Evenson Grey R, Jones C Nathan, McLaughlin Daniel L, Golden Heather E, Lane Charles R, DeVries Ben, Alexander Laurie C, Lang Megan W, McCarty Gregory W, Sharifi Amirreza
Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, OH, USA.
The National Socio-Environmental Synthesis Center, University of Maryland, Annapolis, MD, USA.
J Hydrol X. 2018 Dec 1;1. doi: 10.1016/j.hydroa.2018.10.002.
Wetlands are often dominant features in low relief, depressional landscapes and provide an array of hydrologically driven ecosystem services. However, contemporary models do not adequately represent the role of spatially distributed wetlands in watershed-scale water storage and flows. Such tools are critical to better understand wetland hydrological, biogeochemical, and biological functions and predict management and policy outcomes at varying spatial scales. To develop a new approach for simulating depressional landscapes, we modified the Soil and Water Assessment Tool (SWAT) model to incorporate improved representations of depressional wetland structure and hydrological processes. Specifically, we refined the model to incorporate: (1) water storage capacity and surface flowpaths of individual wetlands and (2) local wetland surface and subsurface exchange. We utilized this model, termed SWAT-DSF (DSF for Depressional Storage and Flows), to simulate the ~289 km Greensboro watershed within the Delmarva Peninsula of the US Coastal Plain. Model calibration and verification used both daily streamflow observations and remotely sensed surface water extent data (ca. 2-week temporal resolution), allowing us to assess model performance with respect to both streamflow and watershed inundation patterns. Our findings demonstrate that SWAT-DSF can successfully replicate distributed wetland processes and resultant watershed-scale hydrology. SWAT-DSF provides improved temporal and spatial characterization of watershed-scale water storage and flows in depressional landscapes, providing a new tool to quantify wetland functions at broad spatial scales.
湿地通常是低起伏、凹陷地貌中的主要特征，提供一系列受水文驱动的生态系统服务。然而，当代模型并未充分体现空间分布的湿地在流域尺度的蓄水和水流中的作用。此类工具对于更好地理解湿地水文、生物地球化学和生物学功能，以及预测不同空间尺度下的管理和政策结果至关重要。为开发一种模拟凹陷地貌的新方法，我们对土壤和水资源评估工具（SWAT）模型进行了修改，以更好地呈现凹陷湿地的结构和水文过程。具体而言，我们对模型进行了优化，纳入了：（1）单个湿地的蓄水能力和地表水流路径，以及（2）当地湿地的地表和地下交换。我们利用这个名为SWAT-DSF（DSF代表凹陷蓄水和水流）的模型，来模拟美国沿海平原德尔马瓦半岛内约289平方公里的格林斯伯勒流域。模型校准和验证使用了每日河流流量观测数据以及遥感地表水范围数据（约两周的时间分辨率），使我们能够评估模型在河流流量和流域淹没模式方面的性能。我们的研究结果表明，SWAT-DSF能够成功复制分布式湿地过程以及由此产生的流域尺度水文情况。SWAT-DSF改进了凹陷地貌中流域尺度蓄水和水流的时空特征描述，为在广泛空间尺度上量化湿地功能提供了一种新工具。
