作者: J. J. Spurgeon , M. A. Pegg , M. J. Hamel
DOI: 10.1002/RRA.3041
关键词: Flow pattern 、 Hydrology 、 Hydrology (agriculture) 、 Multivariate statistical 、 Temporal scales 、 Tributary 、 Statistical analysis 、 Environmental science 、 Flow (mathematics) 、 Scale (map)
摘要: Rivers are hierarchical systems exhibiting processes and patterns across spatial temporal scales principally driven by changes in flow. Hydrological indices estimated with mean or median daily flow data (i.e. scale) may be insensitive to anthropogenic alteration that imparts sub-daily variation Therefore, developed at multiple resolutions provide additional insight into the presence of masked traditional techniques. We characterized regime along longitudinal gradient Platte River, a large Great Plains USA river, using hydrological derived combination multivariate statistical Three unique units were evident scale data, whereas six scale. Flow both not static, but rather extent riverscape depended on climate, tributary inflows human influence. Anthropogenic including hydropeaking was The full complement structure within regulated rivers, therefore, captured discharge values alone. Inductive river classification studies benefit from assessing scales, particularly when investigating modification such as hydropeaking. Copyright © 2016 John Wiley & Sons, Ltd.