Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System

USGS Publications Warehouse

Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight

2017-09-15

A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.

Salamander occupancy in headwater stream networks

USGS Publications Warehouse

Grant, E.H.C.; Green, L.E.; Lowe, W.H.

2009-01-01

1. Stream ecosystems exhibit a highly consistent dendritic geometry in which linear habitat units intersect to create a hierarchical network of connected branches. 2. Ecological and life history traits of species living in streams, such as the potential for overland movement, may interact with this architecture to shape patterns of occupancy and response to disturbance. Specifically, large-scale habitat alteration that fragments stream networks and reduces connectivity may reduce the probability a stream is occupied by sensitive species, such as stream salamanders. 3. We collected habitat occupancy data on four species of stream salamanders in first-order (i.e. headwater) streams in undeveloped and urbanised regions of the eastern U.S.A. We then used an information-theoretic approach to test alternative models of salamander occupancy based on a priori predictions of the effects of network configuration, region and salamander life history. 4. Across all four species, we found that streams connected to other first-order streams had higher occupancy than those flowing directly into larger streams and rivers. For three of the four species, occupancy was lower in the urbanised region than in the undeveloped region. 5. These results demonstrate that the spatial configuration of stream networks within protected areas affects the occurrences of stream salamander species. We strongly encourage preservation of network connections between first-order streams in conservation planning and management decisions that may affect stream species.

New metrics for evaluating channel networks extracted in grid digital elevation models

NASA Astrophysics Data System (ADS)

Orlandini, S.; Moretti, G.

2017-12-01

Channel networks are critical components of drainage basins and delta regions. Despite the important role played by these systems in hydrology and geomorphology, there are at present no well-defined methods to evaluate numerically how two complex channel networks are geometrically far apart. The present study introduces new metrics for evaluating numerically channel networks extracted in grid digital elevation models with respect to a reference channel network (see the figure below). Streams of the evaluated network (EN) are delineated as in the Horton ordering system and examined through a priority climbing algorithm based on the triple index (ID1,ID2,ID3), where ID1 is a stream identifier that increases as the elevation of lower end of the stream increases, ID2 indicates the ID1 of the draining stream, and ID3 is the ID1 of the corresponding stream in the reference network (RN). Streams of the RN are identified by the double index (ID1,ID2). Streams of the EN are processed in the order of increasing ID1 (plots a-l in the figure below). For each processed stream of the EN, the closest stream of the RN is sought by considering all the streams of the RN sharing the same ID2. This ID2 in the RN is equal in the EN to the ID3 of the stream draining the processed stream, the one having ID1 equal to the ID2 of the processed stream. The mean stream planar distance (MSPD) and the mean stream elevation drop (MSED) are computed as the mean distance and drop, respectively, between corresponding streams. The MSPD is shown to be useful for evaluating slope direction methods and thresholds for channel initiation, whereas the MSED is shown to indicate the ability of grid coarsening strategies to retain the profiles of observed channels. The developed metrics fill a gap in the existing literature by allowing hydrologists and geomorphologists to compare descriptions of a fixed physical system obtained by using different terrain analysis methods, or different physical systems described by using the same methods.

EFDC1D - A ONE DIMENSIONAL HYDRODYNAMIC AND SEDIMENT TRANSPORT MODEL FOR RIVER AND STREAM NETWORKS: MODEL THEORY AND USERS GUIDE

EPA Science Inventory

This technical report describes the new one-dimensional (1D) hydrodynamic and sediment transport model EFDC1D. This model that can be applied to stream networks. The model code and two sample data sets are included on the distribution CD. EFDC1D can simulate bi-directional unstea...

Modeling stream network-scale variation in coho salmon overwinter survival and smolt size

EPA Science Inventory

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over ...

Dynamics of wood in stream networks of the western Cascades Range, Oregon

Treesearch

Nicole M. Czarnomski; David M. Dreher; Kai U. Snyder; Julia A. Jones; Frederick J. Swanson

2008-01-01

We develop and test a conceptual model of wood dynamics in stream networks that considers legacies of forest management practices, floods, and debris flows. We combine an observational study of wood in 25 km of 2nd- through 5th-order streams in a steep, forested watershed of the western Cascade Range of Oregon with whole-network studies of forest cutting, roads, and...

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson

2014-01-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

NASA Astrophysics Data System (ADS)

Gomez-Velez, Jesus D.; Harvey, Judson W.

2014-09-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

The road to NHDPlus — Advancements in digital stream networks and associated catchments

USGS Publications Warehouse

Moore, Richard B.; Dewald, Thomas A.

2016-01-01

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water-related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium-resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate-and-transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user-defined applications.

Shuttle radar DEM hydrological correction for erosion modelling in small catchments

NASA Astrophysics Data System (ADS)

Jarihani, Ben; Sidle, Roy; Bartley, Rebecca

2016-04-01

Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modelling of environmental processes. Catchment and hillslope scale runoff and sediment processes (i.e., patterns of overland flow, infiltration, subsurface stormflow and erosion) are all topographically mediated. In remote and data-scarce regions, high resolution DEMs (LiDAR) are often not available, and moderate to course resolution digital elevation models (e.g., SRTM) have difficulty replicating detailed hydrological patterns, especially in relatively flat landscapes. Several surface reconditioning algorithms (e.g., Smoothing) and "Stream burning" techniques (e.g., Agree or ANUDEM), in conjunction with representation of the known stream networks, have been used to improve DEM performance in replicating known hydrology. Detailed stream network data are not available at regional and national scales, but can be derived at local scales from remotely-sensed data. This research explores the implication of high resolution stream network data derived from Google Earth images for DEM hydrological correction, instead of using course resolution stream networks derived from topographic maps. The accuracy of implemented method in producing hydrological-efficient DEMs were assessed by comparing the hydrological parameters derived from modified DEMs and limited high-resolution airborne LiDAR DEMs. The degree of modification is dominated by the method used and availability of the stream network data. Although stream burning techniques improve DEMs hydrologically, these techniques alter DEM characteristics that may affect catchment boundaries, stream position and length, as well as secondary terrain derivatives (e.g., slope, aspect). Modification of a DEM to better reflect known hydrology can be useful, however, knowledge of the magnitude and spatial pattern of the changes are required before using a DEM for subsequent analyses.

A spatial model for a stream networks of Citarik River with the environmental variables: potential of hydrogen (PH) and temperature

NASA Astrophysics Data System (ADS)

Bachrudin, A.; Mohamed, N. B.; Supian, S.; Sukono; Hidayat, Y.

2018-03-01

Application of existing geostatistical theory of stream networks provides a number of interesting and challenging problems. Most of statistical tools in the traditional geostatistics have been based on a Euclidean distance such as autocovariance functions, but for stream data is not permissible since it deals with a stream distance. To overcome this autocovariance developed a model based on the distance the flow with using convolution kernel approach (moving average construction). Spatial model for a stream networks is widely used to monitor environmental on a river networks. In a case study of a river in province of West Java, the objective of this paper is to analyze a capability of a predictive on two environmental variables, potential of hydrogen (PH) and temperature using ordinary kriging. Several the empirical results show: (1) The best fit of autocovariance functions for temperature and potential hydrogen (ph) of Citarik River is linear which also yields the smallest root mean squared prediction error (RMSPE), (2) the spatial correlation values between the locations on upstream and on downstream of Citarik river exhibit decreasingly

Comparisons of Spatial Predictions of Conductivity on a Stream Network in an Appalachian Watershed

EPA Science Inventory

We made spatial predictions of specific conductance based on spatial stream network (SSN) modeling to compare conductivity measurements of components of the network, such as headwaters, tributaries, and mainstem, which have different spatial extents in a study Appalachian watersh...

MODELING FRAMEWORK FOR EVALUATING SEDIMENTATION IN STREAM NETWORKS: FOR USE IN SEDIMENT TMDL ANALYSIS

EPA Science Inventory

A modeling framework that can be used to evaluate sedimentation in stream networks is described. This methodology can be used to determine sediment Total Maximum Daily Loads (TMDLs) in sediment impaired waters, and provide the necessary hydrodynamic and sediment-related data t...

Detecting spatial ontogenetic niche shifts in complex dendritic ecological networks

USGS Publications Warehouse

Fields, William R.; Grant, Evan H. Campbell; Lowe, Winsor H.

2017-01-01

Ontogenetic niche shifts (ONS) are important drivers of population and community dynamics, but they can be difficult to identify for species with prolonged larval or juvenile stages, or for species that inhabit continuous habitats. Most studies of ONS focus on single transitions among discrete habitat patches at local scales. However, for species with long larval or juvenile periods, affinity for particular locations within connected habitat networks may differ among cohorts. The resulting spatial patterns of distribution can result from a combination of landscape-scale habitat structure, position of a habitat patch within a network, and local habitat characteristics—all of which may interact and change as individuals grow. We estimated such spatial ONS for spring salamanders (Gyrinophilus porphyriticus), which have a larval period that can last 4 years or more. Using mixture models to identify larval cohorts from size frequency data, we fit occupancy models for each age class using two measures of the branching structure of stream networks and three measures of stream network position. Larval salamander cohorts showed different preferences for the position of a site within the stream network, and the strength of these responses depended on the basin-wide spatial structure of the stream network. The isolation of a site had a stronger effect on occupancy in watersheds with more isolated headwater streams, while the catchment area, which is associated with gradients in stream habitat, had a stronger effect on occupancy in watersheds with more paired headwater streams. Our results show that considering the spatial structure of habitat networks can provide new insights on ONS in long-lived species.

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

USGS Publications Warehouse

Letcher, Benjamin; Hocking, Daniel; O'Neil, Kyle; Whiteley, Andrew R.; Nislow, Keith H.; O'Donnell, Matthew

2016-01-01

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

A stream temperature model for the Peace-Athabasca River basin

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

Water temperature plays a fundamental role in water ecosystem functioning. Because it regulates flow energy and metabolic rates in organism productivity over a broad spectrum of space and time scales, water temperature constitutes an important indicator of aquatic ecosystems health. In cold region basins, stream water temperature modelling is also fundamental to predict ice freeze-up and break-up events in order to improve flood management. Multiple model approaches such as linear and multivariable regression methods, neural network and thermal energy budged models have been developed and implemented to simulate stream water temperature. Most of these models have been applied to specific stream reaches and trained using observed data, but very little has been done to simulate water temperature in large catchment river networks. We present the coupling of RBM model, a semi-Lagrangian water temperature model for advection-dominated river system, and MESH, a semi-distributed hydrological model, to simulate stream water temperature in river catchments. The coupled models are implemented in the Peace-Athabasca River basin in order to analyze the variation in stream temperature regimes under changing hydrological and meteorological conditions. Uncertainty of stream temperature simulations is also assessed in order to determine the degree of reliability of the estimates.

Modeling stream network-scale variation in Coho salmon overwinter survival and smolt size

Treesearch

Joseph L. Ebersole; Mike E. Colvin; Parker J. Wigington; Scott G. Leibowitz; Joan P. Baker; Jana E. Compton; Bruce A. Miller; Michael A. Carins; Bruce P. Hansen; Henry R. La Vigne

2009-01-01

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over 3 years. Contributing basin area explained the majority of spatial...

Applications of a New England stream temperature model to evaluate distribution of thermal regimes and sensitivity to change in riparian condition

EPA Science Inventory

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that ext...

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation.

PubMed

Holcomb, David A; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

2018-06-25

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

A feedback model of figure-ground assignment.

PubMed

Domijan, Drazen; Setić, Mia

2008-05-30

A computational model is proposed in order to explain how bottom-up and top-down signals are combined into a unified perception of figure and background. The model is based on the interaction between the ventral and the dorsal stream. The dorsal stream computes saliency based on boundary signals provided by the simple and the complex cortical cells. Output from the dorsal stream is projected to the surface network which serves as a blackboard on which the surface representation is formed. The surface network is a recurrent network which segregates different surfaces by assigning different firing rates to them. The figure is labeled by the maximal firing rate. Computer simulations showed that the model correctly assigns figural status to the surface with a smaller size, a greater contrast, convexity, surroundedness, horizontal-vertical orientation and a higher spatial frequency content. The simple gradient of activity in the dorsal stream enables the simulation of the new principles of the lower region and the top-bottom polarity. The model also explains how the exogenous attention and the endogenous attention may reverse the figural assignment. Due to the local excitation in the surface network, neural activity at the cued region will spread over the whole surface representation. Therefore, the model implements the object-based attentional selection.

Spatial Statistical Network Models for Stream and River Temperatures in the Chesapeake Bay Watershed

EPA Science Inventory

Numerous metrics have been proposed to describe stream/river thermal regimes, and researchers are still struggling with the need to describe thermal regimes in a parsimonious fashion. Regional temperature models are needed for characterizing and mapping current stream thermal re...

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

Spatial Statistical Network Models for Stream and River Temperature in the Chesapeake Bay Watershed, USA

EPA Science Inventory

Regional temperature models are needed for characterizing and mapping stream thermal regimes, establishing reference conditions, predicting future impacts and identifying critical thermal refugia. Spatial statistical models have been developed to improve regression modeling techn...

Effects of stream topology on ecological community results from neutral models

EPA Science Inventory

While neutral theory and models have stimulated considerable literature, less well investigated is the effect of topology on neutral metacommunity model simulations. We implemented a neutral metacommunity model using two different stream network topologies, a widely branched netw...

WASP7 Stream Transport - Model Theory and User's Guide: Supplement to Water Quality Analysis Simulation Program (WASP) User Documentation

EPA Science Inventory

The standard WASP7 stream transport model calculates water flow through a branching stream network that may include both free-flowing and ponded segments. This supplemental user manual documents the hydraulic algorithms, including the transport and hydrogeometry equations, the m...

How has climate change altered network connectivity in a mountain stream network?

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

2017-12-01

Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish migration) and indirectly (e.g., stream temperature modeling). Additionally, our results inform management and regulatory needs such as estimating connectivity for entire river networks as a basis for regulation, and identifying the complexity of a shifting baseline in identifying a regulatory basis.

Potential Stream Density in Mid-Atlantic U.S. Watersheds

PubMed Central

Elmore, Andrew J.; Julian, Jason P.; Guinn, Steven M.; Fitzpatrick, Matthew C.

2013-01-01

Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confounding efforts to understand the impacts of land use on stream ecosystems. Here we report on research that predicts stream presence from coupled field observations of headwater stream channels and terrain variables that were calculated both locally and as an average across the watershed upstream of any location on the landscape. Our approach used maximum entropy modeling (MaxEnt), a robust method commonly implemented to model species distributions that requires information only on the presence of the entity of interest. In validation, the method correctly predicts the presence of 86% of all 10-m stream segments and errors are low (<1%) for catchments larger than 10 ha. We apply this model to the entire Potomac River watershed (37,800 km2) and several adjacent watersheds to map stream density and compare our results with the National Hydrography Dataset (NHD). We find that NHD underestimates stream density by up to 250%, with errors being greatest in the densely urbanized cities of Washington, DC and Baltimore, MD and in regions where the NHD has never been updated from its original, coarse-grain mapping. This work is the most ambitious attempt yet to map stream networks over a large region and will have lasting implications for modeling and conservation efforts. PMID:24023704

Summer stream water temperature models for Great Lakes streams: New York

USGS Publications Warehouse

Murphy, Marilyn K.; McKenna, James E.; Butryn, Ryan S.; McDonald, Richard P.

2010-01-01

Temperature is one of the most important environmental influences on aquatic organisms. It is a primary driver of physiological rates and many abiotic processes. However, despite extensive research and measurements, synoptic estimates of water temperature are not available for most regions, limiting our ability to make systemwide and large-scale assessments of aquatic resources or estimates of aquatic species abundance and biodiversity. We used subwatershed averaging of point temperature measurements and associated multiscale landscape habitat conditions from over 3,300 lotic sites throughout New York State to develop and train artificial neural network models. Separate models predicting water temperature (in cold, cool, and warm temperature classes) within small catchment–stream order groups were developed for four modeling units, which together encompassed the entire state. Water temperature predictions were then made for each stream segment in the state. All models explained more than 90% of data variation. Elevation, riparian forest cover, landscape slope, and growing degree-days were among the most important model predictors of water temperature classes. Geological influences varied among regions. Predicted temperature distributions within stream networks displayed patterns of generally increasing temperature downstream but were patchy due to the averaging of water temperatures within stream size-classes of small drainages. Models predicted coldwater streams to be most numerous and warmwater streams to be generally associated with the largest rivers and relatively flat agricultural areas and urban areas. Model predictions provide a complete, georeferenced map of summer daytime mean stream temperature potential throughout New York State that can be used for planning and assessment at spatial scales from the stream segment class to the entire state.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Regional-scale comparison of the effects of lakes and reservoirs versus streams on water quality

NASA Astrophysics Data System (ADS)

Schmadel, N. M.; Harvey, J. W.; Alexander, R. B.; Schwarz, G. E.; Moore, R. B.; Gomez-Velez, J. D.; Scott, D.; Boyer, E. W.

