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USGS2019

Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019

Digital flood-inundation maps for a 9.3-mile reach of the Iowa River along the Meskwaki Settlement, Iowa, were created by the U.S. Geological Survey (USGS) in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa. Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site. Flood profiles were computed for the stream reach by means of a calibrated one-dimensional and two-dimensional step-backwater hydraulic model. The model was calibrated by using the current stage-discharge relation at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa, and stage and discharge data from historic flooding events that were recorded at the streamgage. The hydraulic model was then used to compute eight water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from the NWS “action stage” of 11 feet (ft) to 18 ft, the stage exceeding the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the USGS streamgage 05451770. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each flood stage (water level). In addition, potential modifications to hydraulic structures within the flood plain were modeled so any effects from the potential modifications could be evaluated. Four comparison points, which were along the flood plain, showed little to no change (less than 0.1 ft) in flood elevation from the existing conditions within the flood plain for the 11- to 16-ft stages as referenced to the USGS streamgage 05451770. There were greater changes (more than 0.1 ft) in flood elevation for the 2 comparison points that were closest to the modified hydraulic structure for the 2 highest modeled stages of 17 and 18 ft. The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Iowa↗

USGS1997

The chemical evolution and paragenesis of uranium minerals from the ruggles and palermo granitic pegmatites, New Hampshire

A study of the chemical evolution and paragenesis of the uranium minerals at the Palermo No. 1 and Ruggles granitic pegmatites, Grafton County, New Hampshire, revealed four stages of secondary mineralization. A total of eight uranium minerals were identified in the four stages. The first stage is a mixture of uranyl oxide hydroxide-hydrates represented by mineral "A", which surrounds and replaces a uraninite core. The second stage is a carbonate stage found only at the Palermo No. 1 pegmatite, and is represented by rutherfordine. The third stage is represented by uranyl silicates. At the Palermo No. 1 pegmatite, this stage consists of ??-uranophane, and at the Ruggles pegmatite, it consists of soddyite and ??-uranophane. A final fourth stage is a phosphate stage represented by phosphuranylite and meta-autunite I. The first three stages of mineralization developed from hydrothermal and meteoric processes. With dropping temperatures, hydrothermal fluids reached meteoric temperatures and acquired the characteristics of meteoric water. The pH shifted from acidic (pH less than about 6 at 100??C) to alkaline (pH > 7 at 25??C). Since mineral "A" contains hydroxyl and a low amount of molecular water, it probably formed at a temperature greater than 100??C in the acidic environment. After the first stage, the hydrothermal fluids likely reached the temperatures of meteoric water. The initial pH of the meteoric water was acidic (pH less than about 6 at 25??C) and then slowly shifted to alkaline. The mineralizing fluids became oversaturated in CO3, Ca, K, and Si. Uraninite and mineral "A" became unstable and were replaced by rutherfordine and uranyl silicates. The fourth or phosphate stage developed from the introduction of groundwater. The uranyl phosphate minerals precipitated from an acidic fluid (pH < 7 at 25??C) that was oversaturated with Ca, K, U, and P.

Canadian Mineralogist↗

USGS2021

Geology, mineralogy, and cassiterite geochronology of the Ayawilca Zn-Pb-Ag-In-Sn-Cu deposit, Pasco, Peru

