Table_1_Crop sensitivity to waterlogging mediated by soil temperature and growth stage.xlsx

Waterlogging constrains crop yields in many regions around the world. Despite this, key drivers of crop sensitivity to waterlogging have received little attention. Here, we compare the ability of the SWAGMAN Destiny and CERES models in simulating soil aeration index, a variable contemporaneously used to compute three distinct waterlogging indices, denoted hereafter as WI Destiny, WIASD1, and WIASD2. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI Growth, which accommodates growth stage tolerance, and WI Plus, which accounts for both soil temperature and growth stage. We evaluate these indices using data collected in pot experiments with genotypes “Yang mai 11” and “Zheng mai 7698” that were exposed to both single and double waterlogging events. We found that WI Plus exhibited the highest correlation with yield (-0.82 to -0.86) suggesting that waterlogging indices which integrate effects of temperature and growth stage may improve projections of yield penalty elicited by waterlogging. Importantly, WI Plus not only allows insight into physiological determinants, but also lends itself to remote computation through satellite imagery. As such, this index holds promise in scalable monitoring and forecasting of crop waterlogging.

渍涝胁迫制约着全球诸多地区的作物产量。尽管如此，作物对渍涝敏感性的关键驱动因素却鲜有研究关注。本研究对比了SWAGMAN Destiny与CERES模型在模拟土壤通气指数（soil aeration index）方面的性能——该变量可同时用于计算三种不同的渍涝指数，下文分别记为WI Destiny、WIASD1与WIASD2。随后，我们通过引入两类渍涝严重度指数，分别考量作物生育期与土壤温度对渍涝影响的调控作用：其一为WI Growth（WI Growth），可适配作物生育期的耐渍性差异；其二为WI Plus（WI Plus），可同时纳入土壤温度与作物生育期的影响。我们采用针对基因型为"扬麦11"与"郑麦7698"的盆栽试验数据对上述指数进行评估，这些试验设置了单次与两次渍涝处理。研究结果显示，WI Plus与产量的相关性最高（相关系数介于-0.82至-0.86之间），这表明整合了温度与生育期效应的渍涝指数可优化渍涝导致的产量损失预测精度。尤为关键的是，WI Plus不仅可助力解析渍涝影响的生理决定机制，还可通过卫星影像实现遥感计算。因此，该指数在作物渍涝的规模化监测与预测领域具有良好应用前景。