2017-12-01

Recent physically-based modeling at regional scales has revealed that the potential for biogeochemical transformations of nitrogen—such as denitrification—along a fluvial network may be dominated by hyporheic exchange. However, fluvial networks are comprised of a mosaic of water body types from headwaters to coasts, each potentially playing a different role in water quality. For example, depending on conditions, streams or ponded waters (lakes, reservoirs) may disproportionately act as biogeochemical hotspots. Because downstream water quality reflects an accumulation or blending of processes, it is not clear how ponded waters that vary in number and location across a network influence downstream water quality. Here, we quantified the effects of ponded waters along fluvial networks on the fate of nitrogen in the Northeastern and Mid-Atlantic regions of the United States. We used a spatially referenced model calibrated to land use and water quality data and considered both the number and location of ponded waters across the regions. We experimentally modeled the replacement of nearly 30,000 ponded waters with streams using corresponding estimates of hydraulic geometry and nitrogen removal, thereby providing a direct comparison of the role of ponded waters versus the role of streams with regard to nitrogen removal. We found that pond size, density (total pond area to drainage area), and position within a network were all important factors. These findings complement field measurements and reach-scale modeling by upscaling to reveal cumulative effects. This regional-scale modeling of ponded waters is useful toward developing better strategies for prioritizing creation of new reservoirs or removal of dams, or informing stream restoration at ecologically-relevant scales. This research is a product of the John Wesley Powell Center River Corridor Working Group. powellcenter.usgs.gov/view-project

Predicting thermal regimes of stream networks across the northeast United States: Natural and anthropogenic influences

EPA Science Inventory

We used STARS (Spatial Tools for the Analysis of River Systems), an ArcGIS geoprocessing toolbox, to create spatial stream networks. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance...

Objective assessment of MPEG-2 video quality

NASA Astrophysics Data System (ADS)

Gastaldo, Paolo; Zunino, Rodolfo; Rovetta, Stefano

2002-07-01

The increasing use of video compression standards in broadcasting television systems has required, in recent years, the development of video quality measurements that take into account artifacts specifically caused by digital compression techniques. In this paper we present a methodology for the objective quality assessment of MPEG video streams by using circular back-propagation feedforward neural networks. Mapping neural networks can render nonlinear relationships between objective features and subjective judgments, thus avoiding any simplifying assumption on the complexity of the model. The neural network processes an instantaneous set of input values, and yields an associated estimate of perceived quality. Therefore, the neural-network approach turns objective quality assessment into adaptive modeling of subjective perception. The objective features used for the estimate are chosen according to the assessed relevance to perceived quality and are continuously extracted in real time from compressed video streams. The overall system mimics perception but does not require any analytical model of the underlying physical phenomenon. The capability to process compressed video streams represents an important advantage over existing approaches, like avoiding the stream-decoding process greatly enhances real-time performance. Experimental results confirm that the system provides satisfactory, continuous-time approximations for actual scoring curves concerning real test videos.

Nitrogen retention in rivers: Model development and application to watersheds in the northeastern U.S.A.

USGS Publications Warehouse

Seitzinger, S.P.; Styles, R.V.; Boyer, E.W.; Alexander, R.B.; Billen, G.; Howarth, R.W.; Mayer, B.; Van Breemen, N.

2002-01-01

A regression model (RivR-N) was developed that predicts the proportion of N removed from streams and reservoirs as an inverse function of the water displacement time of the water body (ratio of water body depth to water time of travel). When applied to 16 drainage networks in the eastern U.S., the RivR-N model predicted that 37% to 76% of N input to these rivers is removed during transport through the river networks. Approximately half of that is removed in 1st through 4th order streams which account for 90% of the total stream length. The other half is removed in 5th order and higher rivers which account for only about 10% of the total stream length. Most N removed in these higher orders is predicted to originate from watershed loading to small and intermediate sized streams. The proportion of N removed from all streams in the watersheds (37-76%) is considerably higher than the proportion of N input to an individual reach that is removed in that reach (generally <20%) because of the cumulative effect of continued nitrogen removal along the entire flow path in downstream reaches. This generally has not been recognized in previous studies, but is critical to an evaluation of the total amount of N removed within a river network. At the river network scale, reservoirs were predicted to have a minimal effect on N removal. A fairly modest decrease (<10 percentage points) in the N removed at the river network scale was predicted when a third of the direct watershed loading was to the two highest orders compared to a uniform loading.

A bipartite fitness model for online music streaming services

NASA Astrophysics Data System (ADS)

Pongnumkul, Suchit; Motohashi, Kazuyuki

2018-01-01

This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

Comprehensive model-based prediction of micropollutants from diffuse sources in the Swiss river network

NASA Astrophysics Data System (ADS)

Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian

2014-05-01

Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering wastewater treatment plants. Only a small number of problematic substances are expected from grassland. Landfills and roadways are insignificant within the entire Swiss river network, but may locally lead to considerable water pollution. Considering all substance groups, pesticides and some heavy metals are the main polluters. Many pesticides are expected to exceed AA-EQS and in a substantial percentage of the river network. Modeling a large number of substances from many sources and a huge quantity of stream sections is only possible with a simple model. Nevertheless conclusions are robust and may indicate where and for what kind of substance groups additional efforts for water quality improvements should be undertaken.

Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA

USGS Publications Warehouse

Clayton, J.A.; Kean, J.W.

2010-01-01

Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.

Quantifying spatial and temporal patterns of flow intermittency using spatially contiguous runoff data

NASA Astrophysics Data System (ADS)

Yu (于松延), Songyan; Bond, Nick R.; Bunn, Stuart E.; Xu, Zongxue; Kennard, Mark J.

2018-04-01

River channel drying caused by intermittent stream flow is a widely-recognized factor shaping stream ecosystems. There is a strong need to quantify the distribution of intermittent streams across catchments to inform management. However, observational gauge networks provide only point estimates of streamflow variation. Increasingly, this limitation is being overcome through the use of spatially contiguous estimates of the terrestrial water-balance, which can also assist in estimating runoff and streamflow at large-spatial scales. Here we proposed an approach to quantifying spatial and temporal variation in monthly flow intermittency throughout river networks in eastern Australia. We aggregated gridded (5 × 5 km) monthly water-balance data with a hierarchically nested catchment dataset to simulate catchment runoff accumulation throughout river networks from 1900 to 2016. We also predicted zero flow duration for the entire river network by developing a robust predictive model relating measured zero flow duration (% months) to environmental predictor variables (based on 43 stream gauges). We then combined these datasets by using the predicted zero flow duration from the regression model to determine appropriate 'zero' flow thresholds for the modelled discharge data, which varied spatially across the catchments examined. Finally, based on modelled discharge data and identified actual zero flow thresholds, we derived summary metrics describing flow intermittency across the catchment (mean flow duration and coefficient-of-variation in flow permanence from 1900 to 2016). We also classified the relative degree of flow intermittency annually to characterise temporal variation in flow intermittency. Results showed that the degree of flow intermittency varied substantially across streams in eastern Australia, ranging from perennial streams flowing permanently (11-12 months) to strongly intermittent streams flowing 4 months or less of year. Results also showed that the temporal extent of flow intermittency varied dramatically inter-annually from 1900 to 2016, with the proportion of intermittent (weakly and strongly intermittent) streams ranging in length from 3% to nearly 100% of the river network, but there was no evidence of an increasing trend towards flow intermittency over this period. Our approach to generating spatially explicit and catchment-wide estimates of streamflow intermittency can facilitate improved ecological understanding and management of intermittent streams in Australia and around the world.

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

USGS Publications Warehouse

Alexander, Richard B.; Böhlke, John Karl; Boyer, Elizabeth W.; David, Mark B.; Harvey, Judson W.; Mulholland, Patrick J.; Seitzinger, Sybil P.; Tobias, Craig R.; Tonitto, Christina; Wollheim, Wilfred M.

2009-01-01

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly equally to seasonal and stream-size related variations in the percentage of the stream nitrate flux removed in each watershed.

Drainage networks after wildfire

USGS Publications Warehouse

Kinner, D.A.; Moody, J.A.

2005-01-01

Predicting runoff and erosion from watersheds burned by wildfires requires an understanding of the three-dimensional structure of both hillslope and channel drainage networks. We investigate the small-and large-scale structures of drainage networks using field studies and computer analysis of 30-m digital elevation model. Topologic variables were derived from a composite 30-m DEM, which included 14 order 6 watersheds within the Pikes Peak batholith. Both topologic and hydraulic variables were measured in the field in two smaller burned watersheds (3.7 and 7.0 hectares) located within one of the order 6 watersheds burned by the 1996 Buffalo Creek Fire in Central Colorado. Horton ratios of topologic variables (stream number, drainage area, stream length, and stream slope) for small-scale and large-scale watersheds are shown to scale geometrically with stream order (i.e., to be scale invariant). However, the ratios derived for the large-scale drainage networks could not be used to predict the rill and gully drainage network structure. Hydraulic variables (width, depth, cross-sectional area, and bed roughness) for small-scale drainage networks were found to be scale invariant across 3 to 4 stream orders. The relation between hydraulic radius and cross-sectional area is similar for rills and gullies, suggesting that their geometry can be treated similarly in hydraulic modeling. Additionally, the rills and gullies have relatively small width-to-depth ratios, implying sidewall friction may be important to the erosion and evolutionary process relative to main stem channels.

A GIS-based groundwater travel time model to evaluate stream nitrate concentration reductions from land use change

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2007-01-01

Excessive nitrate-nitrogen (nitrate) loss from agricultural watersheds is an environmental concern. A common conservation practice to improve stream water quality is to retire vulnerable row croplands to grass. In this paper, a groundwater travel time model based on a geographic information system (GIS) analysis of readily available soil and topographic variables was used to evaluate the time needed to observe stream nitrate concentration reductions from conversion of row crop land to native prairie in Walnut Creek watershed, Iowa. Average linear groundwater velocity in 5-m cells was estimated by overlaying GIS layers of soil permeability, land slope (surrogates for hydraulic conductivity and gradient, respectively) and porosity. Cells were summed backwards from the stream network to watershed divide to develop a travel time distribution map. Results suggested that groundwater from half of the land planted in prairie has reached the stream network during the 10 years of ongoing water quality monitoring. The mean travel time for the watershed was estimated to be 10.1 years, consistent with results from a simple analytical model. The proportion of land in the watershed and subbasins with prairie groundwater reaching the stream (10-22%) was similar to the measured reduction of stream nitrate (11-36%). Results provide encouragement that additional nitrate reductions in Walnut Creek are probable in the future as reduced nitrate groundwater from distal locations discharges to the stream network in the coming years. The high spatial resolution of the model (5-m cells) and its simplicity may make it potentially applicable for land managers interested in communicating lag time issues to the public, particularly related to nitrate concentration reductions over time. ?? 2007 Springer-Verlag.

Automated identification of stream-channel geomorphic features from high‑resolution digital elevation models in West Tennessee watersheds

USGS Publications Warehouse

Cartwright, Jennifer M.; Diehl, Timothy H.

2017-01-17

High-resolution digital elevation models (DEMs) derived from light detection and ranging (lidar) enable investigations of stream-channel geomorphology with much greater precision than previously possible. The U.S. Geological Survey has developed the DEM Geomorphology Toolbox, containing seven tools to automate the identification of sites of geomorphic instability that may represent sediment sources and sinks in stream-channel networks. These tools can be used to modify input DEMs on the basis of known locations of stormwater infrastructure, derive flow networks at user-specified resolutions, and identify possible sites of geomorphic instability including steep banks, abrupt changes in channel slope, or areas of rough terrain. Field verification of tool outputs identified several tool limitations but also demonstrated their overall usefulness in highlighting likely sediment sources and sinks within channel networks. In particular, spatial clusters of outputs from multiple tools can be used to prioritize field efforts to assess and restore eroding stream reaches.

Scaling Dissolved Nutrient Removal in River Networks: A Comparative Modeling Investigation

NASA Astrophysics Data System (ADS)

Ye, Sheng; Reisinger, Alexander J.; Tank, Jennifer L.; Baker, Michelle A.; Hall, Robert O.; Rosi, Emma J.; Sivapalan, Murugesu

2017-11-01

Along the river network, water, sediment, and nutrients are transported, cycled, and altered by coupled hydrological and biogeochemical processes. Our current understanding of the rates and processes controlling the cycling and removal of dissolved inorganic nutrients in river networks is limited due to a lack of empirical measurements in large, (nonwadeable), rivers. The goal of this paper was to develop a coupled hydrological and biogeochemical process model to simulate nutrient uptake at the network scale during summer base flow conditions. The model was parameterized with literature values from headwater streams, and empirical measurements made in 15 rivers with varying hydrological, biological, and topographic characteristics, to simulate nutrient uptake at the network scale. We applied the coupled model to 15 catchments describing patterns in uptake for three different solutes to determine the role of rivers in network-scale nutrient cycling. Model simulation results, constrained by empirical data, suggested that rivers contributed proportionally more to nutrient removal than headwater streams given the fraction of their length represented in a network. In addition, variability of nutrient removal patterns among catchments was varied among solutes, and as expected, was influenced by nutrient concentration and discharge. Net ammonium uptake was not significantly correlated with any environmental descriptor. In contrast, net daily nitrate removal was linked to suspended chlorophyll a (an indicator of primary producers) and land use characteristics. Finally, suspended sediment characteristics and agricultural land use were correlated with net daily removal of soluble reactive phosphorus, likely reflecting abiotic sorption dynamics. Rivers are understudied relative to streams, and our model suggests that rivers can contribute more to network-scale nutrient removal than would be expected based upon their representative fraction of network channel length.

A Stream Morphology Classification for Eco-hydraulic Purposes Based on Geospatial Data: a Solute Transport Application Case

NASA Astrophysics Data System (ADS)

Jiménez Jaramillo, M. A.; Camacho Botero, L. A.; Vélez Upegui, J. I.

2010-12-01

Variation in stream morphology along a basin drainage network leads to different hydraulic patterns and sediment transport processes. Moreover, solute transport processes along streams, and stream habitats for fisheries and microorganisms, rely on stream corridor structure, including elements such as bed forms, channel patterns, riparian vegetation, and the floodplain. In this work solute transport processes simulation and stream habitat identification are carried out at the basin scale. A reach-scale morphological classification system based on channel slope and specific stream power was implemented by using digital elevation models and hydraulic geometry relationships. Although the morphological framework allows identification of cascade, step-pool, plane bed and pool-riffle morphologies along the drainage network, it still does not account for floodplain configuration and bed-forms identification of those channel types. Hence, as a first application case in order to obtain parsimonious three-dimensional characterizations of drainage channels, the morphological framework has been updated by including topographical floodplain delimitation through a Multi-resolution Valley Bottom Flatness Index assessing, and a stochastic bed form representation of the step-pool morphology. Model outcomes were tested in relation to in-stream water storage for different flow conditions and representative travel times according to the Aggregated Dead Zone -ADZ- model conceptualization of solute transport processes.

Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model

NASA Astrophysics Data System (ADS)

Zhang, Hong; Hou, Rui; Yi, Lei; Meng, Juan; Pan, Zhisong; Zhou, Yuhuan

2016-07-01

The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.

Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

NASA Astrophysics Data System (ADS)

Dey, S.; Saksena, S.; Merwade, V.

2017-12-01

Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

RIPARIAN SHADE CONTROLS ON STREAM TEMPERATURE NOW AND IN THE FUTURE ACROSS TRIBUTARIES OF THE COLUMBIA RIVER, USA

EPA Science Inventory

Future climates may warm stream temperatures altering aquatic communities and threatening socioeconomically-important species. These impacts will vary across large spatial extents and require special evaluation tools. Statistical stream network models (SSNs) account for spatial a...

Nitrous oxide emission from denitrification in stream and river networks

USGS Publications Warehouse

Beaulieu, J.J.; Tank, J.L.; Hamilton, S.K.; Wollheim, W.M.; Hall, R.O.; Mulholland, P.J.; Peterson, B.J.; Ashkenas, L.R.; Cooper, L.W.; Dahm, Clifford N.; Dodds, W.K.; Grimm, N. B.; Johnson, S.L.; McDowell, W.H.; Poole, G.C.; Maurice, Valett H.; Arango, C.P.; Bernot, M.J.; Burgin, A.J.; Crenshaw, C.L.; Helton, A.M.; Johnson, L.T.; O'Brien, J. M.; Potter, J.D.; Sheibley, R.W.; Sobota, D.J.; Thomas, S.M.

2011-01-01

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N 2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3-) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3-. We suggest that increased stream NO3- loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg??y -1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.

Spatial relationships in a dendritic network: the herpetofaunal metacommunity of the Mattole River catchment of northwest California.

Treesearch

Hartwell Welsh; Garth Hodgson

2010-01-01

We investigated the aquatic and riparian herpetofauna in a 789 km² river catchment in northwest California to examine competing theories of biotic community structuring in catchment stream networks. Research in fluvial geomorphology has resulted in multi-scale models of dynamic processes that cyclically create, maintain, and destroy environments in stream...

Spatial Patterns of Road-Induced Backwater Sediment Storage Across A Rural to Urban Gradient

NASA Astrophysics Data System (ADS)

Copeland, M.; Bain, D.

