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473 records · Page 27Linked to original sources

Characterization of the porosity distribution in the upper part of the karst Biscayne aquifer using common offset ground penetrating radar, Everglades National Park, Florida

The karst Biscayne aquifer is characterized by a heterogeneous spatial arrangement of porosity and hydraulic conductivity, making conceptualization difficult. The Biscayne aquifer is the primary source of drinking water for millions of people in south Florida; thus, information concerning the distribution of karst features that concentrate the groundwater flow and affect contaminant transport is critical. The principal purpose of the study was to investigate the ability of two-dimensional ground penetrating radar (GPR) to rapidly characterize porosity variability in the karst Biscayne aquifer in south Florida. An 800-m-long GPR transect of a previously investigated area at the Long Pine Key Nature Trail in Everglades National Park, collected in fast acquisition common offset mode, shows hundreds of diffraction hyperbolae. The distribution of diffraction hyperbolae was used to estimate electromagnetic (EM) wave velocity at each diffraction location and to assess both horizontal and vertical changes in velocity within the transect. A petrophysical model (complex refractive index model or CRIM) was used to estimate total bulk porosity. A set of common midpoint surveys at selected locations distributed along the common-offset transect also were collected for comparison with the common offsets and were used to constrain one-dimensional (1-D) distributions of porosity with depth. Porosity values for the saturated Miami Limestone ranged between 25% and 41% for common offset GPR surveys, and between 23% and 39% for common midpoint GPR surveys. Laboratory measurements of porosity in five whole-core samples from the saturated part of the aquifer in the study area ranged between 7.1% and 41.8%. GPR estimates of porosity were found to be valid only under saturated conditions; other limitations are related to the vertical resolution of the GPR signal and the volume of the material considered by the measurement methodology. Overall, good correspondence between GPR estimates and the direct porosity values from the whole-core samples confirms the ability of GPR common offset surveys to provide rapid characterization of porosity variability in the Biscayne aquifer. The common offset survey method has several advantages: (1) improved time efficiency in comparison to other GPR acquisition modes such as common midpoints; and (2) enhanced lateral continuity of porosity estimates, particularly when compared to porosity measurements on 1-D samples such as rock cores. The results also support the presence of areas of low EM wave velocity or high porosity under saturated conditions, causing velocity pull-down areas and apparent sag features in the reflection record. This study shows that GPR can be a useful tool for improving understanding of the petrophysical properties of highly heterogeneous systems such as karst aquifers, and thus may assist with the development of more accurate groundwater flow models, such as those used for restoration efforts in the Everglades.

Florida↗

The Grouse & Grazing Project: Effects of cattle grazing on demographic traits of greater sage-grouse

