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At least 1,009 records · Page 56Linked to original sources
USGS2012

Hydrologic, vegetation, and soil data collected in selected wetlands of the Big River Management area, Rhode Island, from 2008 through 2010

The Rhode Island Water Resources Board planned to develop public water-supply wells in the Big River Management Area in Kent County, Rhode Island. Research in the United States and abroad indicates that groundwater withdrawal has the potential to affect wetland hydrology and related processes. In May 2008, the Rhode Island Water Resources Board, the U.S. Geological Survey, and the University of Rhode Island formed a partnership to establish baseline conditions at selected Big River wetland study sites and to develop an approach for monitoring potential impacts once pumping begins. In 2008 and 2009, baseline data were collected on the hydrology, vegetation, and soil characteristics at five forested wetland study sites in the Big River Management Area. Four of the sites were located in areas of potential drawdown associated with the projected withdrawals. The fifth site was located outside the area of projected drawdown and served as a control site. The data collected during this study are presented in this report.

Rhode Island↗
USGS2016

The Montaguto earth flow: nine years of observation and analysis

This paper summarizes the methods, results, and interpretation of analyses carried out between 2006 and 2015 at the Montaguto earth flow in southern Italy. We conducted a multi-temporal analysis of earth-flow activity to reconstruct the morphological and structural evolution of the flow. Data from field mapping were combined with a geometric reconstruction of the basal slip surface in order to investigate relations between basal-slip surface geometry and deformation styles of earth-flow material. Moreover, we reconstructed the long-term pattern of earth-flow movement using both historical observations and modeled hydrologic and climatic data. Hydrologic and climatic data were used to develop a Landslide Hydrological Climatological (LHC) indicator model.

Conference Paper↗
USGS2019

Assessing the hydrologic impact of historical railroad embankments on wetland vegetation response in Canaan Valley, WV (USA): The value of high-resolution data

The recovery of natural ecological processes after disturbance is poorly understood. Some disturbances may be so severe as to set ecosystems onto a new trajectory. The Canaan Valley National Wildlife Refuge in West Virginia protects a unique high-altitude wetland that was heavily disturbed by logging 100 years BP and has since transitioned to a new ecological state (shrub wetland). Refuge managers interested in preserving and restoring ecosystem states expressed concerned about lingering impacts of previous disturbances (logging, railroads, beaver, deer, fire). Available data suggested hydrologic impacts from the remnant rail grade but managers had insufficient quantitative data to assess these impacts. We initiated a fine scale assessment of topography, vegetation distribution, and hydrology to assess impacts from the remnant rail grade using lidar data, vegetation surveys, and piezometers. We developed topographic models, hydrological models, and mapped vegetation distribution. We developed statistical models to assess relationships between vegetation communities, hydrology, and distance to the rail grade. Surprisingly, we found that hydrologic flow paths did not conform to expectation and were not restricted by remnant land use features. For the most part, vegetation communities are responding to topographic and environmental gradients that existed prior to disturbance. Use of highly detailed topographic data (lidar), field hydrology, and vegetation studies allowed us to more accurately assess hydrologic and vegetation regimes, eliminating the need for mitigation, saving significant resources.

West Virginia↗
USGS2001

Hydrogeologic data for the Big River–Mishnock River stream-aquifer system, central Rhode Island

Hydrogeology, ground-water development alternatives, and water quality in the BigMishnock stream-aquifer system in central Rhode Island are being investigated as part of a long-term cooperative program between the Rhode Island Water Resources Board and the U.S. Geological Survey to evaluate the ground-water resources throughout Rhode Island. The study area includes the Big River drainage basin and that portion of the Mishnock River drainage basin upstream from the Mishnock River at State Route 3. This report presents geologic data and hydrologic and water-quality data for ground and surface water. Ground-water data were collected from July 1996 through September 1998 from a network of observation wells consisting of existing wells and wells installed for this study, which provided a broad distribution of data-collection sites throughout the study area. Streambed piezometers were used to obtain differences in head data between surface-water levels and ground-water levels to help evaluate stream-aquifer interactions throughout the study area. The types of data presented include monthly ground-water levels, average daily ground-water withdrawals, drawdown data from aquifer tests, and water-quality data. Historical water-level data from other wells within the study area also are presented in this report. Surface-water data were obtained from a network consisting of surface-water impoundments, such as ponds and reservoirs, existing and newly established partial-record stream-discharge sites, and synoptic surface-water-quality sites. Water levels were collected monthly from the surface-water impoundments. Stream-discharge measurements were made at partial-record sites to provide measurements of inflow, outflow, and internal flow throughout the study area. Specific conductance was measured monthly at partial-record sites during the study, and also during the fall and spring of 1997 and 1998 at 41 synoptic sites throughout the study area. General geologic data, such as estimates of depth to bedrock and depth to water table, as well as indications of underlying geologic structure, were obtained from geophysical surveys. Site-specific geologic data were collected during the drilling of observation wells and test holes. These data include depth to bedrock or refusal, depth to water table, and lithologic information.