2017-12-01

Road networks dominate many landscapes and often interact with stream networks to alter basin sediment dynamics. Currently, conceptual models of catchment-scale sediment fluxes remain at a coarse scale (i.e., the entire catchment) and are unable to resolve important human-driven sediment storage processes. The spatio-temporal complexity of the interactions between road networks and streams has made it challenging to infer the fine-scale impacts of road crossings on fluvial systems. Here, road crossings in multiple drainage networks and the associated backwater sediment accumulations are examined along a rural to urban gradient around Pittsburgh, PA. Preliminary results indicate that upstream drainage area, channel slope, and human activities control stream crossing type and therefore drive associated sediment accumulation, particularly in urban headwater channels. The data indicate that the combination of land use intensity and infrastructure age influences the volume of sediment trapped in road-induced backwaters. Clarification of the coupled human, road-building, and natural stream adjustments will allow for more effective treatments of fluvial impacts, such as the "urban stream syndrome."

ONE-DIMENSIONAL HYDRODYNAMIC/SEDIMENT TRANSPORT MODEL FOR STREAM NETWORKS: TECHNICAL REPORT

EPA Science Inventory

This technical report describes a new sediment transport model and the supporting post-processor, and sampling procedures for sediments in streams. Specifically, the following items are described herein:

EFDC1D - This is a new one-dimensional hydrodynamic and sediment tr...

Spatial statistical network models for stream and river temperature in New England, USA

EPA Science Inventory

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May–September growing ...

Similarity of Stream Width Distributions Across Headwater Systems

NASA Astrophysics Data System (ADS)

Allen, G. H.; Pavelsky, T.; Barefoot, E. A.; Tashie, A.; Butman, D. E.

2016-12-01

The morphology and abundance of streams control the rates of hydraulic and biogeochemical exchange between streams, groundwater, and the atmosphere. In large river systems, studies have used remote sensing to quantify river morphology, and have found that the relationship between river width and abundance is fractal, such that narrow rivers are proportionally more common than wider rivers. However, in headwater systems (stream order 1-3), where many biogeochemical reactions are most rapid, the relationship between stream width and abundance is unknown, reducing the certainty of biogeochemical flux estimates. To constrain this uncertainty, we surveyed two components of stream morphology (wetted stream width and length) in seven physiographically contrasting stream networks in Kings Creek in Konza Prarie, KS; Sagehen Creek in the N. Sierra Nevada Mtns., CA; Elder Creek in Angelo Coast Range Preserve, CA; Caribou Creek in the Caribou Poker Creek Research Watershed, AK; V40 Stream, NZ; Blue Duck Creek, NZ; Stony Creek in Duke Forest, NC. To assess temporal variations, we also surveyed stream geometry in a subcatchment of Stony Creek six times over a range of moderate streamflow conditions (discharge less than 90 percentile of gauge record). Here we show a strikingly consistent gamma statistical distribution of stream width in all surveys and a characteristic most abundant stream width of 32±7 cm independent of flow conditions or basin size. This consistency is remarkable given the substantial physical diversity among the studied catchments. We propose a model that invokes network topology theory and downstream hydraulic geometry to show that, as active drainage networks expand and contract in response to changes in streamflow, the most abundant stream width remains approximately static. This framework can be used to better extrapolate stream size and abundance from large rivers to small headwater streams, with significant impact on understanding of the hydraulic, ecological, and biogeochemical functions of stream networks.

Stream isotherm shifts from climate change and implications for distributions of ectothermic organisms

Treesearch

Daniel J. Isaak; Bruce E. Rieman

2013-01-01

Stream ecosystems are especially vulnerable to climate warming because most aquatic organisms are ectothermic and live in dendritic networks that are easily fragmented. Many bioclimatic models predict significant range contractions in stream biotas, but subsequent biological assessments have rarely been done to determine the accuracy of these predictions. Assessments...

Research on quality metrics of wireless adaptive video streaming

NASA Astrophysics Data System (ADS)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

Evasion of CO2 from streams - the dominant component of the carbon export through the aquatic conduit in a boreal landscape.

PubMed

Wallin, Marcus B; Grabs, Thomas; Buffam, Ishi; Laudon, Hjalmar; Agren, Ånneli; Öquist, Mats G; Bishop, Kevin

2013-03-01

Evasion of gaseous carbon (C) from streams is often poorly quantified in landscape C budgets. Even though the potential importance of the capillary network of streams as C conduits across the land-water-atmosphere interfaces is sometimes mentioned, low-order streams are often left out of budget estimates due to being poorly characterized in terms of gas exchange and even areal surface coverage. We show that evasion of C is greater than all the total dissolved C (both organic and inorganic) exported downstream in the waters of a boreal landscape. In this study evasion of carbon dioxide (CO2 ) from running waters within a 67 km(2) boreal catchment was studied. During a 4 year period (2006-2009) 13 streams were sampled on 104 different occasions for dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC). From a locally determined model of gas exchange properties, we estimated the daily CO2 evasion with a high-resolution (5 × 5 m) grid-based stream evasion model comprising the entire ~100 km stream network. Despite the low areal coverage of stream surface, the evasion of CO2 from the stream network constituted 53% (5.0 (±1.8) g C m(-2)  yr(-1) ) of the entire stream C flux (9.6 (±2.4) g C m(-2)  yr(-1) ) (lateral as DIC, DOC, and vertical as CO2 ). In addition, 72% of the total CO2 loss took place already in the first- and second-order streams. This study demonstrates the importance of including CO2 evasion from low-order boreal streams into landscape C budgets as it more than doubled the magnitude of the aquatic conduit for C from this landscape. Neglecting this term will consequently result in an overestimation of the terrestrial C sink strength in the boreal landscape. © 2012 Blackwell Publishing Ltd.

Implementation of Dynamic Extensible Adaptive Locally Exchangeable Measures (IDEALEM) v 0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sim, Alex; Lee, Dongeun; Wu, K. John

2016-03-04

Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable. One possible solution to reduce the storage of vast amounts ofmore » measured data is to store a random sample, such as one out of 1000 network packets. However, such static sampling methods (linear sampling) have drawbacks: (1) it is not scalable for high-rate streaming data, and (2) there is no guarantee of reflecting the underlying distribution. In this software, we implemented a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.« less

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

Modelling dendritic ecological networks in space: An integrated network perspective

Treesearch

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

Network analysis applications in hydrology

NASA Astrophysics Data System (ADS)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Applications of a New England stream temperature model to ...

EPA Pesticide Factsheets

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that extend into Canada (Detenbeck et al., in review). We excluded stream temperature observations within one kilometer downstream of dams from our model development, so our predictions for those reaches represent potential thermal regimes in the absence of dam effects. We used stream thermal thresholds for mean July temperatures delineating transitions between coldwater, transitional coolwater, and warmwater fish communities derived by Beauchene et al. (2014) to classify expected stream and river thermal regimes across New England. Within the model domain and based on 2006 land-use and air temperatures, the model predicts that 21.8% of stream + river kilometers would support coldwater fish communities (mean July water temperatures 22.3 degrees C mean July temperatures). Application of the model allows us to assess potential condition given full riparian zone restoration as well as potential loss of cold or coolwater habitat given loss of riparian shading. Given restoration of all ripa

A modelling study of hyporheic exchange pattern and the sequence, size, and spacing of stream bedforms in mountain stream networks, Oregon, USA.

Treesearch

Michael N. Gooseff; Justin K. Anderson; Steven M. Wondzell; Justin LaNier; Roy Haggerty

2005-01-01

Studies of hyporheic exchange flows have identified physical features of channels that control exchange flow at the channel unit scale, namely slope breaks in the longitudinal profile of streams that generate subsurface head distributions. We recently completed a field study that suggested channel unit spacing in stream longitudinal profiles can be used to predict the...

Real-Time Earthquake Monitoring with Spatio-Temporal Fields

NASA Astrophysics Data System (ADS)

Whittier, J. C.; Nittel, S.; Subasinghe, I.

2017-10-01

With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

Nitrous oxide emission from denitrification in stream and river networks

PubMed Central

Beaulieu, Jake J.; Tank, Jennifer L.; Hamilton, Stephen K.; Wollheim, Wilfred M.; Hall, Robert O.; Mulholland, Patrick J.; Peterson, Bruce J.; Ashkenas, Linda R.; Cooper, Lee W.; Dahm, Clifford N.; Dodds, Walter K.; Grimm, Nancy B.; Johnson, Sherri L.; McDowell, William H.; Poole, Geoffrey C.; Valett, H. Maurice; Arango, Clay P.; Bernot, Melody J.; Burgin, Amy J.; Crenshaw, Chelsea L.; Helton, Ashley M.; Johnson, Laura T.; O'Brien, Jonathan M.; Potter, Jody D.; Sheibley, Richard W.; Sobota, Daniel J.; Thomas, Suzanne M.

2011-01-01

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3−. We suggest that increased stream NO3− loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg·y−1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change. PMID:21173258

Anomaly Detection in Dynamic Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turcotte, Melissa

2014-10-14

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. Amore » second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.« less

EPA Office of Water (OW): 2002 SPARROW Total NP (Catchments)

EPA Pesticide Factsheets

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling tool with output that allows the user to interpret water quality monitoring data at the regional and sub-regional scale. The model relates in-stream water-quality measurements to spatially referenced characteristics of watersheds, including pollutant sources and environmental factors that affect rates of pollutant delivery to streams from the land and aquatic, in-stream processing . The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and non-point (or ??diffuse??) sources on land to rivers and through the stream and river network. SPARROW estimates contaminant concentrations, loads (or ??mass,?? which is the product of concentration and streamflow), and yields in streams (mass of nitrogen and of phosphorus entering a stream per acre of land). It empirically estimates the origin and fate of contaminants in streams and receiving bodies, and quantifies uncertainties in model predictions. The model predictions are illustrated through detailed maps that provide information about contaminant loadings and source contributions at multiple scales for specific stream reaches, basins, or other geographic areas.

Applications of remote sensing to stream discharge predictions

NASA Technical Reports Server (NTRS)

Krause, F. R.; Winn, C. B.

1972-01-01

A feasibility study has been initiated on the use of remote earth observations for augmenting stream discharge prediction for the design and/or operation of major reservoir systems, pumping systems and irrigation systems. The near-term objectives are the interpolation of sparsely instrumented precipitation surveillance networks and the direct measurement of water loss by evaporation. The first steps of the study covered a survey of existing reservoir systems, stream discharge prediction methods, gage networks and the development of a self-adaptive variation of the Kentucky Watershed model, SNOPSET, that includes snowmelt. As a result of these studies, a special three channel scanner is being built for a small aircraft, which should provide snow, temperature and water vapor maps for the spatial and temporal interpolation of stream gages.

Regional interpretation of water-quality monitoring data

USGS Publications Warehouse

Smith, Richard A.; Schwarz, Gregory E.; Alexander, Richard B.

1997-01-01

We describe a method for using spatially referenced regressions of contaminant transport on watershed attributes (SPARROW) in regional water-quality assessment. The method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity. The regression equation relates measured transport rates in streams to spatially referenced descriptors of pollution sources and land-surface and stream-channel characteristics. Regression models of total phosphorus (TP) and total nitrogen (TN) transport are constructed for a region defined as the nontidal conterminous United States. Observed TN and TP transport rates are derived from water-quality records for 414 stations in the National Stream Quality Accounting Network. Nutrient sources identified in the equations include point sources, applied fertilizer, livestock waste, nonagricultural land, and atmospheric deposition (TN only). Surface characteristics found to be significant predictors of land-water delivery include soil permeability, stream density, and temperature (TN only). Estimated instream decay coefficients for the two contaminants decrease monotonically with increasing stream size. TP transport is found to be significantly reduced by reservoir retention. Spatial referencing of basin attributes in relation to the stream channel network greatly increases their statistical significance and model accuracy. The method is used to estimate the proportion of watersheds in the conterminous United States (i.e., hydrologic cataloging units) with outflow TP concentrations less than the criterion of 0.1 mg/L, and to classify cataloging units according to local TN yield (kg/km2/yr).

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Ning; Yearsley, John; Voisin, Nathalie

2015-05-15

Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well asmore » a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.« less

Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

PubMed

Duda, Piotr; Jaworski, Maciej; Rutkowski, Leszek

2018-03-01

One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated memory is constant and the models incorporate changes of investigated streams. A vast majority of available methods have been developed for data stream classification and only a few of them attempted to solve regression problems, using various heuristic approaches. In this paper, we develop mathematically justified regression models working in a time-varying environment. More specifically, we study incremental versions of generalized regression neural networks, called IGRNNs, and we prove their tracking properties - weak (in probability) and strong (with probability one) convergence assuming various concept drift scenarios. First, we present the IGRNNs, based on the Parzen kernels, for modeling stationary systems under nonstationary noise. Next, we extend our approach to modeling time-varying systems under nonstationary noise. We present several types of concept drifts to be handled by our approach in such a way that weak and strong convergence holds under certain conditions. Finally, in the series of simulations, we compare our method with commonly used heuristic approaches, based on forgetting mechanism or sliding windows, to deal with concept drift. Finally, we apply our concept in a real life scenario solving the problem of currency exchange rates prediction.

From bottles to stream reaches and networks: Consequences of scale in how we interpret the function of freshwaters in the carbon cycle

NASA Astrophysics Data System (ADS)

Hotchkiss, E. R.

2017-12-01

Freshwater biological processes can alter the quantity and quality of organic carbon (OC) inputs from land before they are transported downstream, but the relative role of hydrologic transport and in-stream processing is still not well quantified at the scale of fluvial networks. Despite much research on the role of biology and hydrology in governing the form and fate of C in inland waters, conclusions about the function of freshwater ecosystems in modifying OC still largely depend on where we draw our ecosystem boundaries, i.e., the spatial scale of measurements used to assess OC transformations. Here I review freshwater OC uptake rates derived from bioassay incubations, synoptic modeling, reach-scale experiments, and ecosystem OC spiraling estimates. Median OC uptake velocities from standard bioassay incubations (0.02 m/d) and synoptic modeling (0.04 m/d) are 1-2 orders of magnitude lower than reach-scale experimental DOC additions and ecosystem OC spiraling estimates (2.2 and 0.27 m/d, respectively) in streams and rivers. Together, ecosystem metabolism and OC fluxes can be used to estimate the distance OC travels before being consumed and respired as CO2 through biological processes (i.e., OC spiraling), allowing for a more mechanistic understanding of the role of ecosystem processes and hydrologic fluxes in modifying downstream OC transport. Beyond the reach scale, data from stream network and stream-lake-river modeling simulations show how we may use linked sampling sites within networks to better understand the integrated sources and fate of OC in freshwaters. We currently underestimate the role of upstream processes in contributing to downstream fluxes: moving from single-ecosystem comparisons to linked-ecosystem simulations increases the contribution of in situ OC processing to CO2 emissions from 30% to >40%. Insights from literature reviews, ecosystem process measurements, and model simulations provide a framework for future considerations of integrated C transport, transformations, and fate when scaling patterns and processes in inland waters.

A statistical method to predict flow permanence in dryland streams from time series of stream temperature

USGS Publications Warehouse

Arismendi, Ivan; Dunham, Jason B.; Heck, Michael; Schultz, Luke; Hockman-Wert, David

2017-01-01

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.

A simple prioritization tool to diagnose impairment of stream temperature for coldwater fishes in the Great Basin

USGS Publications Warehouse

Falke, Jeffrey A.; Dunham, Jason B.; Hockman-Wert, David; Pahl, Randy

2016-01-01

We provide a simple framework for diagnosing the impairment of stream water temperature for coldwater fishes across broad spatial extents based on a weight-of-evidence approach that integrates biological criteria, species distribution models, and geostatistical models of stream temperature. As a test case, we applied our approach to identify stream reaches most likely to be thermally impaired for Lahontan Cutthroat Trout Oncorhynchus clarkii henshawi in the upper Reese River, located in the northern Great Basin, Nevada. We first evaluated the capability of stream thermal regime descriptors to explain variation across 170 sites, and we found that the 7-d moving average of daily maximum stream temperatures (7DADM) provided minimal among-descriptor redundancy and, based on an upper threshold of 20°C, was also a good indicator of acute and chronic thermal stress. Next, we quantified the range of Lahontan Cutthroat Trout within our study area using a geographic distribution model. Finally, we used a geostatistical model to assess spatial variation in 7DADM and predict potential thermal impairment at the stream reach scale. We found that whereas 38% of reaches in our study area exceeded a 7DADM of 20°C and 35% were significantly warmer than predicted, only 17% both exceeded the biological criterion and were significantly warmer than predicted. This filtering allowed us to identify locations where physical and biological impairment were most likely within the network and that would represent the highest management priorities. Although our approach lacks the precision of more comprehensive approaches, it provides a broader context for diagnosing impairment and is a useful means of identifying priorities for more detailed evaluations across broad and heterogeneous stream networks.

Retrieval of Sentence Sequences for an Image Stream via Coherence Recurrent Convolutional Networks.