The Ayawilca deposit in Pasco, Peru, represents the most significant recent base-metal discovery in the central Andes and one of the largest undeveloped In resources globally. As of 2018, it hosts an 11.7 Mt indicated resource grading 6.9% Zn, 0.16% Pb, 15 g/t Ag, and 84 g/t In, an additional 45.0 Mt inferred resource grading 5.6% Zn, 0.23% Pb, 17 g/t Ag, and 67 g/t In, and a separate Sn-Cu-Ag inferred resource of 14.5 Mt grading 0.63% Sn, 0.21% Cu, and 18 g/t Ag. Newly obtained U–Pb dates for cassiterite by LA-ICP-MS (22.77 ± 0.41 and 23.05 ± 2.06 Ma) assign the Ayawilca deposit to the Miocene polymetallic belt of central Peru. The polymetallic mineralization occurs as up to 70-m-thick mantos hosted by carbonate rocks of the Late Triassic to Early Jurassic Pucará Group, and subordinately, as steeply dipping veins hosted by rocks of the Pucará Group and overlying Cretaceous sandstones-siltstones of the Goyllarisquizga Group. Relicts of a distal retrograde magnesian skarn and cassiterite (stage pre-A) were identified in the deepest mantos. The volumetrically most important mineralization at Ayawilca comprises a low-sulfidation assemblage (stage A) with quartz, pyrrhotite, arsenopyrite, chalcopyrite, Fe-rich sphalerite, and traces of stannite and herzenbergite. Stage A sphalerite records progressive Fe depletion, from 33 to 10 mol% FeS, which is compatible with the observed transition from low- to a subsequent intermediate-sulfidation stage (B) marked by the crystallization of abundant pyrite and marcasite. Finally, during a later intermediate-sulfidation stage (C) sphalerite (up to 11 mol% FeS), galena, native bismuth, Cu-Pb-Ag sulfosalts, siderite, Mn-Fe carbonates, kaolinite, dickite, and sericite were deposited. This paragenetic evolution shows striking similarities with that at the Cerro de Pasco Cordilleran-type polymetallic deposit, even if at Ayawilca stage C did not reach high-sulfidation conditions. The occurrence of an early retrograde skarn assemblage suggests that the manto bodies at Ayawilca formed at the transition between distal skarn and skarn-free (Cordilleran-type) carbonate-replacement mineralization. Mineral assemblages define a T- f S 2 evolutionary path close to the pyrrhotite-pyrite boundary. Buffering of hydrothermal fluids by underlying Devonian carbonaceous phyllites of the Excelsior Group imposed highly reduced conditions during stage A mineralization (log f O 2 < − 30 atm). The low f O 2 favored efficient Sn mobility during stages pre-A and A, in contrast to other known ore deposits in the polymetallic belt of central Peru, in which the occurrence of Sn minerals is minor. Subsequent cooling, progressive sealing of vein walls, and decreasing buffering potential of the host rocks promoted the shift from low- (stage A) to intermediate-sulfidation (stages B and C) states. LA-ICP-MS analyses reveal significant In contents in Fe-rich sphalerite (up to 1.7 wt%), stannite (up to 1908 ppm), and chalcopyrite (up to 1185 ppm). The highest In content was found in stage A sphalerite that precipitated along with chalcopyrite and stannite, thus pointing to the early, low-sulfidation assemblage as prospective for this high-tech metal in similar mineral systems. Indium was likely incorporated into the sphalerite crystal lattice via Cu + + In 3+ ↔ 2 Zn 2+ and (Sn, Ge) 4+ + (Ga, In) 3+ + (Cu + Ag) + ↔ 4 Zn 2+ coupled substitutions. Indium incorporation mechanisms into the stannite and chalcopyrite crystal lattices remain unclear.

Pasco↗

USGS2004

Textural, compositional, and sulfur isotope variations of sulfide minerals in the Red Dog Zn-Pb-Ag deposits, Brooks Range, Alaska: Implications for Ore Formation

