United States Geological Survey Data Research Articles

Multiscalar Assessment of Mining in River Floodplains of the Southeastern United States

The mining of sediment is a profitable activity involving clearing and digging out large tracts of land and transformation of the topography. Often, these mines, as well as the pits, ponds, and piles of sediment are near or within the floodplains of a fluvial system. During flood events, the river can overtop and erode riparian areas that separate it from the mine, flowing into the pit and causing planform changes including avulsions. The United States Geological Survey (USGS) has mapped mining sites across the United States, but there are still multiple omissions. Google Earth Pro was used to collect geospatial point data on mines that are within the floodplain boundaries of rivers and creeks in the southeast, a region of high biodiversity. Google Earth extracted data were compared to USGS data using ArcGIS Pro, and their proximity to floodplains and channels was analyzed. Distances between the channels and pits prior to avulsion were referenced from literature (Mossa & Marks, 2011) and used to assess potential risk for other sites. It was found that out of the 1,856 total pits from USGS and Google Earth data, 25.9% were omitted from the USGS data set. This supported the conclusion that current data sets, while thorough, are still incomplete and that a better understanding of site location can reduce the risk of avulsions, which can impact infrastructure, property boundaries, flood risk, and ecological health.

Dynamics of forest stands changes on the territory of Skole Beskydy National Nature Park

The relevance of the study is determined by the issue of assessing the condition and utilization of forest cover within the territory of the Skole Beskydy National Nature Park, as well as the necessity to develop effective methods for monitoring and conserving forest ecosystems. The purpose of the study was to investigate the dynamics of forest cover changes within the Skole Beskydy National Nature Park, as well as to assess the losses of forest resources in this area and recommend the obtained series of images to enhance the forest management system. The research was conducted using a comprehensive approach combining various methods of studying forest cover changes and their comparison. The basis for applying remote sensing technologies was the use of specific multispectral satellite images combined with attribute information on forest land geospatial data. The most progressive methods of studying changes in forest plantations based on remote sensing data using geographic information systems have been demonstrated. Satellite images were obtained from the Landsat 8 satellite data set through the United States Geological Survey data portal. The normalized burn ratio and normalized difference vegetation index are calculated and compared. An analysis was also carried out using the Global Forest Watch online resource. As a result of the study, changes in forest cover were identified, an assessment of the changes was provided, and a map reflecting forest changes that occurred in the Skole Beskydy National Nature Park from 2000 to 2020 was developed. According to the results of the analysis, a low level of losses of forest plantations due to natural factors, including losses from fires, was established. The main part of forest losses is caused by anthropogenic factors. The practical significance of the results lies in the possibility of using the obtained series of images within public control and improving the forest management system

Hydrologic Connectivity and Flow Generation from California Vernal Pool, Swale, and Headwater Stream Complexes to Downstream Waters

Many headwater wetlands are integrated into flowpath networks and can serve as sources of streamflow for downgradient waters. We demonstrate this with five years of data in vernal pool, swale, and headwater stream complexes in the Central Valley, California. Long-term United States Geological Survey data suggest that the mean flow duration from the smallest watersheds in this region, including those with vernal pool, swale, and headwater stream complexes, is ~ 85 days per year. Our data concur, indicating that the annual days of flow per year from our vernal pool, swale, and headwater stream complexes ranges from ~ 20–200, but is ~ 85 when annual precipitation is 100% of normal. Peak stages are evident first in vernal pools which then propagate sequentially downstream through swales, headwater streams, and to the Sacramento River at celerities of ~ 1-1.5 m/s, consistent with expected flood wave velocities. Geospatial analyses show that these vernal pool, swale, and headwater stream features cover > 4% of the study area. Our results suggest these systems can be significant sources of streamflow, and therefore play an important role in maintaining the chemical, physical, and biological integrity of downstream waters, which has important implications for the definition of waters of the United States subject to regulation under the Clean Water Act.

Addendum

Previous article FreeAddendumOriginal articleNutrients and warming alter mountain lake benthic algal structure and functionPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreA United States Geological Survey data release accompanies the article by Oleksy et al. “Nutrients and warming alter mountain lake benthic algal structure and function,” that is published in the March issue of Freshwater Science (https://doi.org/10.1086/713068). These data can be cited and accessed with the following citation: Oleksy, I. A., and J. S. Baron. 2021. Field measurements, laboratory, and field experimental data for Sky Pond, Rocky Mountain National Park Colorado, nutrient and warming study, 2015—2017: U.S. Geological Survey data release. (Available from: https://doi.org/10.5066/P9UR2K3E). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Previous article DetailsFiguresReferencesCited by Freshwater Science Volume 40, Number 2June 2021 Published on behalf of the Society for Freshwater Science Article DOIhttps://doi.org/10.1086/714543 Views: 321Total views on this site © 2021 by The Society for Freshwater Science.PDF download Crossref reports no articles citing this article.Related articlesNutrients and warming alter mountain lake benthic algal structure and function12 Feb 2021Freshwater Science

