Статті в журналах з теми "Texas Brazos River"

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1

Waters, Michael R., and Lee C. Nordt. "Late Quaternary Floodplain History of the Brazos River in East-Central Texas." Quaternary Research 43, no. 3 (May 1995): 311–19. http://dx.doi.org/10.1006/qres.1995.1037.

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AbstractThe floodplain along a 75-km segment of the Brazos River, traversing the Gulf Coastal Plain of Texas, has a complex late Quaternary history. From 18,000 to 8500 yr B.P., the Brazos River was a competent meandering stream that migrated from one side of the floodplain to the other, creating a thick layer of coarse-grained lateral accretion deposits. After 8500 yr B.P., the hydrologic regime of the Brazos River changed. The river became an underfit meandering stream that repeatedly became confined within narrow and unstable meander belts that would occasionally avulse. Avulsion occurred four times; first at 8100 yr B.P., then at 2500 yr B.P., again around 500 yr B.P., and finally around 300 yr B.P. The depositional regime on the floodplain also changed after 8500 yr B.P., with floodplain construction dominated by vertical accretion. Most vertical accretion occurred from 8100 to 4200 yr B.P. and from 2500 to 1250 yr B.P. Two major and three minor periods of soil formation are documented in the floodplain sequence. The two most developed soils formed from 4200 to 2500 yr B.P. and from around 1250 to 500 yr B.P. These changes on the floodplain appear to be the result not of a single factor, but of the complex interplay among changes in climate, sediment yield, and intrinsic floodplain variables over time.
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2

Stull, Trevor, and Habib Ahmari. "Estimation of Suspended Sediment Concentration along the Lower Brazos River Using Satellite Imagery and Machine Learning." Remote Sensing 16, no. 10 (May 13, 2024): 1727. http://dx.doi.org/10.3390/rs16101727.

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This article focuses on developing models that estimate suspended sediment concentrations (SSCs) for the Lower Brazos River, Texas, U.S. Historical samples of SSCs from gauge stations and satellite imagery from Landsat Missions and Sentinel Mission 2 were utilized to develop models to estimate SSCs for the Lower Brazos River. The models used in this study to accomplish this goal include support vector machines (SVMs), artificial neural networks (ANNs), extreme learning machines (ELMs), and exponential relationships. In addition, flow measurements were used to develop rating curves to estimate SSCs for the Brazos River as a baseline comparison of the models that used satellite imagery to estimate SSCs. The models were evaluated using a Taylor Diagram analysis on the test data set developed for the Brazos River data. Fifteen of the models developed using satellite imagery as inputs performed with a coefficient of determination R2 above 0.69, with the three best performing models having an R2 of 0.83 to 0.85. One of the best performing models was then utilized to estimate the SSCs before, during, and after Hurricane Harvey to evaluate the impact of this storm on the sediment dynamics along the Lower Brazos River and the model’s ability to estimate SSCs.
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3

Gillespie, B. Marcus, and John R. Giardino. "Determining the migratory activity index for a river: An example from the Brazos River, Texas." Zeitschrift für Geomorphologie 40, no. 4 (December 12, 1996): 417–28. http://dx.doi.org/10.1127/zfg/40/1996/417.

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4

MUNSTER, C., C. MATHEWSON, and C. WROBLESKI. "The Texas A&M University Brazos River Hydrogeologic Field Site." Environmental & Engineering Geoscience II, no. 4 (December 1, 1996): 517–30. http://dx.doi.org/10.2113/gseegeosci.ii.4.517.

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5

Story, Gregory. "An introduction to the NWS West Gulf River Forecast Center." Texas Water Journal 7, no. 1 (July 12, 2016): 56–63. http://dx.doi.org/10.21423/twj.v7i1.7036.

