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USGS2015

2013 Survey of Iowa groundwater and evaluation of public well vulnerability classifications for contaminants of emerging concern

Studies in Iowa have long documented the vulnerability of wells with less than 50 feet (15 meters) of confining materials above the source aquifer to contamination from nitrate and various pesticides. Recent studies in Wisconsin have documented the occurrence of viruses in untreated groundwater, even in wells considered to have little vulnerability to contamination from near-surface activities. In addition, sensitive methods have become available for analyses of pharmaceuticals and pesticides. This study represents the first comprehensive examination of contaminants of emerging concern in Iowa’s groundwater conducted to date, and one of the first conducted in the United States. Raw groundwater samples were collected from 66 public supply wells during the spring of 2013, when the state was recovering from drought conditions. Samples were analyzed for 206 chemical and biological parameters; including 20 general water-quality parameters and major ions, 19 metals, 5 nutrients, 10 virus groups, 3 species of pathogenic bacteria, 5 microbial indicators, 108 pharmaceuticals, 35 pesticides and pesticide degradates, and tritium. The wells chosen for this study represent a diverse range of ages, depths, confining material thicknesses, pumping rates, and land use settings. The most commonly detected contaminant group was pesticide compounds, which were present in 41% of the samples. As many as 6 pesticide compounds were found together in a sample, most of which were chloroacetanilide degradates. While none of the measured concentrations of pesticide compounds exceeded current benchmark levels, several of these compounds are listed on the U.S. Environmental Protection Agency’s Contaminant Candidate List and could be subject to drinking water standards in the future. Despite heavy use in the past decade, glyphosate was not detected, and its metabolite, aminomethylphosphonic acid, was only detected in two of 60 wells tested (3%) at the detection limit of 0.02 μg/L. Pharmaceutical compounds were detected in 35% of 63 samples. Of the 14 pharmaceuticals detected, six had reported concentrations above the method reporting limit, with the maximum reported concentration of 826 ng/L for acetaminophen. Diphenhydramine was the only pharmaceutical to have two detections above the reporting limit, at 24.5 and 145 ng/L. Eight pharmaceuticals had confirmed detections at concentrations below the method reporting limit. Caffeine was the most frequently detected pharmaceutical compound (25%), followed by the caffeine metabolite, 1,7- dimethylxanthine (16%). Microorganisms were detected in 21% of the wells using quantitative polymerase chain reaction methodologies. The most frequently detected microorganism was the pepper mild mottle virus (PMMV), a plant pathogen found in human waste. PMMV was detected in 17% of samples at concentrations ranging from 0.4 to 6.38 gene copies per liter. GII norovirus, human polyomavirus, bovine polyomavirus, and Campylobacter were also detected, while adenovirus, enterovirus, GI norovirus, swine hepatitis E, Salmonella, and enterohemmorhagic E. coli were not detected. No correlations were found between viruses or pathogenic bacteria and microbial indicators. Wells with less than 50 feet (15 meters) of confining material were shown to have greater incidence of surface-related contaminants; however, significant relationships (p<0.05) between confining layer thickness and contaminants were only found for nitrate and herbicides.

Iowa↗

USGS2014

Low-flow characteristics of streams in the Lahaina District, West Maui, Hawai'i

The purpose of this study was to characterize streamflow availability under natural low-flow conditions for streams in the Lahaina District, west Maui, Hawaiʻi. The study-area streams included Honolua Stream and tributary Pāpua Gulch, Honokahua Stream and tributary Mokupeʻa Gulch, Kahana Stream, Honokōwai Stream and tributaries Amalu and Kapāloa Streams, Wahikuli Gulch and tributary Hāhākea Gulch, Kahoma Stream and tributary Kanahā Stream, Kauaʻula Stream, Launiupoko Stream, Olowalu Stream, and Ukumehame Gulch. The results of this study can be used to assist in the determination of technically defensible instream-flow standards for the study-area streams. Low-flow characteristics for natural (unregulated) streamflow conditions were represented by flow-duration discharges that are equaled or exceeded between 50 and 95 percent of the time. Partial-record sites were established on 10 main streams and 5 tributary streams, mainly upstream from existing surface-water diversions. Flow characteristics were determined using historical and current streamflow data from continuous-record streamflow-gaging stations and miscellaneous sites, and additional data collected as part of this study. Based on strategically scheduled observations, six of the study-area streams were ephemeral streams that were observed to remain dry at least 50 percent of the time: Pāpua Gulch, Honokahua Stream and its tributary Mokupeʻa Gulch, Kahana Stream, and Wahikuli Gulch and its tributary Hāhākea Gulch. For the remaining streams with measurable flow, Honolua, Honokōwai, Kahoma, Kanahā, Kauaʻula, Launiupoko, and Olowalu Streams, and Ukumehame Gulch, flow-duration discharges were computed for the 30-year base period (water years 1984–2013), using two record-augmentation techniques. The 95-percent flow-duration discharges ranged from 0 to 4.8 cubic feet per second (ft 3 /s). The 50-percent flow-duration discharges ranged from 0.47 to 9.5 ft 3 /s. This study also estimated the streamflow gains and losses downstream of surface-water diversions using seepage-run measurements. A majority of the streams lost flow downstream from diversions. Measured seepage-loss rates ranged between 0.045 and 1.6 ft3/s per mile of stream reach. Seepage gains mostly occurred upstream from diversions and the measured seepage-gain rates generally ranged between 0.75 and 5.1 ft3/s per mile of stream reach. Under natural-flow conditions, Honolua Stream is estimated to flow to the ocean less than 80 percent of the time and Honokōwai Stream is estimated to flow to the ocean less than 50 percent of the time. Kahoma Stream, Kauaʻula Stream, Olowalu Stream, and Ukumehame Gulch are estimated to flow to the ocean at least 95 percent of the time.

