Plant water deficit index-based irrigation under conditions of salinity

Highlights

• Relative position of soil water and salt to roots affects plant water status.

• Root-weighted approach can enhance estimation of plant water deficit index (PWDI).

• PWDI under salinity was studied for wheat in soil columns and cotton in field.

• Root-weighted PWDI estimation improves irrigation scheduling in salinized field.

Abstract

In arid and semi-arid regions, water scarcity and soil salinization are major factors impacting sustainable agricultural production. In this study, a macroscopic root-water-uptake model was used to adapt a plant water deficit index (PWDI) for irrigation scheduling under conditions of coexisting soil water and salinity stress-causing factors. The traditional approach, estimating PWDI with average root zone soil water and salt amounts, was improved by weighting the effects of soil water and salinity according to the normalized root length density profile. An experiment growing wheat (Triticum aestivum L.) in soil columns and an experiment growing cotton (Gossypium hirsutum L.) in a salinized field were implemented to explore and quantify the effects of soil water and salinity conditions on plant water status, and thus to validate the improvement and evaluate its application, by monitoring soil water and salinity dynamics and plant growth indexes (e.g., leaf area, dry weight, leaf water potential, transpiration and yield). The results indicate that, even under conditions with equal root zone averages of soil matric and osmotic potentials, plant water status might be significantly different. In general, plants were less stressed when more water and less salinity were allocated in the upper root zone with more roots while less water and more salinity occurred in the lower root zone with less roots. By referring to some information in the soil column experiment, a numerical experiment was conducted to further demonstrate the improvement. The root-weighted approach resulted in improved PWDI estimation and thus was more reliable for irrigation scheduling, leading to higher irrigation frequency and quantity, leaf area index, biomass, yield, and transpiration, without significant decrease in water productivity. However, further improvement could be possible by considering the effects of historical soil water and salinity stresses as well as meteorological conditions on plant water status.

Introduction

Salt-affected soils are widely distributed around the world, accounting for about 7% of total land area and seriously threatening agricultural production and ecosystem stability (Wichelns and Qadir, 2014, Li et al., 2018). In some arid and semi-arid regions such as Xinjiang territory in northwest China, about 32% of total irrigated land is saline (Yang et al., 2019). Therefore, to enhance water productivity (WP), defined as crop yield per unit of applied irrigation water, and/or to increase yield itself in arid and semiarid regions, irrigation scheduling must be designed to relieve water and salinity stresses simultaneously (Li et al., 2016).

Salinity affects crops both via non-specific lowering of soil osmotic potential (SOP), and by specific ion toxicity (Homaee, 1999, Karlberg et al., 2006). In saline soil, root-water-uptake (RWU) often declines with decreasing water potential gradient between soil and roots, resulting from decreased soil water content and/or increased salt concentration in soil solution (Homaee et al., 2002a, Homaee et al., 2002b). Water deficit occurs when plant transpiration cannot satisfy atmospheric demand. The ratio of decrease in transpiration relative to demand is defined as a plant water deficit index (PWDI) (Woli et al., 2012, Shi et al., 2015):

$$\mathrm{PWDI}=\frac{T_p-T_a}{T_p}=1-\frac{T_a}{T_p}$$

where T_a and T_p are the actual and potential transpiration rates (cm d⁻¹), respectively. Proper evaluation of PWDI can promote accurate irrigation to efficiently use water resources and/or enhance production (Shi et al., 2015, Shi et al., 2020, Wu et al., 2017).

In addition to transpiration, other physiological indicators such as leaf water potential, photosynthetic rate, leaf stomatal conductance or canopy temperature can theoretically also reflect plant water deficit (Gardner et al., 1992, Jones, 2004, Candogan et al., 2013) and be used for irrigation scheduling. Nevertheless, these plant and canopy-based indicators suffer from difficulty and expense in data acquisition and challenge in translating data into irrigation quantities (Jones, 2004, Shi et al., 2015, Wu et al., 2017). Alternatively, the soil-based approach has been more widely adopted by taking soil water and salinity conditions into account, such as (Dirksen et al., 1993, Homaee et al., 2002c, Muñoz-Carpena et al., 2008):

$$\mathrm{PWDI}=1-\gamma \left(\overline{h}\right)\beta \left(\overline{\phi }\right)$$

where $\overline{h}$ and $\overline{\phi }$ are the arithmetic averages of soil matric potential (SMP) and SOP over the root zone (cm), respectively; $\gamma \left(\overline{h}\right)$ and $\beta \left(\overline{\phi }\right)$ are dimensionless soil water and salinity stress response functions, respectively. In fact, besides soil water and salt amounts, the relative positions of water and salt to roots also significantly impact plant transpiration by changing soil water effectiveness (Raats, 1974, Homaee, 1999, Homaee et al., 2002a, Fujimaki et al., 2008). When soil water and salt amounts over the root zone are constant, more water or less salt in sub-zones with more roots is beneficial for water uptake, compared to situations where more water or less salt occurs in soil with less roots (Dirksen et al., 1993, Homaee, 1999, Shi et al., 2015, Tzohar et al., 2021). To accurately estimate PWDI with a soil-based approach, in addition to soil water and salt amounts, the relative distribution relationship among water, salt and roots should therefore also be considered.

Under conditions with negligible salinity stress, Shi et al. (2015) improved the soil-based approach to estimate PWDI by weighting the effect of soil water according to root distribution:

$$\mathrm{PWDI}=1-{\int }_0^1\gamma \left(h\right)L_{nrd}\left(z_r\right){\mathrm{dz}}_r$$

where z_r (= z/L_r) is the normalized depth, z is the positive downwards vertical coordinate (cm) originating from the soil surface, and L_r is rooting depth (cm); L_nrd(z_r) is the normalized root length density (NRLD); h is the SMP (cm). This improvement has been validated to more accurately evaluate plant water status under various soil, atmosphere, crop and irrigation conditions (Shi et al., 2015, Wu et al., 2017), compared to the traditional approach based on Eq. (2). In the lysimetric experiment, the relative errors of PWDI estimation was reduced from 12.1–19.0% to 9.1–9.5%, and thus taking root-weighted PWDI as a signal to initiate irrigation led to higher irrigation precision, yield and WP (Wu et al., 2017). Furthermore, the improved PWDI estimation exhibited great potential in data-driven smart irrigation by promoting timely supply of appropriate quantities of water to crops, according to predetermined targets of yield and/or WP (Shi et al., 2020, Shi et al., 2021). However, the improvement of PWDI estimation, obtained under drought-stressed condition, cannot be applied in saline soil where water and salinity stresses coexist. Consequently, the objective of the current study was to improve PWDI estimation in saline soil by exploring and quantifying the effects of soil water and salinity conditions on plant water status, and subsequently to evaluate the effects of the improvement on irrigation scheduling, crop yield and WP.