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USGS2022

The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids

Water temperature is a primary control on the health, diversity, abundance, and distribution of aquatic species, but thermal degradation resulting from anthropogenic influences on rivers is a challenge to threatened species worldwide. In the Willamette River Basin, northwestern Oregon, spring-run Chinook salmon ( Oncorhynchus tshawytscha ) and winter-run steelhead ( O. mykiss ) are formerly abundant cold-water-adapted species that are now protected under the Endangered Species Act. Among the challenges to the health of cold-water salmonids in the Willamette River Basin, disruptions in the seasonal patterns of stream temperature imposed by 13 large, multipurpose dams on tributaries to the Willamette River, as well as temperatures routinely in excess of regulatory limits in the Willamette River Basin, are contributing factors. To better understand controls on stream temperature, the sensitivity of stream temperature to flow augmentation as a management tool for suppressing high temperatures, and the implications for threatened salmonids, this study used a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) to investigate spatial and temporal patterns of stream temperature in the Willamette River Basin. This study focused on the upper 160.4 river miles of the Willamette River from the confluence of the Middle Fork and Coast Fork Willamette Rivers (river mile 187.2) to Willamette Falls (river mile 26.8), three representative climate years (2011, a cool and wet year; 2015, an extremely hot and dry year; and 2016, a moderately hot and dry year), and a series of flow-augmentation scenarios. Model results show that the Willamette River upstream from Willamette Falls is divisible into four characteristic “thermal reaches” with similar thermal patterns, depending on tributary input, warming rate, and the timing of thermal response. In general, the Willamette River warms downstream during spring and summer, but patterns are complex, influenced by tributary inflows, and seasonally variable. Except in cool wet years (as illustrated by 2011), modeling suggests that adversely warm conditions for spring-run Chinook salmon are extensive from June or July through August. The thermal influence of flow augmentation from dam storage on four tributaries with U.S. Army Corps of Engineers dams varies spatially along the Willamette River, seasonally, and in magnitude, depending on a range of factors like distance from the Willamette River, the temperature of dam outflow, and the thermal template of tributary reaches controlling stream temperature adjustment to environmental heat fluxes. Modeling suggests that targeted flow management (via augmentation from dam storage) can reduce the extent and duration of thermally stressful conditions for Chinook salmon for short periods, but modeling suggests that flow augmentation is limited in its ability to fundamentally alter the “thermal landscape” (the entire range of temperature variation in a river system over space and time) of the Willamette River. While this research provides general insights into the thermal landscape of the Willamette River and its sensitivity to flow management, additional investigation into the thermal landscape of tributaries downstream from U.S. Army Corps of Engineers dams, as well as the thermal management of reservoirs, storage availability, and dam outflows, would be necessary to target specific management actions for supporting specified rearing or migration conditions for spring-run Chinook salmon and other cold-water-adapted species in the Willamette River Basin.

Oregon↗

USGS2025

Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets

Maintaining streamflow to support human water needs and ecosystem services requires a fundamental understanding of the relations between changes in streamflow processes and ecosystem responses. Changes in the natural patterns in flow, geology, and topography alter the habitats that aquatic organisms rely on for food, shelter, and reproduction. The U.S. Geological Survey (USGS) implemented an ecological-flow framework that encapsulates the basic principles of the Ecological Limits of Hydrologic Alteration (ELOHA) to compare the relations between hydrologic metrics and stream conditions and estimate ecological flow needs in the Barnegat Bay-Little Egg Harbor watershed. As a first step in the ELOHA process, streamflow from two historical time periods (occurring between 1933 and 1988) was compared to streamflow for a recent time period (from 2004-2020) for four major streams in the Barnegat Bay-Little Egg Harbor watershed (North Branch Metedeconk River, Toms River, Cedar Creek, and Westecunk Creek), to evaluate if there were statistically significant differences in streamflow metrics. Analysis of monthly, seasonal, and annual low-flow metrics; patterns in the streamflow record; and general land-use changes were used to develop a better understanding of flow conditions in the watershed. The comparative streamflow analysis indicated that notable changes in flow processes for the study streams occurred between the three periods of record (PORs) evaluated in this study: period of record 1 (POR1, from water years 1933–1958), period of record 2 (POR2, from water years 1974–1988), and period of record 3 (POR3, from water years 2004–2020). For example, the mean of the daily streamflow decreased between the historical POR to the current POR in Cedar Creek but increased in North Branch Metedeconk and Toms Rivers. Larger and more significant changes (p-value <0.10) occurred during specific months or were related to the variability or seasonality of flow. North Branch Metedeconk River and Toms River, the two northern and most developed sites, exhibited changes in low-flow metrics and decreases in minimum n-day moving averages. Decreases in the normalized 75th-percentile exceedance flows were evident at three of the four study sub-basins during POR2 and POR3. In comparison, there was little to no evidence of negative changes to low-flow metrics at Westecunk Creek, the southernmost and least developed site, where all low-flow duration metrics increased as well as seasonal minimum consecutive 7-day average flows. Significant increases in monthly minimums (p-value <0.05) at Cedar Creek for spring months (April, May, and June) also were observed. Natural and anthropogenic processes can alter the landscape resulting in concomitant changes in the streamflow regime. There is a need to assess these changes and synthesize the results into a scientifically defensible set of goals and standards that help support the management of environmental flows. This study represents the initial steps in building the hydrologic foundation to inform management and develop future ecological flow targets that balance water availability for human and ecosystem needs in the Barnegat Bay-Little Egg Harbor watershed.