Hawai'i↗

USGS2015

Avian disease and mosquito vectors in the Kahuku unit of Hawai`i Volcanoes National Park and Ka`u Forest Reserve

While avian disease has been well-studied in windward forests of Hawai‘i Island, there have been few studies in leeward Ka‘u. We surveyed four altitudinal sites ranging from 1,200 to 2,200 m asl in the Kahuku Unit of Hawai‘i Volcanoes National Park (Kahuku) and three altitudinal sites ranging from 1,200 to 1,500 m asl in the Ka‘u Forest Reserve (Ka‘u) for the prevalence of avian disease and presence of mosquitoes. We collected blood samples from native and non-native forest birds and screened for avian malaria (Plasmodium relictum) using PCR diagnostics. We examined birds for signs of avian pox (Avipoxvirus sp.), knemidokoptic mange (Knemidokoptes jamaicensis) and feather ectoparasites. We also trapped adult mosquitoes (Culex quinquefasciatus and Aedes japonicus japonicus) and surveyed for available larval habitat. Between September, 2012 and October, 2014, we completed 3,219 hours of mist-netting in Kahuku capturing 515 forest birds and 3,103 hours of mist-netting in Ka‘u capturing 270 forest birds. We screened 750 blood samples for avian malaria. Prevalence of avian malaria in all species was higher in Ka‘u than Kahuku when all sites were combined for each tract. Prevalence of avian malaria in resident Hawai‘i ‘amakihi (Chlorodrepanis virens) was greatest at the lowest elevation sites in Kahuku (26%; 1,201 m asl) and Ka‘u (42%; 1,178 m asl) and in general, prevalence decreased with increasing elevation and geographically from east to west. Significantly higher prevalence was seen in Ka‘u at comparable low and mid elevation sites but not at comparable high elevation sites. The overall presumptive pox prevalence was 1.7% (13/785) for both tracts, and it was higher in native birds than non-native birds, but it was not significant. Presumptive knemidokoptic mange was detected at two sites in lower elevation Kahuku, with prevalence ranging from 2‒4%. The overall prevalence of ectoparasites (Analges and Proctophyllodes spp.) was 6.7% (53/785). The site with the highest prevalence was Lower Glover in Kahuku (7.2%; 10/138) and Maka‘alia in Ka‘u. In general, mosquito larval habitat was more prevalent at lower elevation sites than higher elevation sites within the Kahuku—Ka‘u landscape, and more prevalent in Ka‘u than Kahuku. We observed significantly more available larval mosquito habitat in total belt transect plots in Ka‘u than Kahuku for both hapu‘u cavities (Χ2 = 47.06, df = 1, p < 0.01) and other habitat types combined (i.e., ground pools, rock holes, tree holes) (Χ2 = 104.35, df = 1, p < 0.01). Mosquitoes were most abundant at low elevation Kahuku, but were captured at all sites up to 1,532 m asl in Kahuku. The malarial infection rate of live mosquitoes was 21% (39/186) at Kahuku and 25% (2/8) at Ka‘u. There were 19 times more larval habitats available in Ka‘u than Kahuku on survey transects, yet we captured 53 times more C. quinquefasciatus mosquitoes in Kahuku. We captured very few adult A. j. japonicus across the landscape (Ntotal = 6) and no Aedes albopictus were detected in this study. Larval surveys along ranch roads and infrastructure revealed that ground pools along rutted, overgrown ranch roads were the likely source of Kahuku mosquitoes. We did not find mosquito larvae associated with ranching infrastructure. Unlike the low elevation forests on windward Hawai‘i Island, avian malaria prevalence, mosquito abundance, and the density of available larval habitat in Kahuku and Ka‘u were relatively low. Although altitudinal variations in climate appear to be the primary factors limiting the distribution of avian disease, habitat type, avian movements, human activity, and feral pig (Sus scrofa) management all may play important roles in determining the prevalence of avian malaria across the Kahuku—Ka‘u landscape.

Hawaii↗

USGS2013

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA. Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA. A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha. Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent. A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval. The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.

Natural Resource Technical Report↗

USGS2021

Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators

The impacts of wind power development on bat and bird populations are commonly assessed by estimating the number of fatalities at wind power facilities through post-construction monitoring (PCM) studies. Standard methodology involves periodic carcass searches on plots beneath turbines (Strickland et al. 2011, US Fish and Wildlife Service 2012). The resulting counts are adjusted to compensate for bias due to imperfect carcass detection by searchers, removal of carcasses by scavengers or other processes (Korner-Nievergelt et al. 2011), and carcasses that may have fallen outside of searched areas. To account for the bias in counts due to imperfect detection and carcass removal, investigators typically conduct bias trial experiments to inform models of carcass detection probability. Many different estimators have been proposed that combine information about the bias trial experiments to estimate a detection probability for carcasses (g) and ultimately obtain an estimate of total mortality (M). The two estimators that have seen the most widespread use in North America recently are the Huso (Huso 2011, Huso et al. 2012) and Shoenfeld (Shoenfeld 2004; also called the Erickson estimator) estimators. GenEst (Dalthorp et al. 2018a, 2018b, 2018c) is the newest statistical estimator to become available and was designed to improve upon the Huso and Shoenfeld estimators by generalizing the key assumptions in both, and to improve comparability among new PCM studies. In addition to relaxing some of the assumptions inherent to the Huso and Shoenfeld estimators, GenEst uses a parametric bootstrap applied to a novel approach to variance estimation (Madsen et al. 2019). The current study was undertaken to document the performance of GenEst relative to the Huso and Shoenfeld estimators. We took a simulation approach to the study because simulation data provides the basis to compare mortality estimators under conditions where the “truth” is known. The estimators were compared on three metrics: 1) bias—the tendency of an estimator to over- or under-estimate actual mortality, 2) precision—the ability of an estimator to constrain an estimate to a narrow range (measured here as the width of a 90% confidence interval [CI] around the point estimate divided by the true, known mortality), and 3) CI coverage—the probability a CI with a specified level of confidence actually includes the true level of mortality. Although our simulations were conceived and designed—and are discussed—with respect to wind power facilities, it is important to note that the estimators and results discussed here are relevant to any post-construction fatality monitoring study that may occur (such as at solar facilities) where detection is imperfect. Although our study treats the problem of mortality estimation when detection is imperfect, it is also important to note that all of the estimators considered here are Horvitz-Thompson (Horvitz and Thompson 1952) style estimators, that is, none are designed to estimate the mortality of rare species as might be necessary under an Incidental Take Permit. The Evidence of Absence estimator (Dalthorp et al. 2017) is still the most appropriate statistical tool for rare event estimation. The simulations cover a broad range of conditions that may occur in field studies and complete results are presented without commentary in the appendix. The main body of this report does not provide a comprehensive treatment of our results; rather, we try to identify some of the more important differences among the estimators and some conditions under which reliable mortality estimates are especially challenging.