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The National Weather Service (NWS) West Gulf River Forecast Center (WGRFC), in cooperation with numerous federal, state, and local government entities, uses the latest science and technology to provide timely and accurate river forecasts in an effort to protect life and property for most of the river drainages in Texas. Disaster preparedness decreases property damage by an estimated $1 billion annually nationwide. The mission is to provide basic hydrologic forecast information for the economic and environmental well-being for the nation. The WGRFC is 1 of 13 river forecast centers within the United States and is located in Fort Worth, Texas. The WGRFC’s area of responsibility stretches from the Rio Grande in southern Colorado, New Mexico and south Texas eastward to the Sabine River along the Texas-Louisiana border. Other rivers in the center’s area of responsibility include the Pecos, Nueces, San Antonio, Guadalupe, Colorado, Brazos, Trinity, and Neches rivers. This article will describe the variety of hydrologic forecasting services routinely provided by the WGRFC. Although flood forecasts are its most well-known product, the WGRFC also generates river and water information used for recreation, reservoir operations, and water supply plans. Additionally, the WGRFC produces estimates of hourly precipitation. To achieve this, the WGRFC has 2 primary functions; a hydrometeorological function and a hydrologic function. This article will describe each function and discuss how each function serves as steps in the preparation and the issuing of hydrologic forecasts. Citation: Story GJ. 2016. Program note: An introduction to the NWS West Gulf River Forecast Center. Texas Water Journal. 7(1):56-63. Available from: https://doi.org/10.21423/twj.v7i1.7036.
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6

Kubicek, Kole M., Amanda K. Pinion, and Kevin W. Conway. "New records of the Mountain Mullet, Dajaus monticola (Bancroft, 1834), and an overview of historical records in Texas." Check List 15, no. 3 (June 7, 2019): 471–78. http://dx.doi.org/10.15560/15.3.471.

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Dajaus monticola (Bancroft, 1834) is an amphidromous species of mugilid known from South and Central America and the islands of the Caribbean but is rarely collected in Gulf coast states of the United States. Two new records of D. monticola collected from the Gulf of Mexico (Brazoria Co.) and the Brazos River (Washington Co.) are reported from Texas. The rare occurrence of D. monticola in Texas is discussed and diagnostic characters used to distinguish this species from other mugilids found in Texas are reevaluated.
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7

Wurbs, Ralph A., and Tae J. Kim. "Condensing Water Availability Models to Focus on Specific Water Management Systems." Texas Water Journal 1, no. 1 (September 1, 2010): 20–32. http://dx.doi.org/10.21423/twj.v1i1.1380.

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The Texas Water Availability Modeling System is routinely applied in administration of the water rights permit system, regional and statewide planning, and an expanding variety of other endeavors. Modeling water management in the 23 river basins of the state reflects about 8,000 water right permits and 3,400 reservoirs. Datasets are necessarily large and complex to provide the decision-support capabilities for which the modeling system was developed. New modeling features are being added, and the different types of applications are growing. Certain applications are enhanced by simplifying the simulation input datasets to focus on particular water management systems. A methodology is presented for developing a condensed dataset for a selected reservoir system that reflects the impacts of all the water rights and accompanying reservoirs removed from the original complete dataset. A set of streamflows is developed that represents flows available to the selected system considering the effects of all the other water rights in the river basin contained in the original complete model input dataset that are not included in the condensed dataset. The methodology is applied to develop a condensed model of the Brazos River Authority reservoir system based on modifying the Texas Water Availability Modeling System dataset for the Brazos River Basin. Citation: Wurbs RA, Kim TJ. 2010. Condensing water availability models to focus on specific water management systems. Texas Water Journal. 1(1):20-32. Available from: https://doi.org/10.21423/twj.v1i1.1380.
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8

Moulton, Stephen R., Daniel Petr, and Kenneth W. Stewart. "Caddisflies (Insecta: Trichoptera) of the Brazos River Drainage in North-Central Texas." Southwestern Naturalist 38, no. 1 (March 1993): 19. http://dx.doi.org/10.2307/3671639.

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9

Wilde, Gene R., and Bart W. Durham. "Habitat associations of the sharpnose shinerNotropis oxyrhynchusin the upper Brazos River, Texas." Journal of Freshwater Ecology 28, no. 4 (December 2013): 453–61. http://dx.doi.org/10.1080/02705060.2013.817358.

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10

Durham, B. W., and G. R. Wilde. "Asynchronous and synchronous spawning by smalleye shinerNotropis bucculafrom the Brazos River, Texas." Ecology of Freshwater Fish 17, no. 4 (December 2008): 528–41. http://dx.doi.org/10.1111/j.1600-0633.2008.00303.x.

