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At least 1,279 records · Page 71Linked to original sources

USGS2003

Characterization and statistical modeling of bacterial (Escherichia coli) outflows from watersheds that discharge into Southern Lake Michigan

Two watersheds in northwestern Indiana were selected for detailed monitoring of bacterially contaminated discharges (Escherichia coli) into Lake Michigan. A large watershed that drains an urbanized area with treatment plants that release raw sewage during storms discharges into Lake Michigan at the outlet of Burns Ditch. A small watershed drains part of the Great Marsh, a wetland complex that has been disrupted by ditching and limited residential development, at the outlet of Derby Ditch. Monitoring at the outlet of Burns Ditch in 1999 and 2000 indicated that E. coli concentrations vary over two orders of magnitude during storms. During one storm, sewage overflows caused concentrations to increase to more than 10,000 cfu/100 mL for several hours. Monitoring at Derby Ditch from 1997 to 2000 also indicated that E. coli concentrations increase during storms with the highest concentrations generally occurring during rising streamflow. Multiple regression analysis indicated that 60% of the variability in measured outflows of E. coli from Derby Ditch (n = 88) could be accounted for by a model that utilizes continuously measured rainfall, stream discharge, soil temperature and depth to water table in the Great Marsh. A similar analysis indicated that 90% of the variability in measured E. coli concentrations at the outlet of Burns Ditch (n = 43) during storms could be accounted for by a combination of continuously measured water-quality variables including nitrate and ammonium. These models, which utilize data that can be collected on a real-time basis, could form part of an Early Warning System for predicting beach closures.

Environmental Monitoring and Assessment↗

USGS2018

Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO 2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO 2 , precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO 2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO 2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ∼ 70 % relative to the baseline scenario, due to elevated CO 2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha −1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.

Greensboro Watershed, Tuckahoe Creek Watershed↗

USGS1999

Pesticides in stream sediment and aquatic biota: distribution, trends, and governing factors

More than 20 years after the ban of DDT and other organochlorine pesticides, pesticides continue to be detected in air, rain, soil, surface water, bed sediment, and aquatic and terrestrial biota throughout the world. Recent research suggests that low levels of some of these pesticides may have the potential to affect the development, reproduction, and behavior of fish and wildlife, and possibly humans. Pesticides in Stream Sediment and Aquatic Biota: Distribution, Trends, and Governing Factors assesses the occurrence and behavior of pesticides in bed sediment and aquatic biota-the two major compartments of the hydrologic system where organochlorine pesticides are most likely to accumulate. This book collects, for the first time, results from several hundred monitoring studies and field experiments, ranging in scope from individual sites to the entire nation. Comprehensive tables provide concise summaries of study locations, pesticides analyzed, and study outcomes. Comprehensive and extensively illustrated, Pesticides in Stream Sediment and Aquatic Biota: Distribution, Trends, and Governing Factors evaluates the sources, environmental fate, geographic distribution, and long-term trends of pesticides in bed sediment and aquatic biota. The book focuses on organochlorine pesticides, but also assesses the potential for currently used pesticides to be found in bed sediment and aquatic biota. Topics covered in depth include the effect of land use on pesticide occurrence, mechanisms of pesticide uptake and accumulation by aquatic biota, and the environmental significance of observed levels of pesticides in stream sediment and aquatic biota.

Book↗

USGS2023

Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA

Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or even thousands of landslide occurrences. This study evaluates strategies for training landslide forecasting models with a scanty record of landslide-triggering events, which is a typical limitation in remote, sparsely populated regions. We evaluate 136 statistical models trained on a precipitation dataset with five landslide-triggering precipitation events recorded near Sitka, Alaska, USA, as well as > 6000 d of non-triggering rainfall (2002–2020). We also conduct extensive statistical evaluation for three primary purposes: (1) to select the best-fitting models, (2) to evaluate performance of the preferred models, and (3) to select and evaluate warning thresholds. We use Akaike, Bayesian, and leave-one-out information criteria to compare the 136 models, which are trained on different cumulative precipitation variables at time intervals ranging from 1 h to 2 weeks, using both frequentist and Bayesian methods to estimate the daily probability and intensity of potential landslide occurrence (logistic regression and Poisson regression). We evaluate the best-fit models using leave-one-out validation as well as by testing a subset of the data. Despite this sparse landslide inventory, we find that probabilistic models can effectively distinguish days with landslides from days without slide activity. Our statistical analyses show that 3 h precipitation totals are the best predictor of elevated landslide hazard, and adding antecedent precipitation (days to weeks) did not improve model performance. This relatively short timescale of precipitation combined with the limited role of antecedent conditions likely reflects the rapid draining of porous colluvial soils on the very steep hillslopes around Sitka. Although frequentist and Bayesian inferences produce similar estimates of landslide hazard, they do have different implications for use and interpretation: frequentist models are familiar and easy to implement, but Bayesian models capture the rare-events problem more explicitly and allow for better understanding of parameter uncertainty given the available data. We use the resulting estimates of daily landslide probability to establish two decision boundaries that define three levels of warning. With these decision boundaries, the frequentist logistic regression model incorporates National Weather Service quantitative precipitation forecasts into a real-time landslide early warning “dashboard” system ( https://sitkalandslide.org/ , last access: 9 October 2023). This dashboard provides accessible and data-driven situational awareness for community members and emergency managers.