AWWI Technical Report↗

USGS1997

Detection of underground voids in Ohio by use of geophysical methods

Geophysical methods are generally classified as electrical, potential field, and seismic methods. Each method type relies on contrasts of physical properties in the subsurface. Forward models based on the physical properties of air- and water-filled voids within common geologic materials indicate that several geophysical methods are technically feasible for detection of subsurface voids in Ohio, but ease of use and interpretation varies widely between the methods. Ground-penetrating radar is the most rapid and cost-effective method for collection of subsurface data in areas associated with voids under roadways. Electrical resistivity, gravity, or seismic reflection methods have applications for direct delineation of voids, but data-collection and analytical procedures are more time consuming. Electrical resistivity, electromagnetic, or magnetic methods may be useful in locating areas where conductive material, such as rail lines, are present in abandoned underground coal mines. Other electrical methods include spontaneous potential and very low frequency (VLF); these latter two methods are considered unlikely candidates for locating underground voids in Ohio. Results of ground-penetrating radar surveys at three highway sites indicate that subsurface penetration varies widely with geologic material type and amount of cultural interference. Two highway sites were chosen over abandoned underground coal mines in eastern Ohio. A third site in western Ohio was chosen in an area known to be underlain by naturally occurring voids in lime stone. Ground-penetrating radar surveys at Interstate 470, in Belmont County, Ohio, indicate subsurface penetration of less than 15 feet over a mined coal seam that was known to vary in depth from 0 to 40 feet. Although no direct observations of voids were made, anomalous areas that may be related to collapse structures above voids were indicated. Cultural interference dominated the radar records at Interstate 70, Guernsey County, Ohio, where coal was mined under the site at a depth of about 50 feet. Interference from overhead powerlines, the field vehicle, and guardrails complicated an interpretation of the radar records where the depth of penetration was estimated to be less than 5 feet. Along State Route 33, in Logan County, Ohio, bedding planes and structures possibly associated with dissolution of limestone were profiled with ground-penetrating radar. Depth of penetration was estimated to be greater than 50 feet.

Water-Resources Investigations Report↗

USGS1998

Health evaluation of pronghorns (Antilocapra americana) on Hart Mountain National Antelope Refuge in southeastern Oregon, 1996-1997.

One hundred four neonatal (fawns) and 40 adult female (does) pronghorn antelope (pronghorns) ( Antilocapra americana ) were captured on the Hart Mountain National Antelope Refuge (HMNAR) in Lake County, southeastern Oregon, between 13 May 1996 and 26 May 1997. Blood and fecal samples were taken for an investigation of low fawn survival that may be due to disease and/or poor nutrition. No abnormalities were found in hematological parameters of adult does (n = 40) or fawns (n = 44 to 67). In general, there were lower serum total proteins (TP) and Blood Urea Nitrogen (BUN) concentrations in this population than in other populations from Alberta, Canada; Idaho; and Baker City, Oregon. Mean BUN values in does were significantly lower (p < 0.001) in December than March. The duration of this apparently low protein content of the December diet may affect the weight of the newborn and consequent survivability if it should continue into late gestation (March-May). Serum copper (Cu) levels in does (range 0.39 to 0.74 ppm) were considered marginal when compared to domestic animals and some wild ungulates. Fawns had low but apparently normal Cu levels at birth and reached the does' marginal values in about three days. Whole blood and serum Selenium (Se) levels (<100 ng/ml) were considered to be marginal to low in most segments of the pronghorn population in this study. However, serum levels of vitamin E (range 1.98 - 3.27 pg/ml), as determined from the does captured in March, are apparently sufficient to offset any signs of deficiency due to low Se levels. No clinical signs of Cu or Se deficiency were observed. Does captured in December 1996 were tested for neutralizing antibodies to Brucella spp. (n = 20, neg.), Leptospira spp. (n = 20, neg.), bluetongue virus (n = 20, 35% pos.), epizootic hemorrhagic disease virus (n = 20, 30% pos.), respiratory syncytial virus (n = 18, neg.), parainfluenza virus type 3 (n = 18, 67% pos.), infectious bovine rhinotracheitis (n = 18, neg.), and bovine viral diarrhea (n = 18, neg.). Seventeen fawns (9F,8M), nine in 1996 and eight in 1997, survived until at least mid-July each year. Fifty-five of 87 dead fawns were necropsied. Predation by coyotes (Canis latrans) accounted for the majority of fawn mortality (62%), as determined by necropsy, during the two combined summer periods. Other causes of mortality for the combined years included predation by eagle (4%), dystocia (2%), septicemic pasteurellosis (5%), starvation/weak fawn syndrome

Oregon↗

USGS2007

Geophysical analysis of the Salmon Peak Formation near Amistad Reservoir Dam, Val Verde County, Texas, and Coahuila, Mexico, March 2006, to aid in piezometer placement

Since 1992, numerous sinkholes have developed northwest of the Amistad Reservoir dam on the Rio Grande. Increases in the discharge of springs south of the dam, on the western side of the Rio Grande, in Coahuila, Mexico, have been documented. In 1995 the Mexico Section of the International Boundary and Water Commission (IBWC) completed a study of the western embankment (Coahuila, Mexico) of the dam that included surface geophysics, borehole geophysics, and installation of piezometers to learn more about subsurface conditions. As part of a 5-year safety inspection in 2005, technical advisors recommended that one line of similarly constructed piezometers be installed on the eastern embankment (Val Verde County, Texas) of the dam for comparison of water levels (potentiometric head) on both the western and eastern embankments of Amistad Reservoir dam. To provide technical assistance for the horizontal and vertical placement of piezometers on the eastern embankment of Amistad Reservoir dam, the U.S. Geological Survey, in cooperation with the U.S. Section of the IBWC, conducted a study along both the western and eastern embankments of Amistad Reservoir dam. The study involved an integrated approach using surface and borehole geophysical methods. In the western embankment investigation, geological and geophysical characteristics that indicate relatively large water-yielding properties of the Salmon Peak Formation were identified. The direct-current (DC) resistivity method was selected as the surface geophysical reconnaissance technique to correlate relatively large water-yielding properties of the Salmon Peak Formation, identified from analysis of borehole geophysical logs, with variations in subsurface resistivity. The dipole-dipole array and the reciprocal Schlumberger array were selected as the most applicable DC resistivity arrays. Two resistivity units were identified in both the dipole-dipole array data and the reciprocal Schlumberger array data along DC resistivity profiles on both embankments. Resistivity unit 1 generally is of relatively low resistivity, ranging from 45 to 150 ohm-meters compared with resistivity unit 2, which ranges from 120 to 345 ohm-meters (depending on the DC array type). The presence of mapped sinkholes in the reservoir north of the western embankment study area and the zone of increased water content (as indicated by zones of low neutron log count rates in nearby piezometers) leads to the conclusion that resistivity unit 1 is a preferential flow path where surface water from Amistad Reservoir is forced into the ground-water system (because of increased head from the reservoir). In the eastern embankment investigation, trends in the spatial distribution of sinkholes and the occurrence of weathered zones were identified from geologic descriptions of cores. The correlation of surface geophysical DC resistivity, historical lithologic data, and general trend of documented sinkholes along the eastern end of the eastern embankment profile were used to justify further exploration (drilling of piezometers) in the eastern expression of resistivity unit 1. The spatial location of the piezometers and the screened intervals were selected to best match the locations of the screened intervals of the western embankment piezometers. Six piezometers were installed on the eastern embankment and logged using borehole geophysical techniques. Surface DC resistivity sections superimposed on the resistivity logs for two piezometers indicate three discernible resistivity units that correlate with resistivity units 2, 1, and 2, respectively, identified in the western embankment study area. Resistivity units 1 and 2 in the DC resistivity profiles generally correspond with low and high resistivity zones, respectively, on the normal and lateral resistivity logs collected in the nearby piezometers at the time of installation.