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11

Phillips, Jonathan D. "Hydrologic and geomorphic flow thresholds in the Lower Brazos River, Texas, USA." Hydrological Sciences Journal 60, no. 9 (August 20, 2015): 1631–48. http://dx.doi.org/10.1080/02626667.2014.943670.

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12

Heymann, D., T. E. Yancey, W. S. Wolbach, M. H. Thiemens, E. A. Johnson, D. Roach, and S. Moecker. "Geochemical Markers of the Cretaceous-Tertiary Boundary Event at Brazos River, Texas, USA." Geochimica et Cosmochimica Acta 62, no. 1 (January 1998): 173–81. http://dx.doi.org/10.1016/s0016-7037(97)00330-x.

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13

DiMarco, Steven F., Josiah Strauss, Nelson May, Ruth L. Mullins-Perry, Ethan L. Grossman, and David Shormann. "Texas Coastal Hypoxia Linked to Brazos River Discharge as Revealed by Oxygen Isotopes." Aquatic Geochemistry 18, no. 2 (January 20, 2012): 159–81. http://dx.doi.org/10.1007/s10498-011-9156-x.

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14

Kennedy, W. J., A. S. Gale, and T. A. Hansen. "The last Maastrichtian ammonites from the Brazos River sections in Falls County, Texas." Cretaceous Research 22, no. 2 (April 2001): 163–71. http://dx.doi.org/10.1006/cres.2001.0245.

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15

Montgomery, H., E. Pessagno, K. Soegaard, C. Smith, I. Mun˜oz, and J. Pessagno. "Misconceptions concerning the Cretaceous/Tertiary boundary at the Brazos River, Falls County, Texas." Earth and Planetary Science Letters 109, no. 3-4 (April 1992): 593–600. http://dx.doi.org/10.1016/0012-821x(92)90117-e.

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16

Funk, Robert D., James W. Mjelde, Frank M. Hons, and Vince A. Saladino. "An Economic Analysis of a Corn-Soybean Crop Rotation Under Various Input Combinations in South Central Texas." Journal of Agricultural and Applied Economics 31, no. 1 (April 1999): 69–81. http://dx.doi.org/10.1017/s0081305200028788.

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AbstractEight input combinations of commercial fertilizer, insecticides, and herbicides on a corn-soybean crop rotation in the Brazos River Bottom of Texas are evaluated. Input combinations which do not fully utilize all three inputs are consistently ranked higher by all criteria as the preferred input strategy for the corn-soybean rotation system. These results, which indicate limited input crop rotations that fall somewhere between the extremes of conventional agricultural production and organic agriculture, deserve further attention as a possible production alternative.
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17

Randklev, Charles R., Benjamin J. Lundeen, Robert G. Howells, and James H. Kennedy. "First Account of a Living Population of Texas Fawnsfoot, Truncilla macrodon (Bivalvia: Unionidae), in the Brazos River, Texas." Southwestern Naturalist 55, no. 2 (June 2010): 297–98. http://dx.doi.org/10.1894/js-31.1.

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18

Leighton, Andrew D., Malcolm B. Hart, Christopher W. Smart, Melanie J. Leng, and Matthew Hampton. "TIMING RECOVERY AFTER THE CRETACEOUS/PALEOGENE BOUNDARY: EVIDENCE FROM THE BRAZOS RIVER, TEXAS, USA." Journal of Foraminiferal Research 47, no. 3 (July 2017): 229–38. http://dx.doi.org/10.2113/gsjfr.47.3.229.

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19

Prauss, Michael L. "The K/Pg boundary at Brazos-River, Texas, USA — An approach by marine palynology." Palaeogeography, Palaeoclimatology, Palaeoecology 283, no. 3-4 (December 2009): 195–215. http://dx.doi.org/10.1016/j.palaeo.2009.09.024.

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20

ALLEN, P. M., R. HOBBS, and N. D. MAIER. "Downstream Impacts of a Dam on a Bedrock Fluvial System, Brazos River, Central Texas." Environmental & Engineering Geoscience xxvi, no. 2 (May 1, 1989): 165–89. http://dx.doi.org/10.2113/gseegeosci.xxvi.2.165.

