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USGS1909

Surface water supply of the United States, 1907-8, Part II. South Atlantic Coast and eastern Gulf of Mexico

This volume contains results of flow measurements made on certain streams in the United States. The work was performed by the water-resources branch of the United States Geological Survey, either independently or in cooperation with organizations mentioned herein. These investigations are authorized by the organic law of the Geological Survey (Stat. L., vol. 20, p. 394)...

Water Supply Paper↗

USGS1910

Surface water supply of the United States, 1907-8, Part III. Ohio River Basin

Water Supply Paper↗

USGS1910

Surface water supply of the United States, 1907-8, Part IV. St. Lawrence River Basin

Water Supply Paper↗

USGS1990

Owls

Eight species of owls regularly occur and may breed in one or more of the southeastern states. Several additional northern or western species appear irregularly as accidentals or during years of southward incursions. In the Southeast, the most common and wide- spread owls are the common barn-owl, eastern screech-owl, great horned owl and barred owl; the most restricted is the burrowing owl. The long-eared, short-eared, and northern saw-whet owls are primarily winter visitors in this region, although small and very localized nesting populations of short-eared owls may occur in Virginia. Long-eared owls and northern saw-whet owls may occur in West Virginia and northern saw-whet owls may occur in the highlands of Tennessee and North Carolina. Several owls of the Southeast are Blue-listed as threatened, endangered, or of local concern, including the common barn-owl, eastern screech-owl, burrow'ing owl and short-eared owl. The nesting status of the long-eared owl and northern saw-whet owl are still poorly known. These two owls should be included on stat and regional lists of species of special concern. Important limiting factors for all owls of the Southeast include habitat loss and human related mortality. Management issues center on obtaining a data base useful in predicting the effects of current forest management practices on owl populations and encouraging use of forestry techniques that least impact owls. Research needs include initiating studies of all aspects of the life history and habitat relationships of each owl species.

Book chapter↗

USGS2000

Application of snow models to snow removal operations on the Going-to-the-Sun Road, Glacier National Park

Snow removal, and the attendant avalanche risk for road crews, is a major issue on mountain highways worldwide. The Going-to-the-Sun Road is the only road that crosses Glacier National Park, Montana. This 80-km highway ascends over 1200m along the wall of a glaciated basin and crosses the continental divide. The annual opening of the road is critical to the regional economy and there is public pressure to open the road as early as possible. Despite the 67-year history of snow removal activities, few stat on snow conditions at upper elevations were available to guide annual planning for the raod opening. We examined statistical relationships between the opening date and nearby SNOTEL data on snow water equivalence (WE) for 30 years. Early spring SWE (first Monday in April) accounted for only 33% of the variance in road opening dates. Because avalanche spotters, used to warn heavy equipment operators of danger, are ineffective during spring storms or low-visibility conditions, we incorporated the percentage of days with precipitation during plowing as a proxy for visibility. This improved the model's predictive power to 69%/ A mountain snow simulator (MTSNOW) was used to calculate the depth and density of snow at various points along the road and field data were collected for comparison. MTSNOW underestimated the observed snow conditions, in part because it does not yet account for wind redistribution of snow. The severe topography of the upper reaches of the road are subjected to extensive wind redistribution of snow as evidence by the formation of "The Big Drift" on the lee side of Logan Pass.

Montana↗

USGS2001

A spatially referenced regression model (SPARROW) for suspended sediment in streams of the Conterminous U.S.

