976 resultados para headwater streams


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Considerable attention has been paid to the potentially confounding effects of geological and seasonal variation on outputs from bioassessments in temperate streams, but our understanding about these influences is limited for many tropical systems. We explored variation in macroinvertebrate assemblage composition and the environmental characteristics of 3rd- to 5th-order streams in a geologically heterogeneous tropical landscape in the wet and dry seasons. Study streams drained catchments with land cover ranging from predominantly forested to agricultural land, but data indicated that distinct water-chemistry and substratum conditions associated with predominantly calcareous and silicate geologies were key determinants of macroinvertebrate assemblage composition. Most notably, calcareous streams were characterized by a relatively abundant noninsect fauna, particularly a pachychilid gastropod snail. The association between geological variation and assemblage composition was apparent during both seasons, but significant temporal variation in compositional characteristics was detected only in calcareous streams, possibly because of limited statistical power to detect change at silicate sites, or the limited extent of our temporal data. We discuss the implications of our findings for tropical bioassessment programs. Our key findings suggest that geology can be an important determinant of macroinvertebrate assemblages in tropical streams and that geological heterogeneity may influence the scale of temporal response in characteristic macroinvertebrate assemblages.

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To better address stream impairments due to excess nitrogen and phosphorus and to accomplish the goals of the Clean Water Act, the U.S. Environmental Protection Agency (EPA) is requiring states to develop numeric nutrient criteria. An assessment of nutrient concentrations in streams on the Delmarva Peninsula showed that nutrient levels are mostly higher than numeric criteria derived by EPA for the Eastern Coastal Plain, indicating widespread water quality degradation. Here, various approaches were used to derive numeric nutrient criteria from a set of 52 streams sampled across Delmarva. Results of the percentile and y-intercept methods were similar to those obtained elsewhere. Downstream protection values show that if numeric nutrient criteria were implemented for Delmarva streams they would be protective of the Choptank River Estuary, meeting the goals of the Chesapeake Bay Total Maximum Daily Load (TMDL).

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Work during this reporting period focused on characterizing temperature, habitat, and biological communities at candidate coolwater sites. During the past year we have collected additional temperature data from 57 candidate streams and other locations and now have records from 232 stream reaches. Eighty-two sites in Illinois have been identified as cool- or coldwater based on these records. Physical habitat surveys have been conducted at 79 sites where temperature data were available. Fish and macroinvertebrate data were obtained from the cooperative basin survey program data managers for candidate sites whenever possible and added to collections made during previous project years. This report summarizes progress for the period beginning 1 October 2009 and ending 30 September 2010. Additional analyses are ongoing and will be presented in the final report upon completion of this project.

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Ethernet connections, which are widely used in many computer networks, can suffer from electromagnetic interference. Typically, a degradation of the data transmission rate can be perceived as electromagnetic disturbances lead to corruption of data frames on the network media. In this paper a software-based measuring method is presented, which allows a direct assessment of the effects on the link layer. The results can directly be linked to the physical interaction without the influence of software related effects on higher protocol layers. This gives a simple tool for a quantitative analysis of the disturbance of an Ethernet connection based on time domain data. An example is shown, how the data can be used for further investigation of mechanisms and detection of intentional electromagnetic attacks. © 2015 Author(s).

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Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous ecological functions, some of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field-validated, landscape-scale approaches for classifying wetlands based on their expected degree of connectivity with stream networks. During the 2015 water year, flow duration was recorded in non-perennial streams (n = 23) connecting forested wetlands and nearby perennial streams on the Delmarva Peninsula (Maryland, USA). Field and GIS-derived landscape metrics (indicators of catchment, wetland, non-perennial stream, and soil characteristics) were assessed as predictors of wetland-stream connectivity (duration, seasonal onset and offset dates). Connection duration was most strongly correlated with non-perennial stream geomorphology and wetland characteristics. A final GIS-based stepwise regression model (adj-R2 = 0.74, p < 0.0001) described wetland-stream connection duration as a function of catchment area, wetland area and number, and soil available water storage.

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Streams in urban areas often utilize channelization and other bank erosion control measures to improve flood conveyance, reduce channel migration, and overbank flooding. This leads to reductions in evapotranspiration and sediment storage on floodplains. The purpose of this study is to quantify the evapotranspiration and sediment transport capacity in the Anacostia Watershed, a large Coastal Plain urban watershed, and to compare these processes to a similar sized non-urban watershed. Times series data of hydrologic and hydraulic changes in the Anacostia, as urbanization progressed between 1939-2014, were also analyzed. The data indicates lower values of warm season runoff in the non-urban stream, suggesting a shift from evapotranspiration to runoff in urban streams. Channelization in the Anacostia also increased flow velocities and decreased high flow width. The high velocities associated with channelization and the removal of floodplain storage sites allows for the continued downstream transport of sediment despite stream bank stabilization.