The Red Dog Zn-Pb deposits are hosted in organic-rich mudstone and shale of the Mississippian Kuna Formation. A complex mineralization history is defined by four sphalerite types or stages: (1) early brown sphalerite, (2) yellow-brown sphalerite, (3) red-brown sphalerite, and (4) late tan sphalerite. Stages 2 and 3 constitute the main ore-forming event and are volumetrically the most important. Sulfides in stages 1 and 2 were deposited with barite, whereas stage 3 largely replaces barite. Distinct chemical differences exist among the different stages of sphalerite. From early brown sphalerite to later yellow-brown sphalerite and red-brown sphalerite, Fe and Co content generally increase and Mn and Tl content generally decrease. Early brown sphalerite contains no more than 1.9 wt percent Fe and 63 ppm Co, with high Mn (up to 37 ppm) and Tl (126 ppm), whereas yellow-brown sphalerite and red-brown sphalerite contain high Fe (up to 7.3 wt %) and Co (up to 382 ppm), and low Mn (<27 ppm) and Tl (<37 ppm). Late tan sphalerite has distinctly lower Fe (< 0.9 wt %) and higher Tl (up to 355 ppm), Mn (up to 177 ppm), and Ge (426 ppm), relative to earlier sphalerite. Wide ranges in concentrations of Ag, Cu, Pb, and Sb characterize all sphalerite types, particularly yellow-brown sphalerite and red-brown sphalerite, and most likely reflect submicroscopic inclusions of galena, chalcopyrite and/or tetrahedrite in the sphalerite. In situ ion microprobe sulfur isotope analyses show a progression from extremely low ??34S values for stage 1 (as low as -37.20???) to much higher values for yellow-brown sphalerite (mean of 3.3???; n = 30) and red-brown sphalerite (mean of 3.4; n = 20). Late tan sphalerite is isotopically light (-16.4 to -27.2???). The textural, chem ical, and isotopic data indicate the following paragenesis: (1) deposition of early brown sphalerite with abundant barite, minor pyrite, and trace galena immediately beneath the sea floor in unconsolidated mud; (2) deposition of yellow-brown sphalerite during subsea-floor hydrothermal recrystallization and coarsening of preexisting barite; (3) open-space deposition of barite, red-brown sphalerite and other sulfides in veins and coeval replacement of barite; and (4) postore sulfide deposition, including the formation of late tan sphalerite breccias. Stage 1 mineralization took place in a low-temperature environment where fluids rich in Ba mixed with pore water or water-column sulfate to form barite, and metals combined with H2S derived from bacterial sulfate reduction to form sulfides. Higher temperatures and salinities and relatively oxidized ore-stage fluids (stages 2 and 3) compared with stage 1 were probably important controls on the abundances and relative amounts of metals in the fluids and the resulting sulfide chemistry. Textural observations and isotopic data show that preexisting barite was reductively dissolved, providing a source of H2S for sulfide mineral formation. In stage 3, the continued flow of hydrothermal fluids caused thermal alteration of organic-rich mudstones and a build-up of methane that led to fluid overpressuring, hydrofracturing, and vein formation. Barite, red-brown sphalerite, and other sulfides were deposited in the veins, and preexisting barite was pervasively replaced by red-brown sphalerite. Hydrothermal activity ceased until Jurassic time when thrusting and large-scale fluid flow related to the Brookian orogeny remobilized and formed late tan sphalerite in tectonic breccias. ?? 2004 by Economic Geology.

Economic Geology↗

USGS1990

The Ag-Mn-Pb-Zn vein, replacement, and skarn deposits of Uchucchacua, Peru; studies of structure, mineralogy, metal zoning, Sr isotopes, and fluid inclusions