Scientific Investigations Report↗

USGS2005

White-tailed deer ecology and management on Fire Island

Deer populations have grown dramatically on Fire Island National Seashore (FIlS) since 1983. Trend data reveal a dichotomy in deer dynamics. In the eastern half of the island, deer density appears to have stabilized between 25-35 deer/km2. In the western half of the island, deer densities are 3-4 times as high in residential communities. Concomitant with that increase has been a general decline in physical stature of some animals, visible impacts on island vegetation, especially in the Sunken Forest, and a perceived increase in the frequency of human and deer interactions. Intensive research on FIlS has shown that deer occupy relatively predictable home ranges throughout the year, but can and do move up and down the island. Impacts of deer on vegetation are most dramatic in the Sunken Forest. Most obvious are the effects of browsing on the herb layer of the Sunken Forest. The least obvious, but perhaps more significant impact is the stark lack of regeneration of canopy tree species since about 1970, which coincides with the initiation of the deer population irruption. A number of herbs and shrubs have been greatly reduced in the understory, and their propagules from the soil. Deer do not readily transmit the bacterium that causes Lyme disease to other organisms, but deer are important hosts for adult ticks which underscores their importance in the transmission pathway of the disease to humans. Deer on FIlS, while occasionally docile, are still wild animals and should be treated as such. Some animals are relatively unafraid of humans due to the absence of predation and a lack of harassment. This in turn has contributed to a longstanding tradition of feeding deer by many residents and visitors, particularly in western portions of the island. Feeding affects both the behavior and population dynamics of deer inhabiting Fire Island. Recent efforts to reduce deer feeding by visitors and residents have been very effective. Ongoing experiments with Porcine Zona Pellucida immunocontraception demonstrate some promise of this technology as a population management tool.. Success appears to be linked directly to factors affecting access to deer, which vary considerably among treatment locations. Continued high National Park Service visibility among communities in the form of interpretive programs, extension and outreach activities, and continued support of research and monitoring of deer and their effects on island biota are keys to successful resolution of persistent issues.

Technical Report↗

USGS2024

The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes

The Chesapeake Bay Program’s (CBP) Science and Technical Advisory Committee (STAC) organized and led a workshop on the science and practice of stream restoration in order to summarize the state of knowledge in order to identify ways to improve stream restoration outcomes. The workshop identified a general framework for explaining the main factors leading to stream restoration outcomes: stream degradation has occurred, leading to regulatory and policy motivations that prioritize project goals, which leads to restoration approaches, assessment and monitoring efforts, and ultimately stream restoration outcomes. In the Chesapeake Bay watershed, stream restoration often occurs in response to Clean Water Act (CWA) mandates to reduce nitrogen, phosphorus, and sediment loads to the Bay. Reviews of stream restoration outcomes summarized at the workshop showed that, in general, stream restorations have led to minimal improvement to stream aquatic biota, effective ‘stabilization’ of channel form over time, moderate improvements to water quality, and short-term negative impacts to riparian vegetation. The fundamental finding of the workshop was that often the primary goal of stream restoration projects is to improve geomorphic stability in the restored reach and downstream water quality, and not to improve local ecological conditions through ‘uplift’ (improvement of one or more ecosystem functions through a restorative activity; a term defined in Appendix D), and therefore these projects often do not improve aquatic macroinvertebrate or fish communities. This conflict in goals is a shortcoming of the currently most common regulatory driver for stream restoration (reducing downstream loads of N, P, and sediment) that could be addressed directly through diversifying goals to include biotic uplift, as biological benefit is an assumed condition for the permitting and crediting of stream restoration projects. It is also likely that current understanding of stressors and drivers of stream ecosystem health is insufficient, and that reach-scale restoration focused on geomorphic restoration is not removing the actual sources of stream health impairment that may arise in the upstream watershed. More science could help to identify how to improve the ecological condition of streams through management. The outcome of stream restoration monitoring has revealed that while geomorphic and hydrodynamic functions of stream restoration projects may be achieved, biotic stream function improvements remain elusive. As such, ensuring uplift may be achieved by avoiding restoration projects that risk resources in higher-quality streams and riparian corridors. Reach-scale restoration often does not effectively mitigate the watershed-scale stressors of stream ecosystems. If a desired outcome of stream restoration includes ecological uplift, then focusing efforts on improving stream ecology could help meet that goal.

Chesapeake Bay watershed↗

USGS2015

Geophysical log analysis of selected test and residential wells at the Shenandoah Road National Superfund Site, East Fishkill, Dutchess County, New York

