectroradiometer (MODIS) data. However, the temporal resolution of DisPATCh data is constrained by the temporal resolution of SMOS (a global coverage every 3 days) and further limited by gaps in MODIS images due to cloud cover. This paper proposes an approach to overcome these limitations based on the assimilation of the 1-km-resolution DisPATCh data into a simple dynamic soil model forced by (inaccurate) precipitation data. The performance of the approach was assessed using ground measurements of surface soil moisture in the Yanco area in Australia and the Tensift-Haouz region in Morocco during 2014. It was found that the analyzed daily 1-km-resolution surface soil moisture compared slightly better to in situ data for all sites than the original disaggregated soil moisture products. Over the entire year, assimilation increased the correlation coefficient between estimated soilmoisture and ground measurements from 0.53 to 0.70, whereas the mean unbiased RMSE (ubRMSE) slightly decreased from 0.07 to 0.06m³m-3 compared to the open-loop force-restoremodel. The proposed assimilation scheme has significant potential for large-scale applications over semiarid areas, since the method is based on data available at the global scale together with a parsimonious land surface model. [ABSTRACT FROM AUTHOR]

The main objective of this study was to evaluate the performance and the domain of validity of the two-source energy balance model (TSEB) for the monitoring of actual evapotranspiration ( ET a ) as a first step towards its use for irrigation planning. Secondary objectives were to analyze the ability of TSEB model to detect water stress and to evaluate evapotranspiration partition between evaporation (E) and transpiration (T) 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 crop water consumption. TSEB computes ET a as the residual of a double component energy balance driven by the radiative surface temperature ( T s ) 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 ( K cb ) and assesses the hydric status directly by solving a two layer soil water budget. Both approaches were evaluated 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. Series of ASTER images were acquired during the first agricultural season. Both models offered fair performances compared to ET a 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 offered smoother performances in all cases. The potentialities of both approaches to predict a water stress index based on the departure from potential evapotranspiration ( ET c ) was evaluated: although the FAO-56 dual was better suited to detect high water stresses, the TSEB model was able to detect moderate stresses without a need to prescribe water inputs. Finally, the partition of ET a between soil evaporation and plant transpiration was estimated indirectly by confrontation between simulated soil evaporation and surface (0–5 cm) soil moisture acquired spatially with Theta Probe sensors and taken as a proxy of soil evaporation. TSEB evaporation was well correlated to surface soil moisture (r = 0.82) for low Leaf Area Index (LAI) values (<1.5 m 2 m −2 ). In addition, TSEB predicted partition compared well to snapshot measurements based on the stable isotope method. This in-depth comparison of two simple tools to monitor ET a leads us to the conclusion that the TSEB model can reasonably be used to map ET a on large scale and possibly for the decision-making process of irrigation scheduling. [ABSTRACT FROM AUTHOR]

The remotely sensed land surface temperature (LST) is a key parameter to monitor surface energy and water fluxes but the strong impact of topography on LST has limited its use to mostly flat areas. To fill the gap, this study proposes a physically-based method to normalize LST data for topographic - namely illumination and elevation - effects over mountainous areas. Both topographic effects are first quantified by inverting a dual-source soil/vegetation energy balance (EB) model forced by 1) the instantaneous solar radiation simulated by a 3D radiative transfer model named DART (Discrete Anisotropic Radiative Transfer) that uses a digital elevation model (DEM), 2) a satellite-derived vegetation index, and 3) local meteorological (air temperature, air relative humidity and wind speed) data available at a given location. The satellite LST is then normalized for topography by simulating the LST using both pixel- and image-scale DART solar radiation and elevation data. The approach is tested on three ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) overpass dates over a steep-sided 6 km by 6 km area in the Atlas Mountain in Morocco. The mean correlation coefficient and root mean square difference (RMSD) between EB-simulated and ASTER LST is 0.80 and 3 °C, respectively. Moreover, the EB-based method is found to be more accurate than a more classical approach based on a multi-linear regression with DART solar radiation and elevation data. The EB-simulated LST is also evaluated against an extensive ground dataset of 135 autonomous 1-cm depth temperature sensors deployed over the study area. While the mean RMSD between 90 m resolution ASTER LST and localized ibutton measurements is 6.1 °C, the RMSD between EB-simulated LST and ibutton soil temperature is 5.4 and 5.3 °C for a DEM at 90 m and 8 m resolution, respectively. The proposed topographic normalization is self-calibrated from (LST, DEM, vegetation index and in situ meteorological data) data available over large extents. As a significant perspective this approach opens the path to using normalized LST as input to evapotranspiration retrieval methods based on LST. [ABSTRACT FROM AUTHOR]

