Applying dual stable isotopes and a MixSIAR model to determine root water uptake of winter wheat

Water sources for root water uptake: Using stable isotopes of hydrogen and oxygen as a research tool in agricultural and agroforestry systems

“…Irrigation and fertilization can largely affect RWU by cultivated plants, leading crops to access distinct proportions of water sources or different proportions of water from various soil depths, especially during dry periods (Goebel et al, 2015;Du et al, 2018). For instance, for maize, different depths of RWU were observed under the application of distinct irrigation treatments, such as furrow irrigation, border irrigation, and alternate furrow irrigation (Wu et al 2018a).…”

“…These could include the improvement of local to regional farming practices such as irrigation or fertilization treatment schemes (e.g. Du et al, 2018;Ma and Song, 2018). Strategic planning at longer timescales would also benefit from insights into the ability of plants to access different sources, especially under changing hydro-climatological conditions such as extreme weather events, droughts or altered flow regimes (e.g.…”

Water Consumption Structure and Root Water Absorption Source of an Oasis Cotton Field in an Arid Area of China

“…The average values were −83.08‰ and −12.26‰, with standard deviations of 38.49‰ and 5.24‰, respectively (Figure 3). The local meteorological water line (LMWL) equation is δD = 7.06δ 18 O + 3.61 (R 2 = 0.92). Compared with that of the global meteorological water line (GMWL: δD = 8.20δ 18 O + 10.00), the slope and intercept of the LMWL were lower, which implied that the local water vapor underwent significant evaporation and had a drier climate than the global average climate.…”

“…The direct comparison method can qualitatively determine the main water absorption level of crop roots; however, when there are multiple points of intersection, it becomes challenging to pinpoint a particular water absorption level. Multivariate linear mixing models can provide a proportion of multiple potential sources of water, yet they do not take into account the complexity of potential sources of water or random errors [18]. The MixSIAR model combines the following two characteristics: first, it includes the uncertainty of different water sources; and second, it includes isotopic characteristics and isotopic fractionation, which allows the input data to be the average of the measured δD and δ 18 O of each water source and the standard deviation of the isotope values of each water source, rather than a single average value of all source isotope data [19].…”

“…Zhang et al [20] reported that Bayesian mixture models are reliable in distinguishing plant water sources. Therefore, D and 18 O isotopes and the MixSIAR model can be applied to quantitatively identify the sources of water absorption of cotton at different growth stages to compensate for the current understanding of the cotton water absorption process in arid areas.…”