The U.S. Geological Survey collected and analyzed geophysical logs from 20 test wells and 23 residential wells at the Shenandoah Road National Superfund Site in East Fishkill, New York, from 2006 through 2010 as part of an Interagency Agreement to provide hydrogeologic technical support to the U.S. Environmental Protection Agency, Region 2. The geophysical logs collected include caliper, gamma, acoustic and optical televiewer, deviation, electromagnetic-induction, magnetic-susceptibility, fluid-property, and flow under ambient and pumped conditions. The geophysical logs were analyzed along with single-well aquifer test data and drilling logs to characterize the lithology, fabric, fractures, and flow zones penetrated by the wells. The results of the geophysical log analysis were used as part of the hydrogeologic characterization of the site and in the design of discrete-zone monitoring installations in the test wells and selected residential wells. Most of the logged test and residential wells penetrated gneiss of the Hudson Highlands Complex or dolostones in the Wappinger Group, and some wells penetrated both the dolostone and gneiss. The bedrock fabric reflects the regional northeast-southwest structural trend, as well as localized folding, and includes foliation in the gneiss and bedding in the dolostone. Many fractures were oriented along the bedrock fabric, whereas others were orthogonal to the fabric. Total wellbore transmissivity of the wells was estimated from short-term, single-well aquifer test data through the use of the Cooper-Jacob analytical solution. An empirical relation was established to estimate total wellbore transmissivity from specific-capacity data for wells with insufficient transient drawdown measurements. Wellbore transmissivity estimates ranged from 0.36 to 370 feet squared per day (ft 2 /d), whereas specific capacities ranged from 0.03 to 2.1 gallons per minute per foot ((gal/min)/ft). Transmissivity and hydraulic heads of individual fracture zones were estimated from the total wellbore transmissivity and flow logs through use of an analytical model based on the Thiem equation. The model-estimated transmissivity of 95 fracture zones delineated in the 43 wells ranged from 0.25 to 340 ft 2 /d, with a median value of 6.7 ft 2 /d. The difference between model-estimated fracture-zone heads and the composite heads in each well ranged from less 0.01 to more than 10 feet (ft). Flow-log analysis generally provided an order of magnitude estimate for the fracture-zone hydraulic-head difference on the basis of a comparison of estimated and measured values. The geophysical logs and their analyses are available for display and download from the U.S. Geological Survey, New York Water Science Center, online geophysical log archive ( http://ny.water.usgs.gov/maps/geologs/ ) in LAS (Log ASCII Standard), PDF, and WellCad formats.

New York↗

USGS2007

Effects of invasive plant species on pollinator service and reproduction in native plants at Acadia National Park

Invasive plant species can have profound negative effects on natural communities by competively excluding native species. Berberis thunbergii (Japanese barberry), Frangula alnus (glossy or alder buckthorn) and Lythrum salicaria (purple loosestrife) are invasive species known to reduce native plant diversity and are thus of great concern to Acadia National Park. Pollinators visit them for nectar and pollen. The effects of invasive plant species on pollinator behavior were investigated by comparing pollinator visitation to co-flowering native and invasive species with visitation to native species growing alone. The effect of invasives on pollination of native plants was studied by comparing fruit set in patches of the native species growing near invasives with patches far from invasive species in Acadia National Park. The coflowering pairs were as follows: in the spring native Vaccinium angustifolium (lowbush blueberry) was paired with B. thunbergii; in early summer native Viburnum nudum (wild raisin) was paired with F. alnus ; in late summer native Spiraea alba (meadowsweet) was paired with L. salicaria. We investigated whether these invasives competed with native plants for pollinators in Acadia and thus negatively affected native plant reproduction. Our objectives were to determine: 1) the influence, if any, of each invasive on pollinator visitation to a co-flowering native species, 2) factors that might affect visitation, 3) invasive pollen transfer to native plants, and 4) whether invasives influence native plant reproduction (fruit set). Our findings indicate that at times the number of flower visitors to natives was lower or the species composition of visitors different when invasives were present, that invasives sometimes attracted more pollinators, that generally the invasives were more rewarding as far as nectar and pollen availability for pollinators, and that generally native plant fruit set and seed set was not significantly lowered in the presence of the invasive. In fact, in one year fruit set of S. alba was significantly greater in the presence of L. salicaria. The number of invasive pollen grains on native stigmas was extremely low; on average less than one grain per stigma. These fruit set and pollen deposition findings indicate that native plant reproduction was not adversely affected in the short term by these invasive species and that therefore competition between the native and invasive species for pollinators did not occur. Native bee populations monitored in 2004-2005 at sites with and without B. thunbergii and/or F. alnus indicated a greater abundance of native bees at sites with these invasives present. Native bees collected from the native and invasive plants were compared with historical records to assess whether invasive plants favor different bee species than those that formerly predominated on Mount Desert Island. This does not appear to be the case. Several species of bumble bees (Bombus spp.) as well as nine solitary bee species were found that were not documented by the Procter surveys of 1917-1940. Collecting of native bees was limited to the study plants, which may, in part, explain why some bee species documented in the Procter Surveys were not found in the present research. A field guide for identification of native bumble bees has been produced to help Park Natural Resource personnel monitor the status of native bee populations in Acadia. Other educational materials were also developed, aimed at educating Park visitors by exposing them to: 1) the role of native plants and their bee pollinators in terrestrial ecosystems; 2) the effects of invasive plants on native plant-pollinator mutualisms; 3) the need for conserving native bees and other pollinators; and 4) conservation strategies for protecting and enhancing native plant-pollinator mutualisms in the Park. Based on the present findings, Acadia Park Resource Management personnel should continue to closely