Alaska↗

USGS2019

Hillslope hydrology in global change research and earth system modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.

Water Resources Research↗

USGS2018

The natural capital accounting opportunity: Let's really do the numbers

The nation’s economic accounts provide objective, regular, and standardized information routinely relied upon by public and private decision makers. But they are incomplete. The U.S. and many other nations currently do not account for the natural capital — such as the wildlife, forests, grasslands, soils, and water bodies—upon which all other economic activity rests. By creating formal natural capital accounts (NCA) and ecosystem goods and services (EGS) accounts, governments and businesses can better understand the past, peer into the future, innovate, conserve, and plan for environmental shocks. They would standardize, regularly repeat, and aggregate diverse natural resource, environmental, and social and economic data and could thereby play a significant role in advancing the science of coupled biophysical and social systems.

BioScience↗

USGS1981

Hydrology of area 25, Eastern Region, Interior Coal Province, Illinois

The eastern region of the Interior Coal Province has been divided into 11 hydrologic study areas. Area 25, located in west-central Illinois, includes the Spoon River and small tributaries to the Illinois River. Pennsylvanian age rocks underlie most of the study area. Illinois, with the largest reserves of bituminous coal, is second only to Montana in total coal reserves. Loess soils cover most of the study area. Agriculture is the dominant land use. Surface water provides 97% of all the water used. Precipitation averages 34 to 35 inches. Water-quality data has been collected at over 31 sites. Analysis for specific conductance, pH, alkalinity, iron, manganese, sulfate and many trace elements and other water-quality constituents have been completed. These data are available from computer storage through the National Water Data Storage and Retrieval System (WATSTORE). (USGS)

Open-File Report↗

USGS1985

Calibration procedure for a daily flow model of small watersheds with snowmelt runoff in the Green River coal region of Colorado

A calibration procedure was developed for the U.S. Geological Survey 's Precipitation-Runoff Modeling System for watersheds in which snowmelt is the major contributor to runoff. The model uses daily values of air temperature and precipitation as input and the output is mean daily discharge. The procedure appears sufficient to calibrate both streamflow volume and the timing of mean daily discharge if other model parameters are reasonably estimated. Model structure and sensitivity analysis suggest that one of the most important parameters is the available water-holding capacity of the soil (SMAX). Changing this parameter through a series of iterations, the calibration procedure minimizes the error between observed and predicted annual discharge. The calibration suggests that the single parameter SMAX may be sufficient for optimizing both the volumes and the timing of runoff, assuming other model parameters are adequately estimated. Additional optimization on parameters sensitive to timing does not appear to improve prediction. This indicates that these parameters were estimated accurately prior to calibration. Further investigation is needed on more watersheds to determine SMAX 's ability to calibrate volume and timing with a constant set of other model parameter values.