Suspended sediment has long been recognized as an important contaminant affecting water resources. Besides its direct role in determining water clarity, bridge scour and reservoir storage, sediment serves as a vehicle for the transport of many binding contaminants, including nutrients, trace metals, semi-volatile organic compounds, a nd numerous pesticides (U.S. Environmental Protection Agency, 2000a). Recent efforts to addr ess water-quality concerns through the Total Maximum Daily Load (TMDL) process have iden tified sediment as the single most prevalent cause of impairment in the Nation’s streams a nd rivers (U.S. Environmental Protection Agency, 2000b). Moreover, sediment has been identified as a medium for the tran sport and sequestration of organic carbon, playing a potentia lly important role in understa nding sources and sinks in the global carbon budget (Stallard, 1998). A comprehensive understanding of sediment fate a nd transport is considered essential to the design and implementation of effective plans for sediment management (Osterkamp and others, 1998, U.S. General Accounting Office, 1990). An exte nsive literature addr essing the problem of quantifying sediment transport has produced a nu mber of methods for estimating its flux (see Cohn, 1995, and Robertson and Roerish, 1999, for us eful surveys). The accuracy of these methods is compromised by uncertainty in the concentration measurements and by the highly episodic nature of sediment movement, particul arly when the methods are applied to smaller basins. However, for annual or decadal flux es timates, the methods are generally reliable if calibrated with extended periods of data (Robertson and Roerish, 1999). A substantial literature also supports the Universal Soil Loss Equation (U SLE) (Soil Conservation Service, 1983), an engineering method for estimating sheet and rill erosion, although the empirical credentials of the USLE have recently been questioned (Tri mble and Crosson, 2000). Conversely, relatively little direct evidence is available concerning the fate of sediment. The common practice of quantifying sediment fate with a sediment deliv ery ratio, estimated from a simple empirical relation with upstream basin area, does not artic ulate the relative importance of individual storage sites within a basin (Wolman, 1977). Rates of sediment deposition in reservoirs and flood plains can be determined from empirical measurement s , but only a limited number of sites have been monitored, and net rates of deposition or loss from other potential sinks and sources is largely unknown (Stallard, 1998). In particular, little is known about how much sediment loss from fields ultimately makes its way to stream channels, and how much sediment is subsequently stored in or lost from th e streambed (Meade and Parker, 1985, Trimble and Crosson, 2000). This paper reports on recent progress made to a ddress empirically the question of sediment fate and transport on a national scale. The model pres ented here is based on the SPAtially Referenced Regression On Watershed attr ibutes (SPARROW) methodology, fi rst used to estimate the distribution of nutrients in str eams and rivers of the United Stat es, and subsequently shown to describe land and stream processes affecting the delivery of nutrients (Smith and others, 1997, Alexander and others, 2000, Preston and Brakeb ill, 1999). The model makes use of numerous spatial datasets, available at the national level, to explain long-term sediment water-quality conditions in major streams and rivers throughou t the United States. Sediment sources are identified using sediment erosion rates from the National Resources I nventory (NRI) (Natural Resources Conservation Service, 2000) and apportioned over the landscape according to 30- meter resolution land-use information from th e National Land Cover Data set (NLCD) (U.S. Geological Survey, 2000a). More than 76,000 reservoirs from the National Inventory of Dams (NID) (U.S. Army Corps of Engin eers, 1996) are identified as pot ential sediment sinks. Other, non-anthropogenic sources and sinks are identified using soil in formation from the State Soil Survey Geographic (STATSGO) data base (Schwarz and Alexander, 1995) and spatial coverages representing surficial rock t ype and vegetative cover. The SPA RROW model empirically relates these diverse spatial datasets to estimates of long-term, mean annual sediment flux computed from concentration and flow measurements co llected over the period 1985 -95 from more than 400 monitoring stations maintained by the Na tional Stream Quality Accounting Network (Alexander and others, 1998), the National Wa ter Quality Assessment Program, and U.S. Geological Survey District offices (Turcios and Gray, in press). Th e calibrated model is used to estimate sediment flux for over 60,000 stream segments included in the River Reach File 1 (RF1) stream network (Alexander and others, 1999). SPARROW uses statis tical methods to calibrate a simple, structural model of riverine water quality, one that imposes mass ba lance in accounting for changes in contaminant flux. As applied here, the mass-balance approach facilitates the interpretation of model results in terms of physical processes affecting sediment transport, and makes possible the estimation of various rates of sediment generation and loss associated with stream channels and features of the landscape. The statistical approach provides a basi s for assessing the error of these inferred rates and of the error in extrapolated estimates of sediment flux made for streams in the RF1 network. An important implication of the holistic modeling approach adopted in this analysis is that estimates of sediment production and loss ar e based on, and therefore consistent with, measurements of in-stream flux. Other ancillary information, such as direct measurements of long-term sediment storage and release from rese rvoirs (Steffen, 1996), is incorporated into the analysis by specifying additional equations expl aining these ancillary variables. The imposition of cross-equation constraints affords this info rmation a statistically consistent weight in explaining in-stream sediment flux. Thus, the me thodology described here represents a general framework for synthesizing a wide spectrum of available information relevant to the understanding of sediment fate and transport.