Greater sage-grouse (Centrocercus urophasianus) were once widespread within sagebrush -grassland ecosystems of western North America, but populations have declined since the mid-1960s. Though sage-grouse were not listed as threatened or endangered under the Endangered Species Act (ESA), when examined in 2015, they remain a species of interest and concern. Roughly half of the sage-grouse’s remaining habitat is on federal land, most of it managed by the Bureau of Land Management (BLM) and the U.S. Forest Service (USFS). Livestock grazing is the most extensive land use within sage-grouse habitat and the effects of livestock grazing on sage-grouse are often debated. The extensive decade-long research project summarized in this report was initiated to provide rigorous experimental research to inform the debate regarding the relationship between livestock grazing and sage-grouse. In 2012, the Idaho Grouse & Grazing Project was started with several partners including the University of Idaho, BLM, Idaho Department of Fish and Game (IDFG), and other partners to evaluate the effects of cattle grazing on sage-grouse vital rates. Many additional supporters have provided resources to this research effort including the Public Lands Council, Idaho Cattle Association, Idaho Governor’s Office of Species Conservation, Western Association of Fish & Wildlife Agencies, U.S. Fish and Wildlife Service, USFS, and numerous grazing associations and ranchers in Idaho. This 10-year research project was a scientifically rigorous and replicated experiment, occurring across five study sites in Idaho. This document is intended to provide a summary of the findings of this unprecedented study. Annual reports are available on the project’s website: https://idahogrousegrazing.org and scientific papers are being prepared and submitted to journals. The project focused on the influence of spring cattle grazing on sage-grouse vital rates across five study sites in Idaho including 21 BLM grazing pastures. From 2014-2023, we captured 1,343 grouse, documented the fate of 1,285 nests, and tracked 399 broods. Vegetation was characterized at 4,777 plots and grazing utilization levels were recorded at >30,000 locations. Because insects are an important food source for sage-grouse hens and their chicks, insect biomass and diversity were also examined in this study. We collected arthropods in 12,151 pitfall samples and 6,217 sweep-net samples across 786 plots within our five study sites. At each study site, three or four grazing treatments were implemented after two years of pre-treatment field investigations. These controlled cattle grazing treatments included spring-grazing in even years, spring-grazing in odd years, spring-and-fall grazing in alternating years, and a no grazing (or rested) control. Once grazing treatments were implemented at a study site, we measured sage-grouse demographic traits for 4-8 years post-treatment. Stocking rate (grazing intensity) was assessed across pastures each year and was influenced by vegetation communities, topography, and water sources. Grazed pastures exhibited lower grass cover and height compared to the no grazing pastures, and the extent of this difference varied based on annual precipitation levels. Rested pastures maintained higher grass cover and grass height, but the differences in habitat structure did not consistently translate to differences in sage-grouse demographic traits. Apparent nesting success varied annually and by site, ranging from 24% to 44% over the study period. Like some other studies, results from this research show that successful (i.e., hatched) sage-grouse nests have taller grass heights than failed nests. The average grass height surrounding successful nests in grazed pastures was shorter than that surrounding successful nests in non-grazed (i.e., rested) pastures. It is well documented that grazing reduces grass height, and these observations have led to widely held assumptions that livestock grazing reduces grass height which negatively affects sage-grouse nesting habitat. At the pasture scale, this study has found that sage-grouse nesting success is no greater in pastures that were rested for 4-8 years than those currently or recently grazed. This study gives no indication that removing cattle from pastures affected nesting success. We found some evidence that nest density varied among the grazing treatments, but we did not see compelling evidence of increases in density of nesting hens following cessation of grazing in the no grazing treatments. Brood survival varied by site and year but showed no strong effect of grazing treatment. Climatic conditions, particularly drought in 2021, had a greater effect on brood survival than grazing metrics. We also found no differences in hen survival among the grazing treatments. Results of this study suggest that hens nesting in spring and fall grazed pastures had similar or even slightly higher brood survival than hens in the rested pastures or the spring grazed pastures. Arthropod biomass and species diversity varied among our study sites and the differences between grazed and rested pastures also varied among study sites. Average biomass and diversity of arthropods was higher in the spring grazed pastures on two of three sites examined but higher in the rested pastures on the other site examined. Some taxa of arthropods were more abundant in grazed pastures while other taxa were more abundant in rested pastures. For example, Carabidae (Ground Beetles) and Formicidae (Ants) had higher biomass in grazed pastures, while Tenebrionidae (Darkling Beetles) and Acrididae (Grasshoppers) had higher biomass in non-grazed pastures. Results indicate that grazing effects on arthropod biomass and arthropod diversity are study site-dependent, suggesting a need to better quantify the most important prey taxa for sage-grouse chicks and to better control for other factors that influence arthropod abundance. Based on results of this research, livestock grazing, when properly managed, does not appear to negatively impact sage-grouse nest survival or brood success. This study provides critical insights for land managers balancing livestock production with sage-grouse conservation, supporting adaptive grazing strategies that maintain both economic and ecological objectives.

Idaho↗

Irrigated areas of India derived using MODIS 500 m time series for the years 2001-2003

The overarching goal of this research was to develop methods and protocols for mapping irrigated areas using a Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m time series, to generate irrigated area statistics, and to compare these with ground- and census-based statistics. The primary mega-file data-cube (MFDC), comparable to a hyper-spectral data cube, used in this study consisted of 952 bands of data in a single file that were derived from MODIS 500 m, 7-band reflectance data acquired every 8-days during 2001-2003. The methods consisted of (a) segmenting the 952-band MFDC based not only on elevation-precipitation-temperature zones but on major and minor irrigated command area boundaries obtained from India's Central Board of Irrigation and Power (CBIP), (b) developing a large ideal spectral data bank (ISDB) of irrigated areas for India, (c) adopting quantitative spectral matching techniques (SMTs) such as the spectral correlation similarity (SCS) R 2 -value, (d) establishing a comprehensive set of protocols for class identification and labeling, and (e) comparing the results with the National Census data of India and field-plot data gathered during this project for determining accuracies, uncertainties and errors. The study produced irrigated area maps and statistics of India at the national and the subnational (e.g., state, district) levels based on MODIS data from 2001-2003. The Total Area Available for Irrigation (TAAI) and Annualized Irrigated Areas (AIAs) were 113 and 147 million hectares (MHa), respectively. The TAAI does not consider the intensity of irrigation, and its nearest equivalent is the net irrigated areas in the Indian National Statistics. The AIA considers intensity of irrigation and is the equivalent of "irrigated potential utilized (IPU)" reported by India's Ministry of Water Resources (MoWR). The field-plot data collected during this project showed that the accuracy of TAAI classes was 88% with a 12% error of omission and 32% of error of commission. Comparisons between the AIA and IPU produced an R 2 -value of 0.84. However, AIA was consistently higher than IPU. The causes for differences were both in traditional approaches and remote sensing. The causes of uncertainties unique to traditional approaches were (a) inadequate accounting of minor irrigation (groundwater, small reservoirs and tanks), (b) unwillingness to share irrigated area statistics by the individual Indian states because of their stakes, (c) absence of comprehensive statistical analyses of reported data, and (d) subjectivity involved in observation-based data collection process. The causes of uncertainties unique to remote sensing approaches were (a) irrigated area fraction estimate and related sub-pixel area computations and (b) resolution of the imagery. The causes of uncertainties common in both traditional and remote sensing approaches were definitions and methodological issues. ?? 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