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21

Davidoff, Andrew J., and Thomas E. Yanccy. "Eustatic cyclicity in the paleocene and eocene: data from the Brazos River Valley, Texas." Tectonophysics 222, no. 3-4 (July 1993): 371–95. http://dx.doi.org/10.1016/0040-1951(93)90360-v.

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22

Kim, Tae Jin. "Application of water rights priority and natural priority orders to river and reservoir operation systems." Canadian Journal of Civil Engineering 38, no. 6 (June 2011): 650–60. http://dx.doi.org/10.1139/l11-040.

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Surface water rights in Texas are developed based on “Prior Appropriation Doctrine”. The Texas Water Availability Model, a computer-based simulation model based on water rights priority order, has been used for computing the amount of water supply and determining the amount of water available for a newly requested water right for the past several years. This study compares the water rights priority and natural priority orders by applying it to the largest sixteen reservoirs in the Brazos River Basin, Texas. The water supply reliability, reservoir storage frequency, and stream flows are analyzed corresponding to each priority orders. The natural priority order increases water supply reliability for most reservoirs about 1 to 2% and mean reservoir storage volume located in the upper basin than water rights priority order. The stream flows based on water rights priority order are more regulated than natural priority order by 3 and 5%. The composite priority order is more effective than each priority order in increasing the water supply reliability.
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23

Borel, Kyna E., R. Karthikeyan, Patricia K. Smith, Lucas F. Gregory, and Raghavan Srinivasan. "Estimating daily potential E. coli Loads in pural Texas watersheds using Spatially Explicit Load Enrichment Calculation Tool (SELECT)." Texas Water Journal 3, no. 1 (November 5, 2012): 42–58. http://dx.doi.org/10.21423/twj.v3i1.6164.

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When developing a watershed protection plan (WPP) or a total maximum daily load (TMDL), it is often difficult to accurately assess pollutant loads and sources for a watershed because insufficient water quality monitoring data are available. According to the Texas Commission on Environmental Quality, there are 274 bacterial impairments in Texas water bodies out of a total of 438 impaired water bodies. Bacterial data are often sparse, which hinders the development of WPPs or TMDLs. To address this lack of data, the Spatially Explicit Load Enrichment Calculation Tool (SELECT) was used to develop WPPs for 3 rural watersheds in Texas that are impaired due to E. coli bacteria: Buck Creek, 5 subwatersheds of Little Brazos River, and Lampasas River. SELECT is an automated geographical information system tool that can assess potential bacteria sources and relative loads in watersheds using spatial factors such as land use, population density, and soil type. The results show how the SELECT methodology was applied and adapted to each watershed based on stakeholder concerns and data availability. Citation: Borel KE, Karthikeyan R, Smith PK, Gregory LF, Srinivasan R. 2012. Estimating daily potential E. coli loads in rural Texas watersheds using Spatially Explicit Load Enrichment Calculation Tool (SELECT). Texas Water Journal. 3(1):42-58. Available from: https://doi.org/10.21423/twj.v3i1.6164.
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24

Jordan, David C., and Mark A. Fonstad. "Two Dimensional Mapping of River Bathymetry and Power Using Aerial Photography and GIS on the Brazos River, Texas." Geocarto International 20, no. 3 (September 2005): 13–20. http://dx.doi.org/10.1080/10106040508542351.

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25

Speijer, Robert P., Peter Schulte, Hartmut Mai, and Christoph Meisen. "Benthic foraminiferal change and sea level across the Cretaceous/Paleogene boundary at Brazos River, Texas." Anuário do Instituto de Geociências 29, no. 1 (January 1, 2006): 507–8. http://dx.doi.org/10.11137/2006_1_507-508.

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26

Zhang, Jiaqi, Yu-Fen Huang, Dinuke Munasinghe, Zheng Fang, Yin-Phan Tsang, and Sagy Cohen. "Comparative Analysis of Inundation Mapping Approaches for the 2016 Flood in the Brazos River, Texas." JAWRA Journal of the American Water Resources Association 54, no. 4 (February 9, 2018): 820–33. http://dx.doi.org/10.1111/1752-1688.12623.

