Your search found 1 records
1 Alvar-Beltran, J.; Saturnin, C.; Gregoire, B.; Camacho, J. L.; Dao, A.; Migraine, J. B.; Marta, A, D. 2023. Using AquaCrop as a decision-support tool for improved irrigation management in the Sahel Region. Agricultural Water Management, 287:108430. (Online first) [doi: https://doi.org/10.1016/j.agwat.2023.108430]
Decision support systems ; Irrigation management ; Tomatoes ; Maize ; Quinoa ; Food security ; Agricultural extension ; Water productivity ; Models ; Water resources ; Precipitation ; Evapotranspiration ; Drought stress ; Canopy ; Irrigation schemes ; Yields ; Crop water use ; Water requirements ; Early warning systems / Sahel / West Africa / Burkina Faso
(Location: IWMI HQ Call no: e-copy only Record No: H052111)
https://www.sciencedirect.com/science/article/pii/S0378377423002950/pdfft?md5=071f68c31d21c94884a3be995aaa27d5&pid=1-s2.0-S0378377423002950-main.pdf
https://vlibrary.iwmi.org/pdf/H052111.pdf
https://vlibrary.iwmi.org/pdf/H052111.pdf
(3.41 MB) (3.41 MB)
Operational systems providing irrigation advisories to agricultural extension workers are paramount, particularly in West Africa where the yield gap represents the greatest agriculture growth-led opportunity. The proposed framework for Burkina Faso, an irrigation decision support system (DSS), is based on in-situ weather and field observations necessary for feeding the atmosphere, soil, and crop modules of crop-water productivity models (e.g., AquaCrop). To optimize water resources, incoming irrigation and precipitation, and outgoing evapotranspiration are constantly monitored and adjusted. The findings of the proposed semi-automatic irrigation DSS indicate that water stresses affecting the canopy cover and stomatal closure are minimized if the proposed irrigation schemes are generated and improved with five-day weather observations. The source of uncertainty in crop models’ evapotranspiration estimations is reduced by systematically comparing the observed crop evapotranspiration (ETc) with historical ETc records. An increase in yields is observed in all studied crops, from 1960 to 2018 kg/ha (tomato dry yields), from 2571 to 2799 kg/ha (maize), and from 1279 to 1385 kg/ha (quinoa) when comparing the 2020–21 and 2021–22 experiments. Results show an optimization of water resources, with a higher evapotranspired water productivity (WPET, expressed as dry weight) when comparing the two experiments, from 0.86 to 0.97 kg/m3 for tomato, from 0.85 to 0.86 kg/m3 for maize, and from 0.67 to 0.73 kg/m3 for quinoa, respectively in 2020–21 and 2021–22. The proposed irrigation DSS can be used to inform extension workers and technical agronomic experts about real-time crop water requirements and, thus, assist the Climate Risk and Early Warning Systems (CREWS) initiative that aims to improve access to weather information for decision-support in agriculture. Afterwards, extension agents can catalyze irrigation advisories and support farmers improve irrigation management at the field level to, ultimately, obtain higher yields.
Powered by DB/Text WebPublisher, from
