Spatial interpolation of river channel topography using the shortest temporal distance
| Autor: | Jiaming Liu, Michael L. Grieneisen, Minghua Zhang, Yanjun Zhang, Huajin Chen, Cuiling Xian |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
010504 meteorology & atmospheric sciences
Water flow 0208 environmental biotechnology River channel topography Geometry 02 engineering and technology 01 natural sciences 020801 environmental engineering Multivariate interpolation Interpolation Euclidean distance Flow velocity Kriging Modified shortest temporal distance Inverse distance weighting Metric (mathematics) Locally varying anisotropy Geology Shortest temporal distance 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Journal of Hydrology. :450-462 |
| ISSN: | 0022-1694 |
| DOI: | 10.1016/j.jhydrol.2016.09.022 |
| Popis: | It is difficult to interpolate river channel topography due to complex anisotropy. As the anisotropy is often caused by river flow, especially the hydrodynamic and transport mechanisms, it is reasonable to incorporate flow velocity into topography interpolator for decreasing the effect of anisotropy. In this study, two new distance metrics defined as the time taken by water flow to travel between two locations are developed, and replace the spatial distance metric or Euclidean distance that is currently used to interpolate topography. One is a shortest temporal distance (STD) metric. The temporal distance (TD) of a path between two nodes is calculated by spatial distance divided by the tangent component of flow velocity along the path, and the STD is searched using the Dijkstra algorithm in all possible paths between two nodes. The other is a modified shortest temporal distance (MSTD) metric in which both the tangent and normal components of flow velocity were combined. They are used to construct the methods for the interpolation of river channel topography. The proposed methods are used to generate the topography of Wuhan Section of Changjiang River and compared with Universal Kriging (UK) and Inverse Distance Weighting (IDW). The results clearly showed that the STD and MSTD based on flow velocity were reliable spatial interpolators. The MSTD, followed by the STD, presents improvement in prediction accuracy relative to both UK and IDW. |
| Databáze: | OpenAIRE |
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