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Vegetative Resistance to Flow Data

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Global Change Master Directory (GCMD)2026-04-25 收录
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https://cmr.earthdata.nasa.gov/search/concepts/C2231554788-CEOS_EXTRA.html
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Surface-water flow models are needed to evaluate restoration and management alternatives for the south Florida ecosystem. Model results are sensitive to expressions used to represent flow resistance due to vegetation. The project seeks to develop methods for representing flow resistance due to vegetation types typically found in the Everglades. The project also seeks an understanding of the effect of vegetation on surface-water flow and improved techniques for measuring flow velocities and water-surface slopes in wetlands. Data fundamental to quantifying the effects that the highly variable vegetation of the Everglades has on shallow surface-water flows is lacking. Models presently being used to manage the ecosystem need to quantify the flow-resistance effects of vegetation in order to properly simulate flow. These management models have been forced to rely primarily on qualitative estimates and engineering judgments for the treatment and representation of vegetative flow resistance. The objectives of this project are: 1) to collect data to produce accurate values of flow-resistance coefficients for use in numerical simulation models, 2) to analyze these flow data to quantify the resistance effects of the submerged vegetation, 3) to investigate the vegetation/flow-resistance correlation in controlled laboratory experiments and in the field, 4) to isolate the key vegetation properties to which the evaluation of resistance effects can best be correlated, and 5) to derive expressions that can be used to more creditably represent these effects in numerical models. These findings can be used to establish the validity of management models presently in use throughout the entire Everglades ecosystem as well as to provide improved expressions for representing the resistance effects of vegetation on flow for incorporation in newly developed models. This project is part of the TIME project.
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