The complex terrain, seasonality, and cold region hydrology of the Nelson Churchill River Basin (NCRB) presents a formidable challenge for hydrological modeling, which complicates the calibration of model parameters. Seasonality leads to different hydrological processes dominating at different times of the year, which translates to time variant sensitivity in model parameters. In this study, Hydrological Predictions for the Environment model (HYPE) is set up in the NCRB to analyze the time variant sensitivity analysis (TVSA) of model parameters using a Global Sensitivity Analysis technique known as Variogram Analysis of Response Surfaces (VARS). TVSA can identify parameters that are highly influential in a short period but relatively uninfluential over the whole simulation period. TVSA is generally effective in identifying model’s sensitivity to event-based parameters related to cold region processes such as snowmelt and frozen soil. This can guide event-based calibration, useful for operational flood forecasting. In contrast to residual based metrics, flow signatures, specifically the slope of the mid-segment of the flow duration curve, allows VARS to detect the influential parameters throughout the timescale of analysis. The results are beneficial for the calibration process in complex and multi-dimensional models by targeting the informative parameters, which are associated with the cold region hydrological processes.

中文翻译：

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基于流特征的寒冷地区水文模型参数时变敏感性分析

尼尔森丘吉尔河流域 (NCRB) 复杂的地形、季节性和寒冷地区水文对水文建模提出了艰巨的挑战，这使得模型参数的校准变得复杂。季节性导致不同的水文过程在一年中的不同时间占主导地位，这转化为模型参数的时间变量敏感性。在本研究中，NCRB 中设置了环境水文预测模型 (HYPE)，以使用称为响应面变差函数分析 (VARS) 的全局灵敏度分析技术来分析模型参数的时变灵敏度分析 (TVSA)。TVSA 可以识别在短时间内影响很大但在整个模拟期间影响相对较小的参数。TVSA 通常可有效识别模型对与寒冷地区过程（如融雪和冻土）相关的基于事件的参数的敏感性。这可以指导基于事件的校准，对业务洪水预报很有用。与基于残差的指标相比，流量特征，特别是流量持续时间曲线中间段的斜率，允许 VARS 在整个分析时间尺度上检测有影响的参数。通过针对与寒冷地区水文过程相关的信息参数，结果有利于复杂和多维模型中的校准过程。与基于残差的指标相比，流量特征，特别是流量持续时间曲线中间段的斜率，允许 VARS 在整个分析时间尺度上检测有影响的参数。通过针对与寒冷地区水文过程相关的信息参数，结果有利于复杂和多维模型中的校准过程。与基于残差的指标相比，流量特征，特别是流量持续时间曲线中间段的斜率，允许 VARS 在整个分析时间尺度上检测有影响的参数。通过针对与寒冷地区水文过程相关的信息参数，结果有利于复杂和多维模型中的校准过程。