Persistent Link:
http://hdl.handle.net/10150/232457
Title:
Remote Sensing Methods To Classify a Desert Wetland
Author:
Mexicano Vargas, Maria de Lourdes
Issue Date:
2012
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Embargo:
Release after 07-Nov-2012
Abstract:
The Cienega de Santa Clara is a 5600 ha, anthropogenic wetland in the delta of the Colorado River in Mexico. It is the inadvertent creation of the disposal of brackish agricultural waste water from the U.S. into the intertidal zone of the river delta in Mexico, but has become an internationally important wetland for resident and migratory water birds. The marsh is dominated by Typha domengensis with Phragmites australis as a sub-dominant species in shallower marsh areas. The most important factor controlling vegetation density was fire. The second significant (P<0.01) factor controlling NDVI was flow rate of agricultural drain water from the U.S. into the marsh. Reduced summer flows in 2001 due to canal repairs, and in 2010 during the YDP test run, produced the two lowest NDVI values of the time series from 2000 to 2011 (P<0.05). Salinity is a further determinant of vegetation dynamics as determined by greenhouse experiments, but was nearly constant over the period 2000 to 2011, so it was not a significant variable in regression analyses. Evapotranspiration (ET) and other water balance components were measured in Cienega de Santa Clara; we used a remote sensing algorithm to estimate ET from meteorological data and Enhanced Vegetation Index values from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite. We used Landsat NDVI imagery from 1978-2011 to determine the area and intensity of vegetation and to estimate evapotranspiration (ET) to construct a water balance. Remote sensing data was supplemented with hydrological data, site surveys and literature citations. The vegetated area increased from 1978 to 1995 and has been constant at about 4200 ha since then. The dominant vegetation type is Typha domingensis (southern cattail), and peak summer NDVI since 1995 has been stable at 0.379 (SD = 0.016), about half of NDVI(max). About 30% of the inflow water is consumed in ET, with the remainder exiting the Cienega as outflow water, mainly during winter months when T. domingensis is dormant.
Type:
text; Electronic Dissertation
Keywords:
emergent wetland; fire effects; Quickbird; remote sensing; Soil, Water & Environmental Science; brackish; cattail marsh
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Soil, Water & Environmental Science
Degree Grantor:
University of Arizona
Advisor:
Glenn, Edward P.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleRemote Sensing Methods To Classify a Desert Wetlanden_US
dc.creatorMexicano Vargas, Maria de Lourdesen_US
dc.contributor.authorMexicano Vargas, Maria de Lourdesen_US
dc.date.issued2012-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.releaseRelease after 07-Nov-2012en_US
dc.description.abstractThe Cienega de Santa Clara is a 5600 ha, anthropogenic wetland in the delta of the Colorado River in Mexico. It is the inadvertent creation of the disposal of brackish agricultural waste water from the U.S. into the intertidal zone of the river delta in Mexico, but has become an internationally important wetland for resident and migratory water birds. The marsh is dominated by Typha domengensis with Phragmites australis as a sub-dominant species in shallower marsh areas. The most important factor controlling vegetation density was fire. The second significant (P<0.01) factor controlling NDVI was flow rate of agricultural drain water from the U.S. into the marsh. Reduced summer flows in 2001 due to canal repairs, and in 2010 during the YDP test run, produced the two lowest NDVI values of the time series from 2000 to 2011 (P<0.05). Salinity is a further determinant of vegetation dynamics as determined by greenhouse experiments, but was nearly constant over the period 2000 to 2011, so it was not a significant variable in regression analyses. Evapotranspiration (ET) and other water balance components were measured in Cienega de Santa Clara; we used a remote sensing algorithm to estimate ET from meteorological data and Enhanced Vegetation Index values from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite. We used Landsat NDVI imagery from 1978-2011 to determine the area and intensity of vegetation and to estimate evapotranspiration (ET) to construct a water balance. Remote sensing data was supplemented with hydrological data, site surveys and literature citations. The vegetated area increased from 1978 to 1995 and has been constant at about 4200 ha since then. The dominant vegetation type is Typha domingensis (southern cattail), and peak summer NDVI since 1995 has been stable at 0.379 (SD = 0.016), about half of NDVI(max). About 30% of the inflow water is consumed in ET, with the remainder exiting the Cienega as outflow water, mainly during winter months when T. domingensis is dormant.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectemergent wetlanden_US
dc.subjectfire effectsen_US
dc.subjectQuickbirden_US
dc.subjectremote sensingen_US
dc.subjectSoil, Water & Environmental Scienceen_US
dc.subjectbrackishen_US
dc.subjectcattail marshen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSoil, Water & Environmental Scienceen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorGlenn, Edward P.en_US
dc.contributor.committeememberFitzsimmons, Kevin M.en_US
dc.contributor.committeememberWissler, Craigen_US
dc.contributor.committeememberGlenn, Edward P.en_US
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