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At least 469 records · Page 26Linked to original sources

Using logistic regression to predict a probability of debris flows in areas burned by wildfires, southern California, 2003-2006

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

California↗

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine and(or) desethyl-atrazine (atrazine/DEA) at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability maps were constructed.

Colorado↗

Methods for estimating annual exceedance-probability discharges for streams in Iowa, based on data through water year 2010

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Iowa↗

Anthropogenic organic compounds in source water of select community water systems in the United States, 2002-10

Drinking water delivered by community water systems (CWSs) comes from one or both of two sources: surface water and groundwater. Source water is raw, untreated water used by CWSs and is usually treated before distribution to consumers. Beginning in 2002, the U.S. Geological Survey’s (USGS) National Water-Quality Assessment Program initiated Source Water-Quality Assessments (SWQAs) at select CWSs across the United States, primarily to characterize the occurrence of a large number of anthropogenic organic compounds that are predominantly unregulated by the U.S. Environmental Protection Agency. Source-water samples from CWSs were collected during 2002–10 from 20 surface-water sites (river intakes) and during 2002–09 from 448 groundwater sites (supply wells). River intakes were sampled approximately 16 times during a 1-year sampling period, and supply wells were sampled once. Samples were monitored for 265 anthropogenic organic compounds. An additional 3 herbicides and 16 herbicide degradates were monitored in samples collected from 8 river intakes and 118 supply wells in areas where these compounds likely have been used. Thirty-seven compounds have an established U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL) for drinking water, 123 have USGS Health-Based Screening Levels (HBSLs), and 29 are included on the EPA Contaminant Candidate List 3. All compounds detected in source water were evaluated both with and without an assessment level and were grouped into 13 categories (hereafter termed as “use groups”) based on their primary use or source. The CWS sites were characterized in a national context using an extract of the EPA Safe Drinking Water Information System to develop spatially derived and system-specific ancillary data. Community water system information is contained in the EPA Public Supply Database, which includes 2,016 active river intakes and 112,099 active supply wells. Ancillary variables including population served, watershed size, land use, population density, and recharge were characterized for each of the watersheds for river intakes and contributing areas for supply wells. A total of 313 samples were collected from 20 river intakes. Between the years of 2002 through 2010, samples were collected approximately 16 times over the course of a year. Seventy-one compounds from 12 of the 13 use groups commonly occurred (detected in greater than or equal to 1 percent of samples using an assessment level of 0.05 microgram per liter or when a compound was detected in greater than or equal to 10 percent of samples without an assessment level) indicating a wide variety of sources and pathways to these rivers and highlighting the importance of source-water protection strategies. A total of 448 supply wells were sampled once during 2002–10 as part of 30 independent groundwater studies. About 15 CWS supply wells were sampled for each independent groundwater study. Twenty-eight compounds from 7 of the 13 use groups commonly occurred indicating a wide variety of sources and pathways exist for these compounds to reach these wells and highlighting the importance of wellhead protection strategies. About one-half the 265 compounds monitored (122) were detected in both surface water and groundwater samples. A more diverse suite of compounds were detected in surface water in comparison to groundwater. However, herbicides and herbicide degradates were the most frequent group of compounds detected in both surface water and groundwater. Sixty-five of the most commonly occurring compounds were detected in one or more samples from both surface water and groundwater. Human-health benchmarks (MCLs for regulated compounds and HBSLs for unregulated compounds) were available for more than one-half the compounds (160 of the 265) monitored in this study. Fifty-eight percent (41 of 71) of the commonly occurring compounds in surface water have a human-health benchmark to which concentrations can be compared; 19 have MCLs and 22 have HBSLs. Eighty-three percent (24 of 28) of the most commonly occurring compounds in groundwater have a human-health benchmark for which concentrations can be compared; 14 have MCLs and 10 have HBSLs. To put results from this study into context with the national distribution of river intakes and supply wells used by CWSs, sites were grouped into the respective national population of land-use quartiles. The increase in compound occurrence with increasing urban and agricultural land use in the watershed or contributing area was more evident for rivers than for supply wells. The increase in detection frequency of herbicides and herbicide degradates with increasing agricultural land use was more evident for rivers than for supply wells. The occurrence of solvents did not change substantially with increasing urban land use for rivers or supply wells. Basic co-occurrence analyses were completed with and without an assessment level. Considering all detections in surface water without an assessment level, approximately 86 percent of source-water samples contained 2 or more compounds, and 50 percent of samples contained at least 14 compounds. Considering all detections in groundwater without an assessment level, 50 percent of samples contained at least three compounds. For the most part, the compounds detected most frequently as individual compounds in the environment often composed the most frequent unique mixtures. Five of the 10 most frequently co-occurring unique mixtures in both surface water and groundwater were the same: atrazine and deethylatrazine; atrazine and chloroform; deethylatrazine and simazine; atrazine and simazine; and deethylatrazine, atrazine, and simazine. Because similar mixtures were identified in both surface water and groundwater without an assessment level, future studies could be directed toward better understanding the toxicological importance of these unique mixtures. Summed concentrations of herbicide degradates were compared to concentrations of the parent herbicides in surface-water and groundwater samples collected from 8 river intakes and 118 CWS wells, from which samples were analyzed for an additional 3 herbicides and 16 degradates. The toxicity to humans for many of these degradate products is largely unknown and thus points to the importance of monitoring these compounds (both the parent and degradate) in the environment. This study highlights the importance of anthropogenic organic compounds in source water of select CWSs in the United States by characterizing their occurrence in surface-water and groundwater samples. Compound concentrations and occurrence are summarized and evaluated in a human-health context, when possible. Additionally, compounds found to co-occur as mixtures for both surface water and groundwater highlight the significance of low-level compound co-occurrence.

