Optimizing the sowing date to improve water management and wheat yield in a large irrigation scheme, through a remote sensing and an evolution strategy-based approach
(2021) In Remote Sensing 13(18).- Abstract
This study aims to investigate the effects of an optimized sowing calendar for wheat over a surface irrigation scheme in the semi-arid region of Haouz (Morocco) on irrigation water requirements, crop growth and development and on yield. For that, a scenario-based simulation approach based on the covariance matrix adaptation–evolution strategy (CMA-ES) was proposed to optimize both the spatiotemporal distribution of sowing dates and the irrigation schedules, and then evaluate wheat crop using the 2011–2012 growing season dataset. Six sowing scenarios were simulated and compared to identify the most optimal spatiotemporal sowing calendar. The obtained results showed that with reference to the existing sowing patterns, early sowing of... (More)
This study aims to investigate the effects of an optimized sowing calendar for wheat over a surface irrigation scheme in the semi-arid region of Haouz (Morocco) on irrigation water requirements, crop growth and development and on yield. For that, a scenario-based simulation approach based on the covariance matrix adaptation–evolution strategy (CMA-ES) was proposed to optimize both the spatiotemporal distribution of sowing dates and the irrigation schedules, and then evaluate wheat crop using the 2011–2012 growing season dataset. Six sowing scenarios were simulated and compared to identify the most optimal spatiotemporal sowing calendar. The obtained results showed that with reference to the existing sowing patterns, early sowing of wheat leads to higher yields compared to late sowing (from 7.40 to 5.32 t/ha). Compared with actual conditions in the study area, the spatial heterogeneity is highly reduced, which increased equity between farmers. The results also showed that the proportion of plots irrigated in time can be increased (from 40% to 82%) compared to both the actual irrigation schedules and to previous results of irrigation optimization, which did not take into consideration sowing dates optimization. Furthermore, considerable reduction of more than 40% of applied irrigation water can be achieved by optimizing sowing dates. Thus, the proposed approach in this study is relevant for irrigation managers and farmers since it provides an insight on the consequences of their agricultural practices regarding the wheat sowing calendar and irrigation scheduling and can be implemented to recommend the best practices to adopt.
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- author
- Belaqziz, Salwa ; Khabba, Saïd ; Kharrou, Mohamed Hakim ; Bouras, El Houssaine LU ; Er-Raki, Salah and Chehbouni, Abdelghani
- publishing date
- 2021-09
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Evolutionary algorithm, Grain yield, Irrigation scheduling, Optimization, Seeding date, Water resources, Wheat
- in
- Remote Sensing
- volume
- 13
- issue
- 18
- article number
- 3789
- publisher
- MDPI AG
- external identifiers
-
- scopus:85115359754
- ISSN
- 2072-4292
- DOI
- 10.3390/rs13183789
- language
- English
- LU publication?
- no
- additional info
- Funding Information: Funding: This research was conducted within the framework of the Joint International Laboratory, TREMA (Télédétection et Ressources en Eau en Méditerranée semi-Aride (http://trema.ucam.ac. ma/), the Center for Remote Sensing Applications, CRSA (https://crsa.um6p.ma/home) and the Lab-SIV Laboratory of the Faculty of Science of Agadir. It was supported by the projects: ERANETMED3-062 CHAAMS “global Change: Assessment and Adaptation to Mediterranean Region Water Scarcity”, ACCWA-823965/H2020-MSCA-RISE-2018 “Accounting for Climate Change in Water and Agriculture Management” and PRIMA-S2-ALTOS-2018 “Managing water resources within Mediterranean agrosystems by Accounting for spatiaL sTructures and cOnnectivitieS”. Other funding was provided by PRIMA-IDEWA projects and OCP S.A. (Office Chérifien des Phosphates) in the context of ASSIWAT project (grant agreement no: 71). Funding Information: This research was conducted within the framework of the Joint International Laboratory, TREMA (Télédétection et Ressources en Eau en Méditerranée semi-Aride (http://trema.ucam.ac. ma/), the Center for Remote Sensing Applications, CRSA (https://crsa.um6p.ma/home) and the LabSIV Laboratory of the Faculty of Science of Agadir. It was supported by the projects: ERANETMED3-062 CHAAMS “global Change: Assessment and Adaptation to Mediterranean Region Water Scarcity”, ACCWA-823965/H2020-MSCA-RISE-2018 “Accounting for Climate Change in Water and Agriculture Management” and PRIMA-S2-ALTOS-2018 “Managing water resources within Mediterranean agrosystems by Accounting for spatiaL sTructures and cOnnectivitieS”. Other funding was provided by PRIMA-IDEWA projects and OCP S.A. (Office Chérifien des Phosphates) in the context of ASSIWAT project (grant agreement no: 71). Publisher Copyright: © 2021 by the authors.
- id
- 417f5ff3-b19f-440f-a381-185153fc2dc8
- date added to LUP
- 2023-01-04 09:46:39
- date last changed
- 2023-01-31 13:18:46
@article{417f5ff3-b19f-440f-a381-185153fc2dc8, abstract = {{<p>This study aims to investigate the effects of an optimized sowing calendar for wheat over a surface irrigation scheme in the semi-arid region of Haouz (Morocco) on irrigation water requirements, crop growth and development and on yield. For that, a scenario-based simulation approach based on the covariance matrix adaptation–evolution strategy (CMA-ES) was proposed to optimize both the spatiotemporal distribution of sowing dates and the irrigation schedules, and then evaluate wheat crop using the 2011–2012 growing season dataset. Six sowing scenarios were simulated and compared to identify the most optimal spatiotemporal sowing calendar. The obtained results showed that with reference to the existing sowing patterns, early sowing of wheat leads to higher yields compared to late sowing (from 7.40 to 5.32 t/ha). Compared with actual conditions in the study area, the spatial heterogeneity is highly reduced, which increased equity between farmers. The results also showed that the proportion of plots irrigated in time can be increased (from 40% to 82%) compared to both the actual irrigation schedules and to previous results of irrigation optimization, which did not take into consideration sowing dates optimization. Furthermore, considerable reduction of more than 40% of applied irrigation water can be achieved by optimizing sowing dates. Thus, the proposed approach in this study is relevant for irrigation managers and farmers since it provides an insight on the consequences of their agricultural practices regarding the wheat sowing calendar and irrigation scheduling and can be implemented to recommend the best practices to adopt.</p>}}, author = {{Belaqziz, Salwa and Khabba, Saïd and Kharrou, Mohamed Hakim and Bouras, El Houssaine and Er-Raki, Salah and Chehbouni, Abdelghani}}, issn = {{2072-4292}}, keywords = {{Evolutionary algorithm; Grain yield; Irrigation scheduling; Optimization; Seeding date; Water resources; Wheat}}, language = {{eng}}, number = {{18}}, publisher = {{MDPI AG}}, series = {{Remote Sensing}}, title = {{Optimizing the sowing date to improve water management and wheat yield in a large irrigation scheme, through a remote sensing and an evolution strategy-based approach}}, url = {{http://dx.doi.org/10.3390/rs13183789}}, doi = {{10.3390/rs13183789}}, volume = {{13}}, year = {{2021}}, }