Effects of alternate wetting and drying irrigation on yield, water and nitrogen use, and greenhouse gas emissions in rice paddy fields

Alternate wetting and drying (AWD) irrigation is a reliable and widespread water-saving technology for rice production. This review aimed to comprehensively assess the changes in water use, yield, nitrogen use efficiency (NUE), and greenhouse gas (GHG) emissions after AWD adoption and explore the optimal AWD water thresholds. Based on abundant data obtained from contrasting experiments between AWD and continuous flooding (CF) irrigation, the effects of AWD were quantified by stepwise multiple linear regression (MLR). The quantitative indices are the changes in total irrigation water ( ΔIW ), water productivity ( ΔWP ), grain yields ( ΔGY ), NUE indices, global warming potential ( ΔGWP ), and yield-scaled global warming potential ( ΔYGWP ) between AWD and CF. It was found that the Δ C-A (i.e. the difference between the CF and AWD thresholds) and soil types were the most noteworthy indicators affecting IW, water productivity, yield and partial factor productivity of N (PFPN). Meanwhile, the Δ C-A and fertilizer-N rates (NR) were two key indicators affecting GHG emissions. Thereafter, for different soil types, a group of optimization models were established to explore the optimal AWD water thresholds for optimizing ΔIW and ΔWP simultaneously without yield, NUE, and GHG emissions penalties. The results showed that the optimal upper limit of AWD ( U AWD ) should be equal to the upper limit of the CF ( U CF ), and the optimal lower limit of AWD ( L AWD ) can be obtained by the model. Taking the clay paddy field as an example, the min ΔIW were −41% to −8%, and the max ΔWP were 11%–54% after adopting optimal AWD water managements. The corresponding ΔGY , ΔPFPN , ΔGWP , ΔYGWP were 0%–1%, 0%–1%, −66% to −15% and −52% to −12%, respectively. This review provides a novel way to estimate the performance of AWD and provide guidance for proper AWD water management. • Effects of AWD on water use, yield, NUE and GHG emissions were reviewed and analyzed. • Δ C-A and soil types were critical indicators for IW, water productivity, yield and PFPN. • Δ C-A and NR were key indicators affecting changes in GHG emissions after AWD adoption. • The optimal water thresholds of AWD were assessed by a novel optimization model. • The optimal U AWD was equal to U CF , and optimal L AWD was obtained by the model.