Uchucchacua is an Ag-Mn-Pb-Zn vein, replacement, and skarn mineral district in the central Andes of Peru. Host rocks are massive Jumasha Formation shelf limestones of Turonian age that have been folded into an asymmetric northeast-verging anticline of Andean trend. Strata near the fold crest are cut by minor dacitic intrusions and have been displaced by a conjugate set of steep wrench faults that strike northwest-southeast and northeast-southwest. Most ore occurrences are restricted to host rocks that lie below marly limestone at the top of the middle Jumasha Formation. Vein ores located along the fracture system have formed by fissure infill and by replacement of limestone wall rocks. Larger sheetlike replacement orebodies are parallel and adjacent to a large fault. Replacement is in zones of brecciation adjacent to fault bends which were dilatent during sinistral slip of the master fracture. Such fracture belts may have been subject to paleokarst solution processes before mineralization.Four paragenetic stages have been identified. Fe, Mn, and Si were introduced at the exoskarn stage (I) as the anhydrous silicates ferroan tephroite, johannsenite, rhodonite, and bustamite. During the early main stage (II) ferroan tephroite was replaced by friedelite and magnetite under oxidizing conditions at a relatively low pH. Pb, Zn, Fe, Cu, and B were introduced; principal sulfides are pyrrhotite, Fe-rich sphalerite, Mn-rich wurtzite, alabandite, galena, chalcopyrite, and tetrahedrite. Pyrrhotite was replaced by other sulfides during later stage II. Main gangue minerals were calcite, kutnohorite, rhodochrosite, and quartz. Ag, As, and Sb were introduced during the late stage (III) in the form of sulfosalts, principally pyrargyrite. Redistribution of metals introduced at stage II resulted in the growth of Fe-poor sphalerite and alabandite accompanied by calcite gangue. Decreasing Fe contents of alabandite and sphalerite during late stage II and stage III, together with the appearance of pyrite, indicate an increase in sulfur fugacity and/or decrease in temperature over this period. The supergene stage (IV) affects the upper 30 to 150 m of most veins and involves the growth of Mn hydroxides, goethite, orpiment, marcasite, cerussite, and siderite.Distribution patterns of metal ratios and high metal values define ore bands, with a succession of antiforms and synforms. Ore-band locations are determined by vein width, itself a function of wall-rock reactivity, and fracture permeability. Metal ratio distributions in the Luz vein show symmetric dispersion of metals at right angles to the ore-band axis. Ag shows the least dispersion with progressively greater dispersion of Pb and Zn.Geologic considerations indicate mineralization at a minimum depth of 1,600 m. Most primary fluid inclusions in calcite of probable stage II origin were trapped over a temperature range of about 200 degrees to 337 degrees C (hydrostatic pressure) or about 225 degrees to 362 degrees C (lithostatic). Fluid inclusions from late stage II quartz were trapped at about 165 degrees to 205 degrees C (hydrostatic) or 190 degrees to 230 degrees C (lithostatic). Salinity ranged from 0.5 to 29.7 equiv wt percent NaCl-CaCl 2 with little relation to temperature. Calcite 87 Sr/ 86 Sr values of 0.70743 to 0.71122 extend well outside the range of values both determined for magmatic rocks of the region and estimated for the host limestones but are probably compatible with older sedimentary rocks of the mine district. Salinity levels and NaCl/CaCl 2 ratios are similar to basinal brines associated with Mississippi Valley-type deposits. It is concluded that basinal brine, expelled from the deforming Mesozoic sequence, was a significant component of the ore fluid. This fluid was probably heated by dacitic magmas or cooling dacitic intrusions; a polygenetic high-salinity magmatic-basinal fluid then rose along existing strike-slip fractures toward the mineralization site where it mixed with heated low-salinity ground water.

Uchucchacua↗

USGS2012

Flood-inundation maps for Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, Atlanta, Georgia

Digital flood-inundation maps for a 5.5-mile reach of the Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Atlanta, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Peachtree Creek at Atlanta, Georgia (02336300) and the USGS streamgage at Chattahoochee River at Georgia 280, near Atlanta, Georgia (02336490). Current water level (stage) at these USGS streamgages may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Peachtree Creek, which is available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC–RAS software for a 6.5-mile reach of Peachtree Creek and was used to compute flood profiles for a 5.5-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Peachtree Creek at Atlanta, Georgia, streamgage (02336300), and the Chattahoochee River at Georgia 280, near Atlanta, Georgia, streamgage (02336490) as well as high water marks collected during the 2010 annual peak flow event. The hydraulic model was then used to determine 50 water-surface profiles. The profiles are for 10 flood stages at the Peachtree Creek streamgage at 1-foot intervals referenced to the streamgage datum and ranging from just above bankfull stage (15.0 feet) to approximately the highest recorded water level at the streamgage (24.0 feet). At each stage on Peachtree Creek, five stages at the Chattahoochee River streamgage, from 26.4 feet to 38.4 feet in 3-foot intervals, were used to determine backwater effects. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from Light Detection and Ranging (LiDAR) data having a 0.3-foot vertical and 16.4-foot horizontal resolution—to delineate the area flooded for each 1-foot increment of stream stage. The availability of these maps, when combined with real-time information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with critical information during flood response activities, such as evacuations and road closures as well as for postflood-recovery efforts.