Scientific Investigations Report↗

Forest soil chemistry and terrain attributes in a Catskills watershed

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

New York↗

Upper Auglaize watershed AGNPS modeling project

The Upper Auglaize Watershed agricultural non-point source modeling project was an interagency effort to use a Geographic Information System (GIS)-based modeling approach for assessing and reducing pollution from agricultural runoff and other non-point sources. This project applied the U.S. Department of Agriculture (USDA), Agricultural Research Service’s AGricultural Non-Point Source (AGNPS) suite of models to the Upper Auglaize River Watershed, a major watershed within the Maumee River Basin. This modeling project was conducted by an interagency team consisting of a partnership between the: (1) USDA, Agricultural Research Service (ARS); (2) USDA, Natural Resources Conservation Service (NRCS); (3) U.S. Army Corps of Engineers (USACE); (4) U.S. Geological Survey (USGS); (5) Ohio State University; (6) University of Toledo (UT); (7) Heidelberg College; (8) Ohio Department of Natural Resources (ODNR), Division of Soil and Water Conservation; (9) Ohio Environmental Protection Agency (OEPA); and (10) Allen, Auglaize, Van Wert, and Putnam Soil and Water Conservation Districts. The partnership was the first step in a process to eventually apply the model in a portioned subset of watersheds for the Maumee Basin, and then to link them to form a comprehensive basin-wide model This work was performed under the authority of Section 516(e) of the Water Resources Development Act (WRDA) of 1996, as amended, for the purpose of assisting State and local watershed managers with their evaluation, prioritization and implementation of alternatives for soil conservation, sediment trapping and non-point source pollution prevention in the Upper Auglaize River watershed. The project team, working in a cooperative effort, used the models to determine sediment sources, contributing locations, and the effect of application of best management practices (BMPs) on rates of sediment delivery to the mouth of the watershed. The results will be used to guide conservation incentive and land treatment programs. The team relied heavily on Geographic Information System (GIS)-based applications to expedite the application of the model. The results of the analysis demonstrated that the application of BMPs would have a positive effect on reducing the loadings of sediment leaving the mouth of the Upper Auglaize Watershed. An application of 17 percent new no-till acres and eight percent new grassland acres, when randomly applied to the watershed, reduced loadings at the mouth to 82 percent of the simulated existing condition loadings. No-till, conversion of cropland to grassland, other uses including grass buffers, and reforestation of parts of the watershed, were all shown by the model to have a measurable effect on reducing sediment loads. Conversion of all of the cropland in the watershed to no-till would reduce the average unit load (tons of sediment per acre) leaving the mouth of the watershed to a level that is 42 percent of the simulated existing condition load. Ephemeral gullies were found to be the primary source of erosion (72 percent), sediment yield (73 percent), and sediment loading (73 percent). Controlling sediment load means controlling gully erosion and possibly trapping sediment yield before it reaches the stream system. Most BMPs (e.g., no-till, conversion of cropland, etc.) that reduce sheet and rill erosion and its sediment yield will also reduce gully erosion and its sediment yield. However, grassed waterways, which have no effect on sheet and rill erosion, are frequently an effective BMP to prevent ephemeral gullies. And, of course, riparian vegetation and sediment traps would reduce the delivery ratios of all types of landscape erosion. New techniques were developed by the team to quantify the ephemeral gully erosion within the model. When calibrated to available stream gage data the model suggests that more (73% in the existing condition simulation) of the sediment load originates from ephemeral gully erosion than from traditional sheet and rill erosion. The model quantified the value of tile drainage in reducing the sediment load from the watershed. Loadings under drained conditions were always less than loadings under undrained conditions for otherwise identical land uses. The average sediment load of all alternatives for drained loadings was 89.2 percent of the load for the corresponding undrained loadings. The model established that while many conservation incentive programs treat tile drainage as a production practice, significant erosion and sediment control benefits are provided by the practice in comparison to cultivation in an undrained state.

