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Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency
Year:
2021
Source of publication :
Agricultural Water Management
Authors :
Ben-Gal, Alon
;
.
Volume :
248
Co-Authors:
  • Shi, J.
  • Wu, X.
  • Zhang, M.
  • Wang, X.
  • Zuo, Q.
  • Wu, X.
  • Zhang, H.
  • Ben-Gal, A
Facilitators :
From page:
0
To page:
0
(
Total pages:
1
)
Abstract:

Knowledge-driven “smart” irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. 

Note:
Related Files :
Crop growth
decision support system
Irrigation scheduling
Regulated deficit irrigation
Soil water transport
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Related Content
More details
DOI :
10.1016/j.agwat.2021.106774
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
53541
Last updated date:
02/03/2022 17:27
Creation date:
17/02/2021 23:53
Scientific Publication
Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency
248
  • Shi, J.
  • Wu, X.
  • Zhang, M.
  • Wang, X.
  • Zuo, Q.
  • Wu, X.
  • Zhang, H.
  • Ben-Gal, A
Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency

Knowledge-driven “smart” irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. 

Scientific Publication
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