New Jersey↗

USGS2022

Choosing an optimal duck season: Integrating hunter values and duck abundance

State wildlife agencies have long struggled to identify optimal hunting season dates for migratory game bird species that meet the diverse and often competing interests of stakeholders. Many approaches have been used to ensure the regulated community participates in the decision-making process, including public hearings, hunter season-date preference surveys, and hunter task forces or committees. Although hearings, surveys, and task force approaches include portions of the regulated community (typically the most avid) they may not necessarily reflect the opinions and values of all stakeholders. Additionally, these approaches rely heavily on limited anecdotal observations that may be unduly influenced by hunter avidity (e.g., days spent afield), hunter density, species preferences, and property access. To address the challenges caused by engaging only portions of the stakeholder community, we used a structured decision-making framework that included a 2017 duck hunter survey to elucidate values of a representative sample of the regulated community in each waterfowl hunting zone in the state of New York, USA. Rather than asking duck hunters about their specific duck hunting season date preferences, we asked them to rank 6 objectives describing what they value in their hunting experience (e.g., maximizing the opportunity to see mallards [ Anas platyrhynchos ] and black ducks [ Anas rubripes ], maximizing the number of weekend days). Four of the 6 objectives described duck species availability (i.e., abundance or immigration) and the remaining 2 described considerations that affect an individual hunter's opportunity or limitation to going duck hunting (i.e., holidays or conflicting hunting seasons). We used spatiotemporal abundance models derived from eBird citizen science data to estimate abundance and immigration rates of ducks in each waterfowl zone. We evaluated up to 9 unique season date alternatives developed by duck hunter task forces to determine which season date alternative best satisfied the competing objectives of duck hunters in each zone. The approach we developed allowed for selection of optimal duck hunting season dates and successfully involved avid duck hunters in the regulation development stages, while ensuring that the values of a representative sample of all stakeholders were directly considered through a clear and transparent decision-making process.

New York↗

USGS2008

Modeling variability and trends in pesticide concentrations in streams

A parametric regression model was developed for assessing the variability and long-term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long-term (inter-annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p-values were accurate for as few as 10 uncensored concentrations during a three-year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean-squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean-squared error and decreases in power. ?? 2008 American Water Resources Association.

Journal of the American Water Resources Associatio↗

USGS1988

Food availability controls seasonal cycle of growth in Macoma balthica (L.) in San Francisco Bay, California

A 2-yr field study of growth in the bivalve Macoma balthica (L.) at four locations in San Francisco Bay, California, U.S., showed that the timing and rate of growth (increase in shell length) were related to food supply. This clam feeds on both planktonic and benthic microalgae, depending on availability. Growth was apparently food-limited during some months, during one year more than the other, and at some locations more than others. Tissue-weight changes were also related to food availability. The heaviest animals were found in that year and at those locations with the highest chl a concentrations. Tissue-weight gains usually coincided with increased shell-growth rate or with reproductive development, although some large animals showed weight gain independent of both of these factors during periods with mid-range chl a levels. Weight losses coincided with spawning or periods of low growth rate, except at one station where, during a period when most animals were reproductively ripe, food concentrations were high, and shell growth was rapid, animals lost weight. This study failed to show a relation between salinity and the timing or rate of change of either shell length or tissue weight. The mild temperatures (10-23 ??C water temperature) of the area studied resulted in no growth inhibition due to low temperature, but there was some indication that the high air temperatures found in these intertidal areas limited growth rates. ?? 1988.