Ohio↗

Assessment of severity and distribution of corrosive ground water in Pennsylvania

Relations between corrosive ground water, water chemistry, and geology in Pennsylvania were evaluated by use of a modified version of the Langelier Saturation Index (LSIsn) and a geologic contact dataset in a Geographic Information System. Water-chemistry information for water samples collected from 4,839 combined private and public-supply wells from 1900 to 1993 was used to calculate the LSIsn. Thirty-eight lithologic subgroups within four major rock types-carbonate, siliciclastic, crystalline, and unconsolidated-in Pennsylvania were grouped together if the mean of ranked LSIsn values were not significantly different. A water is considered corrosive if the LSIsn value is negative, preventing the precipitation of calcium carbonate, therefore, allowing corrosive reactions with the interior of piping systems. Statistical tests of the LSIsn values show the least corrosive waters are in the carbonate lithologic subgroup, and the most corrosive waters are in the quartzite lithologic subgroup. Approximately 58 percent of the 4,839 LSIsn values were considered moderately to extremely corrosive. A map showing the location of 4,839 wells and associated corrosivity range within 11 lithologic subgroups will aid in identifying potential areas of corrosive ground water in Pennsylvania.

Open-File Report↗

Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky

Digital flood inundation maps for a 17-mile reach of Licking River and 4-mile reach of South Fork Licking River near Falmouth, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with Pendleton County and the U.S. Army Corps of Engineers–Louisville District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Licking River at Catawba, Ky., (station 03253500) and the USGS streamgage on the South Fork Licking River at Hayes, Ky., (station 03253000). Current conditions (2015) for the USGS streamgages may be obtained online at the USGS National Water Information System site ( http://waterdata.usgs.gov/nwis ). In addition, the streamgage 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 flood hydrograph forecasts provided by the NWS are usually collocated with USGS streamgages. The forecasted peak-stage information, also available on the NWS Web site, 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 Licking River reach and South Fork Licking River reach by using a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current (2015) stage-discharge relations for the Licking River at Catawba, Ky., and the South Fork Licking River at Hayes, Ky., USGS streamgages. The calibrated model was then used to calculate 60 water-surface profiles for a sequence of flood stages, at 2-foot intervals, referenced to the streamgage datum and ranging from an elevation near bankfull to the elevation associated with a major flood that occurred in the region in 1997. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model of the study area by using geographic information system software. The availability of these flood inundation maps for Falmouth, Ky., along with online information regarding current stages from the USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with information that is critical for flood response activities such as evacuations, road closures, and post-flood recovery efforts.

Kentucky↗

Determination of study reporting limits for pesticide constituent data for the California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project, 2004–2018—Part 1: National Water Quality Schedules 2003, 2032, or 2033, and 2060

