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A watershed classification system ba...

Lafrenz, Martin Dietrich.

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A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina./
Author:	Lafrenz, Martin Dietrich.
Description:	169 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5872.
Contained By:	Dissertation Abstracts International66-11B.
Subject:	Physical Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3197619
ISBN:	9780542418365

A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina.
Lafrenz, Martin Dietrich.

A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina. - 169 p.

Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5872.

Thesis (Ph.D.)--The University of Tennessee, 2005.

Headwater areas have received little attention from researchers, even though headwater catchments can comprise over 70% of the land area in most regions. Headwater streams, being tightly coupled to their adjacent hillslopes, are greatly affected by the upland landscape history in their watersheds. I employ this tight connection in developing a watershed classification system that explicitly links catchment characteristics and stream channel morphology. I test two approaches for classification. First, I assess whether a 'top-down' statistical clustering, based on landscape-scale attributes, forms catchment groups with significantly distinct types of stream channels. In the second 'bottom-up' approach, I test whether catchments grouped by their respective distinct types of stream channels show any significant relationships between channel morphology and landscape-scale attributes. With the top-down technique, I use a geographic information system (GIS) and a digital elevation model (DEM) to delineate 862 headwater catchments; I then use a two-step clustering procedure to create six groups based on catchment shape, area, land use, and geology. For the bottom-up approach, I use channel morphology data, from 51 sampled streams, in a principal components analysis (PCA) and a two-step cluster procedure to create five groups of catchments based on the similarities in stream channel morphology. I then use multinomial logistic regression to test the efficacy of predicting bottom-up group membership using landscape-scale attributes as independent variables. The top-down classification creates groups of catchments with different landscape-scale attributes, but these groups do not have significantly different types of stream channels; this is largely because the top-down approach cannot account for convergence, where different combinations of catchment attributes produce similar types of channel morphology. Being more process-driven, the bottom-up catchment groups represent transitional states in the expected fluvial response to hillslope disturbance; stream channels are either aggrading, degrading, or in dynamic equilibrium. Finally, bottom-up catchment group membership is predicted with better than 80% accuracy. This demonstrates the strong relationship between landscape-scale processes and stream channel morphology, which may allow researchers to anticipate possible changes in stream channel habitat as a function of proposed land use changes.

ISBN: 9780542418365Subjects--Topical Terms:

893400
Physical Geography.

A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina.
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100 1 $a Lafrenz, Martin Dietrich. $3 1913845
245 1 2 $a A watershed classification system based on headwater catchments in Great Smoky Mountains National Park, Tennessee-North Carolina.
300 $a 169 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5872.
500 $a Major Professor: Carol P. Harden.
502 $a Thesis (Ph.D.)--The University of Tennessee, 2005.
520 $a Headwater areas have received little attention from researchers, even though headwater catchments can comprise over 70% of the land area in most regions. Headwater streams, being tightly coupled to their adjacent hillslopes, are greatly affected by the upland landscape history in their watersheds. I employ this tight connection in developing a watershed classification system that explicitly links catchment characteristics and stream channel morphology. I test two approaches for classification. First, I assess whether a 'top-down' statistical clustering, based on landscape-scale attributes, forms catchment groups with significantly distinct types of stream channels. In the second 'bottom-up' approach, I test whether catchments grouped by their respective distinct types of stream channels show any significant relationships between channel morphology and landscape-scale attributes. With the top-down technique, I use a geographic information system (GIS) and a digital elevation model (DEM) to delineate 862 headwater catchments; I then use a two-step clustering procedure to create six groups based on catchment shape, area, land use, and geology. For the bottom-up approach, I use channel morphology data, from 51 sampled streams, in a principal components analysis (PCA) and a two-step cluster procedure to create five groups of catchments based on the similarities in stream channel morphology. I then use multinomial logistic regression to test the efficacy of predicting bottom-up group membership using landscape-scale attributes as independent variables. The top-down classification creates groups of catchments with different landscape-scale attributes, but these groups do not have significantly different types of stream channels; this is largely because the top-down approach cannot account for convergence, where different combinations of catchment attributes produce similar types of channel morphology. Being more process-driven, the bottom-up catchment groups represent transitional states in the expected fluvial response to hillslope disturbance; stream channels are either aggrading, degrading, or in dynamic equilibrium. Finally, bottom-up catchment group membership is predicted with better than 80% accuracy. This demonstrates the strong relationship between landscape-scale processes and stream channel morphology, which may allow researchers to anticipate possible changes in stream channel habitat as a function of proposed land use changes.
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710 2 0 $a The University of Tennessee. $3 1022026
773 0 $t Dissertation Abstracts International $g 66-11B.
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790 $a 0226
791 $a Ph.D.
792 $a 2005
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