Technical Report↗

USGS2024

Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries

Noncommercial, shore-based fisheries provide economic, social, and cultural services to communities throughout the Hawaiian Islands. The State of Hawai‘i Department of Land and Natural Resources (DLNR), Division of Aquatic Resources (DAR) routinely conducts surveys to monitor noncommercial fisheries such that estimates of fishing effort and catch by gear type can be generated and used to implement more sustainable management practices. DAR executes both the Hawai‘i Marine Recreational Fishery Survey (HMRFS), a nationally standardized survey that focuses on intercepting fishers at access points (i.e., boat ramps) across the main Hawaiian Islands, and a set of roving creel surveys on O‘ahu, Maui Nui, and Kaua‘i that observe and intercept fishers at locations along the shoreline outside of those targeted by HMRFS. The latter set of creel surveys were designed to complement HMRFS by expanding its geographic coverage and thus providing a more representative picture of noncommercial fishing in Hawai‘i. Sustainable management priorities set by DAR rely on the availability of statewide, fishery- dependent data. Thus, we collate information from island-based roving creel surveys into a cohesive Statewide Creel Survey Database. Further, we provide preliminary analyses and describe ways that surveys could be streamlined to improve future data collection, analysis, and utility. In so doing, we synthesize the most detailed information to-date about noncommercial shore-based fisheries of Hawai‘i. The unprecedented spatial and temporal coverage of DAR’s dataset reveals the value of their survey efforts over the last decade to address fishery management needs. Our primary objectives, results, and conclusions are summarized below: 1) Integrate DAR roving creel survey data from different islands into a single Statewide Creel Survey Dataset (Chapter II). We describe the collation of creel survey data from O‘ahu, Maui Nui, and Kaua‘i into a statewide dataset. We also offer ways in which these surveys could be streamlined to meet the needs of managers and decision makers. Briefly, these are to create a statewide strategic plan, standardize the execution of standard operating procedures, centralize the creel survey database and associated metadata, and consider using technology that improves the data pipeline, including transitioning from paper-based to electronic systems for data entry and processing. 2) Assess whether the new Statewide Creel Survey Dataset can provide inputs for length-based stock assessments (Chapter III). Only on Maui were interviews conducted with associated catch data. There was reasonably high taxonomic coverage (42 species from 186 interviews with 310 fishers), but low sample sizes for nearly all species precluded the development of length-based stock assessments. We provide summary statistics from the existing data and briefly discuss how technologies could be used to automate analysis of images of noncommercial catch. 3) Analyze the Statewide Creel Survey Dataset for spatial and temporal patterns in fishing effort (Chapter IV): a. Visualizing noncommercial fishing pressure . We found that fishing effort (mean number of fishers observed per survey event at a site) on O'ahu was over three times greater than that recorded during similar surveys conducted on Maui or Kaua'i. We create maps that display the distribution of angling and spearfishing effort around each of the three islands. b. Factors that predict fishing “hotspots” around Maui . Fishing effort on Maui was associated with areas with more wave power and less parking availability. There were half as many fishers in areas with parking lots than in areas with parking on the road shoulder only. c. Changes in fishing effort during the COVID-19 pandemic . There was no change in fishing effort on O‘ahu during the first year of the pandemic, but there was a 20% decline in year 2 and a 33% decline in year 3, both in comparison to pre-pandemic levels. Pre-pandemic creel survey data were unavailable for Maui and Kaua‘i, but fishing effort on these islands also declined as the pandemic progressed at similar or greater rates than those observed on O‘ahu. 4) Quantify potential bias in survey methods by experimentally deriving fisher detection probabilities of shore-based and drone-based surveys (Chapter V): a. Shore-based surveys . We conducted roving creel surveys for four months at three locations around Hilo Bay, designed to emulate and estimate the efficacy of DAR standard operating procedures. There was high agreement between paired observers in counting fishers, leading to near-perfect detection probabilities of both anglers (94%) and spearfishers (97%), but relatively low agreement and detection probabilities of other fishers (throw net, ‘opihi picking, etc.) (52%). b. Drone-based surveys . We used an unmanned aerial vehicle (UAV; operated by DAR staff) to collect imagery of fishers along the Hilo Bay shoreline. We used still images and video clips (with known fishing activity) to build an online survey that was distributed to DAR and HCFRU personnel, asking them to count and categorize resource users as a snorkeler, spearfisher, angler, or other fisher. Only 40.0% of the responses correctly counted and categorized resource users in the image. Anglers were correctly identified and enumerated in 90.0% of the responses, but the correct response rates of the other three user categories ranged from 67.8% – 79.4%. Snorkelers and anglers tended to be undercounted while spearfishers and other fishers were overcounted. 5) Review the potential for incorporating emerging technologies that will improve, augment, and evolve creel survey data collection, especially for spearfishing (Chapter VI). Within the context of monitoring shore-based noncommercial fishing, we review the use of electronic data entry/processing systems with geospatial and image capabilities, field cameras, drones, smart buoys, citizen science apps, data mining social media, artificial intelligence and machine learning. We highlight several of the challenges and considerations when implementing these technologies into creel surveys and provide a synthesis of options that could be used to better estimate spearfishing. The general conclusion of this assessment is that the DAR roving creel survey program is collecting valuable data that supplement the existing HMRFS efforts. However, there are a number of areas that could be improved to make these efforts a more effective tool for decision-making processes in resource management and conservation: 1) Establishment of clear statewide and island objectives for the Statewide Creel Survey Dataset. Currently, data collection efforts are focused towards addressing a very broad purpose – supplementing the HMRFS data collection efforts. However, the results of the preliminary analyses conducted as part of this project suggest that the data could be used to address other areas of need if these objectives were clearly defined. Further, the design of the creel survey would benefit from greater standardization of survey protocols between islands and an effort to define a) the acceptable margins of error associated with the estimates generated by these data and b) the minimum level of change that the surveys would need to detect to be useful to managers. 2) Centralization of data entry, data quality assessment, and data accessibility. Currently, each DAR office manages data entry, checks the data for errors, and is responsible for managing and storing the data. Instituting a centralized data entry system, particularly an online database that can receive survey data from tablets or smartphones running a standardized data collection application would improve efficiency, reduce data entry errors, and accelerate the availability of data to managers. A substantial amount of time and effort from the project described in this report was devoted to checking the dataset for errors. The development and application of data quality assurance protocols would ensure that the data are reliable and available in a timely fashion to support management decisions. 3) Address lingering questions regarding the efficacy of current survey protocols to capture and characterize the spearfishing component of the noncommercial fishery. The results presented in the report suggest that the current creel survey protocols do a good job detecting spearfishers when present but are not capturing sufficient data about their catch or total effort. There are also questions remaining as to whether the survey times and sites are sufficiently capturing the behavior of spearfishers in Hawai‘i. A more thorough assessment – whether through additional research, alteration of survey design, or review of data by representatives of the spearfishing community – would provide insight on how to use the Statewide Creel Survey Database to inform management of spearfishing. 4) Investigate the integration of technological advancements into the creel survey methods. As priorities and needs are developed and formalized, it would be valuable to consider how various technological advancements might enhance and streamline data collection or open new avenues of inquiry.

