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.

在干旱和半干旱地区，缺水和土壤盐渍化是影响可持续农业生产的主要因素。在这项研究中，在土壤水分和盐分胁迫因素并存的条件下，使用宏观根系吸水模型来调整植物水分亏缺指数（PWDI）以进行灌溉调度。通过根据标准化的根长密度分布对土壤水和盐度的影响进行加权，改进了用平均根区土壤水和盐量估算 PWDI 的传统方法。在土壤柱中种植小麦（Triticum aestivum L.）的试验和种植棉花（ Gossypium hirsutum ）的试验L.）在盐渍化田间实施，通过监测土壤水分和盐分动态以及植物生长指标（例如, 叶面积, 干重, 叶水势，蒸腾和产量）。结果表明，即使在土壤基质和渗透势的根区平均值相等的条件下，植物水分状况也可能存在显着差异。一般而言，当更多的水和更少的盐分分配在根系较多的上根区时，植物受到的压力较小，而在根系较少的下根区分配的水分和盐分较少。参考土柱试验中的一些资料，进行了数值试验，进一步论证了改进的效果。根加权方法改进了 PWDI 估计，因此对于灌溉计划更可靠，导致更高的灌溉频率和数量、叶面积指数、生物量、产量和蒸腾，而不会显着降低水生产力。然而，