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Modeling the Natural Drainage Network of the Grand River in Southern Ontario: Agriculture May Increase Total Channel Length of Low-Order Streams

机译:对安大略省南部大河的自然排水网络进行建模:农业可能会增加低序河流的总河道长度

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The Grand River watershed is an important agricultural area in southern Ontario, with several large and growing municipalities. Based on digital elevation models (DEMs), the natural drainage network was modelled to predict flow paths. Channel lengths and locations of the predicted network were compared with a ground-truthed channel network to determine efficacy of the models. Approximately 5% of predicted channels lay 40 m from actual channel locations. This amounted to 388 km of channel that had no corresponding channels in reality. The model was unable to predict, based on topography, 2535 km of actual channel present in the watershed. Channels not anticipated by topography were mostly first-order, with low sinuosity, were most common in areas with high agricultural land use, and are likely excavated extensions to headwater streams to facilitate drainage. In addition, this study showed that Soil and Water Assessment Tool (SWAT) models produced using different DEM resolutions did not predict significantly different stream flows, even when resolution was as low as 200 m. However, these low resolution DEMs did result in under-prediction of sediment export entering Lake Erie, most likely because the low resolution maps failed to account for small localized areas of high slope that would have relatively higher rates of erosion.
机译:大河流域是安大略省南部一个重要的农业地区,拥有数个不断发展的大型市政当局。基于数字高程模型(DEM),对自然排水网络进行建模以预测流动路径。将预测网络的通道长度和位置与地面真实通道网络进行比较,以确定模型的有效性。大约5%的预测通道位于实际通道位置40m以上。总计388 km的通道实际上没有相应的通道。该模型无法根据地形预测流域中2535 km的实际河道。地形无法预料的河道大多是一阶的,曲折度较低,在农业土地使用率较高的地区最常见,并且可能是挖掘到的源头水流的延伸部分,以方便排水。此外,这项研究表明,即使分辨率低至200 m,使用不同DEM分辨率生成的土壤和水评估工具(SWAT)模型也无法预测明显不同的水流。但是,这些低分辨率的DEM确实导致了对进入伊利湖的沉积物出口的预测不足,这很可能是因为低分辨率的地图无法说明高坡度的小局部地区,而这些地区的侵蚀率相对较高。

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