Prediction of Annual Streambank Erosion for Sequoia National Forest, California
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Authors
Kwan, Hilda
Issue Date
2010
Type
Thesis
Language
Keywords
BEHI , Erosion , NBS , Sequoia , Streambank
Alternative Title
Abstract
The US EPA has consistently listed sediment as a leading cause of water quality
impairment in rivers, streams, and lakes, costing approximately $16 billion annually. Yet
prediction methods are not applicable to wildland systems. The Sequoia National Forest
needs to understand mechanisms and rates of streambank erosion to evaluate with
management issues , especially those associated with post-wildfire effects. This study
uses Bank Erosion Hazard Index (BEHI) methods developed in Rosgen (2006) for
predicting streambank erosion. Measurements of bank erosion over a year were evaluated
using BEHI and estimates of Near Bank Stress (NBS). BEHI evaluates bank
susceptibility to erosion based on bank angle, bank and bankfull height, rooting depth and
density, surface protection, and stratification of material within the banks. NBS assesses
energy distribution against the bank measured as a ratio of near-bank maximum depth to
mean bankfull depth. BEHI and NBS were good to fair indicators of streambank erosion
at or near bankfull conditions at riffle features. Individual BEHI variables and several
other physical variables (e.g., elevation, drainage area, and vegetation) significantly
correlated with streambank erosion but had low predictive power (i.e., r
2 0.0007 to r2
0.18) indicating inconsistency in driving variables among locations. This indicates that a
combination of several variables affects streambank erosion. A low r2 (0.23) from
multiple regression analyses shows there may be variables other than those of BEHI that
affect streambank erosion. Bank angle has the lowest predictive power for erosion while
rooting depth had the highest.
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In Copyright(All Rights Reserved)