Dynamic characterization of meandering channels planform
Meandering channels develop different geometry patterns alongthe floodplain during its evolution. These natural processes lead todeveloping lateral and longitudinal migration, describing a sort of sweptthat affect the human activities. As the equilibrium geometry of naturalchannels depends on: the f...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/111112 |
| Acceso en línea: | http://hdl.handle.net/11336/111112 |
| Access Level: | acceso abierto |
| Palabra clave: | RIOS MEANDRIFORMES GEOMETRIA EN PLANTA ANALISIS WAVELET PLANICIE AMAZONICA https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
| Sumario: | Meandering channels develop different geometry patterns alongthe floodplain during its evolution. These natural processes lead todeveloping lateral and longitudinal migration, describing a sort of sweptthat affect the human activities. As the equilibrium geometry of naturalchannels depends on: the flow and sediment discharge, geologicalconditions of valley, soil properties, and vegetation among others, thepreliminary characterization is not easy. Due to this, several engineering and scientific problems require an appropriate description ofmorphological processes. The dynamic characterization like thequantification of wavelength, amplitude, sinuosity, and curvature usingMedium Temporal Scheme (MTS) is using widely. Unlike the traditionalscheme that only uses short or long-term schemes, MTS includes relevantmorphological events (e.g., cutoff). In addition this, the satellite images has increased and achieves a high spatial resolution, even more when studying large basins. This paper presents and validates a MATLAB®-based toolbox called Meander Statistics Toolbox (MStaT) to perform thedynamic characterization of several meandering channels using the MTS.To run MStaT only need the centerline (CL), and the average width ofchannel as input parameters. To maximize the toolbox, MStaT incorporatesthe Wavelet Analysis (WA) to decompose the signal (CL) and obtains thepower spectrum. Finally, two studies cases (synthetic and natural channels) will be presented to validate MStaT. |
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