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A time series of eight high-resolution Landsat TM images, ranging over the crop season, has been acquired over an irrigated area in central Morocco. From this time series, a Normalized Difference Vegetation Index (NDVI) profile was generated for each pixel. In order to get significant profiles, the images were radiometrically corrected, first, using invariant objects located on the scene, based on visual observation of the images, and second, using the reflectance of these objects, estimated from a previously corrected image. In the following step, these NDVI profiles were used to identify four main crop types - bare soil, annual crops, trees on bare soil and trees on annual understory - using a decision tree algorithm. The resulting land cover map and the associated NDVI profiles were then used for an evapotranspiration estimate over the whole area, using the Food and Agriculture Organization (FAO) model. Daily outputs of the Moroccan meteorological model Aire Limitée Adaptation Dynamique développement International (ALADIN) were used to generate reference evapotranspiration (ET0) maps and K c estimates were determined using the NDVI profiles. [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]

For a regional assessment of water needs and consumption in semiarid agricultural zones, one needs robust and simple tools that provide space-time estimates of evaporation losses. Most operational evaporation estimates rely on semiempirical relationships that are not generally applicable. Several authors have proposed physically based simple expressions to model the 'energy-limited' (stage-one) and the 'supply-limited' (stage-two) evaporation rates during a dry down. They use the time compression approximation (TCA) to relate stage-one and stage-two drying. Two asymptotic approximations of the TCA corresponding to the diffusion-dominated and the drainage-dominated flows have been proposed in the literature. In this study a full analytical solution of the TCA is presented. The derived 'supply-limited' evaporation rate is evaluated for a wide range of soil conditions and vegetation cover against a physically based complex soil-vegetation-atmosphere transfer model, the Simple Soil-Plant-Atmosphere Transfer scheme (SiSPAT). SiSPAT solves the differential equations of water flow in a vertical soil column and computes estimates of soil evaporation and transpiration. SiSPAT is used to evaluate the performance of the full solution as well as the two existing asymptotic approximations for the case of sparse to dense vegetation in a semiarid environment. The full analytical solution gives accurate predictions of first- to second-stage evaporation time series for the bare soil and vegetated cover conditions with a leaf area index of 3 or higher. The results of the full solution are closer to the evaporation rate time series simulated by SISPAT than the asymptotic approximations. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this study is to use the FAO-56-based single crop coefficient approach to estimate actual evapotranspiration (AET) of an olive (Olea europaea L.) orchard in the Mediterranean semi arid region of Tensift-basin (central Morocco) during two consecutive growing seasons (2003 and 2004). The results showed that using crop coefficients K c suggested by FAO-56 method yielded an AET overestimation by about 18% when compared against eddy covariance measurements. Therefore, the determination of appropriate K c values is required to accurately estimate crop water requirement of olive orchards in such water scarce area. In this study, after applying the K c values derived over olive orchard in Spain by Pastor and Orgaz [Pastor, M., Orgaz, F., 1994. Riego deficitario del olivar: los programas de recorte de riego en olivar. Agricultura 746, 768–776 (in Spanish)], a better agreement was observed between measured and simulated AET. The root mean square error (RMSE) was reduced by about 28%, from 0.80 to 0.61mm/day for 2003 and from 0.93 to 0.69mm/day for 2004. The used K c values of olives at three crop growth stages (initial, mid-season and maturity) were 0.65, 0.45, and 0.65, respectively, the mid-season stage value being considerably lower than that suggested by the FAO-56. Despite these improvements in the performance of AET simulations, some discrepancies between measured and simulated AET remained, especially when water stress occurred. These discrepancies were ascribed to the estimation of the stress coefficient K c To overcome this problem, we assimilated into FAO-56 single source model estimates of AET derived from a simple energy balance model along with thermal infrared observations. The latter were collected with the ASTER sensor in 2003 and from ground-based measurements in 2004. The results showed a clear improvement for FAO-56 performances after assimilation: for 2003 and 2004, the RMSE values between observations and simulations, respectively, dropped down from 0.61 to 0.52 and from 0.69 to 0.46 (corresponding to relative reductions of 15 and 40%, respectively). [Copyright &y& Elsevier]

Abstract: This study was performed to test three methods based on the FAO-56 “dual” crop coefficient approach to estimate actual evapotranspiration (AET) for winter wheat under different irrigation treatments in the semi-arid region of Tensift Al Haouz, Marrakech (center of Morocco). The three methods differ in the calculation of the basal crop coefficient (K cb) and the fraction of soil surface covered by vegetation (f c). The first approach strictly follows the FAO-56 procedure, with K cb given in the FAO-56 tables and f c calculated from K cb (No-Calibration method). The second method uses local K cb and f c values estimated from field measurements (Local-Calibration method) and the last approach uses a remotely-sensed vegetation index to estimate K cb and f c (NDVI-Calibration method). The analysis was performed on three fields using actual (AET) measured by Eddy Correlation systems. It was shown that the Local-Calibration approach gave best results. Accurate estimates of K cb and f c were necessary for FAO-56 “dual” crop coefficient application. The locally derived K cb for winter wheat taken at initial, mid-season, and maturity crop growth were 0.15, 0.90 and 0.23, respectively. The K cb value at the mid-season stage was found to be considerably less than that suggested by the FAO-56. Similarity between the seasonal pattern of normalized difference vegetation index (NDVI) and K cb showed potential for modelling NDVI into a K cb. The obtained relationships between K cb and NDVI, and between f c and NDVI could be easily incorporated within the FAO-56 “dual” crop coefficient model and, thereby, provide a means to apply remotely sensed observation for real-time wheat irrigation scheduling. The results obtained were very acceptable especially when the soil evaporation is negligible. Therefore, the K cb–NDVI relationship employed in the FAO-56 “dual” crop coefficient model holds great potential for estimating crop water requirements on an operational basis and consumption at a regional scale. [Copyright &y& Elsevier]