Georgia↗

USGS2017

Flood-inundation maps for the St. Joseph River at Elkhart, Indiana

Digital flood-inundation maps for a 6.6-mile reach of the St. Joseph River at Elkhart, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind. Real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site (NWS site EKMI3). Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current stage-discharge rating at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind., and the documented high-water marks from the flood of March 1982. The hydraulic model was then used to compute six water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 23.0 ft (the NWS “action stage”) to 28.0 ft, which is the highest stage interval of the current USGS stage-discharge rating curve and 1 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft root mean squared error and 4.9-ft horizontal resolution, resampled to a 10-ft grid) to delineate the area flooded at each stage. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗

USGS2017

Flood-inundation maps for the White River at Noblesville, Indiana

Digital flood-inundation maps for a 7.5-mile reach of the White River at Noblesville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the White River at Noblesville, Ind., streamgage (USGS station number 03349000). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at the same site as the USGS streamgage (NWS site NBLI3). Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2016) stage-discharge rating at the USGS streamgage 03349000, White River at Noblesville, Ind., and documented high-water marks from the floods of September 4, 2003, and May 6, 2017. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 10.0 ft (the NWS “action stage”) to 24.0 ft, which is the highest stage interval of the current (2016) USGS stage-discharge rating curve and 2 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage. The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.

Indiana↗

USGS2017

Flood-inundation maps for North Fork Salt Creek at Nashville, Indiana

Digital flood-inundation maps for a 3.2-mile reach of North Fork Salt Creek at Nashville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding that correspond to selected water levels (stages) at the North Fork Salt Creek at Nashville, Ind., streamgage (USGS station number 03371650). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also shows observed USGS stages at the same site as the USGS streamgage (NWS site NFSI3). Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2015) stage-discharge rating at the USGS streamgage 03371650, North Fork Salt Creek at Nashville, Ind. The hydraulic model was then used to compute 12 water-surface profiles for flood stages at 1-foot (ft) intervals, except for the highest profile of 22.9 ft, referenced to the streamgage datum ranging from 12.0 ft (the NWS “action stage”) to 22.9 ft, which is the highest stage of the current (2015) USGS stage-discharge rating curve and 1.9 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage. The availability of these maps, along with information regarding current stage from the USGS streamgage, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.

Indiana↗

USGS1996

Paragenetic and minor- and trace-element studies of Mississippi Valley-type ore deposits of the Silesian-Cracow district, Poland

Paragenetic and minor- and trace-element studies were conducted on samples of epigenetic ore and gangue minerals collected from mines and drill core in the Silesian-Cracow (S-C) district of southern Poland. Four discrete mineral suites representing four mineralizing stages can be identified throughout the district. The earliest epigenetic minerals deposited during stage 1 consist of a late dolomite cement together with minor pyrite and marcasite. Stage 2 was the first ore-forming stage and included repetitive deposition of sphalerite and galena in a variety of morphologies. Stage 3 abruptly followed the first ore stage and deposited marcasite and pyrite with variable amounts of late sphalerite and galena. In the samples studied, minerals deposited during stage 3 are predominately marcasite-pyrite with minor sphalerite and galena in the Pomorzany and Olkusz mines, whereas, at the Trzebionka mine, stage 3 mineralization deposited mostly galena and sphalerite with little marcasite or pyrite. Stage 4 minerals include contains barite, followed by calcite, with very minor pyrite and a rare, late granular sphalerite. Compared to other major Mississippi Valley-type (MVT) districts of the world, the Silesian-Cracow district contains sphalerite with the second largest range in Ag concentrations and the largest range in Fe and Cd concentrations of any district. Unlike in other districts, very wide ranges in minor- and trace-element concentrations are also observed in paragenetically equivalent samples collected throughout the district. This wide range indicates that the minor- and trace-element content of the ore-forming environment was highly variable, both spatially and temporally, and suggests that the hydrologic system that the ore fluids traversed from their basinal source was very complex. Throughout the district, a significant increase in Tl, Ge, and As concentrations is accompanied by a lightening of sulfur isotopes between stage 2 and stage 3 minerals. This change appears to record a major district-scale hydrologic event that probably reflects the introduction of fluids with significantly different geochemistry than that of earlier ore-forming fluids.

Prace - Panstwowego Instytutu Geologicznego↗

USGS2017

Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon

In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al. 2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural production can provide critical insights into future management actions for this at-risk population. Multistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin. Typically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al. 2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model. The intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments. As is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because: • It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions. • Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty. • It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data. Thus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.