The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) is a long-term cooperative project designed to assess the quality of groundwater resources used for public and domestic drinking water supplies in the State of California, to monitor and evaluate changes to that quality, to investigate the human and natural factors controlling water quality, and to improve the availability of comprehensive groundwater quality data and information. Between May 18, 2004, and May 3, 2018, the GAMA-PBP collected 3001 groundwater samples for analysis of pesticide constituents by the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL)(note that ‘pesticide constituents’ includes parent compounds and degradates). Of these samples, 2994 were analyzed for pesticide constituents on schedules 2003, 2032, or 2033 (65 to 84 constituents), and 840 were analyzed for pesticide constituents on schedule 2060 (58 constituents). The original dataset reported by the NWQL to the USGS National Water Information System (NWIS) database contained a total of 2,688 detections of 78 pesticide constituents and 253,825 non-detections. In this original dataset, 33 percent of the 3,001 samples analyzed had reported detections of one or more pesticide constituents. This report describes the GAMA-PBP data-quality objectives for pesticide data, the procedures used to establish study reporting limits, and use of those reporting limits to censor the data from the NWQL so that the final data published by the GAMA-PBP meet these data-quality objectives. The final GAMA-PBP dataset for samples collected from May 2004 to May 2018, after censoring, had a total of 1,632 detections of 37 pesticide constituents. In the final GAMA-PBP dataset, 25 percent of the 3,001 samples analyzed had detections of one or more pesticide constituents. The presence of pesticides in groundwater is commonly evaluated by calculating detection frequencies. Detection frequencies for pesticides are sensitive to detection limits and method performance for concentrations near those limits; therefore, the two primary data quality issues addressed in the GAMA-PBP data-quality objectives for pesticides are (1) establishing criteria for classifying data from the laboratory as detections or non-detections for the purpose of data reporting by the project and (2) accounting for changes in analytical methods or method performance over time. The GAMA-PBP addresses these issues by developing study reporting limits that are used as the boundary between detections and non-detections for the reporting of GAMA-PBP results. These reporting limits are defined from method detection limits (MDLs) provided by the NWQL, unless examination of results from laboratory set blanks (LSBs) and GAMA-PBP field blanks indicates that a higher concentration censoring limit is warranted. The GAMA-PBP selected the MDL as the primary choice for defining study reporting limits for consistency with U.S. Environmental Protection Agency (EPA) guidelines for reporting detections of pesticides and other organic constituents. A five-step procedure is used to develop study reporting limits and censor the GAMA-PBP dataset accordingly. The effect of the censoring at each step is described to provide information about the relative effect of each step on the overall censoring of the dataset. Steps 1 and 2 can be implemented at the time the data are received, whereas steps 3−5 require information accumulated over an extended period. Step 1: Reject results that were most likely the result of specific contamination instances attributable to unusual field or laboratory conditions during sample collection or processing. Two such instances were identified, leading to rejection of 25 detections, which were assigned a data-quality indicator code of “Q” for “reviewed and rejected” in the NWIS database. Step 2: Use the NWQL MDLs in effect at the time each sample was analyzed as the reporting limit. A total of 506 detections were censored on this basis. Step 3: Use the maximum MDL established by the NWQL during July 2004–August 2018 (MDLmax) as the reporting limit. The rationale for using the MDLmax as the reporting limit is based primarily on the observation that the concentrations of MDLs generally increased over time. A total of 438 detections were censored on this basis. Step 4: Use the LSBs to identify periods of greater potential laboratory contamination bias and define raised reporting limits to be used during those periods. These periods were defined by using a moving average detection frequency approach. For consistency with the NWQL procedures for defining raised reporting limits on the basis of detections in LSBs, the raised reporting limits were defined as equal to three times the highest concentration measured in an LSB during the period. A total of 25 detections in groundwater samples analyzed during periods of increased laboratory contamination bias were censored. Step 5: Use the LSBs and field blanks to identify potential contamination bias from field or laboratory processes outside of the time periods identified in step 4. The NWQL protocols were used to define the MDLs from blanks analyzed outside of the periods identified in step 4. If an MDL defined from blanks was greater than the MDLmax, the MDL defined from blanks was used to censor the data. One constituent had a study reporting limit defined on this basis, and a total of 62 detections in groundwater samples were censored. As of 2019, the USGS NWIS database does not have the capability to store both the original value reported by the NWQL and the final value published by the GAMA-PBP that reflects application of the quality-control censoring described in this report. In the interim, while this capability is developed, the 1,031 results censored in steps 2−5 are blocked from public release in NWIS, and the GAMA-PBP has published the original and final values in a USGS data release accompanying this report. The entire GAMA-PBP final dataset for pesticide constituents on schedules 2003, 2032, or 2033, or on schedule 2060 is publicly available in that USGS data release, through the USGS GAMA-PBP public web portal, and through the California State Water Resources Control Board GAMA public groundwater information system.

California↗

Precipitation-Runoff Simulations of Current and Natural Streamflow Conditions in the Methow River Basin, Washington

Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation, were simulated reasonably well yet possessed the most uncertainty. Simulations of annual mean streamflow as a percentage of measured annual mean streamflow for the 10-year calibration period at six of the seven streamflow-gaging stations ranged from -35.2 to +26.2 percent, with 65 percent of the simulated values within 15 percent. One station was intentionally calibrated to over-simulate discharge (simulated discharge greater than measured discharge) in order to compensate for observed channel losses not simulated by the model. Simulation of water years 1960-2001 demonstrated great variability in monthly streamflow statistics. The simulated mean monthly flows for 11 streamflow-gaging stations were an average of 2.5 percent higher for water years 1992-2001 than for the entire simulation period. If water year 2001, an extreme drought year, is omitted, simulated mean monthly flows for the 11 streamflow-gaging stations were an average of 9.0 percent higher than for the entire simulation period. The calibrated model also examined the effects of irrigation-canal seepage on streamflow. Irrigation-canal seepage contributed to streamflow throughout the year, with the greatest effect during the irrigation season. Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation

Water-Resources Investigations Report↗

Methods for estimating selected spring and fall low-flow frequency statistics for ungaged stream sites in Iowa, based on data through June 2014