Journal of Experimental Marine Biology and Ecology↗

USGS1999

The effect of frozen soil on snowmelt runoff at Sleepers River, Vermont

Soil frost depth has been monitored at the Sleepers River Research Watershed in northeastern Vermont since 1984. Soil frost develops every winter, particularly in open fields, but its depth varies greatly from year to year in inverse relation to snow depth. During the 15 years of record at a benchmark mid-elevation open site, the annual maximum frost depth varied from 70 to 390 mm. We empirically tested the hypothesis that frozen soil prevents infiltration and recharge, thereby causing an increased runoff ratio (streamflow/(rain+snowmelt)) during the snowmelt hydrograph rise and a decreased runoff ratio during snowmelt recession. The hypothesis was not supported at the 111 km 2 W-5 catchment; there was no significant correlation of the runoff ratio with the seasonal maximum frost depth for either the pre-peak or post-peak period. In an analysis of four events, however, the presence of frost promoted a large and somewhat quicker response to rainfall relative to the no-frost condition, although snow cover caused a much greater time-to-peak regardless of frost status. For six years of flow and frost depth measured at the 59 ha agricultural basin W-2, the hypothesis appeared to be supported. The enhancement of runoff due to soil frost is evident on small plots and in extreme events, such as rain on frozen snow-free soil. In the northeastern USA and eastern Canada, the effect is often masked in larger catchments by several confounding factors, including storage of meltwater in the snowpack, variability in snowmelt timing due to elevational and aspect differences, interspersed forested land where frost may be absent, and the timing of soil thawing relative to the runoff peak.

Hydrological Processes↗

USGS2026

Fire regime shift reveals 17th century socio-ecological change in the Rio Grande del Norte National Monument, New Mexico

Humans have influenced ecosystems for millennia, and social changes can have notable ecological effects. Recent human influence on ecosystems is exemplified by the collapse of fire regimes circa 1900 in the western United States due to increased grazing, fire suppression, and declining Indigenous fire use. Climate can also drive fire regime changes, which is reflected by increasing area burned across the West in recent decades associated with warming and increased aridity. In the southwestern United States during the mid-1600s, large social changes accompanied Spanish colonization. These changes included increases in domestic livestock (e.g., sheep and horses), declines of Indigenous populations and cultural burning, and exploitation of Puebloans that led to the 1680 Pueblo Revolt, an Indigenous uprising that expelled Spanish colonizers for 12 years. The ecological effects of these large social changes are not well studied. The goal of this study was to use tree-ring fire histories to investigate fire dynamics of a sagebrush-dominated landscape in the Rio Grande del Norte National Monument (RGDN) in northern New Mexico, including the effects of historical social and climatic changes. We reconstructed fire history on four forested mountains that rise above the sagebrush/grass plateau. We asked: (1) What was the pre-1900 fire frequency, season, and fire–climate relationship in the RGDN? (2) Was there evidence for fire spread in the sagebrush/grass flats between the mountains? and (3) Did regional social or climate changes influence fire regimes? From 1400 to 1679, we found frequent fire within forests (8–12-year median fire intervals [mfi]) and potential evidence of spreading fire through the sagebrush/grass ecosystem based on greater-than-expected intermountain fire synchrony. However, beginning in the mid-1600s and continuing after the Pueblo Revolt of 1680, there was (1) a significant decline in fire frequency, including 38–166-year mfi and no fire for >350 years at two sites; and (2) only one synchronous fire between mountains. During this 17th century period of socio-ecological change there was no persistent shift in climate. We propose that reduced Indigenous ignitions and increased domestic grazing, which reduced herbaceous fuels and fire spread, are likely causes of the extraordinary early and persistent reduction in fire.

