HR: 0800h
AN: H11C-0688    [Abstracts]
TI: Characteristics of Sediment Load Dynamics: A Nonlinear Pattern Recognition Approach
AU: Sivakumar, B
EM: sbellie@ucdavis.edu
AF: University of California, Davis, Department of Land, Air and Water Resources, Davis, CA 95616, United States
AU: * Jha, S K
EM: skjha@ucdavis.edu
AF: University of California, Davis, Department of Civil and Environmental Engineering, Davis, CA 95616, United States
AU: Sahoo, G B
EM: gbsahoo@ucdavis.edu
AF: University of California, Davis, Department of Civil and Environmental Engineering, Davis, CA 95616, United States
AB: Adequate knowledge of the dynamic characteristics of sediment load in rivers (and channels) is important for studies of river morphology, reservoir sedimentation, soil and water conservation planning, water quality modeling, and design of erosion control structures. Although numerous variables contribute to the occurrence and movement of sediment load (e.g. water flow, land use, sediment concentration, particle size and shape), their levels of influence are often significantly different. Reliable determination of the dominant variables is, therefore, necessary for modeling and prediction purposes, especially from the viewpoints of model complexity and data collection. To this end, an attempt is made in the present study to investigate the utility of a nonlinear dynamic pattern recognition approach, which provides reliable information on the ‘extent of complexity' of the underlying dynamics. Such an approach involves two steps: (1) representation of the multi-variable dynamic system through reconstruction of the available single- or multi-variable data series; and (2) determination of the complexity of the system (defined especially in the context of variability of relevant data) using a neighbor searching procedure. In order to study the general utility and effectiveness of this approach for river systems, sediment load and other river-related data from a large number of sediment gaging stations around the United States (representing different geographic regions, climatic conditions, river sizes and complexities, and land uses) are analyzed.
DE: 1847 Modeling
DE: 1862 Sediment transport (4558)
DE: 1872 Time series analysis (3270, 4277, 4475)
DE: 4420 Chaos (7805)
DE: 4430 Complex systems
SC: Hydrology [H]
MN: 2007 Fall Meeting