Conterminous United States↗

USGS2014

Connecting the dots: a collaborative USGS-NPS effort to expand the utility of monitoring data

The Natural Resource Challenge (National Park Service 1999) was a call to action. It constituted a mandate for monitoring based on the twin premises that (1) natural resources in national parks require active management and stewardship if we are to protect them from gradual degradation, and (2) we cannot protect what we do not understand. The intent of the challenge was embodied in its original description: We must expand existing inventory programs and develop efficient ways to monitor the vital signs of natural systems. We must enlist others in the scientific community to help, and also facilitate their inquiry. Managers must have and apply this information to preserve our natural resources. In this article, we report on ongoing collaborative work between the National Park Service (NPS) and the US Geological Survey (USGS) that seeks to add to our scientific understanding of the ecological processes operating behind vital signs monitoring data. The ultimate goal of this work is to provide insights that can facilitate an understanding of the systems and identify potential opportunities for active stewardship by NPS managers (Bennetts et al. 2007; Mitchell et al. 2014). The bulk of the work thus far has involved Acadia and Rocky Mountain national parks, but there are plans for extending the work to additional parks. Our story stats with work designed to consider ways of assessing the status and condition of natural resources and the potential for historical or ongoing influences of human activities. In the 1990s, the concept of "biotic integrity" began to take hold as an aspiration for developing quantitative indices describing how closely the conditions at a site resemble those found at pristine, unimpacted sites. Quantitative methods for developing indices of biotic integrity (IBIs) and elaborations of that idea (e.g., ecological integrity) have received considerable attention and application of these methods to natural resources has become widespread (Karr 1991; Barbour et al. 1999; Stoddard et al. 2008). Despite widespread use, many questions remain about how metrics are combined to form effective indices and about how to interpret both. Scientists and natural resource specialists within NPS and USGS have joined forces to critique the current analysis methods, with the collaboration involving the Rocky Mountain and Northeast Temperate NPS Inventory and Monitoring (I & M) networks, along with others, and USGS scientists from the National Wetlands Research Center and Patuxent Wildlife Research Center. Funding that initiated the project was from a joint-partnership fund managed by the USGS Ecosystems Program for National Park Monitoring research and the work was focused at Acadia National Park and Rocky Mountain National Park. Here we present synopses of two major issues addressed by the group.

