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Institution

Boise State University

EducationBoise, Idaho, United States
About: Boise State University is a education organization based out in Boise, Idaho, United States. It is known for research contribution in the topics: Population & Computer science. The organization has 3698 authors who have published 8664 publications receiving 210163 citations. The organization is also known as: BSU & Boise State.


Papers
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Journal ArticleDOI
TL;DR: While higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling, Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.
Abstract: This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicate that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.

81 citations

Journal ArticleDOI
TL;DR: A review of textural correlation, inversion of diffusion profiles, chemical correlation, and combined chronologic and thermometric microanalysis can be found in this article, where a new consideration of errors indicates that modeling of chronologic diffusion gradients provides relatively precise constraints on cooling rates, whereas models of chemical diffusion gradient can lead to large cooling rate uncertainties.
Abstract: ![Figure][1] Metamorphic chronology or petrochronology has steadily evolved over several decades through ever improving analytical techniques and more complete understanding of the geochemical and petrologic evolution of metamorphosing rocks. Here, the principal methods by which we link metamorphic temperatures ( T ) and ages ( t ) are reviewed, focusing primarily on accessory minerals. Methods discussed include textural correlation, inversion of diffusion profiles, chemical correlation, and combined chronologic and thermometric microanalysis. Each method demonstrates remarkable power in elucidating petrologic and tectonic processes, as examples from several orogens illustrate, but limitations must also be acknowledged and help define future research directions. Correlation methods are conceptually simple, but can be relatively non-specific regarding pressure-temperature conditions of formation. A new consideration of errors indicates that modeling of chronologic diffusion gradients provides relatively precise constraints on cooling rates, whereas models of chemical diffusion gradients can lead to large (factor of 2 or more) cooling rate uncertainties. Although arguably the best method currently in use, simultaneous T-t measurements are currently limited to zircon, titanite, and rutile. Directions for future improvement include investigation of diffusion profiles for numerous trace element-mineral systems using now-routine depth profiling. New trace element models will help improve chemical correlation methods. The determination of inclusion entrapment P-T conditions based on Raman spectroscopic measurement of inclusion pressures (“thermoba-Raman-try”) may well revolutionize textural correlation methods. [1]: pending:yes

81 citations

Journal ArticleDOI
TL;DR: The data suggest that participants based metacomprehension judgments more on the gist of texts when they generated summaries after a delay; whereas, they based judgmentsmore on details when they generate summaries immediately after reading.

81 citations

Journal ArticleDOI
TL;DR: In this article, Nitrogen and phosphorus dynamics in the Kuparuk River in arctic Alaska were characterized in a 3-year study using routine samples near the mouth of the river at the Arctic Ocean, synoptic whole-river surveys, and temporally intense sampling during storms in three headwater basins.
Abstract: Nitrogen (N) and phosphorus (P) dynamics in the Kuparuk River in arctic Alaska were characterized in a 3-year study using routine samples near the mouth of the river at the Arctic Ocean, synoptic whole-river surveys, and temporally intense sampling during storms in three headwater basins. The Lower Kuparuk River has low nitrate concentrations (mean [NO � -N] D 17 µg l � 1 s 1Ð6 SE) and dissolved inorganic N (DIN, mean [N] D 31 µ gl � 1 s 1Ð2 SE) compared with rivers in more temperate environments. Organic forms constituted on average 90% of the N exported to the Arctic Ocean, and high ratios of dissolved organic N (DON) to total dissolved N (TDN) concentrations (mean 0Ð92) likely result from waterlogged soils formed by reduced infiltration due to permafrost and low hydrologic gradients. Annual export of TDN, DON, and particulate N averaged 52 kg km � 2 ,4 8 kg km � 2 ,a nd 4Ð 1k g km � 2 respectively. During snowmelt, the high volume of runoff typically results in the highest nutrient loads of the year, although high discharge during summer storms can result in substantial nutrient loading over short periods of time. Differences in seasonal flow regime (snowmelt versus rain) and storm-driven variation in discharge appear to be more important for determining nutrient concentrations than is the spatial variation in processes along the transect from headwaters towards the ocean. Both the temporal variation in nitrate : DIN ratios of headwater streams and the spatial variation in nitrate : DIN between larger sub-basins and smaller headwater catchments is likely controlled by shifts in nitrification and soil anoxia. Copyright  2008 John Wiley & Sons, Ltd.

81 citations

Journal ArticleDOI
TL;DR: In this paper, the arrival-time and amplitude information of the dominant Rayleigh wave phase was analyzed from an array of nine short-period passive seismometers located on Bench Glacier, Alaska (USA).
Abstract: [1] Sliding glaciers and brittle ice failure generate seismic body and surface wave energy characteristic to the source mechanism. Here we analyze continuous seismic recordings from an array of nine short-period passive seismometers located on Bench Glacier, Alaska (USA) (61.033°N, 145.687°W). We focus on the arrival-time and amplitude information of the dominant Rayleigh wave phase. Over a 46-hour period we detect thousands of events using a cross-correlation based event identification method. Travel-time inversion of a subset of events (7% of the total) defines an active crevasse, propagating more than 200 meters in three hours. From the Rayleigh wave amplitudes, we estimate the amount of volumetric opening along the crevasse as well as an average bulk attenuation ( Q¯ = 42) for the ice in this part of the glacier. With the remaining icequake signals we establish a diurnal periodicity in seismicity, indicating that surface run-off and subglacial water pressure changes likely control the triggering of these surface events. Furthermore, we find that these events are too weak (i.e., too noisy) to locate individually. However, stacking individual events increases the signal-to-noise ratio of the waveforms, implying that these periodic sources are effectively stationary during the recording period.

81 citations


Authors

Showing all 3902 results

NameH-indexPapersCitations
Jeffrey G. Andrews11056263334
Zhu Han109140748725
Brian R. Flay8932526390
Jeffrey W. Elam8343524543
Pramod K. Varshney7989430834
Scott Fendorf7924421035
Gregory F. Ball7634221193
Yan Wang72125330710
David C. Dunand7252719212
Juan Carlos Diaz-Velez6433414252
Michael K. Lindell6218619865
Matthew J. Kohn6216413741
Maged Elkashlan6129414736
Bernard Yurke5824217897
Miguel Ferrer5847811560
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202370
2022210
2021763
2020695
2019620
2018637