ISPRS Journal of Photogrammetry and Remote Sensing↗

Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins

The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network was leveraged to monitor flood wave velocities, to validate travel times, and to compliment observations from NEXRAD weather radar. The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, USA, which was burned entirely (100 percent burned) by the Waldo Canyon fire during the summer of 2012 ( MTBS, 2020 ). Surface velocity, stage, and precipitation time series collected during the DEFENS deployment on 10 August 2015 were used to monitor and predict flood wave velocities and travel times as a function of stream discharge (discharge; streamflow). The 10 August 2015 event exhibited spatial and temporal variations in rainfall intensity and duration that resulted in a discharge equal to 5.01 cubic meters per second (m 3 /s). Discharge was estimated post-event using a slope-conveyance indirect discharge method and was verified using velocity radars and the probability concept algorithm. Mean flood wave velocities – represented by the kinematic celerity ( c k = 2.619 m e t e r s p e r s e c o n d , m / s ± 0.556 p e r c e n t "> 𝑐 𝑘 = 2.619 𝑚𝑒𝑡𝑒𝑟𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑, m/s ± 0.556 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and dynamic celerity ( c d = 3.533 m / s ± 0.181 p e r c e n t a n d t h e i r u n c e r t a i n t i e s "> 𝑐 𝑑 = 3.533 m/s ± 0.181 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and their uncertainties were computed. L-moments were computed to establish probability density functions (PDFs) and associated statistics for each of the at-a-section hydraulic parameters to serve as a workflow for implementing alert networks in hydrologically similar basins that lack data. Measured flood wave velocities and travel times agreed well with predicted values. Absolute percent differences between predicted and measured flood wave velocities ranged from 1.6 percent to 49 percent and varied with water slope, hydraulic radius, and depth. The kinematic celerity was a better predictor for steep slopes and wide flood plains associated with the Upper Waldo and Middle Waldo radar streamgages; whereas, the dynamic celerity was a better surrogate for shallow slopes and incised channels such as the Lower Waldo radar streamgage. The method demonstrates the potential extensibility of a post-wildfire warning system by (1) leveraging multiple systems (i.e., weather radar, near-field velocity and stage radars, and rain gages) for accurate and timely warnings of debris and floodflows, (2) establishing an order of operations to site, install, and operate near-field radars and conventional rain gages to record floodflows, forecast travel times, and document geomorphic change in this basin and hydrologically similar basins that lack data, and (3) communicating data operationally with the Colorado Department of Transportation engineering staff, National Weather Service forecasters, and emergency managers.

Colorado↗

Mineral Commodity Summaries 2010

Each chapter of the 2010 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2009 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis. National reserves information for most mineral commodities found in this report, including those for the United States, are derived from a variety of sources. The ideal source of such information would be comprehensive evaluations that apply the same criteria to deposits in different geographic areas and report the results by country. In the absence of such evaluations, national reserves estimates compiled by countries for selected mineral commodities are a primary source of national reserves information. Lacking national assessment information by governments, sources such as academic articles, company reports, presentations by company representatives, and trade journal articles, or a combination of these, serve as the basis for national reserves information reported in the mineral commodity sections of this publication. A national estimate may be assembled from the following: historically reported reserves information carried for years without alteration because no new information is available; historically reported reserves reduced by the amount of historical production; and company reported reserves. International minerals availability studies conducted by the U.S. Bureau of Mines (USBM), before 1996, and estimates of identified resources by an international collaborative effort (the International Strategic Minerals Inventory) are the basis for some reserves estimates. The USGS collects information about the quantity and quality of mineral resources but does not directly measure reserves, and companies or governments do not directly report reserves to the USGS. Reassessment of reserves is a continuing process, and the intensity of this process differs for mineral commodities, countries, and time period. Throughout the history of Mineral Commodity Summaries and its predecessor prior to 1978, Commodity Data Summaries, the presentation of resource data has evolved. Although world resources have been discussed each year, presentation of reserves and reserve base data varied. From 1957 through 1979, only reserves information was published in the reports, but from 1980 through 1987, only estimates of reserve base, a concept introduced by the U.S. Bureau of Mines (USBM) and the USGS in 1980, were published. Beginning in 1988, both reserves and reserve base information were listed for each mineral commodity where applicable and available. Prior to 1996, the minerals availability studies conducted by the USBM and work with international collaborators were the basis for reserve base data reported in Mineral Commodity Summaries. When the USBM was closed in 1996, this function was discontinued. Since that time, reserve base estimates have been updated to be consistent with changes in reserves, but the nonreserves component of the information upon which the reserve base data were estimated is not current enough to support defensible reserve base estimates. For that reason, publication of reserve base estimates was discontinued for Mineral Commodity Summaries 2010. Abbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. A resource/reserve classification for minerals, based on USGS Circular 831 (published with the U.S. Bureau of Mines) is Appendix C, and a directory of USGS minerals information country specialists and their responsibilities is Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2010 are welcomed.

Mineral Commodity Summaries↗