The George Wright Forum↗

USGS1993

Wetland modeling and information needs at Stillwater National Wildlife Refuge

The marshes in and around Stillwater National Wildlife Refuge (the Refuge) are extremely dynamic; expanding and contracting in size both seasonally, due to runoff and subsequent evapotranspiration, and over longer periods, due to climatic variation. The dynamic nature of these marshes results in a diversity of wetland habitats, which support a variety of migratory birds. To maintain this wetland diversity and control the loss of migratory bird habitat in the Lahontan Valley, the Refuge was established and currently manages a complex of marsh units. However, changes in the hydrology, and changes that will occur as a result of the Fallon Paiute-Shoshone and Truckee-Carson-Pyramid Lake Water Rights Settlement Act (Public Law 101-618, 104 Stat. 3389), greatly affect the Refuge's wetland management capability. In light of these changes, and the legal requirements associated with environmental impact assessments, the Refuge convened a workshop to discuss several aspects of wetland management in the Lahontan Valley. The workshop, described in this report, had three primary objectives: 1. discuss the types and relative proportions of primary wetland habitats that should be provided as described in the settlement act; 2. discuss wetland management models that might be developed to help manage these marshes under hydrologic regimes likely in the future; and 3. discuss future information and monitoring needs, including proposals for valley-wide biodiversity surveys, which would be helpful when considering withdrawn Bureau of Reclamation (BR) lands for possible incorporation into the Refuge. Several presentations at the beginning of the workshop provided a common basis for discussing these objectives. Refuge staff provided background on the history and past management. The Nature Conservatory discussed their role in the settlement act, proposals for valley-wide biodiversity surveys, and results of a literature review for Stillwater Marsh and the Lahontan Valley (Nachlinger 1993). Kay Fowler provided an historical context of changes in vegetation and waterbird use of the marshes based on her ethnography of the local Paiute Indians (Fowler 1993). Finally, Bob Elston discussed a model that predicts archaeological sites based on environmental variables (Raven and Elston 1989). The workshop was organized by staff from the Refuge and facilitated by the authors of this report. Participants included Ron Anglin, Bill Henry, Anne Janik, Cliff Creger, Fred Paveglio, and Mary Jo Elpers of the U.S. Fish and Wildlife Service (the Service); Jeff Baumgartner, Jan Nachlinger, Hope Humphries, and Graham Chisholm of The Nature Conservancy; David Yardas of the Environmental Defense Fund; David Robertson of Robertson Software, Inc.; Norm Saake, Terry Retterer, and Larry Neel of the Nevada Department of Wildlife; Lew Oring and Kay Fowler of the University of Nevada; and Robert Elston of Intermountain Research.

Report↗

USGS1983

Earthquakes; July-August 1982

During this reporting period, there were three major (7.0-7.9) earthquakes all in unpopulated areas. The quakes occurred north of Macquarie Island on July 7, in the Santa Cruz Islands on August 5, and south of Panama on August 19. In the United Stats, a number of earthquakes occurred, but no damage was reported.

Earthquake Information Bulletin (USGS)↗

USGS2002

Introduction

The Arctic National Wildlife Refuge in northeastern Alaska is one of 16 refuges in Alaska and 539 refuges nationwide within the National Wildlife Refuge System administered by the U.S. Fish and Wildlife Service. First established as the Arctic National Wildlife Range in 1960 by Public Land Order 2214, it initially had a three-fold purpose to preserve unique wildlife, wilderness, and recreation values on 8.9 million acres. In 1980, the Arctic National Wildlife Range was expanded to the southwest and renamed the Arctic National Wildlife Refuge (also called the Arctic Refuge in this report) when the U.S. Congress passed the Alaska National Interest Lands Conservation Act (ANILCA), Public Law 96-487 (94 Stat. 2371). This legislation also designated almost all of the original Arctic National Wildlife Range as wilderness, and it directed the Secretary of the Interior to conduct studies evaluating both the biological resources and the potential petroleum reserves of 1.5 million acres (titled the 1002 Area) on the coastal plain of the Arctic Refuge. In April 1982, the Arctic Refuge staff completed a report summarizing the then current state of knowledge on the fish, wildlife, and their habitats present on the coastal plain of the Arctic Refuge (U.S. Fish and Wildlife Service 1982). From 1982 to 1985, field investigations of biological resources of the 1002 Area were carried out by a number of investigators, and annual reports summarized the results (Garner and Reynolds 1983, 1984, 1985, 1986, 1987). These reports and other resources were used to prepare a Department of the Interior report to Congress: Arctic National Wildlife Refuge, Alaska Coastal Plain Resource Assessment - Report and Recommendation to the Congress of the United States and Final Environmental Impact Satement (Clough et al., 1987).