New Mexico↗

USGS2010

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction ( C p ) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

Water Resources Research↗

USGS2006

Physical habitat classification and instream flow modeling to determine habitat availability during low-flow periods, North Fork Shenandoah River, Virginia

Increasing development and increasing water withdrawals for public, industrial, and agricultural water supply threaten to reduce streamflows in the Shenandoah River basin in Virginia. Water managers need more information to balance human water-supply needs with the daily streamflows necessary for maintaining the aquatic ecosystems. To meet the need for comprehensive information on hydrology, water supply, and instream-flow requirements of the Shenandoah River basin, the U.S. Geological Survey and the Northern Shenandoah Valley Regional Commission conducted a cooperative investigation of habitat availability during low-flow periods on the North Fork Shenandoah River. Historic streamflow data and empirical data on physical habitat, river hydraulics, fish community structure, and recreation were used to develop a physical habitat simulation model. Hydraulic measurements were made during low, medium, and high flows in six reaches at a total of 36 transects that included riffles, runs, and pools, and that had a variety of substrates and cover types. Habitat suitability criteria for fish were developed from detailed fish-community sampling and microhabitat observations. Fish were grouped into four guilds of species and life stages with similar habitat requirements. Simulated habitat was considered in the context of seasonal flow regimes to show the availability of flows that sustain suitable habitat during months when precipitation and streamflow are scarce. The North Fork Shenandoah River basin was divided into three management sections for analysis purposes: the upper section, middle section, and lower section. The months of July, August, and September were chosen to represent a low-flow period in the basin with low mean monthly flows, low precipitation, high temperatures, and high water withdrawals. Exceedance flows calculated from the combined data from these three months describe low-flow periods on the North Fork Shenandoah River. Long-term records from three streamflow-gaging stations were used to characterize the flow regime: North Fork Shenandoah River at Cootes Store, Va. (1925-2002), North Fork Shenandoah River at Mount Jackson, Va. (1943-2002), and North Fork Shenandoah River near Strasburg, Va. (1925-2002). The predominant mesohabitat types (14 percent riffle, 67.3 percent run, and 18.7 percent pool) were classified along the entire river (100 miles) to assist in the selection of reaches for hydraulic and fish community data collection. The upper section has predominantly particle substrate, ranging in size from sand to boulders, and the shortest habitat units. The middle section is a transitional section with increased bedrock substrate and habitat unit length. The lower section has predominantly bedrock substrate and the longest habitat units in the river. The model simulations show that weighted usable-habitat area in the upper management section is highest at flows higher than the 25-percent exceedance flow for July, August, and September. During these three months, total weighted usable-habitat area in this section is often less than the simulated maximum weighted usable-habitat area. Habitat area in the middle management section is highest at flows between the 25- and 75-percent exceedance flows for July, August, and September. In the middle section during these months, both the actual weighted usable-habitat area and the simulated maximum weighted usable-habitat area are associated with this flow range. Weighted usable-habitat area in the lower management section is highest at flows lower than the 75-percent exceedance flow for July, August, and September. In the lower section during these three months, some weighted usable-habitat area is available, but the normal range of flows does not include the simulated maximum weighted usable-habitat area. A time-series habitat analysis associated with the historic streamflow, zero water withdrawals, and doubled water withdrawals was completed. During s

Scientific Investigations Report↗

USGS1988

Experimental Mycoplasma gallisepticum infections in captive-reared wild turkeys

The effects of Mycoplasma gallisepticum (MG) infections on egg production, fertility, and hatchability were studied in captive-reared wild turkeys ( Meleagris gallopavo ). Three groups of adult birds, each consisting of four hens and two toms, were exposed to MG by the respiratory route at the beginning of their breeding season. Fourteen control birds received sterile growth medium. Although no mortality of infected or control birds occurred, egg production during the first breeding season after infection was reduced. The mean number of eggs/hen/day produced by infected groups the first breeding season postexposure (PE) was significantly lower than the control value. The mean number of eggs produced daily by the same hens 1 yr later was unaffected by MG infection. The pecentage of fertile eggs produced by infected groups was slightly reduced in both the first and second breeding seasons PE. Hatchability of fertile eggs from infected hens was significantly lower than eggs from control hens. Productivity may be impaired if MG infections occur in free-ranging wild turkey populations.