Idaho, Oregon, Washington, Wyoming↗

USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗

USGS2000

Ore-fluid evolution at the Getchell Carlin-type gold deposit, Nevada, USA

Minerals and fluid-inclusion populations were examined using petrography, microthermometry, quadrupole mass-spectrometer gas analyses and stable-isotope studies to characterize fluids responsible for gold mineralization at the Getchell Carlin-type gold deposit. The gold-ore assemblage at Getchell is superimposed on quartz-pyrite vein mineralization associated with a Late-Cretaceous granodiorite stock that intruded Lower-Paleozoic sedimentary rocks. The ore assemblage, of mid-Tertiary age, consists of disseminated arsenian pyrite that contains submicrometer gold, jasperoid quartz, and later fluorite and orpiment that fill fractures and vugs. Late ore-stage realgar and calcite enclose ore-stage minerals. Pre-ore quartz trapped fluids with a wide range of salinities (1 to 21 wt.% NaCl equivalent), gas compositions (H 2 O, CO 2 , and CH 4 ), and temperatures (120 to > 360°C). Oxygen- and hydrogen-isotope ratios indicate that pre-ore fluids likely had a magmatic source, and were associated with intrusion of the granodiorite stock and related dikes. Ore-stage jasperoid contains moderate salinity, aqueous fluid inclusions trapped at 180 to 220°C. Ore fluids contain minor CO 2 and trace H 2 S that allowed the fluid to react with limestone host rocks and transport gold, respectively. Aqueous inclusions in fluorite indicate that fluid temperatures declined to ∼ 175°C by the end of ore-stage mineralization. As the hydrothermal system collapsed, fluid temperatures declined to 155 to 115°C and realgar and calcite precipitated. Inclusion fluids in ore-stage minerals have high δD H2O and δ 18 O H2O values that indicate that the fluid had a deep source, and had a metamorphic or magmatic origin, or both. Late ore-stage fluids extend to lower δ H2O values, and have a wider range of δ 18 O H2O values suggesting dilution by variably exchanged meteoric waters. Results show that deeply sourced ore fluids rose along the Getchell fault system, where they dissolved carbonate wall rocks and deposited gold-enriched pyrite and jasperoid quartz. Gold and pyrite precipitated together as H 2 S in the ore fluids reacted with iron in the host rocks. As ore fluids mixed with local aquifer fluids, ore fluids became cooler and more dilute. Cooling caused precipitation of ore-stage fluorite and orpiment, and late ore-stage realgar. Phase separation and/or neutralization of the ore fluid during the waning stages of the hydrothermal ore system led to deposition of late ore-stage calcite.

Nevada↗

USGS1978

Origin of a South Texas roll-type deposit; II, Sulfide petrology and sulfur isotope studies

Petrologic and sulfur isotopic studies have been carried out on drill core samples from a roll-type uranium deposit in the mid-Tertiary Catahoula Tuff, Webb County, south Texas. Epigenetic iron disulfide minerals formed in two distinct stages. The first stage involved sulfidization of the host rock by sulfide (H 2 S, HS-)-bearing solutions that emanated from a fault about 1.5 km downdip from and subparallel to the orebody. Pyrite was the dominant iron disulfide mineral formed from this fault sulfide. The isotopic composition (delta 34 S) of first-stage iron disulfide is quite heavy (>0 per mil), in part because the fault-derived H 2 S was isotopically heavy. The development of the second-stage sulfides was related to processes that formed the uranium roll. Iron disulfide minerals produced during this second stage commonly occur as rims around the first-stage sulfides. The rims are exclusively marcasite in and adjacent to ore, but the pyrite content in these rims increases with increasing distance from ore. The sulfur of the second-stage sulfides in the vicinity of the roll front is isotopically light (--25 to --40 per mil). The virtual absence of organic carbon in the host sand precludes a bacterial origin for the ore-stage iron disulfide minerals and, therefore, eliminates bacterial metabolism as the mechanism for isotopic fractionation. Instead, the sulfur source for ore-stage sulfides was preore (first stage) sulfides, remobilized via partial oxidation to soluble metastable sulfur oxyanions.