Rhode Island↗
USGS2020

Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models

Determining hydrologic conditions prior to instrumental records is a challenge for restoration of freshwater ecosystems worldwide. Paleoecologic data provide this information on past conditions and when these data are used to adjust hydrologic models, allow conditions to be hindcast that may not be directly estimated from the paleo-data alone. In this context, the paleo-data provide real-world estimates as input to the models. Restoration of the Greater Everglades Ecosystem requires this understanding of the hydrology of the natural system prior to significant alterations due to water management and land use. Large scale models such as the Natural Systems Model (NSM 4.6.2) have been used by the South Florida Water Management District and other agencies responsible for restoration to estimate past hydrologic conditions; however, these models typically portray a drier natural system for the beginning of the 20th century than what is indicated by paleoecologic analyses and historical data. The purpose of this study is to estimate pre-20th century water levels, hydroperiods and flow in the freshwater wetlands of the Everglades by using pollen assemblage data in three sediment cores to adjust the Natural Systems Model. This study is designed to further test estimates of flow through the Everglades derived from analysis of sediment cores collected in Florida Bay. The results demonstrate that the NSM 4.6.2 underestimates water levels and hydroperiods in the Everglades compared to the paleo-adjusted NSM 4.6.2 model outputs. Flow models that use the paleo-adjusted water levels as input indicate flow through Shark River Slough in the late 19th century was approximately two times flow between 1990 and 2000, and flow through Taylor Slough was approximately three times flow between 1990 and 2000. The flow estimates derived from this study agree with the estimates derived from earlier studies using estuarine cores. This integration of paleoecologic information and hydrologic models provides resource managers with the best available estimates of past conditions and allows them to set realistic targets for restoration of freshwater ecosystems.

Florida↗
USGS2018

Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal

The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.

Open Water Journal↗
USGS1996

Hydrologic and water-quality data for U.S. Coast Guard Support Center Kodiak, Alaska, 1987-89

Hydrologic and water-quality data were collected at the U.S. Coast Guard Support Center Kodiak on Kodiak Island, Alaska, to determine regional ground-water conditions and if contamination of soils, ground water, or surface water has occurred. Eighteen areas of possible contamination were identified. Ground-water levels, surface- water stages, surface-water discharges, and results of field and laboratory analyses of soil and water samples are presented in tabular form. Many quality-assurance samples had detectable concentrations of methylene chloride and 1,2-dichloroethane, which may be due to sampling or laboratory contamination. Concentrations were as great as 5.9 micrograms per liter for methylene chloride and 2.6 micrograms per liter for 1,2-dichloroethane. Excluding 1,2-dichloroethane, most soil, ground-water, and surface-water samples contained no detectable concentrations of the organic constituents that were analyzed. Chemical analyses were performed on two lake-bed-material samples and more than 100 soil samples. The median lead concentration was 9.8 milligrams per kilogram. Concentrations of tetrachloroethene were as great as 1.1 milligram per kilogram in soils near a laundry. Water samples were collected from 101 wells. The maximum benzene concentration detected in ground water was 78 micrograms per liter from a well at the air station near a site where aviation fuel was spilled. Wells near a laundry yielded water having concentrations of tetrachloroethene as great as 3,000 micrograms per liter, and vinyl chloride as great as 440 micrograms per liter. A well in a former aviation gasoline storage area yielded water with a concentration of trichloroethene as great as 66 micrograms per liter. Water samples were collected from 59 sites on streams, lakes, or ponds. Surface-water samples had much lower concen- trations of organic compounds; the highest concentration of benzene was 2.2 micrograms per liter in a stream near a former aviation-fuel storage area and the maximum vinyl chloride concentration was 15 micrograms per liter in a stream near a former landfill. Tetrachloroethene and trichloroethene were not detected in any surface-water samples.

Open-File Report↗
USGS2024

Opportunities and challenges for precipitation forcing data in post-wildfire hydrologic modeling applications

The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post-wildfire hydrologic hazards including debris flows, flash floods, water-quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data-sparse, headwater catchments in complex terrain, and post-wildfire hydrologic effects are particularly sensitive to high-intensity, short-duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire-induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade-offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post-wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire-prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.