A statewide study was led to develop regression equations for estimating three selected spring and three selected fall low-flow frequency statistics for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include spring (April through June) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and fall (October through December) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years. Estimates of the three selected spring statistics are provided for 241 U.S. Geological Survey continuous-record streamgages, and estimates of the three selected fall statistics are provided for 238 of these streamgages, using data through June 2014. Because only 9 years of fall streamflow record were available, three streamgages included in the development of the spring regression equations were not included in the development of the fall regression equations. Because of regulation, diversion, or urbanization, 30 of the 241 streamgages were not included in the development of the regression equations. The study area includes Iowa and adjacent areas within 50 miles of the Iowa border. Because trend analyses indicated statistically significant positive trends when considering the period of record for most of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. Geographic information system software was used to measure 63 selected basin characteristics for each of the 211streamgages used to develop the regional regression equations. The study area was divided into three low-flow regions that were defined in a previous study for the development of regional regression equations. Because several streamgages included in the development of regional regression equations have estimates of zero flow calculated from observed streamflow for selected spring and fall low-flow frequency statistics, the final equations for the three low-flow regions were developed using two types of regression analyses—left-censored and generalized-least-squares regression analyses. A total of 211 streamgages were included in the development of nine spring regression equations—three equations for each of the three low-flow regions. A total of 208 streamgages were included in the development of nine fall regression equations—three equations for each of the three low-flow regions. A censoring threshold was used to develop 15 left-censored regression equations to estimate the three fall low-flow frequency statistics for each of the three low-flow regions and to estimate the three spring low-flow frequency statistics for the southern and northwest regions. For the northeast region, generalized-least-squares regression was used to develop three equations to estimate the three spring low-flow frequency statistics. For the northeast region, average standard errors of prediction range from 32.4 to 48.4 percent for the spring equations and average standard errors of estimate range from 56.4 to 73.8 percent for the fall equations. For the northwest region, average standard errors of estimate range from 58.9 to 62.1 percent for the spring equations and from 83.2 to 109.4 percent for the fall equations. For the southern region, average standard errors of estimate range from 43.2 to 64.0 percent for the spring equations and from 78.1 to 78.7 percent for the fall equations. The regression equations are applicable only to stream sites in Iowa with low flows not substantially affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. The regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system application. StreamStats allows users to click on any ungaged stream site and compute estimates of the six selected spring and fall low-flow statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged site are provided. StreamStats also allows users to click on any Iowa streamgage to obtain computed estimates for the six selected spring and fall low-flow statistics.

Iowa↗

Irrigation-induced contamination of water, sediment, and biota in the western United States-synthesis of data from the National Irrigation Water Quality Program

