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Integrating Large Wood Jams into Hydraulic Models: Evaluating a Porous Plate Modeling Method
Journal of the American Water Resources Association ( IF 2.6 ) Pub Date : 2020-01-08 , DOI: 10.1111/1752-1688.12818
Roby Ventres‐Pake 1 , Matt Nahorniak 2 , Natalie Kramer 3 , Jennifer O’Neal 1 , Tim Abbe 1
Affiliation  

Large wood (LW) jams are key riverine habitat features that affect hydraulic processes and aquatic habitat. The hydraulic influence of LW jams is poorly understood due to the complexity of fluid dynamics around irregular, porous structures. Here we validated a method for two‐dimensional hydraulic modeling of porous LW jams using the open‐source modeling software Delft3D‐FLOW. We sampled 19 LW jams at three reaches across the Columbia River Basin in the United States. We used computer‐generated porous plates to represent LW jams in the modeling software and calibrated our modeling method by comparing model outputs to measured depths and velocities at validation points. We found that modeling outputs are error‐prone when LW jams are not represented. By representing LW jams as porous plates we reduced average velocity root mean square error (RMSE) values (i.e., improved model accuracy) by 42.8% and reduced average depth RMSE values by 5.2%. These differences impacted habitat suitability index modeling. We found a 15.1% increase in weighted useable area for juvenile steelhead at one test site when LW jams were simulated vs. when they were ignored. We investigated patterns in average RMSE improvements with varying jam size, bankfull obstruction, porosity, and structure type, and river complexity. We also identified research gaps related to field estimation of LW jam porosity and porous structure modeling methods.

中文翻译:

将大型木材果酱整合到水力模型中:评估多孔板建模方法

大型木材(LW)果酱是影响水力过程和水生生境的重要河流生境特征。由于不规则多孔结构周围流体动力学的复杂性,人们对LW堵塞的水力影响了解甚少。在这里,我们使用开源建模软件Delft3D-FLOW验证了多孔LW堵塞的二维水力建模方法。我们在美国哥伦比亚河流域的三个河段采样了19个LW堵塞。我们使用计算机生成的多孔板来表示建模软件中的LW卡纸,并通过将模型输出与验证点处测得的深度和速度进行比较来校准我们的建模方法。我们发现,当未表示LW卡纸时,建模输出容易出错。通过将LW堵塞表示为多孔板,我们将平均速度均方根误差(RMSE)值(即,提高的模型精度)降低了42.8%,并将平均深度RMSE值降低了5.2%。这些差异影响了栖息地适宜性指数建模。我们发现,在模拟LW卡纸时与在忽略LW卡纸时相比,在一个测试点上,青少年钢头的加权可用面积增加了15.1%。我们调查了平均RMSE改进的模式,这些模型具有不同的卡纸大小,河堤阻塞,孔隙度和结构类型以及河流复杂性。我们还确定了与LW堵塞孔隙率现场估算和多孔结构建模方法有关的研究空白。在模拟LW卡纸时与在忽略LW卡纸时相比,在一个测试点上,少年钢头的加权可用面积增加了1%。我们调查了平均RMSE改进的模式,这些模型具有不同的卡纸大小,河堤阻塞,孔隙度和结构类型以及河流复杂性。我们还确定了与LW堵塞孔隙率现场估算和多孔结构建模方法有关的研究空白。在模拟LW卡纸时与在忽略LW卡纸时相比,在一个测试点上,少年钢头的加权可用面积增加了1%。我们调查了平均RMSE改进的模式,这些模型具有不同的卡纸大小,河堤阻塞,孔隙度和结构类型以及河流复杂性。我们还确定了与LW堵塞孔隙率现场估算和多孔结构建模方法有关的研究空白。
更新日期:2020-01-08
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