Hawaii↗

USGS1998

Hydrology and snowmelt simulation of Snyderville Basin, Park City, and adjacent areas, Summit County, Utah

Increasing residential and commercial development is placing increased demands on the ground- and surface-water resources of Snyderville Basin, Park City, and adjacent areas in the southwestern corner of Summit County, Utah. Data collected during 1993-95 were used to assess the quantity and quality of the water resources in the study area. Ground water within the study area is present in consolidated rocks and unconsolidated valley fill. The complex geology makes it difficult to determine the degree of hydraulic connection between different blocks of consolidated rocks. Increased ground-water withdrawal during 1983- 95 generally has not affected ground-water levels. Ground-water withdrawal in some areas, however, caused seasonal fluctuations and a decline in ground-water levels from 1994 to 1995, despite greater-than-normal recharge in the spring of 1995. Ground water generally has a dissolved-solids concentration that ranges from 200 to 600 mg/L. Higher sulfate concentrations in water from wells and springs near Park City and in McLeod Creek and East Canyon Creek than in other parts of the study area are the result of mixing with water that discharges from the Spiro Tunnel. The presence of chloride in water from wells and springs near Park City and in streams and wells near Interstate Highway 80 is probably caused by the dissolution of applied road salt. Chlorofluorocarbon analyses indicate that even though water levels rise within a few weeks of snowmelt, the water took 15 to 40 years to move from areas of recharge to areas of discharge. Water budgets for the entire study area and for six subbasins were developed to better understand the hydrologic system. Ground-water recharge from precipitation made up about 80 percent of the ground-water recharge in the study area. Ground-water discharge to streams made up about 40 percent of the surface water in the study area and ground-water discharge to springs and mine tunnels made up about 25 percent. Increasing use of ground water has the potential to decrease discharge to streams and affect both the amount and quality of surface water in the study area. A comparison of the 1995 to 1994 water budgets emphasizes that the hydrologic system in the study area is very dependent upon the amount of annual precipitation. Although precipitation on the study area was much greater in 1995 than in 1994, most of the additional water resulted in additional streamflow and spring discharge that flows out of the study area. Ground-water levels and groundwater discharge are dependent upon annual precipitation and can vary substantially from year to year. Snowmelt runoff was simulated to assist in estimating ground-water recharge to consolidated rock and unconsolidated valley fill. A topographically distributed snowmelt model controlled by independent inputs of net radiation, meteorological parameters, and snowcover properties was used to calculate the energy and mass balance of the snowcover.

Utah↗

USGS2000

Geohydrology and numerical simulation of groundwater flow in the central Virgin River Basin of Iron and Washington Counties, Utah

Because rapid growth of communities in Washington and Iron Counties, Utah, is expected to cause an increase in the future demand for water resources, a hydrologic investigation was done to better understand ground-water resources within the central Virgin River basin. This study focused on two of the principal ground-water reservoirs within the basin: the upper Ash Creek basin ground-water system and the Navajo and Kayenta aquifer system. The ground-water system of the upper Ash Creek drainage basin consists of three aquifers: the uppermost Quaternary basin-fill aquifer, the Tertiary alluvial-fan aquifer, and the Tertiary Pine Valley monzonite aquifer. These aquifers are naturally bounded by the Hurricane Fault and by drainage divides. On the basis of measurements, estimates, and numerical simulations of reasonable values for all inflow and outflow components, total water moving through the upper Ash Creek drainage basin ground-water system is estimated to be about 14,000 acre-feet per year. Recharge to the upper Ash Creek drainage basin ground-water system is mostly from infiltration of precipitation and seepage from ephemeral and perennial streams. The primary source of discharge is assumed to be evapotranspiration; however, subsurface discharge near Ash Creek Reservoir also may be important. The character of two of the hydrologic boundaries of the upper Ash Creek drainage basin ground-water system is speculative. The eastern boundary provided by the Hurricane Fault is assumed to be a no-flow boundary, and a substantial part of the ground-water discharge from the system is assumed to be subsurface outflow beneath Ash Creek Reservoir along the southern boundary. However, these assumptions might be incorrect because alternative numerical simulations that used different boundary conditions also proved to be feasible. The hydrogeologic character of the aquifers is uncertain because of limited data. Differences in well yield indicate that there is considerable variability in the transmissivity of the basin-fill aquifer. Field data also indicate that the basin-fill aquifer is more transmissive than the underlying alluvial-fan aquifer. Data from the Pine Valley monzonite aquifer indicate that its transmissivity may be highly variable and that it is strongly influenced by the connection of fractures. The Navajo and Kayenta aquifers provide most of the potable water to the municipalities of Washington County. Because of large outcrop exposures, uniform grain size, and large stratigraphic thickness, these formations are able to receive and store large amounts of water. In addition, structural forces have resulted in extensive fracture zones that enhance ground-water recharge and movement within these aquifers. Aquifer testing of the Navajo aquifer indicates that horizontal hydraulic-conductivity values range from 0.2 to 32 feet per day at different locations and may be primarily dependent on the extent of fracturing. Limited data indicate that the Kayenta aquifer generally is less transmissive than the Navajo aquifer. The aquifers are bounded to the south and west by the erosional extent of the formations and to the east by the Hurricane Fault, which completely offsets these formations and is assumed to be a lateral no-flow boundary. Like the Hurricane Fault, the Gunlock Fault is assumed to be a lateral no-flow boundary that divides the Navajo and Kayenta aquifers within the study area into two parts: the main part, between the Hurricane and Gunlock Faults; and the Gunlock part, west of the Gunlock Fault. Generally, the water in the Navajo and Kayenta aquifers contains few dissolved minerals. However, two distinct areas contain water with dissolved-solids concentrations greater than 500 milligrams per liter: a larger area north of the city of St. George and a smaller area a few miles west of the town of Hurricane. Mass-balance calculations indicate that in the higher-dissolved-solids area north of St. George, as much as 2.7 cubic feet per second may be entering the aquifer from underlying formations. For the area west of Hurricane, as much as 1.5 cubic feet per second may be entering the aquifer from underlying formations. On the basis of measurements, estimates, and numerical simulations, total water moving through the Navajo and Kayenta aquifers is estimated to be about 25,000 acre-feet per year for the main part and 5,000 acre-feet per year for the Gunlock part. The primary source of recharge is assumed to be infiltration of precipitation in the main part and seepage from the Santa Clara River in the Gunlock part. The primary source of discharge is assumed to be well discharge for both the main and Gunlock parts of the aquifers. Numerical simulations indicate that faults with major offset, such as the Washington Hollow Fault and an unnamed fault near Anderson Junction, may impede horizontal ground-water flow. Also, increased horizontal hydraulic conductivity along the orientation of predominant surface fracturing may be an important factor in regional ground-water flow. Simulations with increased north-south hydraulic conductivity substantially improved the match to measured water levels in the central area of the model between Snow Canyon and Mill Creek. Numerical simulation of the Gunlock part, using aquifer properties determined for the city of St. George municipal well field, resulted in a reasonable representation of regional water levels and estimated seepage from and to the Santa Clara River. To further quantify the Gunlock part of the Navajo and Kayenta aquifers, a better understanding of ground-water flow at the Gunlock Fault is needed.

