Interactive effects of irrigation system and level on grain yield, crop water use, and greenhouse gas emissions of summer maize in North China Plain.
Sci Total Environ
; 864: 161165, 2023 Mar 15.
Article
in En
| MEDLINE
| ID: mdl-36572302
Irrigation management is one of most critical factors influencing soil N2O and CO2 emissions in dryland agriculture. To explore the effects of irrigation systems and levels on the mitigation of N2O and CO2 emissions from maize fields and to determine the balance among greenhouse gases (GHG) emission, water-saving and grain yield, a two-year field experiment was conducted in the North China Plain (NCP) during the growing seasons of 2018 and 2019. Two irrigation systems (i.e., flood irrigation, FI, and drip irrigation, DI) were adopted with four irrigation levels in each system, including 65 mm/event (sufficient irrigation, CK), 50 mm/event (decreased by 23 %), 35 mm/event (by 46 %) and 20 mm/event (by 69 %), respectively. The results showed that both irrigation systems and levels had significant effects on soil N2O and CO2 emissions (P < 0.05). Nitrous oxide (N2O) and CO2 emissions peaked following irrigation or irrigation + fertilization events during sowing to early filling stage (R1), with the peak values increasing with irrigation levels. Meanwhile, peak values from FI were higher than those from DI at 50 mm and 65 mm irrigation levels. The average cumulative N2O and CO2 emissions of DI treatments were 14.9 % and 6.23 % lower than those of FI treatments (P < 0.05), respectively. Soil moisture was identified as one of the most crucial factors influencing N2O and CO2 fluxes. Deficit irrigation efficiently deceased cumulative N2O and CO2 emissions, but moderate to severe deficit irrigation brought significant reduction in grain yield. Drip irrigation with a slight deficit irrigation level (decreased by 23 %) obtained the best economic and environmental benefits, which achieved the dual goal of lower GHG emissions but higher WUE without sacrificing grain yield.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
Language:
En
Journal:
Sci Total Environ
Year:
2023
Type:
Article