Journal of Wildlife Diseases↗

USGS2011

Comparison and analysis of empirical equations for soil heat flux for different cropping systems and irrigation methods

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center-pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (Rn) ratio (G/Rn) and the normalized difference vegetation index (NDVI). When a significant portion of the ground was bare soil, G/Rn ranged from 0.15 to 0.30 and decreased with increasing NDVI. In contrast to the NDVI progression, the G/Rn ratio decreased with crop growth and development. The G/Rn ratio for subsurface drip irrigated crops was smaller than for the center-pivot irrigated crops. The seasonal average G was 13.1%, 15.2%, 10.9%, and 12.8% of Rn for irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean, respectively. Statistical analyses of the performance of the four models showed a wide range of variation in G estimation. The root mean square error (RMSE) of predictions ranged from 15 to 81.3 W m-2. Based on the wide range of RMSE, it is recommended that local calibration of the models should be carried out for remote estimation of soil heat flux.

Transactions of the ASABE↗

USGS2023

Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

Delaware River Basin↗

USGS2016

Mixed stock analysis of Lake Michigan's Lake Whitefish Coregonus clupeaformis commercial fishery

Lake whitefish ( Coregonus clupeaformis ) support the primary commercial fishery in Lake Michigan. Discrete genetic stocks of lake whitefish have been identified and tagging data suggest stocks are mixed throughout much of the year. Our objectives were to determine if (1) differential stock harvest occurs in the commercial catch, (2) spatial differences in genetic composition of harvested fish were present, and (3) seasonal differences were present in the harvest by commercial fisheries that operate in management zones WI-2 and WFM-01 (Green Bay, Lake Michigan). Mixed stock analysis was conducted on 17 commercial harvest samples (n = 78–145/sample) collected from various ports lake-wide during 2009–2010. Results showed significant mixing with variability in stock composition across most samples. Samples consisted of two to four genetic stocks each accounting for ≥ 10% the catch. In 10 of 17 samples, the stock contributing the largest proportion made up < 60% of the harvest. In general, seasonal and annual differences existed in the proportional stock contribution at a single capture location. Samples from Wisconsin's primary commercial fishing management zone (WI-2) were composed predominately of fish from the Big Bay de Noc (Michigan) stock as opposed to the geographically proximate, North–Moonlight Bay (Wisconsin) stock. These findings have implications for management and allocation of fish to various quotas. Specifically, geographic location of harvest, the current means of allocating harvest quotas, is not the best predictor of genetic stock harvest.

Lake Michigan↗

USGS2011

Comparisons between consumption estimates from bioenergetics simulations and field measurements for walleyes from Oneida Lake, New York

Daily consumption was estimated from the stomach contents of walleyes Sander vitreus collected weekly from Oneida Lake, New York, during June-October 1975, 1992, 1993, and 1994 for one to four age-groups per year. Field rations were highly variable between weeks, and trends in ration size varied both seasonally and annually. The coefficient of variation for weekly field rations within years and ages ranged from 45% to 97%. Field estimates were compared with simulated consumption from a bioenergetics model. The simulation averages of daily ration deviated from those of the field estimates by -20.1% to +70.3%, with a mean across all simulations of +14.3%. The deviations for each time step were much greater than those for the simulation averages, ranging from -92.8% to +363.6%. A systematic trend in the deviations was observed, the model producing overpredictions at rations less than 3.7% of body weight. Analysis of variance indicated that the deviations were affected by sample year and week but not age. Multiple linear regression using backwards selection procedures and Akaike's information criterion indicated that walleye weight, walleye growth, lake temperature, prey energy density, and the proportion of gizzard shad Dorosoma cepedianum in the diet significantly affected the deviations between simulated and field rations and explained 32% of the variance. ?? Copyright by the American Fisheries Society 2008.