A good knowledge of the partitioning of evapotranspiration (ET) is particularly important for improving crop water productivity, especially in semi-arid regions where irrigated agriculture uses up to 85% of total available water. In this paper, stable isotopic method and micrometeorological data were combined to assess the ET partition into plant transpiration and soil evaporation of an irrigated winter wheat field lying in the center of Morocco characterized by a semi-arid climate. Atmospheric, vegetation and soil samples were collected during two consecutive growing seasons (2011–2012 and 2012–2013). The sampling campaign was carried out after and before two irrigation events and lasted for five days. Additionally, an Eddy covariance system and a standard meteorological station were installed. Isotope turbulent mixing relationships, isotopic values of transpired water from plants (T) and that of evaporating water vapor from soil surface (E) were used to estimate fractions of transpiration and evaporation contributing to the total ET. The partition of ET was only performed by using δ 2 H. In fact, results obtained during 2011–2012 period, showed that this method worked well for the deuterium in comparison to oxygen-18 (δ 18 O). After irrigation, the ratios T/ET were about 0.73, 0.59 and 0.74 respectively in Days Of Year (DOY) 53, 54 and 55, averaging 0.69. Prior to irrigation, when the soil was dry, the T/ET ratio was 0.83 and 0.77, respectively in two days (DOY 101 and 102), averaging 0.80. Afterward, these fractions have been used in conjunction with Eddy Covariance measurements for converting the obtained percentages to mm d −1 values which are required by the farmers and the water managers. The obtained averages of evaporation and transpiration were respectively: 1.76 and 3.85 mm d −1 for the 2011–2012 and 1.34 and5.45 mm d −1 for the 2012–2013. Our approach is useful for partitioning ET in an irrigated winter wheat under semi-arid climate at an ecosystem scale on short time steps. [ABSTRACT FROM AUTHOR]

Crop growth simulation models have become important tools to assess and develop deficit irrigation strategies especially in arid and semi-arid regions. In this study, we tested the ability of the FAO developed AquaCrop model (V 4.0) to simulate canopy cover (CC), actual evapotranspiration (ET cact ), total soil water content (TWC) and grain yield (GY) for winter wheat under flood irrigation in the semi-arid region of Tensift Al Haouz, Marrakech (center of Morocco). The simulation was performed at a daily time step, using thermal units, i.e., growing degree days (GDDs) during two successive growing seasons: 2002/2003 and 2003/2004. Firstly, the calibration of the model was performed on three fields during 2002/2003 cropping season. Various parameters affecting CC, ET cact , TWC and GY have been calibrated based on the comparison between measurements and the results of simulations. Afterward, the validation was done on six fields during the 2003/2004 cropping season. The results showed that the model simulates reasonably well CC, ET cact , TWC and GY over two growing seasons. The average values of the Mean Bias Error (MBE) between observed and measured CC, ET cact , TWC and GY were −4.6%, −0.23 mm/day, 17.56 mm and 0.05 t/ha for the calibration fields, and 7.89%, −0.01 mm/day, 0.5 mm and 0.06 t/ha for the validation fields, respectively. Additional statistical parameters like the root mean square error (RMSE) and the Nash–Sutcliffe efficiency (NSE) showed also that the model gives acceptable estimates of CC, ET cact , TWC and GY. After accurate calibration and validation of the AquaCrop model, it was used for irrigation scheduling based on the threshold of the root zone water depletion (D r,threshold ) over two fields with contrasted sowing dates. The various simulations (irrigation scenarios) showed that early sowing is more adequate than late sowing in saving water and obtaining adequate grain yield. It has been also shown that the value 0.6 of D r, threshold can be used as an appropriate threshold of water depletion to improve the wheat irrigation management. Consequently, the AquaCrop model can be considered as a potentially useful tool for planning irrigation schedules on an operational basis in the arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

