Crop yield has been analyzed under different hydrological conditions by many researchers. However, little information is available about the behavior of rice yield for different conditions during its growth. This study investigated the behavior of rice yield under varying hydrological conditions in two regions of India, one rainfed and the other irrigated, for the period 2000–2018. Additionally, it examined how individual, coincidental, and sequential compound extremes, such as rainfall, temperature, and soil moisture, affected rice yield. Four individual, two coincidental, and two sequential compound extremes regression models were developed. These models were designed with yield as a function of individual and compound extremes. Individual extreme models focused on heat and water metrics independently, while compound extremes occurred when heat and water stress coincided or followed each other closely. Linear panel models were used to assess the dependency of rice yield on hydrological parameters. Results indicate that excessive heat negatively affects rice yield, particularly when coupled with low soil moisture. However, excess soil moisture mitigates heat-related damage, highlighting the significance of controlling soil moisture levels. Additionally, coincidental compound extremes pose greater threats to rice yield than sequential ones. The study underscores the importance of considering geographical variations and hydrological variables in understanding crop yield behaviour. Overall, the findings suggest the potential for optimizing soil moisture management to enhance rice yield amidst changing climatic conditions.

许多研究人员已经分析了不同水文条件下的作物产量。然而，关于水稻生长过程中不同条件下的产量行为的信息很少。本研究调查了 2000 年至 2018 年期间印度两个地区（一个雨养地区和另一个灌溉地区）不同水文条件下水稻产量的变化。此外，它还研究了降雨、温度和土壤湿度等个别、巧合和连续的复合极端情况如何影响水稻产量。开发了四个单独的、两个巧合的和两个连续的复合极值回归模型。这些模型的设计将产量作为个体和复合极值的函数。单独的极端模型独立地关注热量和水的指标，而当热量和水的压力同时发生或密切相关时，就会出现复合极端。线性面板模型用于评估水稻产量对水文参数的依赖性。结果表明，过多的热量会对水稻产量产生负面影响，特别是在土壤湿度较低的情况下。然而，过量的土壤湿度可以减轻与热相关的损害，凸显了控制土壤湿度水平的重要性。此外，巧合的复合极端事件对水稻产量的威胁比连续的复合极端事件更大。该研究强调了在理解作物产量行为时考虑地理变化和水文变量的重要性。总体而言，研究结果表明，在不断变化的气候条件下，优化土壤水分管理有可能提高水稻产量。