This study presents a new approach to modeling marsh evolution. The Tidal Marsh Model (TMM) has been developed as a module within the SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) framework. Some unique features of the TMM are dynamic rates, cross-scale simulations, and incorporation of anthropogenic stressors, which allow it to overcome many limitations that current marsh models possess. To evaluate model performance, the TMM was applied in Carter Creek and Taskinas Creek within the York River system (Virginia, USA). We assessed model outputs against field observations focusing on two main aspects: marsh boundary evolution and distribution of marsh sediments. Marsh change is captured with an accuracy of 81% in Carter Creek and an accuracy of 78% in Taskinas Creek. Different statistical descriptors were used to evaluate the model’s ability to reproduce the distribution of observed marsh sediment fractions. Results in both study areas show a satisfactory agreement between sediment model outputs and field observations. This innovative modeling approach will help close some critical knowledge gaps in the current understanding of the system dynamics and allow better implementation of management actions to preserve these ecosystems and their services.

中文翻译：

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模拟潮汐沼泽演变的多尺度方法

这项研究提出了一种模拟沼泽演化的新方法。潮汐沼泽模型（TMM）已作为SCHISM（半隐式跨尺度水科学综合系统模型）框架中的模块而开发。TMM的一些独特功能是动态速率，跨尺度模拟以及人为压力源的合并，这使其可以克服当前沼泽模型所具有的许多限制。为了评估模型的性能，将TMM应用于约克河系统（美国弗吉尼亚州）的Carter Creek和Taskinas Creek。我们针对现场观察评估了模型输出，重点关注两个主要方面：沼泽边界演化和沼泽沉积物分布。在卡特河（Carter Creek）中捕获的沼泽变化的准确度为81％，在塔基纳斯溪（Taskinas Creek）中捕获的准确度为78％。使用不同的统计描述符来评估模型重现观察到的沼泽沉积物馏分分布的能力。两个研究领域的结果表明沉积物模型输出与现场观测结果之间令人满意的一致性。这种创新的建模方法将有助于弥合当前对系统动力学的理解中的一些关键知识鸿沟，并允许更好地实施管理措施以保护这些生态系统及其服务。