In Morocco, wheat production shows a high inter-annual variability due to uncertain rainfall. In view of the importance of this resource to the country's economy, it is important to gain a better understanding of the natural large-scale climate oscillation governing this variability. In this study, we analyzed de-trended (1) time series of common wheat yields (1983-2008) from 11 agricultural provinces that account for 80 % of national wheat production; (2) monthly rainfall and 10-day temperature from ten meteorological stations; (3) 10-day normalized difference vegetation index (NDVI) from the AVHRR sensor; (4) monthly atmospheric climate indices [North Atlantic Oscillation (NAO) and Scandinavian Pattern (SCA)] and monthly 500 hPa geopotentials fields; and (5) monthly sea surface temperature (SST) fields and indices (NIÑO3, Tropical North Atlantic and Tropical South Atlantic). The relationship between rainfall and temperature during tillering in early winter and grain filling in early spring and wheat yields already observed at the plot scale was also found to be significant at the provincial scale. The linkages between wheat yields and large scale climate have been analyzed for the first time over Morocco. In agreement with previous studies, results show a complex and competing influence of different climate phenomena. The NAO is found to be significantly related to yields during the early stage of wheat growth in December, whereas the SCA correlates with yields later in the season, in January and February. Interesting lagged correlations with higher lead time are also highlighted, with the leading modes of SST variability in the equatorial Atlantic during October (the 'Atlantic Niño' mode) and in the North Atlantic (the 'Atlantic tripole' mode) in February. Our conclusion is that regional climate indices and variables represent valuable information with which to increase lead time and skill regarding wheat yield predictions in Morocco. [ABSTRACT FROM AUTHOR]

Highlights: [•] The irrigation scheduling of gravity irrigation network is performed. [•] An evolutionary strategy algorithm is used to perform the optimization. [•] Both crops water demand and irrigation priority are taken into account. [•] The proportion of plots irrigated at appropriate time is increased. [•] The water resource consumption can be reduced. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: The monitoring of crop production and irrigation at a regional scale can be based on the use of ecosystem process models and remote sensing data. The former simulate the time courses of the main biophysical variables which affect crop photosynthesis and water consumption at a fine time step (hourly or daily); the latter allows to provide the spatial distribution of these variables over a region of interest at a time span from 10 days to a month. In this context, this study investigates the feasibility of using the normalised difference vegetation index (NDVI) derived from remote sensing data to provide indirect estimates of: (1) the leaf area index (LAI), which is a key-variable of many crop process models; and (2) crop coefficients, which represent the ratio of actual (AET) to reference (ET0) evapotranspiration. A first analysis is performed based on a dataset collected at field in an irrigated area of the Haouz plain (region of Marrakesh, Central Morocco) during the 2002–2003 agricultural season. The seasonal courses of NDVI, LAI, AET and ET0 have been compared, then crop coefficients have been calculated using a method that allows roughly to separate soil evaporation from plant transpiration. This allows to compute the crop basal coefficient (K cb) restricted to the plant transpiration process. Finally, three relationships have been established. The relationships between LAI and NDVI as well as between LAI and K cb were found both exponential, with associated errors of 30% and 15%, respectively. Because the NDVI saturates at high LAI values (>4), the use of remotely-sensed data results in poor accuracy of LAI estimates for well-developed canopies. However, this inaccuracy was not found critical for transpiration estimates since AET appears limited to ET0 for well-developed canopies. As a consequence, the relationship between NDVI and K cb was found linear and of good accuracy (15%). Based on these relationships, maps of LAI and transpiration requirements have been derived from two Landsat7-ETM+ images acquired at the beginning and the middle of the agricultural season. These maps show the space and time variability in crop development and water requirements over a 3km×3km irrigated area that surrounds the fields of study. They may give an indication on how the water should be distributed over the area of interest in order to improve the efficiency of irrigation. The availability, in the near future, of Earth Observation Systems designed to provide both high spatial resolution (10m) and frequent revisit (day) would make it feasible to set up such approaches for the operational monitoring of crop phenology and irrigation at a regional scale. [Copyright &y& Elsevier]