Colorado↗

USGS2018

Developing hydro-meteorological thresholds for shallow landslide initiation and early warning

Consistent relations between shallow landslide initiation and associated rainfall characteristics remain difficult to identify, due largely to the complex hydrological and geological processes causing slopes to be predisposed to failure and those processes that subsequently trigger failures. Considering the importance of hillslope hydrology for rainfall-induced landsliding, we develop and test a method for identifying hybrid hydro-meteorological thresholds to assess landslide initiation potential. We outline a series of steps for using a landslide inventory in combination with triggering rainfall and antecedent wetness to identify empirical thresholds that can inform landslide early warning systems. The method is semi-automated but remains flexible enough to allow threshold developers to consider data inputs and various performance metrics with different priorities for balancing failed versus false alarms. We demonstrate the utility of our approach for two monitoring sites near Seattle, Washington and in Portland, Oregon, USA, to develop daily bilinear thresholds within a two-dimensional parameter space, which rely on accurate 24 h forecasts, measured recent rainfall and in situ soil saturation. Although there were no prior landslide thresholds for Portland, our new hybrid threshold for the Seattle area outperforms established rainfall-only thresholds for the same region. Introducing subsurface hydrologic monitoring into landslide initiation thresholds has the potential to greatly improve early warning capabilities and help reduce losses.

Oregon, Washington↗

USGS2000

Assessing habitat selection in Spring by male American Woodcock in Maine with a geographic information system

Geographic information system (GIS) technology was used to identify habitats available to and used by male American woodcock (Scolopax minor) equipped with radio transmitters--54 in 1987, 51 in 1988, 46 in 1989 at Moosehorn National Wildlife Refuge, Maine. Woodcock were monitored from time of capture (25 March-15 April) to 15 June each year. To determine habitat selection by male woodcock, the following habitat characteristics were measured: land cover, age and stocking density of the forest overstory, soil drainage and texture, aspect, and percent slope. Habitat selection was examined as affected by the covariates weather and age-class of woodcock, and among years for diurnal and crepuscular periods of the breeding period. Multivariate techniques that compare use and availability of habitats were not available, so a statistical model was developed to rate importance of multiple habitat characteristics selected by woodcock. The most critical period for woodcock in terms of survival was from arrival to: mid-April. Second-year and after-second-year woodcock did not select different (P > 0.05) habitat types, but they did select different types among years and within breeding intervals (P < 0.05). In years when weather was moderate, woodcock selected young, dense stands of speckled alder (Alnus rugosa) and hardwoods, interspersed with forest openings. Suitable habitat can be maintained by creating an uneven-aged forest managed in even-aged blocks composed of several hardwood species. Managers can now quantify suitable woodcock habitat in a GIS and plan large-scale forest-harvesting strategies using data on several habitat characteristics (e.g., land cover, stand age, stocking density, soil drainage and texture, and aspect).

Book chapter↗

USGS2014

Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington

Seasonally frozen ground occurs over approximately one‑third of the contiguous United States, causing increased winter runoff. Frozen ground generally rejects potential groundwater recharge. Nearly all recharge from precipitation in semi-arid regions such as the Columbia Plateau and the Snake River Plain in Idaho, Oregon, and Washington, occurs between October and March, when precipitation is most abundant and seasonally frozen ground is commonplace. The temporal and spatial distribution of frozen ground is expected to change as the climate warms. It is difficult to predict the distribution of frozen ground, however, because of the complex ways ground freezes and the way that snow cover thermally insulates soil, by keeping it frozen longer than it would be if it was not snow covered or, more commonly, keeping the soil thawed during freezing weather. A combination of satellite remote sensing and ground truth measurements was used with some success to investigate seasonally frozen ground at local to regional scales. The frozen-ground/snow-cover algorithm from the National Snow and Ice Data Center, combined with the 21-year record of passive microwave observations from the Special Sensor Microwave Imager onboard a Defense Meteorological Satellite Program satellite, provided a unique time series of frozen ground. Periodically repeating this methodology and analyzing for trends can be a means to monitor possible regional changes to frozen ground that could occur with a warming climate. The Precipitation-Runoff Modeling System watershed model constructed for the upper Crab Creek Basin in the Columbia Plateau and Reynolds Creek basin on the eastern side of the Snake River Plain simulated recharge and frozen ground for several future climate scenarios. Frozen ground was simulated with the Continuous Frozen Ground Index, which is influenced by air temperature and snow cover. Model simulation results showed a decreased occurrence of frozen ground that coincided with increased temperatures in the future climate scenarios. Snow cover decreased in the future climate scenarios coincident with the temperature increases. Although annual precipitation was greater in future climate scenarios, thereby increasing the amount of water available for recharge over current (baseline) simulations, actual evapotranspiration also increased and reduced the amount of water available for recharge over baseline simulations. The upper Crab Creek model shows no significant trend in the rates of recharge in future scenarios. In these scenarios, annual precipitation is greater than the baseline averages, offsetting the effects of greater evapotranspiration in future scenarios. In the Reynolds Creek Basin simulations, precipitation was held constant in future scenarios and recharge was reduced by 1.0 percent for simulations representing average conditions in 2040 and reduced by 4.3 percent for simulations representing average conditions in 2080. The focus of the results of future scenarios for the Reynolds Creek Basin was the spatial components of selected hydrologic variables for this 92 square mile mountainous basin with 3,600 feet of relief. Simulation results from the watershed model using the Continuous Frozen Ground Index provided a relative measure of change in frozen ground, but could not identify the within-soil processes that allow or reject available water to recharge aquifers. The model provided a means to estimate what might occur in the future under prescribed climate scenarios, but more detailed energy-balance models of frozen-ground hydrology are needed to accurately simulate recharge under seasonally frozen ground and provide a better understanding of how changes in climate may alter infiltration.