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27

VanLandeghem, Matthew M., Mukhtar Farooqi, Bobby Farquhar, and Reynaldo Patiño. "Impacts of Golden AlgaPrymnesium parvumon Fish Populations in Reservoirs of the Upper Colorado River and Brazos River Basins, Texas." Transactions of the American Fisheries Society 142, no. 3 (May 2013): 581–95. http://dx.doi.org/10.1080/00028487.2012.754786.

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28

Mihailović, Dragutin, Emilija Nikolić-Đorić, Slavica Malinović-Milićević, Vijay Singh, Anja Mihailović, Tatijana Stošić, Borko Stošić, and Nusret Drešković. "The Choice of an Appropriate Information Dissimilarity Measure for Hierarchical Clustering of River Streamflow Time Series, Based on Calculated Lyapunov Exponent and Kolmogorov Measures." Entropy 21, no. 2 (February 23, 2019): 215. http://dx.doi.org/10.3390/e21020215.

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The purpose of this paper was to choose an appropriate information dissimilarity measure for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations on the Brazos River in Texas (USA), for the period 1989–2016. For that purpose, we selected and compared the average-linkage clustering hierarchical algorithm based on the compression-based dissimilarity measure (NCD), permutation distribution dissimilarity measure (PDDM), and Kolmogorov distance (KD). The algorithm was also compared with K-means clustering based on Kolmogorov complexity (KC), the highest value of Kolmogorov complexity spectrum (KCM), and the largest Lyapunov exponent (LLE). Using a dissimilarity matrix based on NCD, PDDM, and KD for daily streamflow, the agglomerative average-linkage hierarchical algorithm was applied. The key findings of this study are that: (i) The KD clustering algorithm is the most suitable among others; (ii) ANOVA analysis shows that there exist highly significant differences between mean values of four clusters, confirming that the choice of the number of clusters was suitably done; and (iii) from the clustering we found that the predictability of streamflow data of the Brazos River given by the Lyapunov time (LT), corrected for randomness by Kolmogorov time (KT) in days, lies in the interval from two to five days.
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29

Durham, Bart W., and Gene R. Wilde. "Population Dynamics of the Smalleye Shiner, an Imperiled Cyprinid Fish Endemic to the Brazos River, Texas." Transactions of the American Fisheries Society 138, no. 3 (May 2009): 666–74. http://dx.doi.org/10.1577/t07-234.1.

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30

Keller, Gerta. "Extended Cretaceous/Tertiary boundary extinctions and delayed population change in planktonic foraminifera from Brazos River, Texas." Paleoceanography 4, no. 3 (June 1989): 287–332. http://dx.doi.org/10.1029/pa004i003p00287.

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31

Houghton, David C., and Kenneth W. Stewart. "Life History and Case-Building Behavior of Culoptila cantha (Trichoptera: Glossosomatidae) in the Brazos River, Texas." Annals of the Entomological Society of America 91, no. 1 (January 1, 1998): 59–70. http://dx.doi.org/10.1093/aesa/91.1.59.

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32

Woelders, Lineke, and Robert P. Speijer. "Stable seafloor conditions, sea level and food supply during the latest Maastrichtian at Brazos River, Texas." Marine Micropaleontology 121 (December 2015): 41–51. http://dx.doi.org/10.1016/j.marmicro.2015.10.002.

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33

Woelders, Lineke, Robert Speijer, and Philippe Claeys. "Benthic foraminiferal, sea level and climate change across the Cretaceous/Paleogene boundary at Brazos River, Texas." Rendiconti online della Società Geologica Italiana 31 (July 2014): 228–29. http://dx.doi.org/10.3301/rol.2014.135.

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34

Zeng, Fan-Wei, Caroline A. Masiello, and William C. Hockaday. "Controls on the origin and cycling of riverine dissolved inorganic carbon in the Brazos River, Texas." Biogeochemistry 104, no. 1-3 (July 23, 2010): 275–91. http://dx.doi.org/10.1007/s10533-010-9501-y.

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35

Schmitz, B. "An iridium anomaly in the Ludlow Bone Bed from the Upper Silurian, England." Geological Magazine 129, no. 3 (May 1992): 359–62. http://dx.doi.org/10.1017/s0016756800019294.

