Transfer Entropy as a Tool for Hydrodynamic Model Validation.
Transfer Entropy as a Tool for Hydrodynamic Model Validation.
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DOI：
10.3390/e20010058
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发表时间：
2018-01-12
期刊：
影响因子：
--
通讯作者：
Passalacqua P
中科院分区：
文献类型：
--
作者：
Sendrowski A;Sadid K;Meselhe E;Wagner W;Mohrig D;Passalacqua P
数值模型的验证是建模的重要组成部分，以确保模型输出在规定条件下的可靠性。在河流三角洲，模型的稳健验证至关重要，因为模型用于预测土地变化并跟踪水、固体和溶质通过三角洲网络的输送。我们建议使用转移熵（TE）来验证模型结果。 TE 根据强度、时间尺度和方向量化变量之间传递的信息。使用在美国路易斯安那州蜡湖三角洲的分流河道和河道间岛屿收集的水位数据，以及使用 Delft3D 为同一地点生成的模型水位数据，我们评估外部驱动因素（河流流量、潮汐、风）和模型水位之间的耦合程度如何重现观测到的数据耦合。我们使用十天的窗口时间来执行此操作。建模和观察的耦合比较良好；它们的差异反映了模型中风和粗糙度的空间参数化，这阻碍了模型捕获水位的高频波动。该模型比岛屿上的耦合更好地捕获了通道中的耦合，这表明模型中并未完全体现通道-岛屿连通性的机制。总体而言，TE 作为一种额外的验证工具来量化感兴趣系统在多个空间和时间尺度上的耦合。
The validation of numerical models is an important component of modeling to ensure reliability of model outputs under prescribed conditions. In river deltas, robust validation of models is paramount given that models are used to forecast land change and to track water, solid, and solute transport through the deltaic network. We propose using transfer entropy (TE) to validate model results. TE quantifies the information transferred between variables in terms of strength, timescale, and direction. Using water level data collected in the distributary channels and inter-channel islands of Wax Lake Delta, Louisiana, USA, along with modeled water level data generated for the same locations using Delft3D, we assess how well couplings between external drivers (river discharge, tides, wind) and modeled water levels reproduce the observed data couplings. We perform this operation through time using ten-day windows. Modeled and observed couplings compare well; their differences reflect the spatial parameterization of wind and roughness in the model, which prevents the model from capturing high frequency fluctuations of water level. The model captures couplings better in channels than on islands, suggesting that mechanisms of channel-island connectivity are not fully represented in the model. Overall, TE serves as an additional validation tool to quantify the couplings of the system of interest at multiple spatial and temporal scales.
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