RZWQM2 Simulated Drip Fertigation Management to Improve Water and Nitrogen Use Efficiency of Maize in a Solar Greenhouse

Haomiao Cheng, Qilin Yu, Mohmed A. M. Abdalhi, Fan Li, Zhiming Qi, Tengyi Zhu, Wei Cai, Xiaoping Chen and Shaoyuan Feng
Additional contact information
Haomiao Cheng: School of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
Qilin Yu: School of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
Mohmed A. M. Abdalhi: Department of Agricultural Engineering, Faculty of Agricultural Technology and Fish Sciences, Al-Neelain University, Khartoum 12702, Sudan
Fan Li: School of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225127, China
Zhiming Qi: Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
Tengyi Zhu: School of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
Wei Cai: School of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
Xiaoping Chen: School of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225127, China
Shaoyuan Feng: School of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225127, China

Agriculture, 2022, vol. 12, issue 5, 1-14

Abstract: The drip fertigation technique is a modern, efficient irrigation method to alleviate water scarcity and fertilizer surpluses in crop production, while the precise quantification of water and fertilizer inputs is difficult for drip fertigation systems. A field experiment of maize ( Zea mays L.) in a solar greenhouse was conducted to meet different combinations of four irrigation rates (I 125 , I 100 , I 75 and I 50 ) and three nitrogen (N) fertilizer rates (N 125 , N 100 and N 75 ) under surface drip fertigation (SDF) systems. The Root Zone Water Quality Model (RZWQM2) was used to assess the response of soil volumetric water content (VWC), leaf area index (LAI), plant height and maize yield to different SDF managements. The model was calibrated by the I 100 N 100 scenario and validated by the remaining five scenarios (i.e., I 125 N 100 , I 75 N 100 , I 50 N 100 , I 100 N 125 and I 100 N 75 ). The predictions of VWC, LAI and plant height were satisfactory, with relative root mean square errors (RRMSE) < 9.8%, the percent errors (PBIAS) within ±6%, indexes of agreement (IoA) > 0.85 and determination of coefficients (R 2 ) > 0.71, and the relative errors (RE) of simulated yields were in the range of 1.5–7.2%. The simulation results showed that both irrigation and fertilization had multiple effects on water and N stresses. The calibrated model was subsequently used to explore the optimal SDF scenarios for maximizing yield, water use efficiency (WUE) or nitrogen use efficiency (NUE). Among the SDF managements of 21 irrigation rates × 31 N fertilizer rates, the optimal SDF scenarios were I 120 N 130 for max yield (10516 kg/ha), I 50 N 70 for max WUE (47.3 kg/(ha·mm)) and I 125 N 75 for max NUE (30.2 kg/kg), respectively. The results demonstrated that the RZWQM2 was a promising tool for evaluating the effects of SDF management and achieving optimal water and N inputs.

Keywords: RZWQM2; surface drip fertigation; water use efficiency; nitrogen use efficiency (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2077-0472/12/5/672/pdf (application/pdf)
https://www.mdpi.com/2077-0472/12/5/672/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:12:y:2022:i:5:p:672-:d:811004

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().