Texas↗

USGS1999

At-sea distribution of Spectacled Eiders: A 120-year-old mystery resolved

The at-sea distribution of the threatened Spectacled Eider ( Somateria fischeri ) has remained largely undocumented. We identified migration corridors, staging and molting areas, and wintering areas of adult Spectacled Eiders using implanted satellite-transmitters in birds from each of the three extant breeding grounds (North Slope and Yukon-Kuskokwim Delta in Alaska and arctic Russia). Based on transmitter locations, we conducted aerial surveys to provide visual confirmation of eider flocks and to estimate numbers of birds. We identified two principal molting and staging areas off coastal Alaska (Ledyard Bay and eastern Norton Sound) and two off coastal Russia (Mechigmenskiy Bay on the eastern Chukotka Peninsula, and the area between the Indigirka and Kolyma deltas in the Republic of Sakha). We estimated that >10,000 birds molt and stage in monospecific flocks at Mechigmenskiy and Ledyard bays, and several thousand molt and stage in eastern Norton Sound. We further identified eastern Norton Sound as the principal molting and staging area for females nesting on the Yukon-Kuskokwim Delta, and Ledyard Bay and Mechigmenskiy Bay as the principal molting and staging areas for females nesting on the North Slope. Males marked at all three breeding grounds molt and stage in Mechigmenskiy Bay, Ledyard Bay, and the Indigirka-Kolyma delta region. Males from the Yukon-Kuskokwim Delta molt and stage mainly at Mechigmenskiy Bay. Equal numbers of males from the North Slope molt and stage at all three areas, and most males from arctic Russia molt and stage at the Indigirka-Kolyma delta region. Postbreeding migration corridors were offshore in the Bering, Chukchi, and Beaufort seas. In winter, eiders were in the Bering Sea south of St. Lawrence Island. Our estimates from surveys in late winter and early spring suggest that at least 333,000 birds winter in single-species flocks in the pack ice in the Bering Sea.

Alaska↗

USGS2012

Flood-inundation maps for the Saddle River from Rochelle Park to Lodi, New Jersey, 2012

Digital flood-inundation maps for a 2.75-mile reach of the Saddle River from 0.2 mile upstream from the Interstate 80 bridge in Rochelle Park to 1.5 miles downstream from the U.S. Route 46 bridge in Lodi, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Saddle River at Lodi, New Jersey (station 01391500). Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01391500 . The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the Saddle River at Lodi, New Jersey streamgage and documented high-water marks from recent floods. The hydraulic model was then used to determine 11 water-surface profiles for flood stages at the Saddle River streamgage at 1-ft intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the extent of the stage-discharge rating, which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84-ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

New Jersey↗

USGS2013

Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013

Digital flood-inundation maps for a 4.1-mile reach of the Saddle River from 0.6 miles downstream from the New Jersey-New York State boundary in Upper Saddle River Borough to 0.2 miles downstream from the East Allendale Road bridge in Saddle River Borough, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to select water levels (stages) at the USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey. Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01390450. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations (in effect March 2013) at USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey, and documented high-water marks from recent floods. The hydraulic model was then used to determine eight water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the upper extent of the stage-discharge rating which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps along with real-time streamflow data and information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

New Jersey↗

USGS2014

Flood inundation maps for the Wabash and Eel Rivers at Logansport, Indiana

Digital flood-inundation maps for an 8.3-mile reach of the Wabash River and a 7.6-mile reach of the Eel River at Logansport, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage Wabash River at Logansport, Ind. (sta. no. 03329000) and USGS streamgage Eel River near Logansport, Ind. (sta. no. 03328500). Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/ . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system http:/water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgages 03329000, Wabash River at Logansport, Ind., and 03328500, Eel River near Logansport, Ind. The calibrated hydraulic model was then used to determine five water-surface profiles for flood stage at 1-foot intervals referenced to the Wabash River streamgage datum, and four water-surface profiles for flood stages at 1-foot intervals referenced to the Eel River streamgage datum. The stages range from bankfull to approximately the highest stages that have occurred since 1967 when three flood control dams were built upstream of Logansport, Ind. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [lidar] data having a 0.37-foot vertical accuracy and 3.9-foot horizontal resolution) in order to delineate the area flooded at each stage. The availability of these maps, along with information available on the Internet regarding current stages from the USGS streamgages at Logansport, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post flood recovery efforts.

Indiana↗