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Person

Laura M Norman

Supervisory Research Physical Scientist
Western Geographic Science Center

Email: lnorman@usgs.gov
Office Phone: 520-670-5510
Fax: 520-670-5113
ORCID: 0000-0002-3696-8406

Location
UA - ENRB - AZWSC
520 N. Park Ave
Tucson , AZ 85719
US

Supervisor: Susan P Benjamin
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This data release contains data used in an associated publication: Petrakis, R.E., Norman, L.M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., and Pulliam, H.R., 2021, Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A.: Water, v. 13, no. 21, p. 2955, https://doi.org/10.3390/w13212955. The overarching effects and benefits of land management decisions, such as through watershed restoration, are often not fully understood due to a lacking control within an experimental design. This can be addressed through the application of a paired watershed approach, allowing for comparison between treatment and control watersheds. We developed and applied a statistic-based...
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This dataset provides location information and some limited attributes of known and potential ciénegas in the Madrean Archipelago ecoregion and closely surrounding area. This was created using point data and information provided by Dean Hendrickson and Thomas Minckley, combined with potential locations derived from analysis of classified raster land cover images and other specialized datasets. Ciénegas, as defined here, are wetlands in arid and semi-arid regions associated with groundwater or lotic components that ideally result in perennial waters on temporal scales of decades to centuries. Ciénegas are typically located at elevations ranging from 0 to 2000m. Ciénegas are typified by significant differences in...
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Annual (1986-2020) land-use/land cover maps at 30-meter resolution of the Tucson metropolitan area, Arizona and the greater Santa Cruz Watershed including Nogales, Sonora, Mexico. Maps were created using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier in Google Earth Engine. The maps contain 13 classes based on the National Land Cover Classification scheme and modified to reflect local land cover types. Data are presented as a stacked, multi-band raster with one "band" for each year (Band 1 = 1986, Band 2 = 1987 and so on). Note that the year 2012 was left out of our time series because of lack of quality Landsat data....
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This dataset contains hydrological data collected at a series of leaky weirs on a working ranchland site in a semiarid ecosystem in Cochise County, Arizona, from 2018-2020. Leaky weirs are a type of structure being experimented with by land managers in aridlands to reduce peak flow events and increase recharge to the aquifer. The weirs are constructed of rock cemented into place in areas of exposed bedrock within the channel are built to allow for water to leak through slowly. Three sites were instrumented for monitoring, one control and two sites treated with ‘leaky weirs’. At each site, at least one pressure transducer was installed in a piezometer to measure water level. Each site also had multiple “3-in-1” gauges,...
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Mapping Riparian Vegetation Response to Climate Change on the San Carlos Apache Reservation and Upper Gila River Watershed to Inform Restoration Priorities: 1935 to Present (Phase 2)
Recently intensifying drought conditions have caused increased stress to non-native tamarisk vegetation across riparian areas of the San Carlos Apache Tribe (hereafter Tribe) and the Upper Gila River watershed in Arizona and New Mexico. This also increases wildfire risk in the area, making the removal of tamarisk vegetation a primary restoration and climate adaptation objective for the Tribe. The research from this project can improve the Tribe’s capacity to map tamarisk and other riparian vegetation, in addition to monitoring the relative condition and water stress of the vegetation in a timely manner. Specifically, the project will help identify where tamarisk is on the reservation and inform restoration actions...
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