Transactions of the American Fisheries Society↗

USGS1964

Supergene iron ores of minas Gerais, Brazil

The iron ores of Minas Gerais , Brazil , fall into two categories: (1) hypogene hematite ore averaging 66 percent or more Fe, and (2) lower-grade supergene ores . Most ore now extracted is high-grade hypogene ore ; lower-grade supergene ores will be of much future value. All supergene ores formed by weathering of itabirite, a metamorphosed oxide-facies iron formation averaging about 38 percent Fe and 44 percent Si02. The Caue Itabirite crops out for about 540 linear kilometers in central Minas Gerais . Supergene ores fall into three intergradational categories: (1) enriched itabirite, averaging 49 percent Fe, easily con-centratable, with reserves about 25,000 million tons; (2) intermediate grade ores , averaging perhaps 63 percent Fe, with indicated and inferred reserves more than 600 million tons; and (3) canga, averaging between 57 and 62 percent Fe, with reserves in the hundreds of millions of tons. Disaggregation of hard and brittle itabirite by solution primarily of quartz and secondarily of other soluble constituents causes residual enrichment in iron with minor hydration of hematite. As weathering continues, most of the quartz is removed and more of the hematite is hydrated, producing intermediate grade ore . Secondary enrichment by limonite is important. The final weathering product is canga. In canga, almost all the iron is hydrated, and the rock is still further impoverished in Si02 and residually enriched in A1203 and P. Canga also forms by cementation of iron -rich detritus by limonite. Four factors control the supergene ore -forming process: (1) physiography, for ores occur on ridges and plateaus; (2) climate, for seasonal rainfall is apparently needed for the formation of extensive canga blankets; (3) grain size of the original itabirite, for quartz with a grain size much greater than 0.1 millimeter is not readily soluble; and (4) composition of the iron formation. The chemically inert and physically resistant canga blanket is essential to supergene ore formation because soft weathering products would otherwise be removed as fast as formed. Thus, canga gives time for the formation of other ore types. Iron fixed as cementing limonite in canga and as enriching limonite in intermediate grade ore was derived by leaching and hydration of hematite from itabirite. It probably moved in the ferrous state and was precipitated as insoluble hydrous ferric oxide primarily by oxygenation of the solutions, to a lesser extent by their evaporation at or near the surface, and to a still smaller degree by pH changes. The data show that the high-grade hematite ore , 66 percent Fe or higher, cannot have formed directly by supergene action. Geochemical processes resulting in supergene concentration of iron also concentrated alumina and phosphorus. The high-grade ore contains about the same low percentages of these materials as unweathered itabirite.

Minas Gerais↗

USGS2014

Effects of land use, stream habitat, and water quality on biological communities of wadeable streams in the Illinois River Basin of Arkansas, 2011 and 2012

The Illinois River Basin includes an area of diverse land use in northwestern Arkansas. Land-use data collected in 2006 indicate that most of the land in the basin is agricultural. The agricultural land is used primarily for production of poultry and cattle. Eighteen sites were selected from the list of candidate sites based on drainage area, land use, presence or absence of an upstream wastewater-treatment plant, water quality, and other information gathered during the reconnaissance. An important consideration in the process was to select sites along gradients of forest to urban land use and forest to agricultural land use. Water-quality samples were collected for analysis of nutrients, and a multiparameter field meter was used to measure water temperature, specific conductance, pH, and dissolved oxygen. Streamflow was measured immediately following the water-quality sampling. Macroalgae coverage was estimated and periphyton, macroinvertebrate, and fish communities were sampled at each site. Stream habitat also was assessed. Many types of land-use, water-quality, and habitat factors affected one or more aspects of the biological communities. Several macroinvertebrate and fish metrics changed in response to changes in percent forest; sites that would be considered most disturbed, based on these metrics, are sites with the highest percentages of urban land use in their associated basins. The presence of large mats of macroalgae was one of the most noticeable biological characteristics in several streams within the Illinois River Basin. The highest macroalgae percent cover values were recorded at four sites downstream from wastewater-treatment plants. Macroalgae percent cover was strongly correlated only with bed substrate size, canopy closure, and specific conductance. Periphyton metrics were most often and most strongly correlated with riparian shading, specific conductance, substrate turbidity, percent agriculture, poultry house density, and unpaved road density; some of these factors were strongly correlated with percent forest, percent urban, or percent agriculture. Total biovolume of periphyton was not strongly correlated with any of the land use, habitat, or water-quality factors assessed in the present study. Although algal growth typically increases with higher nutrient concentrations and less shading, the standing crop of periphyton on rocks can be reduced by herbivorous macroinvertebrates and fish, which may explain why total biovolume in Ozark streams was not strongly affected by water-quality (or other habitat) factors. A macroinvertebrate index and several macroinvertebrate metrics were adversely affected by increasing urban and agricultural land use and associated environmental factors. Factors most commonly affecting the index and metrics included factors associated with water quality, stream geometry, sediment, land-use percentages, and road density. In general, the macroinvertebrate index was higher (indicative of least disturbance) at sites with greater percentages of forest in their basins, lower percentages of urban land in their basins, and lower paved road density. Upstream wastewater-treatment plants affected several metrics. For example, three of the five lowest macroinvertebrate index scores, two of the five lowest percent predator values, and two of the five highest percent gatherer-collector values were at sites downstream from wastewater-treatment plants. The Ozark Highlands fish index of biotic integrity and several fish metrics were adversely affected by increasing urban and agricultural land use and associated factors. Factors affecting these metrics included factors associated with nutrients, sediment, and shading. In general, the fish index of biotic integrity was higher at sites with higher percentages of forest in their basins, lower percentages of urban land in their basins, higher unpaved road density, and lower paved and total road density. Upstream wastewater-treatment plants seemed to affect some fish community metrics substantially but had little effect on other metrics. For example, three of the five lowest relative abundances of lithophilic spawner minus stonerollers and four of the five highest stoneroller abundances were at sites downstream from wastewater-treatment plants. Interpretations of the results of the study described in this report are limited by a number of factors. These factors individually and collectively add to uncertainty and variability in the responses to various environmental stresses. Notwithstanding the limiting factors, the biological responses of macroalgae cover and periphyton, macroinvertebrate, and fish metrics to environmental variables provide multiple lines of evidence that biological communities of these streams are affected by recent and ongoing land-use practices. For several biological metrics there appears to be a threshold of about 40 to 50 percent forest where values of these metrics change in magnitude. However, the four sites with more than 50 percent forest in their basins were the four sites sampled in late May–early June of 2012 (rather than July–August of 2011). The relative influence of season and forest percentage on the biological communities at these sites is unknown.

