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Hydrogeomorphic wetland assessment m...

Whelchel, Adam W.

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Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont./
作者:	Whelchel, Adam W.
面頁冊數:	461 p.
附註:	Adviser: Bruce L. Vasilas.
Contained By:	Dissertation Abstracts International67-01B.
標題:	Hydrology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3205424
ISBN:	9780542519345

Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont.
Whelchel, Adam W.

Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont. - 461 p.

Adviser: Bruce L. Vasilas.

Thesis (Ph.D.)--University of Delaware, 2006.

A hydrogeomorphic functional assessment model (HGM) has been developed and applied in this document to slope wetlands within the Mid-Atlantic Piedmont reference domain. This required the characterization of a regional slope wetland subclass, calibration of model variables using reference wetland data, definition of relationship between model variables and functional capacity, and development of an unmodified and modified assessment model for deriving functional capacity indices.

ISBN: 9780542519345Subjects--Topical Terms:

545716
Hydrology.

Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont.
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245 1 0 $a Hydrogeomorphic wetland assessment model for slope wetlands in the Mid-Atlantic Piedmont.
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520 $a A hydrogeomorphic functional assessment model (HGM) has been developed and applied in this document to slope wetlands within the Mid-Atlantic Piedmont reference domain. This required the characterization of a regional slope wetland subclass, calibration of model variables using reference wetland data, definition of relationship between model variables and functional capacity, and development of an unmodified and modified assessment model for deriving functional capacity indices.
520 $a The slope wetland subclass was defined using 26 reference sites within the Mid-Atlantic Piedmont Physiographic Region of Pennsylvania, Delaware, and Maryland. Model variables used to define six slope wetland functions were developed and calibrated based on geomorphology, landuse, hydrology, soils, and vegetation data collected between August 1999 and October 2004. Geomorphology parameters consisted of area, edge, length, width, slope, microtopography, nearest wetland distance, and surface outflow channel configuration. Land use at the catchment basin, landscape (1 km), buffer (100m), and within wetland scale was determined using the Anderson Level 2 classification system. ArcGIS (c) software was used to assess spatial variables associated with wetland functions. Hydrologic regimes were determined using a cumulative frequency analysis to identify the probability of water table depth (WTD) exceedence of specific quantized depth classes. Soil profile field descriptions identified litter thickness, soil structure, horizon thickness, matrix color, redoximorphic features, texture, and presence of hydric soil indicators. Soil sample analysis consisted of particle size distribution, bulk density, water content, cation exchange capacity (CEC), total carbon (C), manganese, total nitrogen (N), extractable phosphorous (P), and mineralogy. Soil redox potential, presence of reduced iron, P (water soluble, Bray P-1, acid oxalate, groundwater), N (total N, nitrate (NO3-)), and other nutrients were measured quarterly (August 1999--September 2003). Vegetative communities were assessed by percent cover of each plant species within five strata. Alpha, beta, gamma, evenness, and Shannon Diversity Index for each reference site were assessed. An indicator species analysis was conducted with a Monte Carlo test of significance of observed maximum indicator values. Reference site grouping based on species abundance was assessed with a cluster analysis. Nonmetric multidimensional scaling (NMS) determined species data dimensionality. Environmental variables and vegetative composition relationships were identified with Canonical Correspondence Analysis. (Abstract shortened by UMI.)
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