Reanalysis of Water Withdrawal for Irrigation, Electric Power, and Public Supply Sectors in the Conterminous United States, 1950–2016

AbstractAccurately measuring water use by the economy is essential for developing reliable models of water resource availability. Indeed, these models rely on retrospective analyses that provide insights into shifting human population demands and adaptions to water shortages. However, accurate, methodologically consistent, empirically authentic, and spatiotemporally comprehensive historical datasets for water withdrawals are scarce. Herein, we present a reanalysis of annual resolution (1950–2016) historical data set on irrigation, electric power, and public supply water withdrawal within the conterminous United States (US) at the county‐level, and, for power plants, at the site‐level. To estimate electric power water use, we synthesized a historically comprehensive list of generators and historic patterns in generation across fuels, prime movers, and cooling technologies. Irrigation water use estimation required building a crop‐demand model that utilized historical information on irrigated acreage for crops and golf courses, stage‐specific crop water demand, and climate information. To estimate public water supply use, we developed a random forest model constructed from information on population, infrastructure, climate, and land cover. These estimates generally agree with total county and state water use information provided by the US Geological Survey (USGS) water use circular and estimates generated from independent studies for specific years. However, we also observed discrepancies between our estimates and USGS data that appear to be caused by inconsistencies in the methods used by the USGS's primary data sources at the state level over decades of data collection, highlighting the importance of reanalysis to yield spatiotemporally consistent and intercomparable estimates of water use.

Tsunami Modelling of the 8th September 2017 Mexico Earthquake of M 8.1, Using Two Different Software

On 8th of September 2017, an earthquake of magnitude Mw 8.1 was generated offshore Mexico, Chiapas area, at 04:49 UTC, with a depth of 72 km and the following coordinates: Latitude 15.02 N, Longitude 93.81 W, 98 km away from Pijijiapan (Mexico). The fault plane solution of the event was normal plane. Maximum tsunami waves of 1.1 m were measured at Salina Cruz sea level station, following the earthquake. Tsunami modelling simulations were accomplished using the earthquake’s parameters (location, magnitude, depth) and moment tensor solutions given by 3 different agencies: United States Geological Survey (USGS), German Research Centre for Geosciences (GFZ) and Global Centroid Moment Tensor (GCMT). For every case studied, the affected locations, sea level estimates and maximum wave heights were computed. There are two software used for modelling, the Tsunami Analysis Tool (TAT), provided and developed by the Joint Research Centre, Ispra, Italy and TRIDEC Cloud, provided by the German Research Centre for Geosciences (GFZ), Potsdam, Germany. After analysing the modelling scenarios, a comparison between the results of the two software was accomplished, for the same earthquake parameters. The results show that the parameters of GCMT computed with TAT overestimate those computed with TRIDEC, of maximum 3.9 m wave height at Arista with TAT and 2.46 m with TRIDEC. For the GFZ parameters, the estimates give 3.5 m for Pasito de la Senora with TAT, compared to 1.64 m maximum waves at Puerto Madero with TRIDEC. For the USGS data set, the results are similar, maximum waves of 2.4 m at Pasito de la Senora with TAT, and 2.9 m at Puerto Madero with TRIDEC. The Salina Cruz station, where 1.1 m height waves were measured, gives results only for the simulations ran with TAT, with 1.0 m for the GFZ earthquake parameters, 0.6 m for USGS and 1.4 m for the GCMT parameters.

Features of western disturbances simulated over north India using different land‐use data sets

Three strong western disturbances (WDs) that occurred over north India in 2008 and 2009 are simulated with two different types of land‐use data using a Weather Research and Forecasting (WRF) model. The two different land‐use land covers (LULCs) used are Advanced Wide Field Sensor (AWiFS) data and United States Geological Survey (USGS) data. The distribution pattern of rainfall produced by the WRF is compared with a corresponding Tropical Rainfall Measuring Mission (TRMM) pattern. Rainfall at specific locations is compared with India Meteorological Department (IMD) station data at different locations over north India. Root mean square errors (RMSEs) in rainfall from model simulations using two sets of land‐use data are compared with the TRMM and it is found that the simulations with AWiFS data show lower RMSEs. The wind, mean sea‐level pressure and relative humidity simulated by the model are compared with the patterns from National Center for Environmental Prediction (NCEP) Final Analysis (FNL) data. From the study, it is observed that precipitation is affected by land‐cover changes. The precipitation and circulation patterns are better simulated using AWiFS land‐use data compared with USGS data.