Idaho;Oregon;Washington↗

USGS2013

A spatial features register: Toward standardization of spatial features

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

Cartography and Geographic Information Systems↗

USGS2005

Occurrence of fecal-indicator bacteria and protocols for identification of fecal-contamination sources in selected reaches of the West Branch Brandywine Creek, Chester County, Pennsylvania

The presence of fecal-indicator bacteria indicates the potential presence of pathogens originating from the fecal matter of warm-blooded animals. These pathogens are responsible for numerous human diseases ranging from common diarrhea to meningitis and polio. The detection of fecal-indicator bacteria and interpretation of the resultant data are, therefore, of great importance to water-resource managers. Current (2005) techniques used to assess fecal contamination within the fluvial environment primarily assess samples collected from the water column, either as grab samples or as depth- and (or) width-integrated samples. However, current research indicates approximately 99 percent of all bacteria within nature exist as attached, or sessile, bacteria. Because of this condition, most current techniques for the detection of fecal contamination, which utilize bacteria, assess only about 1 percent of the total bacteria within the fluvial system and are, therefore, problematic. Evaluation of the environmental factors affecting the occurrence and distribution of bacteria within the fluvial system, as well as the evaluation and modification of alternative approaches that effectively quantify the larger population of sessile bacteria within fluvial sediments, will present water-resource managers with more effective tools to assess, prevent, and (or) eliminate sources of fecal contamination within pristine and impaired watersheds. Two stream reaches on the West Branch Brandywine Creek in the Coatesville, Pa., region were studied between September 2002 and August 2003. The effects of sediment particle size, climatic conditions, aquatic growth, environmental chemistry, impervious surfaces, sediment and soil filtration, and dams on observed bacteria concentrations were evaluated. Alternative approaches were assessed to better detect geographic sources of fecal contamination including the use of turbidity as a surrogate for bacteria, the modification and implementation of sandbag bacteria samplers, and the use of optical brighteners. For the purposes of this report, sources of bacteria were defined as geographic locations where elevated concentrations of bacteria are observed within, or expected to enter, the main branch of the West Branch Brandywine Creek. Biologic sources (for example, waterfowl) were noted where applicable; however, no specific study of biologic sources (such as bacterial source tracking) was conducted. Data indicated that specific bacterial populations within fluvial sediments could be related to specific particle-size ranges. This relation is likely the result of the reduced porosity and permeability associated with finer sediments and the ability of specific bacteria to tolerate particular environments. Escherichia coli (E. coli) showed a higher median concentration (2,160 colonies per gram of saturated sediment) in the 0.125 to 0.5-millimeter size range of natural sediments than in other ranges, and enterococcus bacteria showed a higher median concentration (61,830 colonies per gram of saturated sediment) in the 0.062 to 0.25-millimeter size range of natural sediments than in other ranges. There were insufficient data to assess the particle-size relation to fecal coliform bacteria and (or) fecal streptococcus bacteria. Climatic conditions were shown to affect bacteria concentrations in both the water column and fluvial sediments. Drought conditions in 2002 resulted in lower overall bacteria concentrations than the more typically wet year of 2003. E. coli concentrations in fluvial sediment along the Coatesville study reach in 2002 had a median concentration of 92 colonies per gram of saturated sediment; in 2003, the median concentration had risen to 4,752 colonies per gram of saturated sediment. Symbiotic relations between bacteria and aquatic growth were likely responsible for increased bacteria concentrations observed within an impoundment area on the Coatesville study reach. This reach showed evidence of elevated aquatic growth and sharp increases in E. coli concentrations from upstream to downstream through the impoundment area in both 2002 and 2003. In 2003, E. coli concentrations within the waters column increased from 940 colonies per 100 milliliters upstream to 6,000 colonies per 100 milliliters at the dam crest. Given that these bacteria likely resulted from natural bacterial regrowth, the use of E. coli as an indicator of fecal contamination was severely impaired. Variable environmental conditions along the West Branch Brandywine Creek made the common field-chemical parameters of specific conductance, temperature, pH, and dissolved oxygen ineffective and (or) impossible to use for the determination of inputs of fecal contamination. Extreme variations in chemical gradients commonly were related to the urban/industrial signature of the watershed. For example, during base-flow sampling in 2002, specific-conductance values exceeding 1,000 microsiemens per centimeter observed in effluent from a local steel mill. This effluent raised the specific conductance within the West Branch Brandywine from just above 200 microsiemens per centimeter upstream from the outfall to just below 500 microsiemens per centimeter downstream from the outfall. These chemical gradients also, likely, had an effect on the initial colonization of bacteria, the formation of biofilms, and the persistence of certain types of bacteria along the study reach. Data collected in 2003 indicated that nutrients increased during both base-flow and stormflow conditions along the Coatesville study reach. For example, during base-flow sampling in 2003, 20 pounds of phosphorus was shown to enter the West Branch Brandywine Creek along the Coatesville study reach. The largest contributors to this base-flow nutrient load were likely two wastewater-treatment facilities adjacent to the study reach. During