PubMed

Park, Cesc Chunseong; Kim, Youngjin; Kim, Gunhee

2018-04-01

We propose an approach for retrieving a sequence of natural sentences for an image stream. Since general users often take a series of pictures on their experiences, much online visual information exists in the form of image streams, for which it would better take into consideration of the whole image stream to produce natural language descriptions. While almost all previous studies have dealt with the relation between a single image and a single natural sentence, our work extends both input and output dimension to a sequence of images and a sequence of sentences. For retrieving a coherent flow of multiple sentences for a photo stream, we propose a multimodal neural architecture called coherence recurrent convolutional network (CRCN), which consists of convolutional neural networks, bidirectional long short-term memory (LSTM) networks, and an entity-based local coherence model. Our approach directly learns from vast user-generated resource of blog posts as text-image parallel training data. We collect more than 22 K unique blog posts with 170 K associated images for the travel topics of NYC, Disneyland , Australia, and Hawaii. We demonstrate that our approach outperforms other state-of-the-art image captioning methods for text sequence generation, using both quantitative measures and user studies via Amazon Mechanical Turk.

Evaluation of Elevation, Slope and Stream Network Quality of SPOT Dems

NASA Astrophysics Data System (ADS)

El Hage, M.; Simonetto, E.; Faour, G.; Polidori, L.

2012-07-01

Digital elevation models are considered the most useful data for dealing with geomorphology. The quality of these models is an important issue for users. This quality concerns position and shape. Vertical accuracy is the most assessed in many studies and shape quality is often neglected. However, both of them have an impact on the quality of the final results for a particular application. For instance, the elevation accuracy is required for orthorectification and the shape quality for geomorphology and hydrology. In this study, we deal with photogrammetric DEMs and show the importance of the quality assessment of both elevation and shape. For this purpose, we produce several SPOT HRV DEMs with the same dataset but with different template size, that is one of the production parameters from optical images. Then, we evaluate both elevation and shape quality. The shape quality is assessed with in situ measurements and analysis of slopes as an elementary shape and stream networks as a complex shape. We use the fractal dimension and sinuosity to evaluate the stream network shape. The results show that the elevation accuracy as well as the slope accuracy are affected by the template size. Indeed, an improvement of 1 m in the elevation accuracy and of 5 degrees in the slope accuracy has been obtained while changing this parameter. The elevation RMSE ranges from 7.6 to 8.6 m, which is smaller than the pixel size (10 m). For slope, the RMSE depends on the sampling distance. With a distance of 10 m, the minimum slope RMSE is 11.4 degrees. The stream networks extracted from these DEMs present a higher fractal dimension than the reference river. Moreover, the fractal dimension of the extracted networks has a negligible change according to the template size. Finally, the sinuosity of the stream networks is slightly affected by the change of the template size.

Effect of morphology and discharge on hyporheic exchange flows in two small streams in the Cascade Mountains of Oregon, USA.

Treesearch

Steven M. Wondzell

2006-01-01

Stream-tracer injections were used to examine the effect of channel morphology and changing stream discharge on hyporheic exchange flows. Direct observations were made from well networks to follow tracer movement through the hyporheic zone. The reach-integrated influence of hyporheic exchange was evaluated using the transient storage model (TSM) OTIS-P. Transient...

Characterization, adaptive traffic shaping, and multiplexing of real-time MPEG II video

NASA Astrophysics Data System (ADS)

Agrawal, Sanjay; Barry, Charles F.; Binnai, Vinay; Kazovsky, Leonid G.

1997-01-01

We obtain network traffic model for real-time MPEG-II encoded digital video by analyzing video stream samples from real-time encoders from NUKO Information Systems. MPEG-II sample streams include a resolution intensive movie, City of Joy, an action intensive movie, Aliens, a luminance intensive (black and white) movie, Road To Utopia, and a chrominance intensive (color) movie, Dick Tracy. From our analysis we obtain a heuristic model for the encoded video traffic which uses a 15-stage Markov process to model the I,B,P frame sequences within a group of pictures (GOP). A jointly-correlated Gaussian process is used to model the individual frame sizes. Scene change arrivals are modeled according to a gamma process. Simulations show that our MPEG-II traffic model generates, I,B,P frame sequences and frame sizes that closely match the sample MPEG-II stream traffic characteristics as they relate to latency and buffer occupancy in network queues. To achieve high multiplexing efficiency we propose a traffic shaping scheme which sets preferred 1-frame generation times among a group of encoders so as to minimize the overall variation in total offered traffic while still allowing the individual encoders to react to scene changes. Simulations show that our scheme results in multiplexing gains of up to 10% enabling us to multiplex twenty 6 Mbps MPEG-II video streams instead of 18 streams over an ATM/SONET OC3 link without latency or cell loss penalty. This scheme is due for a patent.

Two-Stream Transformer Networks for Video-based Face Alignment.

PubMed

Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.

Challenges and Opportunities of Long-Term Continuous Stream Metabolism Measurements at the National Ecological Observatory Network

NASA Astrophysics Data System (ADS)

Goodman, K. J.; Lunch, C. K.; Baxter, C.; Hall, R.; Holtgrieve, G. W.; Roberts, B. J.; Marcarelli, A. M.; Tank, J. L.

2013-12-01

Recent advances in dissolved oxygen sensing and modeling have made continuous measurements of whole-stream metabolism relatively easy to make, allowing ecologists to quantify and evaluate stream ecosystem health at expanded temporal and spatial scales. Long-term monitoring of continuous stream metabolism will enable a better understanding of the integrated and complex effects of anthropogenic change (e.g., land-use, climate, atmospheric deposition, invasive species, etc.) on stream ecosystem function. In addition to their value in the particular streams measured, information derived from long-term data will improve the ability to extrapolate from shorter-term data. With the need to better understand drivers and responses of whole-stream metabolism come difficulties in interpreting the results. Long-term trends will encompass physical changes in stream morphology and flow regime (e.g., variable flow conditions and changes in channel structure) combined with changes in biota. Additionally long-term data sets will require an organized database structure, careful quantification of errors and uncertainties, as well as propagation of error as a result of the calculation of metabolism metrics. Parsing of continuous data and the choice of modeling approaches can also have a large influence on results and on error estimation. The two main modeling challenges include 1) obtaining unbiased, low-error daily estimates of gross primary production (GPP) and ecosystem respiration (ER), and 2) interpreting GPP and ER measurements over extended time periods. The National Ecological Observatory Network (NEON), in partnership with academic and government scientists, has begun to tackle several of these challenges as it prepares for the collection and calculation of 30 years of continuous whole-stream metabolism data. NEON is a national-scale research platform that will use consistent procedures and protocols to standardize measurements across the United States, providing long-term, high-quality, open-access data from a connected network to address large-scale change. NEON infrastructure will support 36 aquatic sites across 19 ecoclimatic domains. Sites include core sites, which remain for 30 years, and relocatable sites, which move to capture regional gradients. NEON will measure continuous whole-stream metabolism in conjunction with aquatic, terrestrial and airborne observations, allowing researchers to link stream ecosystem function with landscape and climatic drivers encompassing short to long time periods (i.e., decades).

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

USGS Publications Warehouse

Selbig, William R.

2015-01-01

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2 °C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin.

PubMed

Selbig, William R

2015-07-15

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2°C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery. Published by Elsevier B.V.

Neurodynamics for auditory stream segregation: tracking sounds in the mustached bat's natural environment.

PubMed

Kanwal, Jagmeet S; Medvedev, Andrei V; Micheyl, Christophe

2003-08-01

During navigation and the search phase of foraging, mustached bats emit approximately 25 ms long echolocation pulses (at 10-40 Hz) that contain multiple harmonics of a constant frequency (CF) component followed by a short (3 ms) downward frequency modulation. In the context of auditory stream segregation, therefore, bats may either perceive a coherent pulse-echo sequence (PEPE...), or segregated pulse and echo streams (P-P-P... and E-E-E...). To identify the neural mechanisms for stream segregation in bats, we developed a simple yet realistic neural network model with seven layers and 420 nodes. Our model required recurrent and lateral inhibition to enable output nodes in the network to 'latch-on' to a single tone (corresponding to a CF component in either the pulse or echo), i.e., exhibit differential suppression by the alternating two tones presented at a high rate (> 10 Hz). To test the applicability of our model to echolocation, we obtained neurophysiological data from the primary auditory cortex of awake mustached bats. Event-related potentials reliably reproduced the latching behaviour observed at output nodes in the network. Pulse as well as nontarget (clutter) echo CFs facilitated this latching. Individual single unit responses were erratic, but when summed over several recording sites, they also exhibited reliable latching behaviour even at 40 Hz. On the basis of these findings, we propose that a neural correlate of auditory stream segregation is present within localized synaptic activity in the mustached bat's auditory cortex and this mechanism may enhance the perception of echolocation sounds in the natural environment.

Exploring the impact of big data in economic geology using cloud-based synthetic sensor networks

NASA Astrophysics Data System (ADS)

Klump, J. F.; Robertson, J.

2015-12-01

In a market demanding lower resource prices and increasing efficiencies, resources companies are increasingly looking to the realm of real-time, high-frequency data streams to better measure and manage their minerals processing chain, from pit to plant to port. Sensor streams can include real-time drilling engineering information, data streams from mining trucks, and on-stream sensors operating in the plant feeding back rich chemical information. There are also many opportunities to deploy new sensor streams - unlike environmental monitoring networks, the mine environment is not energy- or bandwidth-limited. Although the promised efficiency dividends are inviting, the path to achieving these is difficult to see for most companies. As well as knowing where to invest in new sensor technology and how to integrate the new data streams, companies must grapple with risk-laden changes to their established methods of control to achieve maximum gains. What is required is a sandbox data environment for the development of analysis and control strategies at scale, allowing companies to de-risk proposed changes before actually deploying them to a live mine environment. In this presentation we describe our approach to simulating real-time scaleable data streams in a mine environment. Our sandbox consists of three layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, (b) a measurement layer - a network of RESTful synthetic sensor microservices which can simulate measurements of ground-truth properties, and (c) a control layer, which integrates the sensor streams and drives the measurement and optimisation strategies. The control layer could be a new machine learner, or simply a company's existing data infrastructure. Containerisation allows rapid deployment of large numbers of sensors, as well as service discovery to form a dynamic network of thousands of sensors, at a far lower cost than physically building the network.

Maximization Network Throughput Based on Improved Genetic Algorithm and Network Coding for Optical Multicast Networks

NASA Astrophysics Data System (ADS)

Wei, Chengying; Xiong, Cuilian; Liu, Huanlin

2017-12-01

Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex

PubMed Central

Wang, Quanxin; Sporns, Olaf; Burkhalter, Andreas

2012-01-01

Much of the information used for visual perception and visually guided actions is processed in complex networks of connections within the cortex. To understand how this works in the normal brain and to determine the impact of disease, mice are promising models. In primate visual cortex, information is processed in a dorsal stream specialized for visuospatial processing and guided action and a ventral stream for object recognition. Here, we traced the outputs of 10 visual areas and used quantitative graph analytic tools of modern network science to determine, from the projection strengths in 39 cortical targets, the community structure of the network. We found a high density of the cortical graph that exceeded that previously shown in monkey. Each source area showed a unique distribution of projection weights across its targets (i.e. connectivity profile) that was well-fit by a lognormal function. Importantly, the community structure was strongly dependent on the location of the source area: outputs from medial/anterior extrastriate areas were more strongly linked to parietal, motor and limbic cortex, whereas lateral extrastriate areas were preferentially connected to temporal and parahippocampal cortex. These two subnetworks resemble dorsal and ventral cortical streams in primates, demonstrating that the basic layout of cortical networks is conserved across species. PMID:22457489

Recovery of Phytophthora species from drainage points and tributaries within two forest stream networks: a preliminary report

Treesearch

J. Hwang; S.W. Oak; S.N. Jeffers

2011-01-01

To evaluate the number of stream sample sites needed to effectively survey a given stream network for species of Phytophthora, two stream networks, Davidson River and Cathey's Creek, in western North Carolina (USA) were studied. One-litre water samples were collected from the terminal drainage points and most of the tributaries in each stream...

Learning in Stochastic Bit Stream Neural Networks.

PubMed

van Daalen, Max; Shawe-Taylor, John; Zhao, Jieyu

1996-08-01

This paper presents learning techniques for a novel feedforward stochastic neural network. The model uses stochastic weights and the "bit stream" data representation. It has a clean analysable functionality and is very attractive with its great potential to be implemented in hardware using standard digital VLSI technology. The design allows simulation at three different levels and learning techniques are described for each level. The lowest level corresponds to on-chip learning. Simulation results on three benchmark MONK's problems and handwritten digit recognition with a clean set of 500 16 x 16 pixel digits demonstrate that the new model is powerful enough for the real world applications. Copyright 1996 Elsevier Science Ltd

Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model

Treesearch

Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose

2013-01-01

Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

PubMed Central

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

PubMed

Kotevska, Olivera; Kusne, A Gilad; Samarov, Daniel V; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County.

MID-ATLANTIC COASTAL STREAMS STUDY: STATISTICAL DESIGN FOR REGIONAL ASSESSMENT AND LANDSCAPE MODEL DEVELOPMENT

EPA Science Inventory

A network of stream-sampling sites was developed for the Mid-Atlantic Coastal Plain (New Jersey through North Carolina) a collaborative study between the U.S. Environmental Protection Agency and the U.S. Geological Survey. A stratified random sampling with unequal weighting was u...

Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning

ERIC Educational Resources Information Center

Deng, Lawrence Y.; Keh, Huan-Chao; Liu, Yi-Jen

2010-01-01

More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model.…

MID-ATLANTIC COASTAL STREAMS STUDY: STATISTICAL DESIGN FOR REGIONAL ASSESSMENT AND LANDSCAPE MODEL DEVELOPMENT

EPA Science Inventory

A network of stream-sampling sites was developed for the Mid-Atlantic Coastal Plain (New Jersey through North Carolina) as part of collaborative research between the U.S. Environmental Protection Agency and the U.S. Geological Survey. A stratified random sampling with unequal wei...

High-efficient Extraction of Drainage Networks from Digital Elevation Model Data Constrained by Enhanced Flow Enforcement from Known River Map

NASA Astrophysics Data System (ADS)

Wu, T.; Li, T.; Li, J.; Wang, G.

2017-12-01

Improved drainage network extraction can be achieved by flow enforcement whereby information of known river maps is imposed to the flow-path modeling process. However, the common elevation-based stream burning method can sometimes cause unintended topological errors and misinterpret the overall drainage pattern. We presented an enhanced flow enforcement method to facilitate accurate and efficient process of drainage network extraction. Both the topology of the mapped hydrography and the initial landscape of the DEM are well preserved and fully utilized in the proposed method. An improved stream rasterization is achieved here, yielding continuous, unambiguous and stream-collision-free raster equivalent of stream vectors for flow enforcement. By imposing priority-based enforcement with a complementary flow direction enhancement procedure, the drainage patterns of the mapped hydrography are fully represented in the derived results. The proposed method was tested over the Rogue River Basin, using DEMs with various resolutions. As indicated by the visual and statistical analyses, the proposed method has three major advantages: (1) it significantly reduces the occurrences of topological errors, yielding very accurate watershed partition and channel delineation, (2) it ensures scale-consistent performance at DEMs of various resolutions, and (3) the entire extraction process is well-designed to achieve great computational efficiency.

Scalable Video Streaming in Wireless Mesh Networks for Education

ERIC Educational Resources Information Center

Liu, Yan; Wang, Xinheng; Zhao, Liqiang

2011-01-01

In this paper, a video streaming system for education based on a wireless mesh network is proposed. A wireless mesh network is a self-organizing, self-managing and reliable intelligent network, which allows educators to deploy a network quickly. Video streaming plays an important role in this system for multimedia data transmission. This new…

Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

PubMed

Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

2014-01-01

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.

Research note: Mapping spatial patterns in sewer age, material, and proximity to surface waterways to infer sewer leakage hotspots

USGS Publications Warehouse

Hopkins, Kristina G.; Bain, Daniel J.

2018-01-01

Identifying areas where deteriorating sewer infrastructure is in close proximity to surface waterways is needed to map likely connections between sewers and streams. We present a method to estimate sewer installation year and deterioration status using historical maps of the sewer network, parcel-scale property assessment data, and pipe material. Areas where streams were likely buried into the sewer system were mapped by intersecting the historical stream network derived from a 10-m resolution digital elevation model with sewer pipe locations. Potential sewer leakage hotspots were mapped by identifying where aging sewer pipes are in close proximity (50-m) to surface waterways. Results from Pittsburgh, Pennsylvania (USA), indicated 41% of the historical stream length was lost or buried and the potential interface between sewers and streams is great. The co-location of aging sewer infrastructure (>75 years old) near stream channels suggests that 42% of existing streams are located in areas with a high potential for sewer leakage if sewer infrastructure fails. Mapping the sewer-stream interface provides an approach to better understand areas were failing sewers may contribute a disproportional amount of nutrients and other pathogens to surface waterways.

Analytic Strategies of Streaming Data for eHealth.

