Analytical and statistical modeling to evaluate effectiveness of stream restoration in reducing stream bank erosion
Date of Award
Doctor of Philosophy (PhD)
Civil and Environmental Engineering
Shobha K. Bhatia
Stream restoration, Bank erosion
Civil and Environmental Engineering | Civil Engineering | Engineering | Environmental Engineering
With increasing knowledge of the negative impact of human activities on the watershed system, growing numbers of stream restoration projects have been carried out during the last decade in the United States. Stream restoration is defined as to return a deteriorated ecosystem to a close approximation of its condition prior to disturbance. One primary objective of stream restoration is to stabilize stream banks and, thus, to mitigate bank erosion. However, the effectiveness of stream restoration in reducing stream bank erosion is seldom systematically studied. This scarcity is partially due to the relatively short history of stream restoration, as well as to the complex nature of stream bank erosion processes. Therefore, a procedure for the purpose of assessing the effects of stream restoration on bank erosion needs to be developed.
In this study, a methodology for evaluating the effectiveness of stream restoration in reducing bank erosion is developed. The Batavia Kill stream restoration projects (Greene County, New York) and the monitoring data from the Batavia Kill watershed are used to perform the evaluation. This evaluation is undertaken by comparing two scenarios of stream bank erosion. One scenario represents the "actual" response of the stream bank to stream restoration, and is termed here the "with restoration scenario", while the other represents a hypothetical scenario assuming no stream restoration were conducted, and is termed here the "without restoration scenario". For the first scenario, stream bank erosion is measured from erosion monitoring activities. For the second scenario, however, a prediction model needs to be developed to estimate bank erosion.
The multivariate regression method is used to develop the stream bank erosion prediction model. This method relates stream bank erosion to a range of explanatory variables including instruments representing geomorphological characteristics, flow conditions, rainfall conditions, temperature, vegetation index, soil erodibility, and sediment features. The general to specific approach is used to specify the regression model, and a series of statistical tests is applied to check the model accuracy and the validity of the regression model. The regression model is also compared with two other competing models to assess its predictability. These two models are Rosgen's stream bank erosion prediction model and Bank Stability and Toe Erosion Model (BSTEM) developed by the United States Department of Agriculture, Agricultural Research Service. The results show that the regression model developed in this study accurately predicts stream bank erosion and is superior to the competing models in terms of stream bank erosion predictability on the Batavia Kill stream. (Abstract shortened by UMI.)
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Chen, Yanwei, "Analytical and statistical modeling to evaluate effectiveness of stream restoration in reducing stream bank erosion" (2005). Civil and Environmental Engineering - Dissertations. Paper 10.