The main goal of this research was to evaluate the potential of the HYDRUS-1D numerical model for estimating the soil moisture (θ) at different depths, actual crop evapotranspiration (ETa) and its components (crop transpiration, Ta and soil evaporation, Ea) as well as the deep percolation (DP) of irrigated winter wheat under different water managements in the semi-arid region of Tensift-basin (central Morocco). The HYDRUS-1D simulations were performed at daily time step during the two growing seasons: 2002/2003 and 2015/2016. The model was firstly calibrated based on one field "denoted F1" data during the 2002/2003 cropping season by using the Levenberg-Marquardt method implemented in HYDRUS-1D model for optimizing various parameters of Van Genuchten equation that provide the minimum difference between measured and simulated soil moisture at four layers of soil (0–5, 5–10, 10–20, 20–30, 30–50 cm). Afterwards, the model validation was done based on the data from four fields of wheat: two fields "denoted F2 and F3" during the 2002/2003 and two other fields "denoted F4 and F5" during the 2015/2016 cropping season. All fields were irrigated with flooding system except the field F5 where drip irrigation was undertaken. In-situ measurements of θ was carried out using Time Domain Reflectometry (TDR) and gravimetric method ETa was measured by the Eddy Covariance system Ta and Ea were monitored using a lysimeter in F5 field. The results showed that the HYDRUS-1D model simulates the θ, ETa, Ta and Ea reasonably well. Additionally, the evaluation of the irrigation system on DP losses was investigated by comparing the simulation results over flood (F4) and drip (F5) irrigated fields. It was found that about 56% and 20% of seasonal supplied water were lost by DP in F4 and F5 sites, respectively. Such unexpected high amount of DP taking place in F5 field is due to the improper use of the drip irrigation system. • HYDRUS-1D model was calibrated for estimating water balance components (θ, ETa, Ta, Ea and DP) over irrigated winter wheat. • Compared to in-situ measurements, the HYDRUS-1D model simulates θ, ETa, Ta and Ea values reasonably well. • HYDRUS-1D model can be used to advise growers for improving irrigation management. [ABSTRACT FROM AUTHOR]

Abstract: The potential of FORMOSAT-2 and ENVISAT/ASAR for the monitoring of irrigated wheat crops over Tensift/Marrakech semi-arid plain in Morocco is investigated. The green leaf area index (GLAI) was obtained from time series of vegetation index acquired by the FORMOSAT-2 instrument with a 25% accuracy. This information was then incorporated into a canopy functioning model to provide spatial estimates of GLAI, aerial biomass and top-soil moisture. These outputs were evaluated by comparing them to ground data collected on eight wheat fields monitored during the 2005–2006 agricultural season. The model accurately simulates the time courses of GLAI and aerial biomass during the vegetative phase. Finally, we analysed the spatio-temporal variations of ASAR backscattering co-polarization ratio as a function of biomass water content on the basis of simulations performed over 69 other wheat fields. The purpose of such analysis is to retrieve this last biophysical variable from ASAR images. The sensitivity of ASAR data to vegetation appears to be deteriorated by the sensitivity of to the variability of soil conditions encountered in the study area (roughness and moisture). [Copyright &y& Elsevier]