Arkansas↗

USGS2022

A novel regression method for harmonic analysis of time series

Harmonic analysis of time series is an important technique in remote sensing to reveal seasonal land surface dynamics. However, frequency selection in the harmonic analysis is often difficult because high-frequency components are useful for delineating seasonal dynamics but sensitive to noise and gaps in time series. On the other hand, it is challenging to obtain temporally continuous satellite data with high quality because of atmospheric contamination. We developed a novel regression method named Harmonic Adaptive Penalty Operator (HAPO) for harmonic analysis of unevenly distributed time series. We introduced a new penalty function to minimize unexpected fluctuations in the model, which can substantially reduce the overfitting issue of regression in time series with temporal gaps. Specifically, the new penalty function minimizes the length of the model curve and the value range difference between the model and the time series observations. We compared HAPO with three widely used regression methods (OLS: Ordinary Least Squares; LASSO: Least Absolute Shrinkage and Selection Operator; and Ridge) in different scenarios using Landsat time series data across the United States. First, we evaluated methods using the Landsat surface reflectance time series within a single year. HAPO showed low and consistent monthly Root Mean Square Deviation (RMSD) values, in which most of the time RMSD of predicted reflectance were less than 0.04. More importantly, HAPO showed consistent and less bias given varying density and irregularity of time series. Second, we evaluated methods using multi-year time series. HAPO was a better predictor of relatively short time series (< 4 years) with steady low RMSD values. When a longer time series ( 4 years) was used, all four methods showed similar RMSD values, but HAPO outperformed the other methods if there were temporal gaps. Therefore, for places with large seasonal observation gaps or for time series that are relatively short (less than 4 years), HAPO can provide more consistent and accurate results in harmonic analysis of time series.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS1991

Seasonal and geothermal production variations in concentrations of He and CO2 in soil gases, Roosevelt Hot Springs Known Geothermal Resource Area, Utah, U.S.A.

To increase understanding of natural variations in soil gas concentrations, CO 2 , He, O 2 and N 2 were measured in soil gases collected regularly for several months from four sites at the Roosevelt Hot Springs Known Geothermal Resource Area, Utah. Soil temperature, air temperature, per cent relative humidity, barometric pressure and amounts of rain and snowfall were also monitored to determine the effect of meteorological parameters on concentrations of the measured gases. Considerable seasonal variation existed in concentrations of CO 2 and He. The parameters that most affected the soil-gas concentrations were soil and air temperatures. Moisture from rain and snow probably affected the soil-gas concentrations also. However, annual variations in meteorological parameters did not appear to affect measurements of anomalous concentrations in samples collected within a time period of a few days. Production from some of the geothermal wells probably affected the soil-gas concentrations.

Utah↗