Alaska, Northwest Territories, Yukon Territory↗

USGS2021

Appendix C: Central sands lakes study technical report: Modeling documentation

This report provides the necessary documentation of the numerical models developed for the Central Sands Lake study in central Wisconsin and will be included as a technical appendix in the report to the Wisconsin State Legislature by the Wisconsin Department of Natural Resources (WDNR) in response to 2017 Wisconsin Act 10. This legislation directed WDNR to determine whether existing and potential groundwater withdrawals are causing or are likely to cause significant reduction of mean seasonal water levels at Pleasant Lake, Long Lake, and Plainfield Lake (s. 281.34(7m)(2)(b), Wis. Stats.) in Waushara County, Wisconsin. To evaluate the potential hydrologic connection between groundwater withdrawals and the nearby study lakes, hydrologic models were created that focused on the lakes of interest and yet were large enough to cover a broad enough region to extend to the major hydrologic boundaries of the natural flow system. The areas near the lakes require finer-scale grid discretization (or spacing) to better represent the lakes and streams in the model, but also need to cover a large enough area to include the groundwater withdrawal locations that have the potential to cause reduction in water levels in the lakes. To accomplish these goals, three groundwater models were created: a regional model extending to major hydrologic boundaries; and two inset models, inheriting boundaries from the regional model but focused near the lakes. Each of the inset models, in turn, included a detailed area close to the lakes surrounded by an area at the same spatial scale as the regional model (Figure 1). To support WDNR in evaluating the connection between groundwater withdrawals and lake levels, a representative time period was required over which to compare land use with and without irrigated agriculture and for WDNR to evaluate potential lake stage and flux changes related to irrigated agriculture. WDNR chose the climate period of 1981-2018 to be representative of a typical period and provided two land use scenarios—one with no irrigated agriculture and one with assumed crop rotations similar to current conditions—to simulate with groundwater models to, then, compare lake responses with. As a result, simulations over this climate record are not intended to recreate the history of 1981-2018 because land use changed over that time. These runs are, instead, intended to provide a basis on which to compare land use with and without irrigation-related groundwater withdrawals based on the current arrangement of land use and a varied climatic record. Groundwater withdrawals focused on irrigated-agriculture-related water use because greater than 95% of groundwater withdrawal in the two inset models around the study lakes is for irrigated agriculture water use. The period of 2012-2018 was used for parameter estimation (synonymously referred to as “history matching”) for the groundwater models. This time period was chosen because it includes the most complete water use records to simulate groundwater withdrawals. History matching was performed using groundwater elevations, lake stages, and streamflow observations over the 2012-2018 time period and processed observations derived from those raw data. Climatic data were incorporated into the model using a soil-water balance approach. A soil water balance model was constructed at the scale of the regional groundwater model to both calculate recharge based on land use and climate, and in the long-term climate-period runs, to estimate water use required by irrigated agriculture to apply as well boundary conditions in the groundwater model in the absence of reported water use values over that period.

Wisconsin↗

USGS2025

A generalization error bound of physics-informed neural networks for ecological diffusion models

Ecological diffusion equations (EDEs) are partial differential equations (PDEs) that model spatiotemporal dynamics, often applied to wildlife diseases. Derived from ecological mechanisms, EDEs are useful for forecasting, inference, and decision-making, such as guiding surveillance strategies for wildlife diseases. Physics-informed neural networks (PINNs) offer a cutting-edge approach to approximating the solution of EDEs by constraining the loss function. PINNs have shown empirical success in forecasting and inference in wildlife disease problems. However, theoretical properties of PINNs in this context remain unexplored. In this paper, we derive a generalization error bound for PINNs applied to forward problems in EDEs, providing new crucial theoretical results for statistical analysis. Furthermore, we compare the performance of PINNs with commonly used numerical solvers, showing that PINNs achieve competitive accuracy while providing important modelling flexibility. Our results help connecting theory and application in EDE-based statistical models for ecological systems.

Stat↗