碩士 / 國立臺北科技大學 / 土木與防災研究所 / 97 / Riparian buffer zones are essential to control nonpoint source pollution and create healthy ecosystem for stream, inasmuch as they slow nutrients and sediments and filter them out of surface runoff before those nutrients and sediments reach the water bodies. Moreover, the buffer zones stabilize streambanks and floodsplains as well as provide habitat for wildlife and fish. The riparian buffer ecosystem has been recommended as one of the best management practices (BMPs) to mitigate nonpoint source pollution effectively. However, the variation of pollution reduction efficiency depended on the hydrologic condition, sizes of buffer zones, vegetation characteristics, and biomass harvesting managements. Provided that field experiments are expensive and limited to hydrologic conditions, physiographic characteristics and herbaceous buffer scenarios, mathematical models become the best tools available to help quantify the water quality benefits of riparian buffers under varying site conditions. The Riparian Ecosystem Management Model (REMM) has been developed to simulate surface and subsurface riparian buffer hydrology, sediment transport, vegetation growth, and nutrient (C, N, P) dynamics. The REMM model requires numerous inputs to simulate the complex riparian ecosystem. This study aims to explore the mechanism and evaluate the sensitivity of parameters in the REMM model for its application on Feitsui Reservoir watershed to analyze nonpoint source pollution reduction. The Condition Number (CN) method was employed to measure sensitivity of various parameters for associated model outputs. The results indicate that volumetric water content (θ), field capacity (FC), and porosity (ψ) are the most sensitive parameters for deep seepage, surface and subsurface runoff predictions. In addition, particulate surface organic N, organic P, and sediment yield are moderately sensitive to percentage of bare soil (BS) and interrill roughness (R). As for all nutrient loadings, nutrient-associated parameters are found to be less sensitive. However, parameters sensitive for runoffs also have great impacts on nutrient loadings. Overall, volumetric water content (θ), field capacity (FC), and porosity (ψ) are highly sensitive for all model outputs, which suggest the potential uncertainty of model predictions. Additional attentions are advised for those parameters during modeling and calibration.
| Identifer | oai:union.ndltd.org:TW/097TIT05653076 |
| Date | January 2009 |
| Creators | Tung-ping Chen, 陳東平 |
| Contributors | Tzyy-Woei Chu, 朱子偉 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 115 |
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