Watershed models have been increasingly applied to investigate the impacts of environmental changes on water quantity and quality and to support decision-making. Thus, accurately capturing physical processes and the characteristics of the watershed system is vital to achieving reliable results. Channel geometry features such as cross-sectional shape, bankfull channel width, and depth affect hydraulic parameters like hydraulic radius, wetted perimeter, and cross-sectional area. These, in turn, play important roles in streamflow dynamics, flow velocity, erosion, nutrient transport, and stream ecology. However, the representation of bankfull channel width is often oversimplified in watershed models. Power-law regression equations relating geometric parameters and upstream drainage area are commonly used to calculate bankfull channel width in watershed models. This approach has limitations and may resonate in the misrepresentation of channel geometry with implications for water quantity and quality estimations. This study evaluates how bankfull channel width is represented in a popular watershed model and presents alternative data sources derived from aerial measurements, empirical models, LiDAR, and a global database to mitigate potential misrepresentations. To assess the impacts of bankfull channel width on water quantity and quality, we designed a series of modeling experiments through the Soil and Water Assessment Tool (SWAT) model. We test our methodology in the Alabama-Coosa-Tallapoosa river basin, a large watershed system draining to the Gulf of Mexico coast. Our findings indicate that, overall, the regression equation used in the ArcSWAT program (SWAT's GIS interface) can overestimate bankfull channel width by as much as three times in our study domain. In testing the effects of bankfull width on model simulations we found negligeable implication for water yield predictions. On the other hand, 1-day maximum flows were greatly increased (20%) by using channel width values from the alternative data sources. Simulated water quality was also affected, with stream water temperature showing better agreement with observations under the proposed scenarios. Sediment loadings increased by as much as 118% under the alternative data sources of channel width. Nitrate and phosphate loadings had opposite responses and showed decreases as high as 8.3 and 18.8%, respectively, relative to the default model. Our findings demonstrate that bankfull channel width is misrepresented in watershed models with underlying impacts on simulated water quantity, quality, and ecological flows. Our analysis found bankfull channel width as an important parameter affecting high flows and water quality, and the freely available data sources tested in this study showed good matches with field measurements, making our findings readily available and broadly useful to the modeling community.

流域模型越来越多地应用于研究环境变化对水量和水质的影响并支持决策。因此，准确捕获流域系统的物理过程和特征对于获得可靠的结果至关重要。河道几何特征（例如横截面形状、满岸河道宽度和深度）会影响水力参数（例如水力半径、润湿周长和横截面积）。反过来，这些在水流动力学、流速、侵蚀、养分输送和河流生态学中发挥着重要作用。然而，在流域模型中，满岸河道宽度的表示往往过于简单化。涉及几何参数和上游流域面积的幂律回归方程通常用于计算流域模型中的满岸河道宽度。这种方法有局限性，并且可能会误报渠道几何形状，从而影响水量和水质估计。本研究评估了如何在流行的分水岭模型中表示满岸河道宽度，并提出了来自航空测量、经验模型、激光雷达和全球数据库的替代数据源，以减少潜在的误报。为了评估满岸河道宽度对水量和水质的影响，我们通过水土评估工具（SWAT）模型设计了一系列建模实验。我们在阿拉巴马-库萨-塔拉普萨河流域测试了我们的方法，这是一个流向墨西哥湾海岸的大型流域系统。我们的研究结果表明，总体而言，ArcSWAT 程序（SWAT 的 GIS 接口）中使用的回归方程可能会在我们的研究领域高估满岸河道宽度多达三倍。在测试满岸宽度对模型模拟的影响时，我们发现对产水量预测的影响可以忽略不计。另一方面，通过使用来自替代数据源的通道宽度值，1 天最大流量大幅增加 (20%)。模拟的水质也受到影响，溪流水温与建议情景下的观测结果更加一致。在河道宽度的替代数据源下，沉积物负荷增加了 118%。硝酸盐和磷酸盐负载量具有相反的响应，并且相对于默认模型分别降低高达 8.3% 和 18.8%。我们的研究结果表明，满岸河道宽度在流域模型中被歪曲，对模拟水量、质量和生态流量产生潜在影响。我们的分析发现，满岸河道宽度是影响高流量和水质的重要参数，并且本研究中测试的免费可用数据源显示出与现场测量的良好匹配，使我们的研究结果易于获得并且对建模界广泛有用。