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Ecological studies were conducted in the ichthyofauna of Cedro, a small headwater stream located in a degraded area of State of São Paulo, Brazil, situated in the upper Paraná River basin. These are the results of two non-consecutive years observations and collections in two biotopes of that stream: a pool and a rapid. The ecological characteristics studied change in space and time. The present richness of species is high (21 species), nine of which are constant, six accessory and six accidental. The diversity is low (0.69 to 2.38), and the numeric predominance, from one to three species, occurred in both biotopes. The most frequent species are Poecilia reticulata (Peters, 1859) (28.1%), Corydoras cf. aeneus (Gill, 1858) (20.3%) and Hypostomus cf. ancistroides (Ihering, 1911) (19.8%). The density ranges from 0.7 to 19.8 specimens/m³. The similarity index indicates high similarity between the ichthyofauna (45.0% to 95.0%) inside the same or contiguous biotopes. The evenness (0.46 to 1.0) is comparable to those found in similar studies carried out in other streams.

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With the advanced technology of medical devices and sensors, an abundance of medical data streams are available. However, data analysis techniques are very limited, especially for processing massive multiple physiological streams that may only be understood by medical experts. The state-of-the-art techniques only allow multiple medical devices to independently monitor different physiological parameters for the patient's status, thus they signal too many false alarms, creating unnecessary noise, especially in the Intensive Care Unit (ICU). An effective solution which has been recently studied is to integrate information from multiple physiologic parameters to reduce alarms. But it is a challenge to detect abnormalities from high frequently changed physiological streams data, since abnormalities occur gradually due to the complex situation of patients. An analysis of ICU physiological data streams shows that many vital physiological parameters are changed periodically (such as heart rate, arterial pressure, and respiratory impedance) and thus abnormalities are generally abnormal period patterns. In this paper, we develop a Mining Abnormal Period Patterns from Multiple Physiological Streams (MAPPMPS) method to detect and rank abnormalities in medical sensor streams. The efficiency and effectiveness of the MAPPMPS method is demonstrated by a real-world massive database of multiple physiological streams sampled in ICU, comprising 250 patients' streams (each stream involving over 1.3 million data points) with a total size of 28 GB data.

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The advance of positioning technology enables us to online collect moving object data streams for many applications. One of the most significant applications is to detect emergency event through observed abnormal behavior of objects for disaster prediction. However, the continuously generated moving object data streams are often accumulated to a massive dataset in a few seconds and thus challenge existing data analysis techniques. In this paper, we model a process of emergency event forming as a process of rolling a snowball, that is, we compare a size-rapidly-changed (e.g., increased or decreased) group of moving objects to a snowball. Thus, the problem of emergency event detection can be resolved by snowball discovery. Then, we provide two algorithms to find snowballs: a clustering-and-scanning algorithm with the time complexity of O(n 2) and an efficient adjacency-list-based algorithm with the time complexity of O(nlogn). The second method adopts adjacency lists to optimize efficiency. Experiments on both real-world dataset and large synthetic datasets demonstrate the effectiveness, precision and efficiency of our algorithms © 2014 Springer International Publishing Switzerland.

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Continuous sensor stream data are often recorded as a series of discrete points in a database from which knowledge can be retrieved through queries. Two classes of uncertainties inevitably happen in sensor streams that we present as follows. The first is Uncertainty due to Discrete Sampling (DS Uncertainty); even if every discrete point is correct, the discrete sensor stream is uncertain – that is, it is not exactly like the continuous stream – since some critical points are missing due to the limited capabilities of the sensing equipment and the database server. The second is Uncertainty due to Sampling Error (SE Uncertainty); sensor readings for the same situation cannot be repeated exactly when we record them at different times or use different sensors since different sampling errors exist. These two uncertainties reduce the efficiency and accuracy of querying common patterns. However, already known algorithms generally only resolve SE Uncertainty. In this paper, we propose a novel method of Correcting Imprecise Readings and Compressing Excrescent (CIRCE) points. Particularly, to resolve DS Uncertainty, a novel CIRCE core algorithm is developed in the CIRCE method to correct the missing critical points while compressing the original sensor streams. The experimental study based on various sizes of sensor stream datasets validates that the CIRCE core algorithm is more efficient and more accurate than a counterpart algorithm to compress sensor streams. We also resolve the SE Uncertainty problem in the CIRCE method. The application for querying longest common route patterns validates the effectiveness of our CIRCE method.