In October 1985 the U.S. Department of the Interior (DOI), through the National Irrigation Water Quality Program (NIWQP), began a series of field investigations at 26 areas in the Western United States to determine whether irrigation drainage has had harmful effects on fish, wildlife, and humans or has reduced beneficial uses of water. In 1992 NIWQP initiated the Data Synthesis Project to evaluate data collected during the field investigations. Geologic, climatologic, and hydrologic data were evaluated and water, sediment, and biota from the 26 areas were analyzed to identify commonalities and dominant factors that result in irrigation-induced contamination of water and biota. Data collected for the 26 area investigations have been compiled and merged into a common data base. The structure of the data base is designed to enable assessment of relations between contaminant concentrations in water, sediment, and biota. The data base is available to the scientific community through the World Wide Web at URL http://www.usbr.gov/niwqp . Analysis of the data base for the Data Synthesis included use of summary statistics, factor analysis, and logistic regression. A Geographic Information System was used to store and analyze spatially oriented digital data such as land use, geology and evaporation rates. In the U.S. Department of the Interior (DOI) study areas, samples of water, bottom sediment, and biota were collected for trace-element and pesticide analysis. Contaminants most commonly associated with irrigation drainage were identified by comparing concentrations in water with established criteria. For surface water, the criteria used were typically chronic criteria for the protection of freshwater aquatic life. Because ground water can discharge to the surface where wildlife can be exposed to it, the criteria used for ground water were both the maximum contaminant levels (MCL's) for drinking water and the chronic criteria for the protection of freshwater aquatic life. Data collected by the NIWQP studies indicated that, in surface water, filtered and unfiltered samples had nearly the same concentrations of arsenic, boron, molybdenum, and selenium for concentrations greater than about 10 micrograms per liter. Therefore, in this concentration range, filtered concentrations can be directly compared to biological-effect levels developed for unfiltered samples. In the range of 1 to 10 micrograms per liter there may be a tendency for unfiltered arsenic concentrations to be greater than filtered concentrations. For selenium, however, the data suggest differences from equality in that range result from analytical imprecision and not a general tendency for unfiltered concentrations to be greater than filtered concentrations. This relation may not be true in lentic, nutrient-rich waters because in such settings algae can bioaccumulate large amounts of selenium and other trace elements. Selenium was the trace element in surface water that most commonly exceeded chronic criteria for the protection of freshwater aquatic life; more than 40 percent of the selenium concentrations in surface-water samples exceeded the U.S. Environmental Protection Agency (USEPA) aquatic-life chronic criterion (5 micrograms per liter). In 12 of the 26 areas at least 25 percent of the surface water-samples had selenium concentrations that either equaled or exceeded the chronic criterion (5 micrograms per liter). More than 28 percent of boron concentrations and almost 17 percent of the molybdenum concentrations exceeded the aquatic life criteria established by the State of California (550 and 19 micrograms per liter, respectively). In ground water, more than 22 percent of the arsenic concentrations and more than 35 percent of the selenium concentrations exceeded the MCL (10 and 50 micrograms per liter, respectively). Few samples of uranium in surface water exceeded a criterion for the protection of aquatic life (300 micrograms per liter), but 44 percent of the uranium concentrations in ground water exceeded the MCL (30 micrograms per liter). Molybdenum, selenium and uranium were the trace elements most commonly found in bottom-sediment samples that exceeded the upper limit of the 95th percentile expected range in soils of the Western United States. Selenium is the only trace element for which ecological sediment guidelines are used in this report. Selenium concentrations commonly exceeded the ecological sediment guideline of two micrograms per gram. DDT and its degradation products DDD and DDE were the most common pesticide residues found in surface water at concentrations exceeding criteria. However, almost all the samples exceeding the criteria were from a single study area, the Owyhee-Vale Reclamation Project areas in Oregon and Idaho. The organochlorine pesticide chlordane was detected in 30 percent of the bottom-sediment samples, and undegraded DDT was detected in 21 percent. DDT or its degradation products were detected in all 21 study areas where bottom-sediment samples were analyzed for organochlorine pesticides. A principal-components analysis indicated that elevated selenium concentrations in surface water are not associated with elevated boron, molybdenum, or arsenic concentrations. The occurrence of selenium is associated with sulfate and uranium. The association of boron and molybdenum with chloride suggests that evaporative processes control their concentrations. Arsenic is not associated with any other measured trace element and is associated negatively with selenium. This report focuses on selenium because it was the trace element most frequently found at concentrations exceeding criteria for the protection of aquatic life. Selenium concentrations in water are dynamic, and, at a given site, the selenium concentration can change by an order of magnitude during a year and from one year to another. In some areas, selenium contamination may not occur during normal or wet periods. However, during a drought, reduced water deliveries may result in selenium contamination by evaporative concentration. Marine sedimentary rocks, especially those of Late Cretaceous age, are likely to be seleniferous. Irrigation of soils derived from them can contribute large amounts of selenium to drainwater; shallow wells in and near irrigated areas contained hundreds to thousands of micrograms per liter of selenium. The median selenium concentration in surface-water samples from NIWQP sites associated with Upper Cretaceous marine sedimentary rocks is 7 micrograms per liter (range less than 1 to 8,300 micrograms per liter) and from sites not associated with such rocks is 0.4 micrograms per liter (range less than 1 to 390 micrograms per liter). Irrigation-induced selenium contamination has been observed only in arid or semiarid areas. In those NIWQP study areas having local geologic sources of selenium, typically more than 25 percent of the surface-water samples exceed the chronic criterion for selenium if the evaporation rate is 3.0 times greater than the annual precipitation. In terminal water bodies, selenium accumulates and is not flushed out. In both terminal and flow-through lakes and ponds, the median selenium concentrations in surface water for samples collected from June through August are nearly the same (1.0 and 0.8 micrograms per liter, respectively). However, the 75th-percentile selenium concentration for terminal water bodies (24 µg/L) is significantly higher than for flow-through systems (4 µg/L). Selenium concentrations in biota were compared with concentrations that have been demonstrated to have adverse effects on similar species (the effect level) or to have adverse effects on another species if consumed (the dietary effect level). Twenty-five percent of the plant samples had selenium concentrations exceeding the dietary effect level (3 micrograms per gram dry weight) whereas more than 57 percent of the invertebrate samples and 61 percent of the fish samples exceeded the dietary effect level. Of the more than 2,000 bird eggs collected, 44 percent had