PubMed

Yoon, Sunmoo

2016-01-01

New analytic strategies for streaming big data from wearable devices and social media are emerging in ehealth. We face challenges to find meaningful patterns from big data because researchers face difficulties to process big volume of streaming data using traditional processing applications.1 This introductory 180 minutes tutorial offers hand-on instruction on analytics2 (e.g., topic modeling, social network analysis) of streaming data. This tutorial aims to provide practical strategies of information on reducing dimensionality using examples of big data. This tutorial will highlight strategies of incorporating domain experts and a comprehensive approach to streaming social media data.

Modeling the capacity of riverscapes to support beaver dams

NASA Astrophysics Data System (ADS)

Macfarlane, William W.; Wheaton, Joseph M.; Bouwes, Nicolaas; Jensen, Martha L.; Gilbert, Jordan T.; Hough-Snee, Nate; Shivik, John A.

2017-01-01

The construction of beaver dams facilitates a suite of hydrologic, hydraulic, geomorphic, and ecological feedbacks that increase stream complexity and channel-floodplain connectivity that benefit aquatic and terrestrial biota. Depending on where beaver build dams within a drainage network, they impact lateral and longitudinal connectivity by introducing roughness elements that fundamentally change the timing, delivery, and storage of water, sediment, nutrients, and organic matter. While the local effects of beaver dams on streams are well understood, broader coverage network models that predict where beaver dams can be built and highlight their impacts on connectivity across diverse drainage networks are lacking. Here we present a capacity model to assess the limits of riverscapes to support dam-building activities by beaver across physiographically diverse landscapes. We estimated dam capacity with freely and nationally-available inputs to evaluate seven lines of evidence: (1) reliable water source, (2) riparian vegetation conducive to foraging and dam building, (3) vegetation within 100 m of edge of stream to support expansion of dam complexes and maintain large colonies, (4) likelihood that channel-spanning dams could be built during low flows, (5) the likelihood that a beaver dam is likely to withstand typical floods, (6) a suitable stream gradient that is neither too low to limit dam density nor too high to preclude the building or persistence of dams, and (7) a suitable river that is not too large to restrict dam building or persistence. Fuzzy inference systems were used to combine these controlling factors in a framework that explicitly also accounts for model uncertainty. The model was run for 40,561 km of streams in Utah, USA, and portions of surrounding states, predicting an overall network capacity of 356,294 dams at an average capacity of 8.8 dams/km. We validated model performance using 2852 observed dams across 1947 km of streams. The model showed excellent agreement with observed dam densities where beaver dams were present. Model performance was spatially coherent and logical, with electivity indices that effectively segregated capacity categories. That is, beaver dams were not found where the model predicted no dams could be supported, beaver avoided segments that were predicted to support rare or occasional densities, and beaver preferentially occupied and built dams in areas predicted to have pervasive dam densities. The resulting spatially explicit reach-scale (250 m long reaches) data identifies where dam-building activity is sustainable, and at what densities dams can occur across a landscape. As such, model outputs can be used to determine where channel-floodplain and wetland connectivity are likely to persist or expand by promoting increases in beaver dam densities.

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

NASA Astrophysics Data System (ADS)

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

2018-05-01

Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989-2016) suggested the highest probabilities of intermittence (> 35 %) in 1989-1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the temporal variability of intermittent rivers and ephemeral streams.

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Jaafar, Othman; Deo, Ravinesh C.; Kisi, Ozgur; Adamowski, Jan; Quilty, John; El-Shafie, Ahmed

2016-11-01

Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations. The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. Based on the partial autocorrelation functions of historical stream-flow data, a set of five input combinations with lagged stream-flow values are employed to establish the best forecasting model. A comparative investigation is conducted to evaluate the performance of the ELM compared to other data-driven models: support vector regression (SVR) and generalized regression neural network (GRNN). The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. The results revealed that the ELM model outperformed the SVR and the GRNN models across a number of statistical measures. In quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). Based on the findings of this study, several recommendations were suggested for further exploration of the ELM model in hydrological forecasting problems.

A time-varying subjective quality model for mobile streaming videos with stalling events

NASA Astrophysics Data System (ADS)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.

2015-09-01

Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

Evidence for fish dispersal from spatial analysis of stream network topology

USGS Publications Warehouse

Hitt, N.P.; Angermeier, P.L.

2008-01-01

Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

Stochastic Packet Loss Model to Evaluate QoE Impairments

NASA Astrophysics Data System (ADS)

Hohlfeld, Oliver

With provisioning of broadband access for mass market—even in wireless and mobile networks—multimedia content, especially real-time streaming of high-quality audio and video, is extensively viewed and exchanged over the Internet. Quality of Experience (QoE) aspects, describing the service quality perceived by the user, is a vital factor in ensuring customer satisfaction in today's communication networks. Frameworks for accessing quality degradations in streamed video currently are investigated as a complex multi-layered research topic, involving network traffic load, codec functions and measures of user perception of video quality.

Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

PubMed Central

Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire

2009-01-01

This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145

New ArcGIS tools developed for stream network extraction and basin delineations using Python and java script

NASA Astrophysics Data System (ADS)

Omran, Adel; Dietrich, Schröder; Abouelmagd, Abdou; Michael, Märker

2016-09-01

Damages caused by flash floods hazards are an increasing phenomenon, especially in arid and semi-arid areas. Thus, the need to evaluate these areas based on their flash flood risk using maps and hydrological models is also becoming more important. For ungauged watersheds a tentative analysis can be carried out based on the geomorphometric characteristics of the terrain. To process regions with larger watersheds, where perhaps hundreds of watersheds have to be delineated, processed and classified, the overall process need to be automated. GIS packages such as ESRI's ArcGIS offer a number of sophisticated tools that help regarding such analysis. Yet there are still gaps and pitfalls that need to be considered if the tools are combined into a geoprocessing model to automate the complete assessment workflow. These gaps include issues such as i) assigning stream order according to Strahler theory, ii) calculating the threshold value for the stream network extraction, and iii) determining the pour points for each of the nodes of the Strahler ordered stream network. In this study a complete automated workflow based on ArcGIS Model Builder using standard tools will be introduced and discussed. Some additional tools have been implemented to complete the overall workflow. These tools have been programmed using Python and Java in the context of ArcObjects. The workflow has been applied to digital data from the southwestern Sinai Peninsula, Egypt. An optimum threshold value has been selected to optimize drainage configuration by statistically comparing all of the extracted stream configuration results from DEM with the available reference data from topographic maps. The code has succeeded in estimating the correct ranking of specific stream orders in an automatic manner without additional manual steps. As a result, the code has proven to save time and efforts; hence it's considered a very useful tool for processing large catchment basins.

Integration and segregation in auditory streaming

NASA Astrophysics Data System (ADS)

Almonte, Felix; Jirsa, Viktor K.; Large, Edward W.; Tuller, Betty

2005-12-01

We aim to capture the perceptual dynamics of auditory streaming using a neurally inspired model of auditory processing. Traditional approaches view streaming as a competition of streams, realized within a tonotopically organized neural network. In contrast, we view streaming to be a dynamic integration process which resides at locations other than the sensory specific neural subsystems. This process finds its realization in the synchronization of neural ensembles or in the existence of informational convergence zones. Our approach uses two interacting dynamical systems, in which the first system responds to incoming acoustic stimuli and transforms them into a spatiotemporal neural field dynamics. The second system is a classification system coupled to the neural field and evolves to a stationary state. These states are identified with a single perceptual stream or multiple streams. Several results in human perception are modelled including temporal coherence and fission boundaries [L.P.A.S. van Noorden, Temporal coherence in the perception of tone sequences, Ph.D. Thesis, Eindhoven University of Technology, The Netherlands, 1975], and crossing of motions [A.S. Bregman, Auditory Scene Analysis: The Perceptual Organization of Sound, MIT Press, 1990]. Our model predicts phenomena such as the existence of two streams with the same pitch, which cannot be explained by the traditional stream competition models. An experimental study is performed to provide proof of existence of this phenomenon. The model elucidates possible mechanisms that may underlie perceptual phenomena.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

USGS Publications Warehouse

Kashuba, Roxolana; McMahon, Gerard; Cuffney, Thomas F.; Qian, Song; Reckhow, Kenneth; Gerritsen, Jeroen; Davies, Susan

2012-01-01

In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Wireless network interface energy consumption implications of popular streaming formats

NASA Astrophysics Data System (ADS)

Chandra, Surendar

2001-12-01

With the proliferation of mobile streaming multimedia, available battery capacity constrains the end-user experience. Since streaming applications tend to be long running, wireless network interface card's (WNIC) energy consumption is particularly an acute problem. In this work, we explore the WNIC energy consumption implications of popular multimedia streaming formats from Microsoft (Windows media), Real (Real media) and Apple (Quick Time). We investigate the energy consumption under varying stream bandwidth and network loss rates. We also explore history-based client-side strategies to reduce the energy consumed by transitioning the WNICs to a lower power consuming sleep state. We show that Microsoft media tends to transmit packets at regular intervals; streams optimized for 28.8 Kbps can save over 80% in energy consumption with 2% data loss. A high bandwidth stream (768 Kbps) can still save 57% in energy consumption with less than 0.3% data loss. For high bandwidth streams, Microsoft media exploits network-level packet fragmentation, which can lead to excessive packet loss (and wasted energy) in a lossy network. Real stream packets tend to be sent closer to each other, especially at higher bandwidths. Quicktime packets sometimes arrive in quick succession; most likely an application level fragmentation mechanism. Such packets are harder to predict at the network level without understanding the packet semantics.

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

USGS Publications Warehouse

Graves, D.; Maule, A.

2014-01-01

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead (Oncorhynchus mykiss), a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming

NASA Astrophysics Data System (ADS)

Faruq Ibn Ibrahimy, Abdullah; Rafiqul, Islam Md; Anwar, Farhat; Ibn Ibrahimy, Muhammad

2013-12-01

The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper.

A low cost strategy to monitor the expansion and contraction of the flowing stream network in mountainous headwater catchments

NASA Astrophysics Data System (ADS)

Assendelft, Rick; van Meerveld, Ilja; Seibert, Jan

2017-04-01

Streams are dynamic features in the landscape. The flowing stream network expands and contracts, connects and disconnects in response to rainfall events and seasonal changes in catchment wetness. Sections of the river system that experience these wet and dry cycles are often referred to as temporary streams. Temporary streams are abundant and widely distributed freshwater ecosystems. They account for more than half of the total length of the global stream network, are unique habitats and form important hydrological and ecological links between the uplands and perennial streams. However, temporary streams have been largely unstudied, especially in mountainous headwater catchments. The dynamic character of these systems makes it difficult to monitor them. We describe a low-cost, do-it-yourself strategy to monitor the occurrence of water and flow in temporary streams. We evaluate this strategy in two headwater catchments in Switzerland. The low cost sensor network consists of electrical resistivity sensors, water level switches, temperature sensors and flow sensors. These sensors are connected to Arduino microcontrollers and data loggers, which log the data every 5 minutes. The data from the measurement network are compared with observations (mapping of the temporary stream network) as well as time lapse camera data to evaluate the performance of the sensors. We look at how frequently the output of the sensors (presence and absence of water from the ER and water level data, and flow or no-flow from the flow sensors) corresponds to the observed channel state. This is done for each sensor, per sub-catchment, per precipitation event and per sensor location to determine the best sensor combination to monitor temporary streams in mountainous catchments and in which situation which sensor combination works best. The preliminary results show that the sensors and monitoring network work well. The data from the sensors corresponds with the observations and provides information on the expansion of the stream network pattern.

Spatial reasoning to determine stream network from LANDSAT imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Wang, S.; Elliott, D. B.

1983-01-01

In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

Cooperation stimulation strategies for peer-to-peer wireless live video-sharing social networks.

PubMed

Lin, W Sabrina; Zhao, H Vicky; Liu, K J Ray

2010-07-01

Human behavior analysis in video sharing social networks is an emerging research area, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on video sharing systems. Users watching live streaming in the same wireless network share the same limited bandwidth of backbone connection to the Internet, thus, they might want to cooperate with each other to obtain better video quality. These users form a wireless live-streaming social network. Every user wishes to watch video with high quality while paying as little as possible cost to help others. This paper focuses on providing incentives for user cooperation. We propose a game-theoretic framework to model user behavior and to analyze the optimal strategies for user cooperation simulation in wireless live streaming. We first analyze the Pareto optimality and the time-sensitive bargaining equilibrium of the two-person game. We then extend the solution to the multiuser scenario. We also consider potential selfish users' cheating behavior and malicious users' attacking behavior and analyze the performance of the proposed strategies with the existence of cheating users and malicious attackers. Both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and attack resistance, and help provide reliable services for wireless live streaming applications.

Spatial and temporal variability in the effects of wildfire and drought on thermal habitat for a desert trout

USGS Publications Warehouse

Schultz, Luke; Heck, Michael; Hockman-Wert, David; Allai, T; Wengerd, Seth J.; Cook, NA; Dunham, Jason B.

2017-01-01

We studied how drought and an associated stressor, wildfire, influenced stream flow permanence and thermal regimes in a Great Basin stream network. We quantified these responses by collecting information with a spatially extensive network of data loggers. To understand the effects of wildfire specifically, we used data from 4 additional sites that were installed prior to a 2012 fire that burned nearly the entire watershed. Within the sampled network 73 reaches were classified as perennial, yet only 51 contained surface water during logger installation in 2014. Among the sites with pre-fire temperature data, we observed 2–4 °C increases in maximum daily stream temperature relative to an unburned control in the month following the fire; effects (elevated up to 6.6 °C) appeared to persist for at least one year. When observed August mean temperatures in 2015 (the peak of regionally severe drought) were compared to those predicted by a regional stream temperature model, we observed deviations of −2.1°-3.5°. The model under-predicted and over-predicted August mean by > 1 °C in 54% and 10% of sites, respectively, and deviance from predicted was negatively associated with elevation. Combined drought and post-fire conditions appeared to greatly restrict thermally-suitable habitat for Lahontan cutthroat trout (Oncorhynchus clarkii henshawi).

Estimation of Total Nitrogen and Phosphorus in New England Streams Using Spatially Referenced Regression Models

USGS Publications Warehouse

Moore, Richard Bridge; Johnston, Craig M.; Robinson, Keith W.; Deacon, Jeffrey R.

2004-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEIWPCC), has developed a water-quality model, called SPARROW (Spatially Referenced Regressions on Watershed Attributes), to assist in regional total maximum daily load (TMDL) and nutrient-criteria activities in New England. SPARROW is a spatially detailed, statistical model that uses regression equations to relate total nitrogen and phosphorus (nutrient) stream loads to nutrient sources and watershed characteristics. The statistical relations in these equations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW models are built using a hydrologic network of 42,000 stream reaches and associated watersheds. Watershed boundaries are defined for each stream reach in the network through the use of a digital elevation model and existing digitized watershed divides. Nutrient source data is from permitted wastewater discharge data from USEPA's Permit Compliance System (PCS), various land-use sources, and atmospheric deposition. Physical watershed characteristics include drainage area, land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. The New England SPARROW models for total nitrogen and total phosphorus have R-squared values of 0.95 and 0.94, with mean square errors of 0.16 and 0.23, respectively. Variables that were statistically significant in the total nitrogen model include permitted municipal-wastewater discharges, atmospheric deposition, agricultural area, and developed land area. Total nitrogen stream-loss rates were significant only in streams with average annual flows less than or equal to 2.83 cubic meters per second. In streams larger than this, there is nondetectable in-stream loss of annual total nitrogen in New England. Variables that were statistically significant in the total phosphorus model include discharges for municipal wastewater-treatment facilities and pulp and paper facilities, developed land area, agricultural area, and forested area. For total phosphorus, loss rates were significant for reservoirs with surface areas of 10 square kilometers or less, and in streams with flows less than or equal to 2.83 cubic meters per second. Applications of SPARROW for evaluating nutrient loading in New England waters include estimates of the spatial distributions of total nitrogen and phosphorus yields, sources of the nutrients, and the potential for delivery of those yields to receiving waters. This information can be used to (1) predict ranges in nutrient levels in surface waters, (2) identify the environmental variables that are statistically significant predictors of nutrient levels in streams, (3) evaluate monitoring efforts for better determination of nutrient loads, and (4) evaluate management options for reducing nutrient loads to achieve water-quality goals.

Flow velocity and the hydrologic behavior of streams during baseflow.

Treesearch

Steven M. Wondzell; Michael N. Gooseff; Brian L. McGlynn

2007-01-01

Diel variations in stream discharge have long been recognized, but are relatively little studied. Here we demonstrate that these diel fluctuations can be used to investigate both streamflow generation and network routing. We treat evapo-transpiration (ET) as a distributed impulse function in an advection model and analyze the effect of ET on diel fluctuations in...

Recent findings related to measuring and modeling forest road erosion

Treesearch

W. J. Elliot; R. B. Foltz; P. R. Robichaud

2009-01-01

Sediment is the greatest pollutant of forest streams. In the absence of wildfire, forest road networks are usually the main source of sediment in forest watersheds. An understanding of forest road erosion processes is important to aid in predicting sediment delivery from roads to streams. The flowpath followed by runoff is the key to understanding road erosion...