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AbstractThe Ludlow Bone Bed in the Upper Silurian of the Welsh Borderland shows an anomalously high concentration of iridium (0.49 ppb) compared with background (0.040 ppb Ir). Considering the overall major and trace element pattern and the mineralogy of the bone bed, it appears that the bulk of their has precipitated from sea water and is not primarily related to an asteroid impact event. A secondary relation of the Ir to such an event, however, cannot be excluded. The profound sedimentological similarity (skeletal sands and hummocky cross-stratification) between the Ir-carrying ‘storm deposit’ at the Cretaceous–Tertiary boundary at Brazos River, Texas, and the LBB and overlying sediments may indicate such a relation.
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36

Suh, Charles P. C., John K. Westbrook, and Jesus F. Esquivel. "Species of Stink Bugs in Cotton and Other Row Crops in the Brazos River Bottom of Texas." Southwestern Entomologist 38, no. 4 (December 2013): 561–70. http://dx.doi.org/10.3958/059.038.0402.

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37

Smith, Kathryn M. "Lithic Activity Area Investigations at the Longhorn Site (41KT53) in the Upper Brazos River Basin, Western Texas." Plains Anthropologist 57, no. 222 (May 2012): 91–108. http://dx.doi.org/10.1179/pan.2012.011.

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38

Van Plantinga, Alexander A., and Ethan L. Grossman. "Stable and clumped isotope sclerochronologies of mussels from the Brazos River, Texas (USA): Environmental and ecologic proxy." Chemical Geology 502 (December 2018): 55–65. http://dx.doi.org/10.1016/j.chemgeo.2018.10.012.

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39

Kimball, Rustin A., and Merlynd K. Nestell. "Multi-factored stratigraphy and new correlation standards in the lower part of the Canyon Group (Missourian, Upper Pennsylvanian), Wise County, Texas: A can of worms untangled." Stratigraphy 4, no. 4 (2007): 329–52. http://dx.doi.org/10.29041/strat.04.4.03.

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Several Late Pennsylvanian (Early Missourian) age limestone beds exposed in isolated outcrops in the Trinity River Valley in southwestern Wise County and named by Böse (1917), and Scott and Armstrong (1932) are assigned to the Palo Pinto Formation (lower part of the Canyon Group). Clearly designated type localities or type sections were not given for some limestone beds named in these two previous studies. These limestone units in southwest Wise County occur in coherent stratigraphic sequences in three key areas: along Dry Creek, around Martin Lake, and along Boons Creek. Original type localities have been located and suitable reference sections have been established for these limestone beds. The Canyon Group was established for outcrops of strata in the Brazos River Valley. Correlation of strata between the type area and strata in the Trinity River Valley is based on stratigraphic position, textural characteristics of the limestone, and similarities in flora and fauna, including the presence of distinctive algae and fusulinacean species of Triticites and Nankinella. Equivalence of several of the units named by Scott and Armstrong (1932) is established: the Boone Creek Limestone and Hudson Bridge Limestone; the Sanders Bridge Limestone and unnamed (Yl4) limestone; and the Martin Lake Limestone and Balsora Limestone. The names first used in the literature and retained here are the Boone Creek Limestone, Sanders Bridge Limestone, and the Martin Lake Limestone. Two additional limestone units present between the Martin Lake Limestone and the Willow Point Limestone are formally designated here as the Bridgeport Road Limestone and the Kirkman Limestone. The findings of this investigation follow the Canyon Group nomenclature established by Laury (1962). The two new limestone units, along with the Bridgeport Coal and the Willow Point Limestone, are placed in the Posideon Formation, with the Willow Point Limestone forming the top member. In the Posideon Formation, the Bridgeport Road Limestone may correlate to one of the lower limestone units within the Pp1 shale of Laury (1962) in the type area. The time-synchronous overlying conodont rich core shale has been correlated previously to the Pp1 shale in the type area. The Kirkman Limestone is correlated to the Pp2 limestone, and the Willow Point Limestone to the Wiles Limestone, both correlations based on the presence of overlying time-synchronous core shale in both river valleys. The Sanders Bridge Limestone is correlated to the middle of the Palo Pinto Formation in the type area in the Brazos River Valley.
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