stormflow sampling in 2003, 480 pounds of phosphorus was shown to enter the West Branch Brandywine Creek along the Coatesville study reach. Data, along with other research, indicated the largest contributor to this stormflow nutrient load was likely remobilized sediment originating from a large dam impoundment. These elevated nutrient concentrations were considered sufficient to promote accelerated aquatic growth along the reach. Data collected in 2003 showed that wastewater constituents entered the West Branch Brandywine Creek largely from urban storm-sewer systems. Samples from the primary storm sewer for the city of Coatesville had detections for 20 of 69 wastewater constituents. These constituents included both strong and weak indicators of fecal contamination and generally indicated the storm-sewer system along the Coatesville study reach was a likely source of fecal-indicator bacteria and fecal contamination under base-flow conditions. By comparison, 5 constituents were detected in samples from the upstream end of the reach, and 10 constituents were detected in samples from the downstream end of the reach. During stormflow, numbers of detections were similar along the entire length of the study reach-five in samples from the upstream end, eight in samples from the center of the reach, and seven in samples from the downstream end of the reach. These data indicate that point sources (such as culverts and pipes, septic systems, and wastewater-treatment facilities) are not likely the origin of bacteria contamination during stormflow. The bacteria concentrations observed during stormflow events probably result from remobilized sessile bacteria stored within fluvial sediments. In this case, these bacteria should not be considered indicators of current fecal contamination. Impervious surfaces were found to increase bacteria concentrations along the West Branch Brandywine Creek because contaminated runoff from impervious areas generally flows into, and is concentrated within, the confines of the local storm-sewer system. During 2002, storm-sewer outfalls draining impervious areas were associated with all major locations of elevated bacterial concentrations (greater than 1,200 colonies per gram of saturated sediment) in fluvial sediments. During 2003, wetter conditions and overall bacteria concentrations higher than in 2002 resulted in point sources of bacterial contamination becoming less pronounced; however, the storm-sewer system, draining adjacent impervious areas, was still observed to be the primary source of bacteria along the reach. Where stormwater and (or) other runoff from these areas was allowed to infiltrate and (or) flow through wetland and riparian buffers, bacteria concentrations were not observed to be elevated above background levels commonly observed throughout similar areas of the same reach. Two run-of-the-river dams along the Coatesville study reach were evaluated for their effects on observed bacterial concentrations. These dams were shown to have greater or lesser effects on bacterial concentrations depending on the size of the structure and the capacity of the structure to impede flows. The smaller upstream dam had an approximate height of 3 feet and showed little observed effect on measured turbidity values; these data indicated that the dam did not effectively impede the flow of water or sediment within the West Branch Brandywine Creek. Consequently, this small dam did not show any observed effect on bacterial concentrations either upstream or downstream of the structure. The larger dam, near the middle of the reach, had an approximate height of 20 feet and showed greater effects on both turbidity and bacteria concentrations. The capacity of the larger dam to impede flows, combined with nutrients entering the reach, resulted in increased biologic activity throughout the impoundment area. Within this larger impoundment, enterococcus bacteria populations were observed to decrease sharply and E. coli bacteria populations were observed to increase sharply as flow approached the dam crest. All bacteria levels were then observed to drop to background levels, in both the water column and fluvial sediment, immediately downstream from the dam crest. Additional study is required to determine the cause for this rapid die off. Turbidity was assessed as a potential surrogate for E. coli bacteria. Regression analysis indicated higher turbidity levels usually can indicate higher concentrations of bacteria (R2 = 0.67), but the relation was too sporadic on the West Branch Brandywine Creek to use turbidity as a surrogate for estimated bacteria concentrations. Evaluation of data from individual base-flow and stormflow events resulted in variable and generally poor statistical relations between E. coli bacteria and turbidity (R2 values ranged from 0.02 to 0.94). Sandbag samplers were used in 2003 to determine their suitability for the assessment of fecal contamination. Sandbag samplers rely on the ability of bacteria to attach to surfaces and use the larger sessile bacteria populations instead of the more commonly used planktonic bacteria populations. E. coli bacteria concentrations observed in the sandbag samplers, after 1 week in place, were similar to those found within natural sediments collected concurrently. Enterococcus bacteria concentrations within the same sandbag samplers were not similar, and were generally lower, than those observed within the natural sediments. This discrepancy was likely because sand within the samplers was sieved to a size that was likely too coarse for enterococcus bacteria to persist. Optical-brightener samplers were installed along with each sandbag sampler. Optical brighteners are additives used in common household detergents; therefore, detection of optical brighteners, along with elevated fecal-indicator bacteria concentrations, strongly indicates a link to humans. Positive results for optical brighteners were detected only at the outfalls of two sewage-treatment facilities; because of treatment of the effluent from these facilities, these samples did not have elevated bacteria concentrations. The lack of additional positive results was largely because this method is not sensitive to low concentrations of optical brighteners.

