Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa

An algorithm developed to identify, delineate, and derive the morphology of drained depressional features within a landscape was applied to the Iowa portion of the Des Moines Lobe (DML-IA) geomorphic sub-region of the Prairie Pothole Region of North America (PPR), using high resolution LiDAR derived...

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Main Author: McDeid, Samuel Marcus
Format: Text
Language:English
Published: Iowa State University Digital Repository 2017
Subjects:
DML
Online Access:https://lib.dr.iastate.edu/etd/15574
https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=6581&context=etd
id ftiowastateuniv:oai:lib.dr.iastate.edu:etd-6581
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spelling ftiowastateuniv:oai:lib.dr.iastate.edu:etd-6581 2023-05-15T16:01:28+02:00 Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa McDeid, Samuel Marcus 2017-01-01T08:00:00Z application/pdf https://lib.dr.iastate.edu/etd/15574 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=6581&context=etd en eng Iowa State University Digital Repository https://lib.dr.iastate.edu/etd/15574 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=6581&context=etd Graduate Theses and Dissertations Morphology Prairie Pothole Wetland Wetland Delineation Environmental Sciences text 2017 ftiowastateuniv 2018-11-26T01:38:11Z An algorithm developed to identify, delineate, and derive the morphology of drained depressional features within a landscape was applied to the Iowa portion of the Des Moines Lobe (DML-IA) geomorphic sub-region of the Prairie Pothole Region of North America (PPR), using high resolution LiDAR derived Digital Elevation Models (DEMs). Nearly 240,000 unique upland depressions were identified and their individual morphologies determined. Testing of our algorithm against an algorithm designed to integrate over triangulated surface representations of 975 randomly selected depressions from the DML-IA dataset reveals that our computational process produces morphology results to within 0.3 and 2% of those obtained using the latter process, and is nearly 3 orders of magnitude faster. Maximum areas of inundation, maximum depths, and maximum storage volumes were determined to follow a power-law distribution. Maximum volume was determined to be strongly related to maximum area through a power-law model, the coefficients of which appear to vary significantly from other areas of the PPR, but are in close agreement with values obtained for small sub-areas of the DML-IA, and for a large river basin in North Saskatchewan, CN. While the majority (80%) of depressions within the DML-IA are less than 1 ha in area, these only comprise 9.8% of the total potential depressional storage and 25.6% of the total depressional wetland area of this landscape. More than half of the potential storage capacity is provided by depressions between 1 and 30 ha. Text DML Digital Repository @ Iowa State University
institution Open Polar
collection Digital Repository @ Iowa State University
op_collection_id ftiowastateuniv
language English
topic Morphology
Prairie Pothole Wetland
Wetland Delineation
Environmental Sciences
spellingShingle Morphology
Prairie Pothole Wetland
Wetland Delineation
Environmental Sciences
McDeid, Samuel Marcus
Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
topic_facet Morphology
Prairie Pothole Wetland
Wetland Delineation
Environmental Sciences
description An algorithm developed to identify, delineate, and derive the morphology of drained depressional features within a landscape was applied to the Iowa portion of the Des Moines Lobe (DML-IA) geomorphic sub-region of the Prairie Pothole Region of North America (PPR), using high resolution LiDAR derived Digital Elevation Models (DEMs). Nearly 240,000 unique upland depressions were identified and their individual morphologies determined. Testing of our algorithm against an algorithm designed to integrate over triangulated surface representations of 975 randomly selected depressions from the DML-IA dataset reveals that our computational process produces morphology results to within 0.3 and 2% of those obtained using the latter process, and is nearly 3 orders of magnitude faster. Maximum areas of inundation, maximum depths, and maximum storage volumes were determined to follow a power-law distribution. Maximum volume was determined to be strongly related to maximum area through a power-law model, the coefficients of which appear to vary significantly from other areas of the PPR, but are in close agreement with values obtained for small sub-areas of the DML-IA, and for a large river basin in North Saskatchewan, CN. While the majority (80%) of depressions within the DML-IA are less than 1 ha in area, these only comprise 9.8% of the total potential depressional storage and 25.6% of the total depressional wetland area of this landscape. More than half of the potential storage capacity is provided by depressions between 1 and 30 ha.
format Text
author McDeid, Samuel Marcus
author_facet McDeid, Samuel Marcus
author_sort McDeid, Samuel Marcus
title Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
title_short Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
title_full Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
title_fullStr Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
title_full_unstemmed Morphologic characterization of upland depressional wetlands on the Des Moines Lobe of Iowa
title_sort morphologic characterization of upland depressional wetlands on the des moines lobe of iowa
publisher Iowa State University Digital Repository
publishDate 2017
url https://lib.dr.iastate.edu/etd/15574
https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=6581&context=etd
genre DML
genre_facet DML
op_source Graduate Theses and Dissertations
op_relation https://lib.dr.iastate.edu/etd/15574
https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=6581&context=etd
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