Utah↗

USGS1977

Hydrologic evaluation of Ashley Valley, northern Uinta basin area, Utah

The water resources of the northern Uinta Basin, Utah and Colorado, were studied during 1971-74. Ashley Valley was evaluated in slightly greater detail than the general area, in order to assess the general relation of ground- and surface-water supplies. In Ashley Valley , the principal source of both irrigation supply and ground-water recharge is the flow from Ashley Creek canyon . Ground-water recharge to the valley fill, however, is mainly from canal and field losses along the west side of the valley. The permeability of the fill in most places is high, and water-level records indicate rapid changes in storage in response to the annual applications of irrigation water. Prior to the distribution of water from Steinaker Reservoir, the short runoff season led to a brief, intense irrigation period that was followed by a long period of post-irrigation drainage. After the reservoir began operation, smaller applications of water were made during a longer season, and ground-water levels rose in parts of the valley , mainly the lower areas. Despite local water-level rises, no perennially gaining reaches of the canals were observed. The amount of ground water available from storage in Ashley Valley is estimated to be 50,000-75,000 acre-feet (62-92 cubic hectometres), or enough water to supply irrigation in the valley for a maximum of 2 years. The ground-water storage varies annually about 10 percent and has not changed significantly. Ground water is discharged from Ashley Valley both by seepage back to Ashley Creek and by evapotranspiration . Evapotranspiration of surface and ground water has increased by an estimate 20 percent above the 48,000 acre-feet (59 cubic hectometers) determined for pre-reservoir conditions. As a result, the water that flows from Ashley Valley has been degraded in chemical quality. The water from Ashley Creek canyon is fresh . Mixing of snowmelt and base flow in Steinaker Reservoir yields a water of more uniform quality; but despite some concentration by evaporation from the reservoir, the outflow from the reservoir is fresh. Ground water in most of the valley is fresh , but the water increases in dissolved-solids concentration toward the south and east as a result of both evapotranspiration and solution of minerals from the valley fill and soils .

Utah↗

USGS2021

Toward improved decision-support tools for Delta Smelt management actions

The Collaborative Science and Adaptive Management Program (CSAMP) has endorsed a goal of reversing the recent downward trajectory of the Delta Smelt population within 5-10 generations, with the long-term aim of establishing a self-sustaining population. An ambitious agenda of management actions is planned, and more management actions are being considered. This White Paper furthers one of the recommendations in the 2019 Delta Smelt Science Plan – the need to predict the potential ecological effects of taking a management action. Existing statistical models can be highly informative in assessing the response of Delta Smelt to changing system conditions and management actions. However, management actions can shift or alter conditions in ways that models based on analysis of historical data may not be able to represent, and short-term or localized effects may be missed with models designed to assess effects at the population level. Decision support tools (DSTs) are computer-based tools developed to assist decision-making, often combining computationally intensive analysis and spatial mapping of environmental relationships. DSTs can be used in planning processes that evaluate an array of actions, such as in Structured Decision Making (SDM), where DSTs are needed to compare among alternatives. DSTs can also be used to explore the potential effects of different approaches to implementing management actions. The goal of this White Paper is to identify plausible options for DSTs that could be developed for future use to evaluate management actions that seek to either reverse the decline of Delta Smelt or minimize or mitigate the effects of other water management actions. Different types of management actions lead to different needs for DSTs. This White Paper was developed using three types of actions currently being considered to enhance the Delta Smelt population: Supplementation with Hatchery Fish, Summer-Fall Habitat, and Food Enhancement actions. These three management actions target different parts of the estuary and different processes, with a variety of possible metrics to gauge performance. Three DSTs are proposed that collectively address management questions related to the management actions considered, with each requiring a slightly different set of processes to be included and producing an array of outputs at varying spatial and temporal scales: DST 1. Modeling Fish Movement, Survival, and Reproduction Across Their Range. This DST can address management questions that require information about Delta Smelt spatial distribution and movement. • DST 1 could be used to compare conditions with and without management actions in place, how the management action performs among different types of water years (with varied flow and associated abiotic conditions), and to assess relative change with different variations and strategies of the management actions. • DST 2. Changes in Habitat Conditions and Delta Smelt Response. This DST is intended to evaluate combinations of conditions that are considered to provide suitable habitat for Delta Smelt, and Delta Smelt response. Delta Smelt habitat is generally described as open water with low salinity (0 to 6), turbidity of at least 12 NTU, suitable temperature conditions, and sufficient food availability to support growth. • DST 3. Regional Effects of Food Subsidy. This DSTs seeks to evaluate effectiveness of food enhancement actions by providing information on responses of the immediate targets of the action (i.e., phytoplankton or zooplankton) and tracing those to projected growth responses of Delta Smelt. There is not a single DST that adequately addresses management questions relevant to all management actions, although there is some overlap in the management questions each of the three DSTs can address. For each of the DSTs a substantial foundation of models and approaches already exists and modeling has already been applied to several of the management actions described. However, a number of outstanding issues remain for further development of the proposed DSTs. These are summarized in this White Paper together with potential approaches that could be applied or tested. Some components for the DSTs are already available and thus development could be relatively easy. However, for several of the topics identified there are gaps in knowledge that currently limit formulation of model structure and process representations. This presents challenges to readily incorporate some needed mechanisms into the models. Eleven next steps, aligned with relevant DSTs, are outlined. The next steps vary in their complexity or technical ‘lift’ required. Many build on existing work, or methods and approaches that have already been developed or are underway, while others require additional thinking to establish a viable approach. Some interim utility for decisions could be gained during initial development of the DSTs with further features added over time. Development of a DST requires engagement of both managers and scientists. Identifying the outputs and resolution needed for management purposes early in development of any DST is essential for effective pursuit of next steps and suitable approaches to address challenges. Dialog between managers and technical experts also informs what process-based simulation can do, and what tradeoffs are acceptable to meet a given purpose. To further develop the DSTs outlined here for application in the estuary requires: - Engagement of a committed group of technical experts with appropriate expertise. - The development of a coordinated workplan including appropriate project management and tracking. - Dialog between potential users (i.e., managers and policy makers) and technical experts. - Resources to pursue DST development including personnel and computational resources. This White Paper demonstrates the potential for moving toward DSTs for a variety of management actions in support of Delta Smelt that include mechanistic representations of physical and biological processes. Through focused effort from technical experts, managers and policy makers, DSTs can be developed to provide quantitative predictions of management effects on the ecosystem, targeting the changes the management actions seek to achieve, how these effects compare to ambient conditions, and how the effects vary among water year types or with timing and location of actions. Importantly, solid foundations exist which can be leveraged, refined, and built upon to specifically inform current and future management decisions.

White Paper↗

USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