Advanced Performance Modeling with Combined Passive and Active Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dovrolis, Constantine; Sim, Alex

2015-04-15

To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performancemore » information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.« less

A Scalable Multimedia Streaming Scheme with CBR-Transmission of VBR-Encoded Videos over the Internet

ERIC Educational Resources Information Center

Kabir, Md. H.; Shoja, Gholamali C.; Manning, Eric G.

2006-01-01

Streaming audio/video contents over the Internet requires large network bandwidth and timely delivery of media data. A streaming session is generally long and also needs a large I/O bandwidth at the streaming server. A streaming server, however, has limited network and I/O bandwidth. For this reason, a streaming server alone cannot scale a…

Monitoring network-design influence on assessment of ecological condition in wadeable streams

EPA Science Inventory

We investigated outcomes of three monitoring networks for assessing ecological character and condition of wadeable streams in the Waikato region, New Zealand. Sites were selected 1) based on a professional judgment network, 2) within categories of stream and watershed characteris...

Scaling measurements of metabolism in stream ecosystems: challenges and approaches to estimating reaeration

NASA Astrophysics Data System (ADS)

Bowden, W. B.; Parker, S.; Song, C.

2016-12-01

Stream ecologists have used various formulations of an oxygen budget approach as a surrogate to measure "whole-stream metabolism" (WSM) of carbon in rivers and streams. Improvements in sensor technologies that provide reliable, high-frequency measurements of dissolved oxygen concentrations in adverse field conditions has made it much easier to acquire the basic data needed to estimate WSM in remote locations over long periods (weeks to months). However, accurate estimates of WSM require reliable measurements or estimates of the reaeration coefficient (k). Small errors in estimates of k can lead to large errors in estimates of gross ecosystem production and ecosystem respiration and so the magnitude of the biological flux of CO2 to or from streams. This is an especially challenging problem in unproductive, oligotrophic streams. Unfortunately, current methods to measure reaeration directly (gas evasion) are expensive, labor-intensive, and time-consuming. As a consequence, there is a substantial mismatch between the time steps at which we can measure reaeration versus most of the other variables required to calculate WSM. As a part of the NSF Arctic Long-Term Ecological Research Project we have refined methods to measure WSM in Arctic streams and found a good relationship between measured k values and those calculated by the Energy Dissipation Model (EDM). Other researchers have also noted that this equation works well for both low- and high-order streams. The EDM is dependent on stream slope (relatively constant) and velocity (which is related to discharge or stage). These variables are easy to measure and can be used to estimate k a high frequency (minutes) over large areas (river networks). As a key part of the NSF MacroSystems Biology SCALER project we calculated WSM for multiple reaches in nested stream networks in six biomes across the United States and Australia. We calculated k by EDM and fitted k via a Bayesian model for WSM. The relationships between measured k and calculated (EDM) k (standardized to 20°C) were variable but useful. The relationships between calculated (EDM) k and inferred (Bayesian) k were inconsistent, suggesting that there are additional factors we need to understand to better refine estimates of whole-stream metabolic C exchange over river networks and among regions.

Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

USGS Publications Warehouse

Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K; Schindler, Daniel E.

2016-01-01

A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

A model for evaluating stream temperature response to climate change scenarios in Wisconsin

USGS Publications Warehouse

Westenbroek, Stephen M.; Stewart, Jana S.; Buchwald, Cheryl A.; Mitro, Matthew G.; Lyons, John D.; Greb, Steven

2010-01-01

Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.

Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Todd Vollmer; Milos Manic

The planned large scale deployment of smart grid network devices will generate a large amount of information exchanged over various types of communication networks. The implementation of these critical systems will require appropriate cyber-security measures. A network anomaly detection solution is considered in this work. In common network architectures multiple communications streams are simultaneously present, making it difficult to build an anomaly detection solution for the entire system. In addition, common anomaly detection algorithms require specification of a sensitivity threshold, which inevitably leads to a tradeoff between false positives and false negatives rates. In order to alleviate these issues, thismore » paper proposes a novel anomaly detection architecture. The designed system applies the previously developed network security cyber-sensor method to individual selected communication streams allowing for learning accurate normal network behavior models. Furthermore, the developed system dynamically adjusts the sensitivity threshold of each anomaly detection algorithm based on domain knowledge about the specific network system. It is proposed to model this domain knowledge using Interval Type-2 Fuzzy Logic rules, which linguistically describe the relationship between various features of the network communication and the possibility of a cyber attack. The proposed method was tested on experimental smart grid system demonstrating enhanced cyber-security.« less

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

SOUND SURVEY DESIGNS CAN FACILITATE INTEGRATING STREAM MONITORING DATA ACROSS MULTIPLE PROGRAMS

EPA Science Inventory

Multiple agencies in the Pacific Northwest monitor the condition of stream networks or their watersheds. Some agencies use a stream "network" perspective to report on the fraction or length of the network that either meets or violates particular criteria. Other agencies use a "wa...

Continuous Dissolved Oxygen Measurements and Modelling Metabolism in Peatland Streams

PubMed Central

Dick, Jonathan J.; Soulsby, Chris; Birkel, Christian; Malcolm, Iain; Tetzlaff, Doerthe

2016-01-01

Stream water dissolved oxygen was monitored in a 3.2km2 moorland headwater catchment in the Scottish Highlands. The stream consists of three 1st order headwaters and a 2nd order main stem. The stream network is fringed by peat soils with no riparian trees, though dwarf shrubs provide shading in the lower catchment. Dissolved oxygen (DO) is regulated by the balance between atmospheric re-aeration and the metabolic processes of photosynthesis and respiration. DO was continuously measured for >1 year and the data used to calibrate a mass balance model, to estimate primary production, respiration and re-aeration for a 1st order site and in the 2nd order main stem. Results showed that the stream was always heterotrophic at both sites. Sites were most heterotrophic in the summer reflecting higher levels of stream metabolism. The 1st order stream appeared more heterotrophic which was consistent with the evident greater biomass of macrophytes in the 2nd order stream, with resulting higher primary productivity. Comparison between respiration, primary production, re-aeration and potential physical controls revealed only weak relationships. However, the most basic model parameters (e.g. the parameter linking light and photosynthesis) controlling ecosystem processes resulted in significant differences between the sites which seem related to the stream channel geometry. PMID:27556278

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE PAGES

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.; ...

2016-03-26

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Internal Catchment Process Simulation in a Snow-Dominated Basin: Performance Evaluation with Spatiotemporally Variable Runoff Generation and Groundwater Dynamics

NASA Astrophysics Data System (ADS)

Kuras, P. K.; Weiler, M.; Alila, Y.; Spittlehouse, D.; Winkler, R.

2006-12-01

Hydrologic models have been increasingly used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models, however, are also plagued by uncertainty stemming from a limited understanding of hydrological processes in forested catchments and parameter equifinality is a common concern. This has created the necessity to improve our understanding of how hydrological systems work, through the development of hydrological measures, analyses and models that address the question: are we getting the right answers for the right reasons? Hence, physically-based, spatially-distributed hydrologic models should be validated with high-quality experimental data describing multiple concurrent internal catchment processes under a range of hydrologic regimes. The distributed hydrology soil vegetation model (DHSVM) frequently used in forest management applications is an example of a process-based model used to address the aforementioned circumstances, and this study takes a novel approach at collectively examining the ability of a pre-calibrated model application to realistically simulate outlet flows along with the spatial-temporal variation of internal catchment processes including: continuous groundwater dynamics at 9 locations, stream and road network flow at 67 locations for six individual days throughout the freshet, and pre-melt season snow distribution. Model efficiency was improved over prior evaluations due to continuous efforts in improving the quality of meteorological data in the watershed. Road and stream network flows were very well simulated for a range of hydrological conditions, and the spatial distribution of the pre-melt season snowpack was in general agreement with observed values. The model was effective in simulating the spatial variability of subsurface flow generation, except at locations where strong stream-groundwater interactions existed, as the model is not capable of simulating such processes and subsurface flows always drain to the stream network. The model has proven overall to be quite capable in realistically simulating internal catchment processes in the watershed, which creates more confidence in future model applications exploring the effects of various forest management scenarios on the watershed's hydrological processes.

Do network relationships matter? Comparing network and instream habitat variables to explain densities of juvenile coho salmon (Oncorhynchus kisutch) in mid-coastal Oregon, USA

Treesearch

Rebecca L. Flitcroft; Kelly M. Burnett; Gordon H. Reeves; Lisa M. Ganio

2012-01-01

Aquatic ecologists are working to develop theory and techniques for analysis of dynamic stream processes and communities of organisms. Such work is critical for the development of conservation plans that are relevant at the scale of entire ecosystems. The stream network is the foundation upon which stream systems are organized. Natural and human disturbances in streams...

Real-time video streaming in mobile cloud over heterogeneous wireless networks

NASA Astrophysics Data System (ADS)

Abdallah-Saleh, Saleh; Wang, Qi; Grecos, Christos

2012-06-01

Recently, the concept of Mobile Cloud Computing (MCC) has been proposed to offload the resource requirements in computational capabilities, storage and security from mobile devices into the cloud. Internet video applications such as real-time streaming are expected to be ubiquitously deployed and supported over the cloud for mobile users, who typically encounter a range of wireless networks of diverse radio access technologies during their roaming. However, real-time video streaming for mobile cloud users across heterogeneous wireless networks presents multiple challenges. The network-layer quality of service (QoS) provision to support high-quality mobile video delivery in this demanding scenario remains an open research question, and this in turn affects the application-level visual quality and impedes mobile users' perceived quality of experience (QoE). In this paper, we devise a framework to support real-time video streaming in this new mobile video networking paradigm and evaluate the performance of the proposed framework empirically through a lab-based yet realistic testing platform. One particular issue we focus on is the effect of users' mobility on the QoS of video streaming over the cloud. We design and implement a hybrid platform comprising of a test-bed and an emulator, on which our concept of mobile cloud computing, video streaming and heterogeneous wireless networks are implemented and integrated to allow the testing of our framework. As representative heterogeneous wireless networks, the popular WLAN (Wi-Fi) and MAN (WiMAX) networks are incorporated in order to evaluate effects of handovers between these different radio access technologies. The H.264/AVC (Advanced Video Coding) standard is employed for real-time video streaming from a server to mobile users (client nodes) in the networks. Mobility support is introduced to enable continuous streaming experience for a mobile user across the heterogeneous wireless network. Real-time video stream packets are captured for analytical purposes on the mobile user node. Experimental results are obtained and analysed. Future work is identified towards further improvement of the current design and implementation. With this new mobile video networking concept and paradigm implemented and evaluated, results and observations obtained from this study would form the basis of a more in-depth, comprehensive understanding of various challenges and opportunities in supporting high-quality real-time video streaming in mobile cloud over heterogeneous wireless networks.

Spatial structures of stream and hillslope drainage networks following gully erosion after wildfire

USGS Publications Warehouse

Moody, J.A.; Kinner, D.A.

2006-01-01

The drainage networks of catchment areas burned by wildfire were analysed at several scales. The smallest scale (1-1000 m2) representative of hillslopes, and the small scale (1000 m2 to 1 km2), representative of small catchments, were characterized by the analysis of field measurements. The large scale (1-1000 km2), representative of perennial stream networks, was derived from a 30-m digital elevation model and analysed by computer analysis. Scaling laws used to describe large-scale drainage networks could be extrapolated to the small scale but could not describe the smallest scale of drainage structures observed in the hillslope region. The hillslope drainage network appears to have a second-order effect that reduces the number of order 1 and order 2 streams predicted by the large-scale channel structure. This network comprises two spatial patterns of rills with width-to-depth ratios typically less than 10. One pattern is parallel rills draining nearly planar hillslope surfaces, and the other pattern is three to six converging rills draining the critical source area uphill from an order 1 channel head. The magnitude of this critical area depends on infiltration, hillslope roughness and critical shear stress for erosion of sediment, all of which can be substantially altered by wildfire. Order 1 and 2 streams were found to constitute the interface region, which is altered by a disturbance, like wildfire, from subtle unchannelized drainages in unburned catchments to incised drainages. These drainages are characterized by gullies also with width-to-depth ratios typically less than 10 in burned catchments. The regions (hillslope, interface and chanel) had different drainage network structures to collect and transfer water and sediment. Copyright ?? 2005 John Wiley & Sons, Ltd.

Managing fish habitat for flow and temperature extremes ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

Application of Hierarchy Theory to Cross-Scale Hydrologic Modeling of Nutrient Loads

EPA Science Inventory

We describe a model called Regional Hydrologic Modeling for Environmental Evaluation 16 (RHyME²) for quantifying annual nutrient loads in stream networks and watersheds. RHyME² is 17 a cross-scale statistical and process-based water-quality model. The model ...

Urban Stream Burial Increases Watershed-Scale Nitrate Export.

PubMed

Beaulieu, Jake J; Golden, Heather E; Knightes, Christopher D; Mayer, Paul M; Kaushal, Sujay S; Pennino, Michael J; Arango, Clay P; Balz, David A; Elonen, Colleen M; Fritz, Ken M; Hill, Brian H

2015-01-01

Nitrogen (N) uptake in streams is an important ecosystem service that reduces nutrient loading to downstream ecosystems. Here we synthesize studies that investigated the effects of urban stream burial on N-uptake in two metropolitan areas and use simulation modeling to scale our measurements to the broader watershed scale. We report that nitrate travels on average 18 times farther downstream in buried than in open streams before being removed from the water column, indicating that burial substantially reduces N uptake in streams. Simulation modeling suggests that as burial expands throughout a river network, N uptake rates increase in the remaining open reaches which somewhat offsets reduced N uptake in buried reaches. This is particularly true at low levels of stream burial. At higher levels of stream burial, however, open reaches become rare and cumulative N uptake across all open reaches in the watershed rapidly declines. As a result, watershed-scale N export increases slowly at low levels of stream burial, after which increases in export become more pronounced. Stream burial in the lower, more urbanized portions of the watershed had a greater effect on N export than an equivalent amount of stream burial in the upper watershed. We suggest that stream daylighting (i.e., uncovering buried streams) can increase watershed-scale N retention.

Urban Stream Burial Increases Watershed-Scale Nitrate Export

PubMed Central

Beaulieu, Jake J.; Golden, Heather E.; Knightes, Christopher D.; Mayer, Paul M.; Kaushal, Sujay S.; Pennino, Michael J.; Arango, Clay P.; Balz, David A.; Elonen, Colleen M.; Fritz, Ken M.; Hill, Brian H.

2015-01-01

Nitrogen (N) uptake in streams is an important ecosystem service that reduces nutrient loading to downstream ecosystems. Here we synthesize studies that investigated the effects of urban stream burial on N-uptake in two metropolitan areas and use simulation modeling to scale our measurements to the broader watershed scale. We report that nitrate travels on average 18 times farther downstream in buried than in open streams before being removed from the water column, indicating that burial substantially reduces N uptake in streams. Simulation modeling suggests that as burial expands throughout a river network, N uptake rates increase in the remaining open reaches which somewhat offsets reduced N uptake in buried reaches. This is particularly true at low levels of stream burial. At higher levels of stream burial, however, open reaches become rare and cumulative N uptake across all open reaches in the watershed rapidly declines. As a result, watershed-scale N export increases slowly at low levels of stream burial, after which increases in export become more pronounced. Stream burial in the lower, more urbanized portions of the watershed had a greater effect on N export than an equivalent amount of stream burial in the upper watershed. We suggest that stream daylighting (i.e., uncovering buried streams) can increase watershed-scale N retention. PMID:26186731

Ice stream activity scaled to ice sheet volume during Laurentide Ice Sheet deglaciation.

PubMed

Stokes, C R; Margold, M; Clark, C D; Tarasov, L

2016-02-18

The contribution of the Greenland and West Antarctic ice sheets to sea level has increased in recent decades, largely owing to the thinning and retreat of outlet glaciers and ice streams. This dynamic loss is a serious concern, with some modelling studies suggesting that the collapse of a major ice sheet could be imminent or potentially underway in West Antarctica, but others predicting a more limited response. A major problem is that observations used to initialize and calibrate models typically span only a few decades, and, at the ice-sheet scale, it is unclear how the entire drainage network of ice streams evolves over longer timescales. This represents one of the largest sources of uncertainty when predicting the contributions of ice sheets to sea-level rise. A key question is whether ice streams might increase and sustain rates of mass loss over centuries or millennia, beyond those expected for a given ocean-climate forcing. Here we reconstruct the activity of 117 ice streams that operated at various times during deglaciation of the Laurentide Ice Sheet (from about 22,000 to 7,000 years ago) and show that as they activated and deactivated in different locations, their overall number decreased, they occupied a progressively smaller percentage of the ice sheet perimeter and their total discharge decreased. The underlying geology and topography clearly influenced ice stream activity, but--at the ice-sheet scale--their drainage network adjusted and was linked to changes in ice sheet volume. It is unclear whether these findings can be directly translated to modern ice sheets. However, contrary to the view that sees ice streams as unstable entities that can accelerate ice-sheet deglaciation, we conclude that ice streams exerted progressively less influence on ice sheet mass balance during the retreat of the Laurentide Ice Sheet.

What Role Does "Elongation" Play in "Tool-Specific" Activation and Connectivity in the Dorsal and Ventral Visual Streams?

