Plants, especially trees, provide ecological functions but may harm the flood conveyance efficiency of rivers. Understanding the impacts of tree heights, tree areas, and tree locations on flood levels is crucial for floodplain management. This study aims to present a methodology to improve the performance of hydrodynamic modeling by considering plant resistance with the goal of analyzing flood risk reduction strategies that support ecological conservation enhancement. An unmanned aerial vehicle was used to collect floodplain topography, landcover, and tree characteristic data. A modified maximum likelihood classification scheme was developed by incorporating the tree height information to improve the landcover classification. The water-blocking effect of trees, which represents the reduced flood conveyance area, was investigated by establishing tree obstructions in hydrodynamic models. Two hydrodynamic models were established with different tree obstruction setups and Manning's n values, including blocked obstructions (BOs) and conventional high n-values (Adj-n). Among the model setups, the Manning's n values of the trees remained the same as that of the soil in the BO model, in which trees were modeled as blocking obstructions. The n-values of trees were determined to be 0.022 in the BO model and refined to 0.055 in the Adj-n model after the model calibration and verification processes. The results indicated that the simulated flood levels of the BO model were very similar to those of the Adj-n model. The NSE values were 0.98 and 0.97 in the simulations of two historical typhoon events, indicating that the BO model could obtain reliable predictions without altering the n-values. The verified BO model was used to evaluate the degrees of influence of tree heights, tree coverage areas, and tree locations on flood levels. Several nature-based solutions were proposed to analyze the tradeoffs between reducing flood prevention and enhancing wetland restoration using the verified BO model, suggesting a win–win strategy for natural river management.

中文翻译：

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识别树木特征以确定输水对城市河流自然洪水管理的阻塞效应

植物，尤其是树木，提供生态功能，但可能会损害河流的洪水输送效率。了解树木高度、树木面积和树木位置对洪水位的影响对于洪泛区管理至关重要。本研究旨在提出一种通过考虑植物抵抗力来提高水动力建模性能的方法，目的是分析支持加强生态保护的洪水风险降低策略。无人机用于收集洪泛区地形、土地覆盖和树木特征数据。通过结合树高信息来改进土地覆盖分类，开发了一种改进的最大似然分类方案。树木的阻水作用，代表了洪水输送面积的减少，通过在水动力模型中建立树木障碍物来研究。使用不同的树木障碍设置和曼宁的方法建立了两个水动力模型n值，包括阻塞的障碍物 (BO) 和传统的高n 值(Adj- n )。在模型设置中，树木的曼宁n值与 BO 模型中土壤的曼宁n值保持相同，其中树木被建模为阻塞障碍物。所述Ñ测定的树木-值是在BO模型0.022和在Adj-精制以0.055 Ñ模型校准和验证过程后的模型。结果表明，BO 模型的模拟洪水位与 Adj- n模型的模拟洪水位非常相似。模型。在两次历史台风事件的模拟中，NSE 值分别为 0.98 和 0.97，表明 BO 模型可以在不改变n 值的情况下获得可靠的预测。经验证的 BO 模型用于评估树木高度、树木覆盖面积和树木位置对洪水位的影响程度。提出了几种基于自然的解决方案，以使用经过验证的 BO 模型分析减少防洪和加强湿地恢复之间的权衡，提出了自然河流管理的双赢策略。