<![CDATA[This study proposes an adaptive water allocation framework based on the pipeline P(t)→SPI(t)→A(t), with SPI serving as a control variable to represent hydrological conditions probabilistically. Analysis shows that rainfall is non-stationary and dominated by stochastic variability, making a mean-based approach unrepresentative. Integrating SPI enables dynamic adjustment of allocations to actual conditions, reducing the deficit by 12.96% and increasing efficiency from 46.32% to 53.49%. Validation of the dataset shows high consistency with the presence of systematic scale bias, making it more suitable for anomaly-based analysis. Sensitivity analysis identifies bounded responsiveness, where the system is adaptive under normal conditions but remains stable under extreme conditions. Conceptually, this study transforms the SPI into a decision variable, thereby establishing a causal relationship between hydroclimatic variability and allocation decisions and enhancing the system’s resilience to drought risk.]]>
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