Characterization of water use and productivity dynamics across four C₃ and C₄ row crops under optimal growth conditions

Crop selection in irrigated conditions entails characterization of crop water use and productivity dynamics under limited freshwater availability in a changing climate and environment. There is ample scope to optimally irrigate row crops, given the associated economic returns under full irrigation, and relatively non-alarming groundwater declines to require limited irrigation, at least in many parts of the United States, including Nebraska. However, a fair and careful comparative assessment of cereal row crops for their efficiency of water use and associated metrics under optimal growth conditions is lacking. We conducted field research in semi-arid south central Nebraska during 2016–2018 to comprehensively characterize water use and productivity dynamics in four major C3 (soybean and winter wheat) and C4 [maize (long season or L.S. and shorter season or S.S.) and sorghum] crops under consistent and well-managed conditions. Crop-specific signatures were found in seasonal profiles of total soil-water and soil-water depletion. The highest seasonal total evapotranspiration (ET_a) was demonstrated by winter wheat (604 mm), followed by L.S. maize (594 mm), soybean (591 mm), S.S. maize (547 mm), and sorghum (518 mm). Normalization and scaling of ET_a was accomplished so as to better reflect comparative ET_a per unit of heat accumulation (thermal units or TU). ET_a was also studied relative to evaporative demand using single and basal crop coefficients (K_c and K_cb, respectively). Consequently, empirical functions were developed for K_c and K_cb using base-scales of days after emergence, cumulative TU (CTU), and normalized CTU. Crop-specific sensitivity of K_cb to morphological area was studied. Crop water productivity based on grain yield (WP_GY) and aboveground biomass (WP_AGB) was quantified and it was found that the two C₄ crops were 89% more water-efficient than their C₃ counterparts. Finally, the importance of VPD to explain the variability and improve prediction of WP_AGB in various crops was established.