Pennsylvania↗

USGS1991

Seismic response of transamerical building. I. Data and preliminary analysis

The objective of this paper is to present preliminary analyses of a set of acceleration response records obtained during the October 17, 1989 Loma Prieta earthquake (Ms = 7.1) from the 60-story vertically tapered, pyramid-shaped Trans-america Building-a landmark of San Francisco. The building was instrumented in 1985 with 22 channels of synchronized sensors consisting of 13 uniaxial accelerometers deployed throughout the structure and connected to a central recording system and three triaxial strong-motion accelerographs at three different levels of the structure. No free-field accelerographs are at the site. The acceleration records permit the study of the behavior of this unique structure. The predominant translational response of the building and the associated frequency at approximately 0.28 Hz are identified from the records and their Fourier amplitude spectra. The records do not indicate any significant torsional motion. However, there is rocking type soil-structure interaction, and an associated frequency of approximately 2.0 Hz is identified from the Fourier amplitude spectra of the differential motions between the ground level and that at the basement. In addition, the response spectra for the basement motions indicate significant resonance in both directions at a period of approximately 0.5 seconds.

Journal of Structural Engineering↗

USGS2020

Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico

Landslides in Puerto Rico range from nuisances to deadly events. Centuries of agricultural and urban modification of the landscape have perturbed many already unstable hillsides on the tropical island. One of the main triggers of mass wasting on the island is the high-intensity rainfall that is associated with tropical atmospheric systems. Puerto Rico’s geographic position and rugged topography render millions of residents vulnerable to widespread landslide events. In this study, a high-resolution (5 meters), high-intensity rainfall-induced landslide susceptibility model was produced using the frequency-ratio method. Datasets utilized in the model included a complete-island landslide inventory created from imagery obtained after Hurricanes Irma and María impacted the island during September 2017, slope inclination, land-surface curvature, soil type, geologic terrane, mean annual precipitation, land use, soil moisture, and distance to roadways and streams. The final data product (plate 1) is a statistically viable representation of where landslides are likely to initiate during or soon after intense rainfall, with a robust receiver operating characteristic area-under-curve value of 0.87. The model output raster pixel values were binned into 100 equal-area quantiles and then classified into Low, Moderate, High, Very High, and Extremely High classes of susceptibility. The Extremely High susceptibility classification represents the most vulnerable 1 percent of the island, whereas Very High, High, Moderate, and Low classifications cover 9, 20, 30, and 40 percent of the island, respectively. The susceptibility map is intended to assist in planning future development, mitigation measures, and post-event emergency response; however, it is not a substitute for site-specific, slope-stability assessments performed by licensed geologists and engineers. Additionally, the map does not portray locations where landslide material may travel after mobilization, and which may be at extreme risk; nor does it necessarily portray where landslides may occur during earthquakes or mass wasting triggered by prolonged, relatively low-intensity rainfall.