PubMed

Chen, Juan; Snow, Jacqueline C; Culham, Jody C; Goodale, Melvyn A

2018-04-01

Images of tools induce stronger activation than images of nontools in a left-lateralized network that includes ventral-stream areas implicated in tool identification and dorsal-stream areas implicated in tool manipulation. Importantly, however, graspable tools tend to be elongated rather than stubby, and so the tool-selective responses in some of these areas may, to some extent, reflect sensitivity to elongation rather than "toolness" per se. Using functional magnetic resonance imaging, we investigated the role of elongation in driving tool-specific activation in the 2 streams and their interconnections. We showed that in some "tool-selective" areas, the coding of toolness and elongation coexisted, but in others, elongation and toolness were coded independently. Psychophysiological interaction analysis revealed that toolness, but not elongation, had a strong modulation of the connectivity between the ventral and dorsal streams. Dynamic causal modeling revealed that viewing tools (either elongated or stubby) increased the connectivity from the ventral- to the dorsal-stream tool-selective areas, but only viewing elongated tools increased the reciprocal connectivity between these areas. Overall, these data disentangle how toolness and elongation affect the activation and connectivity of the tool network and help to resolve recent controversies regarding the relative contribution of "toolness" versus elongation in driving dorsal-stream "tool-selective" areas.

Monitoring Supraglacial Streams over Three Months in Southwest Greenland

NASA Astrophysics Data System (ADS)

Muthyala, R.; Rennermalm, A.; Leidman, S. Z.; Cooper, M. G.; Cooley, S. W.; Smith, L. C.; van As, D.

2017-12-01

Supraglacial river networks are the most efficient conduits for evacuation of meltwater runoff produced on Greenland ice sheet. These rivers are prominent features on the ablation zone of southwest Greenland. However, little is known about the transport of meltwater through supraglacial stream network and most of the in-situ observations only capture a few days of streamflow. Here we report three months of observations of water level and discharge collected during summer of 2016, in two small supraglacial streams near the ice sheet margin in southwest Greenland. We also compare streamflow observations with meteorological data from a nearby automatic weather station. The two sites are very different, with the lower basin relatively steep, smooth and dark while the upper basin has rugged terrain and deeply incised stream channels. These catchment characteristics propagate to different relationships with meteorological parameters. For example, upper basin stream water levels show a strong covariance with surface temperature while the lower basin water levels do not. We also find differences in temporal variation of supraglacial stream water level, with the upper basin having two distinct peaks, in mid-June and mid-July, while the lower basin shows gradual decrease from June to August. Long-term supraglacial stream observations such as these will ultimately help assess how well surface mass balance models can simulate ice sheet runoff.

Learning From Short Text Streams With Topic Drifts.

PubMed

Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

2017-09-18

Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

Spatial statistical network models for stream and river temperature in New England, USA

NASA Astrophysics Data System (ADS)

Detenbeck, Naomi E.; Morrison, Alisa C.; Abele, Ralph W.; Kopp, Darin A.

2016-08-01

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May-September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5°C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total).

Data from selected U.S. Geological Survey National Stream Water-Quality Networks (WQN)

USGS Publications Warehouse

Alexander, Richard B.; Slack, J.R.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.; Briel, L.I.; Buttleman, K.P.

1996-01-01

This CD-ROM set contains data from two USGS national stream water-quality networks, the Hydrologic Benchmark Network (HBN) and the National Stream Quality Accounting Network (NASQAN), operated during the past 30 years. These networks were established to provide national and regional descriptions of stream water-quality conditions and trends, based on uniform monitoring of selected watersheds throughout the United States, and to improve our understanding of the effects of the natural environment and human activities on water quality. The HBN, consisting of 63 relatively small, minimally disturbed watersheds, provides data for investigating naturally induced changes in streamflow and water quality and the effects of airborne substances on water quality. NASQAN, consisting of 618 larger, more culturally influenced watersheds, provides information for tracking water-quality conditions in major U.S. rivers and streams.

Real-Time Visualization of Network Behaviors for Situational Awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

Increased functional connectivity in the ventral and dorsal streams during retrieval of novel words in professional musicians.

PubMed

Dittinger, Eva; Valizadeh, Seyed Abolfazl; Jäncke, Lutz; Besson, Mireille; Elmer, Stefan

2018-02-01

Current models of speech and language processing postulate the involvement of two parallel processing streams (the dual stream model): a ventral stream involved in mapping sensory and phonological representations onto lexical and conceptual representations and a dorsal stream contributing to sound-to-motor mapping, articulation, and to how verbal information is encoded and manipulated in memory. Based on previous evidence showing that music training has an influence on language processing, cognitive functions, and word learning, we examined EEG-based intracranial functional connectivity in the ventral and dorsal streams while musicians and nonmusicians learned the meaning of novel words through picture-word associations. In accordance with the dual stream model, word learning was generally associated with increased beta functional connectivity in the ventral stream compared to the dorsal stream. In addition, in the linguistically most demanding "semantic task," musicians outperformed nonmusicians, and this behavioral advantage was accompanied by increased left-hemispheric theta connectivity in both streams. Moreover, theta coherence in the left dorsal pathway was positively correlated with the number of years of music training. These results provide evidence for a complex interplay within a network of brain regions involved in semantic processing and verbal memory functions, and suggest that intensive music training can modify its functional architecture leading to advantages in novel word learning. © 2017 Wiley Periodicals, Inc.

A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

Laws of valley growth

NASA Astrophysics Data System (ADS)

Seybold, Hansjoerg; Yi, Robert; Willenbring, Jane; Kirchner, James; Rothman, Daniel

2015-04-01

The question of how the channel heads advance has long been debated [1,2]. By studying a simplified setting - channels incised by re-emerging groundwater flow - we seek insight into the headward growth of channel networks, by combining theoretical modeling with field observations. A concept for how such seepage channel systems form was first proposed by T. Dunne in the early 1980s [2]. A small bulge in the sidewall of a stream focuses ground water flow. This results in a larger flux and therefore a higher erosion rate in this direction. Over time such small perturbations grow into newly formed streams, but how they do so and how erosion depends on the water flux is unclear. The theory of diffusive growth provides a theoretical framework to describe channelization in response to groundwater flow. For this system the underlying physical equations are well-defined, and numerical and analytical predictions can be obtained and tested in the field. If a stream advances at a rate v˜ q^η, where q is the discharge of ground water into the tip, theory predicts that η has to be smaller than a critical value η^star to obtain ramified networks [3]. We test this hypothesis by measuring erosion rates in a field site in the Florida Panhandle, which provides a natural laboratory to study channel incision by re-emerging groundwater flow [4]. Our theoretical network reconstruction yields tip growth rates which we can directly compare to observational rates obtained from cosmogenic 10Be measurements. This comparison of theory and observation allows us to verify the existence of a constitutive discharge-erosion relation, and to better characterize growth and competition of streams at the channel head. [1] Montgommery, D. R. and Dietrich, W. E. Where do channels begin?, Nature, 336, no. 6196 (1988): 232-234 [2] Dunne, T. Formation and controls of channel networks, Prog. Phys. Geogr., 4 (1980): 211-239 [3] Carleson, L. and Makarov, N. Laplacian path models, J. Anal. Math., 87, no. 1 (2002): 103-150 [4] Devauchelle, O., Petroff, A. P., Seybold, H., & Rothman, D. H. Ramification of stream networks, PNAS, 109 (51), 20832-20836.

EML, VEGA, ODM, LTER, GLEON - considerations and technologies for building a buoy information system at an LTER site

NASA Astrophysics Data System (ADS)

Gries, C.; Winslow, L.; Shin, P.; Hanson, P. C.; Barseghian, D.

2010-12-01

At the North Temperate Lakes Long Term Ecological Research (NTL LTER) site six buoys and one met station are maintained, each equipped with up to 20 sensors producing up to 45 separate data streams at a 1 or 10 minute frequency. Traditionally, this data volume has been managed in many matrix type tables, each described in the Ecological Metadata Language (EML) and accessed online by a query system based on the provided metadata. To develop a more flexible information system, several technologies are currently being experimented with. We will review, compare and evaluate these technologies and discuss constraints and advantages of network memberships and implementation of standards. A Data Turbine server is employed to stream data from data logger files into a database with the Real-time Data Viewer being used for monitoring sensor health. The Kepler work flow processor is being explored to introduce quality control routines into this data stream taking advantage of the Data Turbine actor. Kepler could replace traditional database triggers while adding visualization and advanced data access functionality for downstream modeling or other analytical applications. The data are currently streamed into the traditional matrix type tables and into an Observation Data Model (ODM) following the CUAHSI ODM 1.1 specifications. In parallel these sensor data are managed within the Global Lake Ecological Observatory Network (GLEON) where the software package Ziggy streams the data into a database of the VEGA data model. Contributing data to a network implies compliance with established standards for data delivery and data documentation. ODM or VEGA type data models are not easily described in EML, the metadata exchange standard for LTER sites, but are providing many advantages from an archival standpoint. Both GLEON and CUAHSI have developed advanced data access capabilities based on their respective data models and data exchange standards while LTER is currently in a phase of intense technology developments which will eventually provide standardized data access that includes ecological data set types currently not covered by either ODM or VEGA.

CCSDS Advanced Orbiting Systems Virtual Channel Access Service for QoS MACHETE Model

NASA Technical Reports Server (NTRS)

Jennings, Esther H.; Segui, John S.

2011-01-01

To support various communications requirements imposed by different missions, interplanetary communication protocols need to be designed, validated, and evaluated carefully. Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in "Simulator of Space Communication Networks" (NPO-41373), NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. By building abstract behavioral models of network protocols, one can validate performance after identifying the appropriate metrics of interest. The innovators have extended the MACHETE model library to include a generic link-layer Virtual Channel (VC) model supporting quality-of-service (QoS) controls based on IP streams. The main purpose of this generic Virtual Channel model addition was to interface fine-grain flow-based QoS (quality of service) between the network and MAC layers of the QualNet simulator, a commercial component of MACHETE. This software model adds the capability of mapping IP streams, based on header fields, to virtual channel numbers, allowing extended QoS handling at link layer. This feature further refines the QoS v existing at the network layer. QoS at the network layer (e.g. diffserv) supports few QoS classes, so data from one class will be aggregated together; differentiating between flows internal to a class/priority is not supported. By adding QoS classification capability between network and MAC layers through VC, one maps multiple VCs onto the same physical link. Users then specify different VC weights, and different queuing and scheduling policies at the link layer. This VC model supports system performance analysis of various virtual channel link-layer QoS queuing schemes independent of the network-layer QoS systems.

Dendritic Connectivity, Heterogeneity, and Scaling in Urban Stormwater Networks: Implications for Socio-Hydrology

NASA Astrophysics Data System (ADS)

Mejia, A.; Jovanovic, T.; Hale, R. L.; Gironas, J. A.

2017-12-01

Urban stormwater networks (USNs) are unique dendritic (tree-like) structures that combine both artificial (e.g., swales and pipes) and natural (e.g., streams and wetlands) components. They are central to stream ecosystem structure and function in urban watersheds. The emphasis of conventional stormwater management, however, has been on localized, temporal impacts (e.g., changes to hydrographs at discrete locations), and the performance of individual stormwater control measures. This is the case even though control measures are implemented to prevent impacts on the USN. We develop a modeling approach to retrospectively study hydrological fluxes and states in USNs and apply the model to an urban watershed in Scottsdale, Arizona, USA. Using outputs from the model, we analyze over space and time the network properties of dendritic connectivity, heterogeneity, and scaling. Results show that as the network growth over time, due to increasing urbanization, it tends to become more homogenous in terms of topological features but increasingly heterogeneous in terms of dynamic features. We further use the modeling results to address socio-hydrological implications for USNs. We find that the adoption over time of evolving management strategies (e.g., widespread implementation of vegetated swales and retention ponds versus pipes) may be locally beneficial to the USN but benefits may not propagate systematically through the network. The latter can be reinforced by sudden, perhaps unintended, changes to the overall dendritic connectivity.

MODELING THE EFFECT OF STREAM NETWORK CHARACTERISTICS AND JUVENILE MOVEMENT ON COHO SALMON

EPA Science Inventory

Simulation modeling can be a valuable tool for improving our scientific understanding of the mechanisms that affect fish abundance and sustainability. Spatially explicit models, in particular, can be used to study interactions between fish biology and spatiotemporal habitat patt...

Real-time video streaming using H.264 scalable video coding (SVC) in multihomed mobile networks: a testbed approach

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2011-03-01

Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.

A method to assess longitudinal riverine connectivity in tropical streams dominated by migratory biota

USGS Publications Warehouse

Crook, K.E.; Pringle, C.M.; Freeman, Mary C.

2009-01-01

1. One way in which dams affect ecosystem function is by altering the distribution and abundance of aquatic species. 2. Previous studies indicate that migratory shrimps have significant effects on ecosystem processes in Puerto Rican streams, but are vulnerable to impediments to upstream or downstream passage, such as dams and associated water intakes where stream water is withdrawn for human water supplies. Ecological effects of dams and water withdrawals from streams depend on spatial context and temporal variability of flow in relation to the amount of water withdrawn. 3. This paper presents a conceptual model for estimating the probability that an individual shrimp is able to migrate from a stream's headwaters to the estuary as a larva, and then return to the headwaters as a juvenile, given a set of dams and water withdrawals in the stream network. The model is applied to flow and withdrawal data for a set of dams and water withdrawals in the Caribbean National Forest (CNF) in Puerto Rico. 4. The index of longitudinal riverine connectivity (ILRC), is used to classify 17 water intakes in streams draining the CNF as having low, moderate, or high connectivity in terms of shrimp migration in both directions. An in-depth comparison of two streams showed that the stream characterized by higher water withdrawal had low connectivity, even during wet periods. Severity of effects is illustrated by a drought year, where the most downstream intake caused 100% larval shrimp mortality 78% of the year. 5. The ranking system provided by the index can be used as a tool for conservation ecologists and water resource managers to evaluate the relative vulnerability of migratory biota in streams, across different scales (reach-network), to seasonally low flows and extended drought. This information can be used to help evaluate the environmental tradeoffs of future water withdrawals. ?? 2008 John Wiley & Sons, Ltd.

Mapping longitudinal stream connectivity in the North St. Vrain Creek watershed of Colorado

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wohl, Ellen; Rathburn, Sara; Chignell, Stephen

We use reach-scale stream gradient as an indicator of longitudinal connectivity for water, sediment, and organic matter in a mountainous watershed in Colorado. Stream reaches with the highest gradient tend to have narrow valley bottoms with limited storage space and attenuation of downstream fluxes, whereas stream reaches with progressively lower gradients have progressively more storage and greater attenuation. We compared the distribution of stream gradient to stream-reach connectivity rankings that incorporated multiple potential control variables, including lithology, upland vegetation, hydroclimatology, road crossings, and flow diversions. We then assessed connectivity rankings using different weighting schemes against stream gradient and against field-basedmore » understanding of relative connectivity within the watershed. Here, we conclude that stream gradient, which is simple to map using publicly available data and digital elevation models, is the most robust indicator of relative longitudinal connectivity within the river network.« less

Mapping longitudinal stream connectivity in the North St. Vrain Creek watershed of Colorado

DOE PAGES

Wohl, Ellen; Rathburn, Sara; Chignell, Stephen; ...

2016-05-06

We use reach-scale stream gradient as an indicator of longitudinal connectivity for water, sediment, and organic matter in a mountainous watershed in Colorado. Stream reaches with the highest gradient tend to have narrow valley bottoms with limited storage space and attenuation of downstream fluxes, whereas stream reaches with progressively lower gradients have progressively more storage and greater attenuation. We compared the distribution of stream gradient to stream-reach connectivity rankings that incorporated multiple potential control variables, including lithology, upland vegetation, hydroclimatology, road crossings, and flow diversions. We then assessed connectivity rankings using different weighting schemes against stream gradient and against field-basedmore » understanding of relative connectivity within the watershed. Here, we conclude that stream gradient, which is simple to map using publicly available data and digital elevation models, is the most robust indicator of relative longitudinal connectivity within the river network.« less

Understanding the Perceptions of Network Gatekeepers on Bandwidth and Online Video Streams in Ahmadu Bello University, Nigeria

ERIC Educational Resources Information Center

Odigie, Imoisili Ojeime; Gbaje, Ezra Shiloba

2017-01-01

Online video streaming is a learning technology used in today's world and reliant on the availability of bandwidth. This research study sought to understand the perceptions of network gatekeepers about bandwidth and online video streams in Ahmadu Bello University, Nigeria. To achieve this, the interpretive paradigm and the Network Gatekeeping…

A Spiking Neural Network Based Cortex-Like Mechanism and Application to Facial Expression Recognition

PubMed Central

Fu, Si-Yao; Yang, Guo-Sheng; Kuai, Xin-Kai

2012-01-01

In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism. PMID:23193391

A spiking neural network based cortex-like mechanism and application to facial expression recognition.

PubMed

Fu, Si-Yao; Yang, Guo-Sheng; Kuai, Xin-Kai

2012-01-01

In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism.