Infrared acousto-optic tunable filter point spectrometer for detection of organics on mineral surfaces

A prototype infrared (IR) acousto-optic tunable filter (AOTF)-based point spectrometer has been designed for examining and analyzing potential biological samples collected in situ from the planets or other solar system objects. The reflectance spectrometer operates at a wavelength range of 1.6 to 3.6 μm, which is diagnostic of minerals and organics, and inspects a 1-mm sized spot on the sample. The tuning component is the AOTF that has been utilized in a variety of spectral detection applications. The instrument’s specification and design approach including the selected components is described. The data acquisition system, the electronic components, and their interconnections are presented. The instrument’s radiometric performance is examined and described by a noise equivalent reflectance value of 0.13% that is obtained from the laboratory measurements. The device has been demonstrated by measuring the reflectance spectra for a variety of geological samples and comparing the results with the United States Geological Survey data.

A practical approach to formulate stage–discharge relationship in natural rivers

This study proposes a new formulation technique for modeling stage–discharge relationship, as an alternative approach to standard regression techniques. An explicit neural network formulation (ENNF) is derived by using data obtained from United States Geological Survey data base. The neural network model is trained and tested using time series of daily stage and discharge data from two stations in Pennsylvania, USA. The model is compared with the standard rating curve (SRC) technique. Statistical parameters such as average, standard deviation, minimum, and maximum values, as well as criteria such as root mean square error, the efficiency coefficient (E), and determination coefficient (R2) are used to measure the performance of the ENNF. Considerably, well performance is achieved in modeling streamflow by using ENNF. The comparison results reveal that the suggested formulations perform better than the conventional SRC.

Development of an Improved Methodology to Assess Potential Unconventional Gas Resources

Considering the important role played today by unconventional gas resources in North America and their enormous potential for the future around the world, it is vital to both policy makers and industry that the volumes of these resources and the impact of technology on these resources be assessed. To provide for optimal decision making regarding energy policy, research funding, and resource development, it is necessary to reliably quantify the uncertainty in these resource assessments. Since the 1970s, studies to assess potential unconventional gas resources have been conducted by various private and governmental agencies, the most rigorous of which was by the United States Geological Survey (USGS). The USGS employed a cell-based, probabilistic methodology which used analytical equations to calculate distributions of the resources assessed. USGS assessments have generally produced distributions for potential unconventional gas resources that, in our judgment, are unrealistically narrow for what are essentially undiscovered, untested resources. In this article, we present an improved methodology to assess potential unconventional gas resources. Our methodology is a stochastic approach that includes Monte Carlo simulation and correlation between input variables. Application of the improved methodology to the Uinta–Piceance province of Utah and Colorado with USGS data validates the means and standard deviations of resource distributions produced by the USGS methodology, but reveals that these distributions are not right skewed, as expected for a natural resource. Our investigation indicates that the unrealistic shape and width of the gas resource distributions are caused by the use of narrow triangular input parameter distributions. The stochastic methodology proposed here is more versatile and robust than the USGS analytic methodology. Adoption of the methodology, along with a careful examination and revision of input distributions, should allow a more realistic assessment of the uncertainty surrounding potential unconventional gas resources.

On the use of ocean color remote sensing to measure the transport of dissolved organic carbon by the Mississippi River Plume

We investigated the use of ocean color remote sensing to measure the transport of dissolved organic carbon (DOC) by the Mississippi River to the Gulf of Mexico. From 2000 to 2005 we recorded surface measurements of DOC, colored dissolved organic matter (CDOM), salinity, and water-leaving radiances during five cruises to the Mississippi River Plume. These measurements were used to develop empirical relationships to derive DOC, CDOM, and salinity from monthly composites of SeaWiFS imagery collected from 1998 through 2005. We compared our remote sensing estimates of river flow and DOC transport with data collected by the United States Geological Survey (USGS) from 1998 through 2005. Our remote sensing estimates of river flow and DOC transport correlated well ( r 2 ∼ 0.70) with the USGS data. Our remote sensing estimates and USGS field data showed low variability in DOC concentrations in the river end-member (7–11%), and high seasonal variability in river flow (∼ 50%). Therefore, changes in river flow control the variability in DOC transport, indicating that the remote sensing estimate of river flow is the most critical element of our DOC transport measurement. We concluded that it is possible to use this method to estimate DOC transport by other large rivers if there are data on the relationship between CDOM, DOC, and salinity in the river plume.

Sediment-Transporting Characteristics of Streams

Natural streams may have an ill-defined relationship between sediment load and discharge. United States Geological Survey data for several western streams included information on temperature, velocity, depth, width, and bed material, as well as concentration and discharge. The variability of the load-discharge characteristics of these streams was assessed by the use of a relationship for the sediment-transporting capacity of streams and the measured variability of the factors determining the load. Although a direct comparison between prediction and observation was not feasible for every set of measurements, the predicted range of variation in sediment load was more than sufficient to explain the observed variation.