WIREs Water↗
USGS2004

The USGS/EROS Data Center produces seamless hydrologic derivatives with GIS

Increasingly, many local, state, and federal agencies mandated to manage water resources are finding that their needs are not being met by existing digital data sets. Current national coverage of digital data sets, such as drainage basin boundaries and consistent elevation-derived parameters, does not exist or is not of a suitable scale or consistency to allow management of small or midsize watersheds. This problem has become more significant as the management of water resources, both in terms of quantity and quality, is becoming more and more based on the watershed scale.

ArcNews↗
USGS1976

Hydrologic studies of the U.S. Geological Survey related to coal development on Colorado

This report summarizes the hydrologic studies related to coal development being conducted by the U.S. Geological Survey in the State of Colorado. The objective of the hydrologic data-acquisition program is to collect surface-water quality and quantity data and ground-water level records. These data are needed to define predevelopment conditions and to monitor the effects of construction and operation of coal mines and waste-disposal areas. Data-acquisition activities related to coal development in Colorado have concentrated on the Yampa River basin. A description of the hydrologic data-acquisition activities, including parameters collected and frequency of collection, precedes the summaries of the three interpretive studies currently in progress. Each study summary consists of the project title, definition of the problem being studied, objective of the study, approach of the study, and when known, the schedule for completion of the study and proposed report products resulting from the study. (Woodard-USGS)

Open-File Report↗
USGS1989

Hydrogeologic data for the Canal Creek area, Aberdeen Proving Ground, Maryland, April 1986-March 1988

This report is a compilation of hydrologic and geologic data collected for the period April 1986 through March 1988 for the Canal Creek area of Aberdeen Proving Ground, Maryland. Geologic data include lithologic logs for 73 sites and geophysical logs for 71 sites. Hydrologic data consist of hydrographs and synoptic water level measurements. The hydrographs were taken from eight wells that were equipped with continuous water level recorders, and the synoptic water-level measurements were made four times during the study. Well-construction data also are included for 149 observation wells. (USGS)

Open-File Report↗
USGS2007

Hydrologic conditions in northwest Florida: 2006 water year

National data for streamflow, ground-water levels, and quality of water for the 2006 water year are accessible to the public on the U.S. Geological Survey's (USGS) Site Information Management System (SIMS) website http://web10capp.er.usgs.gov/adr06_lookup/search.jsp. This fact sheet describes data and hydrologic conditions throughout northwest Florida during the 2006 water year (fig. 1), when record-low monthly streamflow conditions were reported at several streamgage locations. Prior to 1960, these data were published in various USGS Water-Supply Papers and included water-related data collected by the USGS during the water year (October 1 to September 30). In 1961, a series of annual reports, 'Water Resources Data-Florida,' was introduced that published surface-water data. In 1964, a similar report was introduced for the purposes of publishing water-quality data. In 1975, the reports were merged to a single volume and were expanded to publish data for surface water, water quality, and ground-water levels. Formal publication of the annual report series was discontinued at the end of the 2005 water year, upon activation of the SIMS website database.

Florida↗
USGS2019

Predicting hydrologic disturbance of streams using species occurrence data

Aquatic organisms have adapted over evolutionary time-scales to hydrologic variability represented by the natural flow regime of rivers and streams in their unimpaired state. Rapid landscape change coupled with growing human demand for water have altered natural flow regimes of many rivers and streams on a global scale. Climate non-stationarity is expected to further intensify hydrologic variability, placing increased pressure on aquatic communities. Using a machine learning approach and georeferenced species occurrence data, we modeled and mapped spatial patterns of hydrologic disturbance for streams in Arkansas, Missouri, and eastern Oklahoma. Random forest (RF) models trained on fish community data, hydrologic, and landscape metrics for gaged streams in the National Hydrography (NHDPlusV2) database were used to predict a hydrologic disturbance index (HDI) for ungaged streams. The HDI is part of the USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGESII) database and is a composite index of watershed-scale disturbance from anthropogenic stressors. Fish presence/absence data had similar overall model prediction accuracy (77%; 95% CI: 0.74, 0.80) as flow variables (76%; CI: 0.73, 0.80). Including topographic variables increased the RF prediction accuracy of both the fish (90%; CI: 0.88, 0.92) and flow models (86%; CI: 0.84, 0.89). Spatial patterns of hydrologic disturbance suggest distinct ecohydrological regions exist where conservation actions may be focused. Streams with low HDI were predominately located in the Ozark Highlands, Boston Mountains, and Ouachita Mountains. Correlation analysis of HDI by flow regime showed groundwater stable streams had the lowest disturbance frequency, with over 50% of stream reaches with low HDI located in forested land cover. HDI was highest for big rivers, intermittent runoff streams and streams in areas of agricultural land use. Our results show long-term georeferenced biological data can provide a valuable resource for predictive modeling of hydrologic disturbance for ungaged rivers and streams.

