The performance criteria have been often used in the hydrological model evaluation or calibration. Since the performance criteria have their own advantages and disadvantages, it is necessary to understand the impact of each performance criterion on the model evaluation or calibration to be used for the purposes of model applications. The Liu Mean Efficiency (LME) was proposed for the design flow estimates from hydrological modeling data by reformulating the three metric components (correlation, variability, and bias measures) in the Nash and Sutcliffe efficiency (NSE) or the Kling and Gupta Efficiency (KGE) to improve the flow variability in the runoff simulations optimized with the NSE or KGE. This article has discussed that the LME criterion has weaknesses of an underdetermined system that can potentially induce the vagueness in comparative assessments for alternative model performance as well as an overestimation system that can substantially reduce the reliability in design flow estimates through hydrological modeling. A complement approach to the limitations of the LME is necessary for the LME to be made fit for a rational performance criterion.

性能标准经常用于水文模型评估或校准。由于性能标准各有优缺点，因此有必要了解每个性能标准对模型评估或校准的影响，以便用于模型应用。通过重新制定 Nash 和 Sutcliffe 效率 (NSE) 或 Kling 和 Gupta 效率 (KGE) 中的三个度量组件（相关性、可变性和偏差度量），提出 Liu 平均效率 (LME) 用于从水文建模数据估算设计流量) 以改善使用 NSE 或 KGE 优化的径流模拟中的流量可变性。本文讨论了 LME 标准存在欠定系统的弱点，该系统可能会导致替代模型性能比较评估的模糊性，以及可能导致通过水文建模显着降低设计流量估计可靠性的高估系统。要使 LME 适合合理的绩效标准，就必须采用补充方法来解决 LME 的局限性。