Puerto Rico↗

USGS2014

Dendroclimatic potential of plains cottonwood (Populus deltoides subsp. monilifera) from the Northern Great Plains, USA

A new 368-year tree-ring chronology (A.D. 1643–2010) has been developed in western North Dakota using plains cottonwood ( Populus deltoides subsp. monilifera ) growing on the relatively undisturbed floodplain of the Little Missouri River in the North Unit of Theodore Roosevelt National Park. We document many slow-growing living trees between 150–370 years old that contradict the common understanding that cottonwoods grow fast and die young. In this northern location, cottonwood produces distinct annual rings with dramatic interannual variability that strongly crossdate. The detrended tree-ring chronology is significantly positively correlated with local growing season precipitation and soil moisture conditions (r = 0.69). This time series shows periods of prolonged low radial tree growth during the known droughts of the instrumental record ( e.g. 1931–1939 and 1980–1981) and also during prehistory ( e.g. 1816–1823 and 1856–1865) when other paleoclimate studies have documented droughts in this region. Tree rings of cottonwood will be a useful tool to help reconstruct climate, streamflow, and the floodplain history of the Little Missouri River and other northern river systems.

North Dakota↗

USGS2021

Simulation of dissolved organic carbon flux in the Penobscot Watershed, Maine

Dissolved organic carbon (DOC) is an important component of the carbon cycle as a measure of the hydrological transport of carbon between terrestrial carbon pools into soil pools and eventually into streams. As a result, changes in DOC in rivers and streams may indicate alterations in the storage of terrestrial carbon. Exploring the complex interactions between biogeochemical cycling and hydrologic processes, as well as the micro-climate variabilities that impact the rate of DOC fluxes, are challenging because the information is not readily available from in-situ measurements or from empirical models alone. This is particularly true of large-scale watersheds. The Penobscot Watershed is the largest watershed of the Gulf of Maine and the second largest in New England. Its typical soils, with high organic matter and a large forested and wetland landscape, result in higher DOC fluxes than what has been observed previously for most rivers in the northern temperate or boreal zones (Hope et al., 1994; Mulholland, 1997; Aitkenhead and McDowell, 2000). In this study, we emphasized the simulation of streamflow and DOC fluxes from the Penobscot Watershed (and several tributaries within the Penobscot Watershed) using the spatially distributed process-based Regional Hydro-Ecological Simulation System (RHESSys) model. Simulated results were evaluated using field measurements (streamflow, DOC fluxes) and remotely sensed products (Net Primary Production (NPP) and Leaf Area Index (LAI) from Moderate Resolution Imaging Spectroradiometer (MODIS). The average DOC flux for the Penobscot Watershed during 2004-2012 using the RHESSys model was 69 kg C/ha/year. The RHESSys simulated DOC flux is shown to correlate well with observed values, as well as with results previously reported from the empirical Load Estimator (LOADEST) model (71 kg C/ha/year) for 2004-2007 ( Huntington and Aiken, 2013). Our simulated results also show a temporal variation in the amount of DOC flux, indicating that the antecedent DOC concentration from one year can impact the DOC export in following years. Thus, DOC concentration is positively correlated with streamflow and antecedent precipitation, in agreement with previous studies (Ågren et al., 2010; Huntington and Aiken, 2013; Tian et al., 2013 ). The successful application of the rigorous RHESSys model in the Penobscot Watershed makes it a reasonable platform to test future scenarios impacting the hydrology and biogeochemistry within similar large complex watersheds.

Maine↗

USGS2008

Uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in terrestrial ecosystems

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. For example, most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with the same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and their estimates may be incomplete for model initialisation, calibration, validation and sensitivity analysis of generalised predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from site to landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision processes in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.

Book chapter↗