selenium concentrations exceeding 6 micrograms per gram, a threshold value for reduced hatchability. In 14 areas, selenium concentrations in eggs from some populations of birds exceeded 6 micrograms per gram. Selenium-caused deformities of bird embryos were found in four of the NIWQP study areas; however, most study areas were not systematically surveyed for such deformities. Eggs were sampled from 34 species of birds belonging to 10 orders. Nearly all the eggs collected come from aquatic species of birds, with American coots, mallards, and American avocets being the three species most frequently collected. Of the 34 species, at least one set of eggs from 16 species had a geometric-mean selenium concentration of at least 12.5 micrograms per gram, a high-risk threshold. All three species of grebes yielded at least one set of high risk eggs, as did four of five species of shorebirds and five of eleven species of waterfowl. Egg-set data were examined to determine if some feeding guilds are more at risk to selenium poisoning than others. Analysis of data for waterbird eggs from the study areas where the 75th percentile selenium concentration in surface water exceeded 5 µg/L suggests that herbivorous birds may bioaccumulate less selenium than insect- and fish-eating birds. For birds from these study areas, selenium concentrations for 39 percent of the egg sets from herbivorous birds fell in the normal range (less than 3 µg/g) while only 7 and 0 percent, respectively, of egg sets from insect- and fish-eating birds fall in the normal range. Although herbivorous birds may bioaccumulate less selenium, it does not appear that any waterbird feeding guilds are particularly well buffered from exposure to selenium contamination. Predictive tools were developed to aid managers in identifying specific land areas at risk for irrigation-induced selenium contamination. The tools range from identifying broad geographic regions where selenium contamination is likely, to assessing the probability that selenium concentrations in a specific stream or lake exceed the chronic criterion for selenium. A geographic information system was used to prepare a map that identifies land areas in the Western United States that are susceptible to selenium contamination if irrigated. On the basis of the 75th percentile, selenium concentration in surface water, 12 of the 26 NIWQP study areas were classified as contaminated, two as seleniferous, and 12 as uncontaminated. The map correctly identified both seleniferous areas and 10 of 12 selenium-contaminated areas as susceptible; 10 of 12 uncontaminated areas were correctly identified as not being susceptible. About 160,000 square miles are identified as being susceptible; of that area, about 4,100 square miles have been identified by satellite imagery as actively being irrigated. Principal-components analysis and pattern-recognition techniques indicate that major-ion chemistry of water samples alone can be used to identify selenium- and nonselenium-producing areas in the Western United States. Water samples composed of simple salts of sulfate typically have concentrations of selenium that exceed 3 µg/g, whereas samples composed of simple salts of chloride or carbonate typically have low selenium concentrations. Weathering of soils that contain reduced-sulfur minerals, such as pyrite, mobilizes sulfur and selenium because selenium commonly substitutes for sulfur in these minerals. In areas where the bedrock is composed of Upper Cretaceous marine sedimentary rocks, logistic regression of data from the NIWQP sites indicates that if the dissolved-solids concentration equals 1,000 milligrams per liter, the probability is about 69 percent that the selenium concentration will exceed 5 micrograms per liter, the U.S. Environmental Protection Agency chronic criterion. In areas where the bedrock is not composed of such rocks, the probability is only about 10 percent. The avian-egg data within the biotic data base were used to make a quantitative toxicological risk assessment. Of the 23 study areas where avian eggs were sampled, 14 areas yielded at least one egg containing 6 µg/g selenium, the threshold for embryotoxicity. However, only 6 of the study areas yielded eggs containing enough selenium to expect selenium-induced teratogenesis of duck embryos. Predicted probabilities of discovering embryo teratogenesis matched field observations in 13 of the 14 study areas reporting results of embryo assessments. Bird eggs were collected from 161 individual sampling sites and at 79 of those sites selenium concentrations in one or more eggs exceeded 6 µg/g. At the 79 sites where biological effects are expected on the basis of selenium concentrations in the eggs, the median rate was 3.9 percent of the hens losing at least one egg to selenium-induced embryotoxicity. This corresponds to about 1.2 percent selenium-induced egg inviability among otherwise viable eggs. Across all NIWQP study areas, the overall rate of hens projected to lose at least one egg to selenium-induced embryotoxicity is estimated to be 1.9 percent, which corresponds to about 0.3 percent selenium-induced egg inviability among otherwise viable eggs. After accounting for increased mortality of selenium poisoned-hatchlings due to other factors such as weather and predators, it was estimated that that increases of 0.3 and 1.2 percent in inviable eggs would cause approximately a 1.4 and 5.4 percent depression in nesting success. Regional surveys of nesting success among ducks revealed that duck populations commonly exist near their demographic break-even point. The vulnerable demographic condition of North American duck populations during the mid-1960's to mid-1980's was primarily due to noncontaminant factors, such as poor-quality nesting habitat and dry climatic cycles. Under such conditions, rates of 1.4- to 5.4-percent depression in nesting success caused by exposure to selenium from irrigation projects can be crucial for avian populations already close to their demographic break-even point. Even the worst-case levels of contaminant effects, however, could be tolerated by populations of ducks existing just modestly above demographic break-even points. This suggests the biotic risk to ducks could be addressed by reducing irrigation-induced water pollution but more effectively by restoring high-quality (more predator-safe) nesting habitat. An analysis at the nesting-site level was made of the relation between selenium content of water and bird eggs. Eggs from 93 bird populations were collected from nesting sites where the water sample collected during April-July contained less than 5 µg/L selenium. The average selenium concentration in egg sets was embryotoxic in 19 of the 93 populations. Of the populations collected at sites where the selenium in the water was less than 1 microgram per liter, only four of 54 populations contained embryotoxic concentrations. Eggs from 65 populations of birds were collected from nesting sites where selenium concentrations in water samples collected during April-July equaled or exceeded 5 µg/L, and 55 of those 65 populations contained embryotoxic concentrations of selenium in the eggs. An analysis at the study-area level was made of the relation between selenium contamination of water and selenium contamination of the food chain and egg loss due to selenium poisoning. Most food organisms, particularly aquatic invertebrates and fish, contained potentially harmful amounts of selenium in study areas where selenium concentrations in more than 25 percent of the water samples exceed 5 µg/L. The analysis also indicates that some hens are predicted to lose eggs to selenium poisoning in all study areas where selenium concentrations in more than 25 percent of the water samples exceed 5 µg/L. These results suggest that areas where selenium contamination of the food chain and loss of eggs to selenium poisoning is occurring may be identified using the same methods developed to identify areas where selenium contamination of water is likely to occur.