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Radio Frequency Identification (RFID) enabled systems are evolving in many applications that need to know the physical location of objects such as supply chain management. Naturally, RFID systems create large volumes of duplicate data. As the duplicate data wastes communication, processing, and storage resources as well as delaying decision-making, filtering duplicate data from RFID data stream is an important and challenging problem. Existing Bloom Filter-based approaches for filtering duplicate RFID data streams are complex and slow as they use multiple hash functions. In this paper, we propose an approach for filtering duplicate data from RFID data streams. The proposed approach is based on modified Bloom Filter and uses only a single hash function. We performed extensive empirical study of the proposed approach and compared it against the Bloom Filter, d-Left Time Bloom Filter, and the Count Bloom Filter approaches. The results show that the proposed approach outperforms the baseline approaches in terms of false positive rate, execution time, and true positive rate.

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Several teams of researchers at multiple universities are currently measuring annual and seasonal fluxes of carbon dioxide and other greenhouses gases (nitrous oxide and methane) in riparian wetlands and upland forests in the Tenderfoot Creek Experimental Forest (TCEF), a subalpine watershed in the Little Belt Mountains, Montana. In the current thesis, the author characterized the geochemistry and stable carbon isotope composition of shallow groundwater, soil water, and stream water in upper Stringer Creek, near sites that are being investigated for gas chemistry and microbial studies. It was hypothesized that if methanogenesis were a dominant process in the riparian wetlands of upper Stringer Creek, then this should impart a characteristic signal in the measured stable isotopic composition of dissolved inorganic carbon in shallow groundwater. For the most part, the major solute composition of shallow groundwater in upper Stringer Creek was similar to that of the stream. However, several wells completed in wetland soil had highly elevated concentrations of Fe2+ and Mn2+ which were absent in the well-oxygenated surface water. Use of sediment pore-water samplers (peepers) demonstrated a rapid increase in Fe2+ and Mn2+ with depth, most feasibly explained by microbial reduction of Fe- and Mn-oxide minerals. In general, the pH of shallow groundwater was lower than that of the stream. Since concentrations of CO2 in the groundwater samples were consistently greater than atmospheric pCO2, exchange of CO2 gas across the stream/air interface occurred in one direction, from stream to air. Evasion of CO2 partly explains the higher pH values in the stream. Microbial processes involving breakdown of organic carbon, including aerobic respiration, anaerobic respiration, and methanogenesis, explain the occurrence of excess CO2 in the groundwater. In general, the isotopic composition of total dissolved inorganic carbon (DIC) decreased with increasing DIC concentration, consistent with aerobic and/or anaerobic respiration being the dominant metabolic process in shallow groundwater. However, a minority of wells contained high DIC concentrations that were anomalously heavy in u13C, and these same wells had elevated concentrations of dissolved methane. It is concluded that the wells with isotopically-heavier DIC have likely been influenced by acetoclastic methanogenesis. Results from shallow groundwater wells and one of the peeper samplers suggest a possible link between methanogenesis and bacterial iron reduction.

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Siloxanes are widely used in personal care and industrial products due to their low surface tension, thermal stability, antimicrobial and hydrophobic properties, among other characteristics. Volatile methyl siloxanes (VMS) have been detected both in landfill gas and biogas from anaerobic digesters at wastewater treatment plants. As a result, they are released to gas phase during waste decomposition and wastewater treatment. During transformation processes of digester or landfill gas to energy, siloxanes are converted to silicon oxides, leaving abrasive deposits on engine components. These deposits cause increased maintenance costs and in some cases complete engine overhauls become necessary. ^ The objectives of this study were to compare the VMS types and levels present in biogas generated in the anaerobic digesters and landfills and evaluate the energetics of siloxane transformations under anaerobic conditions. Siloxane emissions, resulting from disposal of silicone-based materials, are expected to increase by 29% within the next 10 years. Estimated concentrations and the risk factors of exposure to siloxanes were evaluated based on the initial concentrations, partitioning characteristics and persistence. It was determined that D4 has the highest risk factor associated to bioaccumulation in liquid and solid phase, whereas D5 was highest in gas phase. Additionally, as siloxanes are combusted, the particle size range causes them to be potentially hazardous to human health. When inhaled, they may affix onto the alveoli of the lungs and may lead to development of silicosis. Siloxane-based COD-loading was evaluated and determined to be an insignificant factor concerning COD limits in wastewater. ^ Removal of siloxane compounds is recommended prior to land application of biosolids or combustion of biogas. A comparison of estimated costs was made between maintenance practices for removal of siloxane deposits and installation/operation of fixed-bed carbon absorption systems. In the majority of cases, the installation of fixed-bed adsorption systems would not be a feasible option for the sole purpose of siloxane removal. However they may be utilized to remove additional compounds simultaneously.^