This paper describes the setting and results of a real-time experiment of irrigation scheduling by a time series of optical satellite images under real conditions, which was carried out on durum wheat in the Haouz plain (Marrakech, Morocco), during the 2012/13 agricultural season. For the purpose of this experiment, the irrigation of a reference plot was driven by the farmer according to, mainly empirical, irrigation scheduling while test plot irrigations were being managed following the FAO-56 method, driven by remote sensing. Images were issued from the SPOT4 (Take5) data set, which aimed at delivering image time series at a decametric resolution with less than five-day satellite overpass similar to the time OPEN ACCESSRemote Sens. 2014, 6 11183 series ESA Sentinel-2 satellites will produce in the coming years. With a Root Mean Square Error (RMSE) of 0.91mm per day, the comparison between daily actual evapotranspiration measured by eddy-covariance and the simulated one is satisfactory, but even better at a five-day integration (0.59mm per day). Finally, despite a chaotic beginning of the experiment-the experimental plot had not been irrigated to get rid of a slaking crust, which prevented good emergence-our plot caught up and yielded almost the same grain crop with 14% less irrigation water. This experiment opens up interesting opportunities for operational scheduling of flooding irrigation sectors that dominate in the semi-arid Mediterranean area.
In this study, a simple model, based on a light-use-efficiency model, was developed in order to estimate growth and yield of the irrigated winter wheat under semi-arid conditions. The originality of the proposed method consists in (1) the modifying of the expression of the conversion coefficient (εconv) by integrating an appropriate stress threshold (ksconv) for triggering irrigation, (2) the substitution of the product of the two maximum coefficients of interception (εimax) and conversion (εconv_max) by a single parameter εmax, (3) the modeling of εmax as a function of the Cumulative Growing Degree Days (CGDD) since sowing date, and (4) the dynamic expression of the harvest index (HI) as a function of the CGDD and the final harvest index (HI0) depending on the maximum value of the Normalized Difference Vegetation Index (NDVI). The calibration and validation of the proposed model were performed based on the observations of wheat dry matter (DM) and grain yield (GY) which were collected on the R3 irrigated district of the Haouz plain (center of Morocco), during three agricultural seasons. Further, the outputs of the simple model were also evaluated against the AquaCrop model estimates. The model calibration allowed the parameterization of εmax in four periods according to the wheat phenological stages. By contrast, a linear evolution was sufficient to represent the relationship between HI and CGDD. For the model validation, the obtained results showed a good agreement between the estimated and observed values with a Root Mean Square Error (RMSE) of about 1.07 and 0.57 t/ha for DM and GY, respectively. These correspond to a relative RMSE of about 19% for DM and 20% for GY. Likewise, although of its simplicity, the accuracy of the proposed model seems to be comparable to that of the AquaCrop model. For GY, R2, and RMSE values were respectively 0.71 and 0.44 t/ha for the developed approach and 0.88 and 0.37 t/ha for AquaCrop. Thus, the proposed simple light-use-efficiency model can be considered as a useful tool to correctly reproduce DM and GY values.
<p>In this study, we developed a simple and spatialized wheat yield method based on the Monteith's three efficiency model. The originality of the method consists in: (1) the expression of the conversion coefficient (&#949;<sub>conv</sub>) by considering an appropriate stress threshold (k<sub>sconv</sub>) for triggering irrigation, (2) the substitution of the product of the two maximum coefficients of interception (&#949;<sub>imax</sub>) and conversion (&#949;<sub>conv_max</sub>) by a single parameter &#949;<sub>max</sub>, (3) the modeling of &#949;<sub>max</sub> as a function of the Cumulative Growing Degree Days (CGDD) since sowing date, and (4) the dynamic expression of the harvest index HI as a function of the CGDD and the final harvest index HI<sub>0</sub> depending of the maximum values of the Normalized Difference Vegetation Index (NDVI).</p><p>The calibration and validation of the proposed model were performed by using observed dry matter (DM) and grain yield (GY) on wheat conducted on the irrigated zone R3 of the Haouz plain (center of Morocco), during three agricultural seasons 2002/2003, 2008/2009 and 2012/2013. The model calibration allowed the parameterization of &#949;<sub>max</sub> in four periods according to the wheat phenological stages. By contrast, a linear evolution was sufficient to represent the relationship between HI and CGDD. The model validation was performed at the field and regional scales. For the field scale, the obtained results showed a good agreement between the estimated and observed values of DM and GY with Root Mean Square Error (RMSE) of about 1.07 t/ha and 0.57 t/ha for DM and GY, respectively. Likewise, at the regional scale, the proposed approach was tested over the irrigated district (R3) by using Landsat/spot images for mapping GY and DM. The RMSE values were 1.21 t/ha and 0.34 t/ha between measured and simulated DM and GY, respectively.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.