Arkansas, Missouri, Oklahoma↗
USGS2026

Logical data model for hydrographic data based on HY_Features concepts

This report describes background and design of the “hydrofabric data model” which defines logic for implementation of data schemas and software that deals with hydrologic geospatial data. As a “logical” data model, the hydrofabric data model specifies details necessary to support compatibility of data and software that satisfy diverse needs without unnecessarily restricting implementation details. The logic presented in this report is based on concepts defined in WaterML2 Part 3 Surface Hydrology Features Concepts and is designed to serve the needs of a range of hydroscience use cases. Development of international community standards applicable to hydrofabrics began, prompted by the World Meteorological Organization Commission for Hydrology, in 2012 [5] . More than 10 years later, this report documents one aspect of a long-term research and development activity that traces its roots back that far. This report describes terminology, use cases, and background as context preceding presentation of the logical model and discussion of its design. Three appendices document related data models, an example encoding of the hydrofabric data model, and an artificial schematic and tabular data example. The sections of the report can be accessed in the Clause 5 section.

OCG Public Engineering Report↗
USGS2001

Selected hydrologic and water-quality data for Kamas Valley and vicinity, Summit County, Utah, 1997-2000

This report contains hydrologic and water-quality data collected in the Kamas Valley vicinity during a study from 1997 to 2000. The study area is in Summit County in north-central Utah and is part of the Middle Rocky Mountains Physiographic Province described by Fenneman (1931). Data were collected in Kamas Valley between the Uinta Mountains on the east and the West Hills on the west, the upper Weber River area, the Samak area along Beaver Creek, the Woodland area, and the Indian Hollow area. These areas, where population growth and water demand are concentrated, encompass about 70 square miles and include the Weber River, Beaver Creek, and Provo River drainages. Surface water is the dominant hydrologic resource. The combined average flow from these three drainages is about 345,000 acre-feet per year. Ground water is present in the unconsolidated deposits in Kamas Valley, in stream alluvium along Beaver Creek and the upper Weber River, and in the consolidated rocks surrounding Kamas Valley.

Utah↗
USGS1994

Hydrologic, water-quality, and meteorologic data from selected sites in the Upper Catawba River Basin, North Carolina, January 1993 through March 1994

Hydrologic, water-quality, and meteorologic data were collected from January 1993 through March 1994 as part of a water-quality investigation of the Upper Catawba River Basin, North Carolina. Specific objectives of the investigation were to characterize the water quality of Rhodhiss Lake, Lake Hickory, and three tributary streams, and to calibrate hydrodynamic water-quality models for the two reservoirs. Sampling locations included 11 sites in Rhodhiss Lake, 14 sites in Lake Hickory, and 3 tributary sites. Tributary sites were located at Lower Creek upstream from Rhodhiss Lake and at Upper Little River and Middle Little River upstream from Lake Hickory. During 21 sampling visits, specific conductance, pH, water temperature, dissolved-oxygen concentration, and water transparency were measured at all sampling locations. Water samples were collected for analysis of biochemical oxygen demand, fecal coliform bacteria, hardness, alkalinity, total and volatile suspended solids, suspended sediment, nutrients, total organic carbon, chlorophyll, iron, calcium, and magnesium from three sites in each reservoir and from the three tributary sites. Chemical and particle-size analyses of bottom material from Rhodhiss Lake and Lake Hickory were performed once during the study. At selected locations, automated instruments recorded water level, streamflow, water temperature, solar radiation, and air temperature at 15-minute intervals throughout the study. Hydrologic data presented in the report include monthly water-level statistics and daily mean values of discharge. Diagrams, tables, and statistical summaries of water-quality data are provided. Meteorologic data in the report include monthly precipitation, and daily mean values of solar radiation and air temperature.

North Carolina↗
USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗
USGS1982

A summary of selected publications, project activities, and data sources related to hydrology in the Warrior and Plateau coal fields of Alabama

The report is a reference source on hydrologic information related to coal-mining activities in the Warrior and Plateau coal fields of Alabama. It contains a bibliography of more than 200 references and selected annotations. Also included is information on maps, automated-data bases, water-monitoring programs, and data-source agencies and organizations.

Open-File Report↗