Sendrowski Alicia, Sadid Kazi, Meselhe Ehab, Wagner Wayne, Mohrig David, Passalacqua Paola
Department of Civil, Architectural and Environmental Engineering, Center for Water and the Environment, The University of Texas at Austin, Austin, TX 78712, USA.
The Water Institute of the Gulf, Baton Rouge, LA 70802, USA.
Entropy (Basel). 2018 Jan 12;20(1):58. doi: 10.3390/e20010058.
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.
数值模型的验证是建模的一个重要组成部分,以确保在规定条件下模型输出的可靠性。在河流三角洲地区,鉴于模型用于预测土地变化以及追踪水、固体和溶质通过三角洲网络的输送情况,对模型进行稳健的验证至关重要。我们建议使用转移熵(TE)来验证模型结果。TE从强度、时间尺度和方向等方面量化变量之间传递的信息。利用在美国路易斯安那州蜡湖三角洲分流河道和河道间岛屿收集的水位数据,以及使用Delft3D为相同位置生成的模拟水位数据,我们评估外部驱动因素(河流流量、潮汐、风)与模拟水位之间的耦合在多大程度上再现了观测到的数据耦合。我们使用十天的时间窗口随时间进行此项操作。模拟和观测的耦合情况比较吻合;它们之间的差异反映了模型中风和粗糙度的空间参数化,这使得模型无法捕捉水位的高频波动。模型在河道中比在岛屿上能更好地捕捉耦合情况,这表明模型中未充分体现河道与岛屿之间的连通机制。总体而言,TE作为一种额外的验证工具,可在多个空间和时间尺度上量化感兴趣系统的耦合情况。