western United States↗

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

Scientific Investigations Report↗

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.

Florida↗

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗

Archive of digital boomer and CHIRP seismic reflection data collected during USGS field activity 08LCA03 in Lake Panasoffkee, Florida, May 2008

In May of 2008, the U.S. Geological Survey (USGS) conducted geophysical surveys in Lake Panasoffkee, located in central Florida, as part of the USGS Lakes and Coastal Aquifers (LCA) study. This report serves as an archive of unprocessed digital boomer and Compressed High Intensity Radar Pulse (CHIRP)* seismic reflection data, trackline maps, navigation files, Field Activity Collection System (FACS) logs, Geographic Information System (GIS) files, and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (a relative increase in signal amplitude) digital images of the seismic profiles and geospatially corrected interactive profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. *Due to poor data acquisition conditions associated with the lake bottom sediments, only two CHIRP tracklines were collected during this field activity. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are provided. The USGS Florida Integrated Science Center (FISC) - St. Petersburg assigns a unique identifier to each cruise or field activity. For example, 08LCA03 tells us the data were collected in 2008 for the Lakes and Coastal Aquifers (LCA) study and the data were collected during the third field activity for that study in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The naming convention used for each seismic line is as follows: yye##a, where 'yy' are the last two digits of the year in which the data were collected, 'e' is a 1-letter abbreviation for the equipment type (for example, b for boomer and c for CHIRP), '##' is a 2-digit number representing a specific track, and 'a' is a letter representing the section of a line if recording was prematurely terminated or rerun for quality or acquisition problems. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and, when discharged, emits a short acoustic pulse, or shot, which propagates through the water, sediment column, or rock beneath. The acoustic energy is reflected at density boundaries (such as the seafloor, sediment, or rock layers beneath the seafloor), detected by the receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2-D) vertical profile of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the boomer acquisition geometry. The EdgeTech SB-424 CHIRP system used for this survey has a vertical resolution of 4 - 8 cm, a penetration depth that is usually less than 2 m beneath the seafloor, and uses a signal of continuously varying frequency. The towfish is a sound source and receiver, which is typically towed 2 - 5 m above the seafloor. The acoustic energy is reflected at density boundaries (such as the seafloor or sediment layers beneath the seafloor), detected by a receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.125 s) and recorded for specific intervals of time (for example, 50 ms); the resulting profile is a two-dimensional vertical image of the shallow geologic structure beneath the ship track. Figure 2 displays the acquisition geometry for the CHIRP system. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics.

Florida↗

Land cover mapping of the National Park Service northwest Alaska management area using Landsat multispectral and thematic mapper satellite data

A land cover map of the National Park Service northwest Alaska management area was produced using digitally processed Landsat data. These and other environmental data were incorporated into a geographic information system to provide baseline information about the nature and extent of resources present in this northwest Alaskan environment. This report details the methodology, depicts vegetation profiles of the surrounding landscape, and describes the different vegetation types mapped. Portions of nine Landsat satellite (multispectral scanner and thematic mapper) scenes were used to produce a land cover map of the Cape Krusenstern National Monument and Noatak National Preserve and to update an existing land cover map of Kobuk Valley National Park Valley National Park. A Bayesian multivariate classifier was applied to the multispectral data sets, followed by the application of ancillary data (elevation, slope, aspect, soils, watersheds, and geology) to enhance the spectral separation of classes into more meaningful vegetation types. The resulting land cover map contains six major land cover categories (forest, shrub, herbaceous, sparse/barren, water, other) and 19 subclasses encompassing 7 million hectares. General narratives of the distribution of the subclasses throughout the project area are given along with vegetation profiles showing common relationships between topographic gradients and vegetation communities.

Open-File Report↗