Design Automation for Streaming Systems

DTIC Science & Technology

2005-12-16

which are FIFO buffered channels. We develop a process network model for streaming sys - tems (TDFPN) and a hardware description language with built in...and may include an automatic address generator. A complete synthesis sys - tem would provide separate segment operator implementations for every...Acoustics, Speech, and Signal Processing (ICASSP ’89), pages 988– 991, 1989. [Luk et al., 1997] Wayne Luk, Nabeel Shirazi, and Peter Y. K. Cheung

Conjunctive-management models for sustained yield of stream-aquifer systems

USGS Publications Warehouse

Barlow, P.M.; Ahlfeld, D.P.; Dickerman, D.C.

2003-01-01

Conjunctive-management models that couple numerical simulation with linear optimization were developed to evaluate trade-offs between groundwater withdrawals and streamflow depletions for alluvial-valley stream-aquifer systems representative of those of the northeastern United States. A conjunctive-management model developed for a hypothetical stream-aquifer system was used to assess the effect of interannual hydrologic variability on minimum monthly streamflow requirements. The conjunctive-management model was applied to the Hunt-Annaquatucket-Pettaquamscutt stream-aquifer system of central Rhode Island. Results show that it is possible to increase the amount of current withdrawal from the aquifer by as much as 50% by modifying current withdrawal schedules, modifying the number and configuration of wells in the supply-well network, or allowing increased streamflow depletion in the Annaquatucket and Pettaquamscutt rivers. Alternatively, it is possible to reduce current rates of streamflow depletion in the Hunt River by as much as 35% during the summer, but such reductions would result increases in groundwater withdrawals.

Cumulative Significance of Hyporheic Exchange and Biogeochemical Processing in River Networks

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.

2014-12-01

Biogeochemical reactions in rivers that decrease excessive loads of nutrients, metals, organic compounds, etc. are enhanced by hydrologic interactions with microbially and geochemically active sediments of the hyporheic zone. The significance of reactions in individual hyporheic flow paths has been shown to be controlled by the contact time between river water and sediment and the intrinsic reaction rate in the sediment. However, little is known about how the cumulative effects of hyporheic processing in large river basins. We used the river network model NEXSS (Gomez-Velez and Harvey, submitted) to simulate hyporheic exchange through synthetic river networks based on the best available models of network topology, hydraulic geometry and scaling of geomorphic features, grain size, hydraulic conductivity, and intrinsic reaction rates of nutrients and metals in river sediment. The dimensionless reaction significance factor, RSF (Harvey et al., 2013) was used to quantify the cumulative removal fraction of a reactive solute by hyporheic processing. SF scales reaction progress in a single pass through the hyporheic zone with the proportion of stream discharge passing through the hyporheic zone for a specified distance. Reaction progress is optimal where the intrinsic reaction timescale in sediment matches the residence time of hyporheic flow and is less efficient in longer residence time hyporheic flow as a result of the decreasing proportion of river flow that is processed by longer residence time hyporheic flow paths. In contrast, higher fluxes through short residence time hyporheic flow paths may be inefficient because of the repeated surface-subsurface exchanges required to complete the reaction. Using NEXSS we found that reaction efficiency may be high in both small streams and large rivers, although for different reasons. In small streams reaction progress generally is dominated by faster pathways of vertical exchange beneath submerged bedforms. Slower exchange beneath meandering river banks mainly has importance only in large rivers. For solutes entering networks in proportion to water inputs it is the lower order streams that tend to dominate cumulative reaction progress.

Fragmentation alters stream fish community structure in dendritic ecological networks.

PubMed

Perkin, Joshuah S; Gido, Keith B

2012-12-01

Effects of fragmentation on the ecology of organisms occupying dendritic ecological networks (DENs) have recently been described through both conceptual and mathematical models, but few hypotheses have been tested in complex, real-world ecosystems. Stream fishes provide a model system for assessing effects of fragmentation on the structure of communities occurring within DENs, including how fragmentation alters metacommunity dynamics and biodiversity. A recently developed habitat-availability measure, the "dendritic connectivity index" (DCI), allows for assigning quantitative measures of connectivity in DENs regardless of network extent or complexity, and might be used to predict fish community response to fragmentation. We characterized stream fish community structure in 12 DENs in the Great Plains, USA, during periods of dynamic (summer) and muted (fall) discharge regimes to test the DCI as a predictive model of fish community response to fragmentation imposed by road crossings. Results indicated that fish communities in stream segments isolated by road crossings had reduced species richness (alpha diversity) relative to communities that maintained connectivity with the surrounding DEN during summer and fall. Furthermore, isolated communities had greater dissimilarity (beta diversity) to downstream sites notisolated by road crossings during summer and fall. Finally, dissimilarity among communities within DENs decreased as a function of increased habitat connectivity (measured using the DCI) for summer and fall, suggesting that communities within highly connected DENs tend to be more homogeneous. Our results indicate that the DCI is sensitive to community effects of fragmentation in riverscapes and might be used by managers to predict ecological responses to changes in habitat connectivity. Moreover, our findings illustrate that relating structural connectivity of riverscapes to functional connectivity among communities might aid in maintaining metacommunity dynamics and biodiversity in complex dendritic ecosystems.

Effectiveness of the New Hampshire stream-gaging network in providing regional streamflow information

USGS Publications Warehouse

Olson, Scott A.

2003-01-01

The stream-gaging network in New Hampshire was analyzed for its effectiveness in providing regional information on peak-flood flow, mean-flow, and low-flow frequency. The data available for analysis were from stream-gaging stations in New Hampshire and selected stations in adjacent States. The principles of generalized-least-squares regression analysis were applied to develop regional regression equations that relate streamflow-frequency characteristics to watershed characteristics. Regression equations were developed for (1) the instantaneous peak flow with a 100-year recurrence interval, (2) the mean-annual flow, and (3) the 7-day, 10-year low flow. Active and discontinued stream-gaging stations with 10 or more years of flow data were used to develop the regression equations. Each stream-gaging station in the network was evaluated and ranked on the basis of how much the data from that station contributed to the cost-weighted sampling-error component of the regression equation. The potential effect of data from proposed and new stream-gaging stations on the sampling error also was evaluated. The stream-gaging network was evaluated for conditions in water year 2000 and for estimated conditions under various network strategies if an additional 5 years and 20 years of streamflow data were collected. The effectiveness of the stream-gaging network in providing regional streamflow information could be improved for all three flow characteristics with the collection of additional flow data, both temporally and spatially. With additional years of data collection, the greatest reduction in the average sampling error of the regional regression equations was found for the peak- and low-flow characteristics. In general, additional data collection at stream-gaging stations with unregulated flow, relatively short-term record (less than 20 years), and drainage areas smaller than 45 square miles contributed the largest cost-weighted reduction to the average sampling error of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active stations, the reactivation of discontinued stations, or the activation of new stations to maximize the regional information content provided by the stream-gaging network. Final decisions regarding altering the New Hampshire stream-gaging network would require the consideration of the many uses of the streamflow data serving local, State, and Federal interests.

A geostatistical state-space model of animal densities for stream networks.

PubMed

Hocking, Daniel J; Thorson, James T; O'Neil, Kyle; Letcher, Benjamin H

2018-06-21

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty under-estimated. We developed a novel statistical method to account for spatio-temporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 years. Increasing the number of survey sites within the network improved the performance of the non-spatial model but only marginally improved the density estimates in the spatio-temporal model. We applied this model to Brook Trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 years from 1981 - 2014. We found the model including temporal and spatio-temporal autocorrelation best described young-of-the-year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately-high spatio-temporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatio-temporal correlation and higher temporal autocorrelation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

USGS Publications Warehouse

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danny L. Anderson

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates amore » new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.« less

Data modeling of network dynamics

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad

2004-01-01

This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.

From genes to brain development to phenotypic behavior: "dorsal-stream vulnerability" in relation to spatial cognition, attention, and planning of actions in Williams syndrome (WS) and other developmental disorders.

PubMed

Atkinson, Janette; Braddick, Oliver

2011-01-01

Visual information is believed to be processed through two distinct, yet interacting cortical streams. The ventral stream performs the computations needed for recognition of objects and faces ("what" and "who"?) and the dorsal stream the computations for registering spatial relationships and for controlling visually guided actions ("where" and "how"?). We initially proposed a model of spatial deficits in Williams syndrome (WS) in which visual abilities subserved by the ventral stream, such as face recognition, are relatively well developed (although not necessarily in exactly the same way as in typical development), whereas dorsal-stream functions, such as visuospatial actions, are markedly impaired. Since these initial findings in WS, deficits of motion coherence sensitivity, a dorsal-stream function has been found in other genetic disorders such as Fragile X and autism, and as a consequence of perinatal events (in hemiplegia, perinatal brain anomalies following very premature birth), leading to the proposal of a general "dorsal-stream vulnerability" in many different conditions of abnormal human development. In addition, dorsal-stream systems provide information used in tasks of visuospatial memory and locomotor planning, and these systems are closely coupled to networks for attentional control. We and several other research groups have previously shown deficits of frontal and parietal lobe function in WS individuals for specific attention tasks [e.g., Atkinson, J., Braddick, O., Anker, S., Curran, W., & Andrew, R. (2003). Neurobiological models of visuospatial cognition in children with Williams Syndrome: Measures of dorsal-stream and frontal function. Developmental Neuropsychology, 23(1/2), 141-174.]. We have used the Test of Everyday Attention for Children (TEA-Ch) which aims to attempt to separate components of attention with distinct brain networks (selective attention, sustained attention, and attention control-executive function) testing a group of older children with WS, but this test battery is too demanding for many children and adults with WS. Consequently, we have devised a new set of tests of attention, the Early Childhood Attention Battery (ECAB). This uses similar principles to the TEA-Ch, but adapted for mental ages younger than 6 years. The ECAB shows a distinctive attention profile for WS individuals relative to their overall cognitive development, with relative strength in tasks of sustained attention and poorer performance on tasks of selective attention and executive control. These profiles, and the characteristic developmental courses, also show differences between children with Down's syndrome and WS. This chapter briefly reviews new research findings on WS in these areas, relating the development of brain systems in WS to evidence from neuroimaging in typically developing infants, children born very preterm, and normal adults. The hypothesis of "dorsal-stream(s) vulnerability" which will be discussed includes a number of interlinked brain networks, subserving not only global visual processing and formulation of visuomotor actions but interlinked networks of attention. Copyright © 2011 Elsevier B.V. All rights reserved.

Sensitivity of New England Stream Temperatures to Air Temperature and Precipitation Under Projected Climate

NASA Astrophysics Data System (ADS)

Huang, T.; Samal, N. R.; Wollheim, W. M.; Stewart, R. J.; Zuidema, S.; Prousevitch, A.; Glidden, S.

2015-12-01

The thermal response of streams and rivers to changing climate will influence aquatic habitat. This study examines the impact that changing climate has on stream temperatures in the Merrimack River, NH/MA USA using the Framework for Aquatic Modeling in the Earth System (FrAMES), a spatially distributed river network model driven by air temperature, air humidity, wind speed, precipitation, and solar radiation. Streamflow and water temperatures are simulated at a 45-second (latitude x longitude) river grid resolution for 135 years under historical and projected climate variability. Contemporary streamflow (Nash-Sutcliffe Coefficient = 0.77) and river temperatures (Nash-Sutcliffe Coefficient = 0.89) matched at downstream USGS gauge data well. A suite of model runs were made in combination with uniformly increased daily summer air temperatures by 2oC, 4 oC and 6 oC as well as adjusted precipitation by -40%, -30%, -20%, -10% and +10% as a sensitivity analysis to explore a broad range of potential future climates. We analyzed the summer stream temperatures and the percent of river length unsuitable for cold to warm water fish habitats. Impacts are greatest in large rivers due to the accumulation of river temperature warming throughout the entire river network. Cold water fish (i.e. brook trout) are most strongly affected while, warm water fish (i.e. largemouth bass) aren't expected to be impacted. The changes in stream temperatures under various potential climate scenarios will provide a better understanding of the specific impact that air temperature and precipitation have on aquatic thermal regimes and habitat.

The NorWeST Stream Temperature Database, Model, and Climate Scenarios for the Northwest U.S. (Invited)

NASA Astrophysics Data System (ADS)

Isaak, D.; Wenger, S.; Peterson, E.; Ver Hoef, J.; Luce, C.; Hostetler, S. W.; Kershner, J.; Dunham, J.; Nagel, D.; Roper, B.

2013-12-01

Anthropogenic climate change is warming the Earth's rivers and streams and threatens significant changes to aquatic biodiversity. Effective threat response will require prioritization of limited conservation resources and coordinated interagency efforts guided by accurate information about climate, and climate change, at scales relevant to the distributions of species across landscapes. Here, we describe the NorWeST (i.e., NorthWest Stream Temperature) project to develop a comprehensive interagency stream temperature database and high-resolution climate scenarios across Washington, Oregon, Idaho, Montana, and Wyoming (~400,000 stream kilometers). The NorWeST database consists of stream temperature data contributed by >60 state, federal, tribal, and private resource agencies and may be the largest of its kind in the world (>45,000,000 hourly temperature recordings at >15,000 unique monitoring sites). These data are being used with spatial statistical network models to accurately downscale (R2 = 90%; RMSE < 1 C) global climate patterns to all perennially flowing reaches within river networks at 1-kilometer resolution. Historic stream temperature scenarios are developed using air temperature data from RegCM3 runs for the NCEP historical reanalysis and future scenarios (2040s and 2080s) are developed by applying bias corrected air temperature and discharge anomalies from ensemble climate and hydrology model runs for A1B and A2 warming trajectories. At present, stream temperature climate scenarios have been developed for 230,000 stream kilometers across Idaho and western Montana using data from more than 7,000 monitoring sites. The raw temperature data and stream climate scenarios are made available as ArcGIS geospatial products for download through the NorWeST website as individual river basins are completed (http://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.shtml). By providing open access to temperature data and scenarios, the project is fostering new research on stream temperatures and better collaborative management of aquatic resources through improved: 1) climate vulnerability assessments for sensitive species, 2) decision support tools that use regionally consistent scenarios, 3) water quality assessments, and 4) temperature and biological monitoring programs. Additional project details are contained in this Great Northern Landscape Conservation Cooperative newsletter (http://greatnorthernlcc.org/features/streamtemp-database).

Revisiting Horton's laws with considerations of the directly drained VS source area

NASA Astrophysics Data System (ADS)

Yang, Soohyun; Paik, Kyungrock

2015-04-01

River networks have been regarded as excellent examples of self-similar patterns in nature. Fractal characteristics of river networks have been quantified through scaling relations between several morphologic variables (e.g., Hack, 1957; Flint, 1974). In particular, Horton's legendary study on scaling properties between numbers and lengths of streams in different orders (Horton, 1945) has significantly influenced research studies in this subject. Today, Horton's laws are referred to the log-linear relationships of three variables across stream orders, i.e., number, length, and area which is later added by Schumm (1956). In a closer look, there is a conceptual inconsistency between their definitions though. While length is defined as the length of stream of a specific order only, area by its definition includes drainage area of lower order streams. To deal with this inconsistency, there was an attempt to distinguish the average area drained directly by the stream of a particular order in the Hortonian formulation (Marani et al., 1991; Beer and Borgas, 1993). Nevertheless, there remains an interesting problem in the definition of directly drained area for 1st order and for the rest orders in these studies. While the whole area of 1st order stream is regarded as the directly drained area in these studies, for a channel to form it needs the minimum drainage area named source area. In this study, we evaluate how significant considering this zero order area separately is in understanding overall river network organization. To this end, we define new expression for the directly drained area and revisit Horton's laws with a generalized formulation. To test the proposed ideas, several river networks extracted from digital elevation models (DEMs) are analyzed. References Beer, T., & Borgas, M. (1993). Horton's laws and the fractal nature of streams. Water Resources Research, 29(5), 1475-1487. Flint, J. J. (1974). Stream gradient as a function of order, magnitude, and discharge. Water Resources Research, 10(5), 969-973. Hack, J. T. (1957). Studies of longitudinal river profiles in Virginia and Maryland. US, Geological Survey Professional Paper, 294. Horton, R. E. (1945). Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geological Society of America Bulletin, 56(3), 275-370. Marani, A., Rigon, R., & Rinaldo, A. (1991). A note on fractal channel networks. Water Resources Research, 27(12), 3041-3049. Schumm, S. A. (1956). Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geological Society of America Bulletin, 67(5), 597-646.

Inference of Stream Network Fragmentation Patterns from Ground Water - Surface Water Interactions on the High Plains Aquifer

NASA Astrophysics Data System (ADS)

Chandler, D. G.; Yang, X.; Steward, D. R.; Gido, K.

2007-12-01

Stream networks in the Great Plains integrate fluxes from precipitation as surface runoff in discrete events and groundwater as base flow. Changes in land cover and agronomic practices and development of ground water resources to support irrigated agriculture have resulted in profound changes in the occurrence and magnitude of stream flows, especially near the Ogallala aquifer, where precipitation is low. These changes have demonstrably altered the aquatic habitat of western Kansas, with documented changes in fish populations, riparian communities and groundwater quality due to stream transmission losses. Forecasting future changes in aquatic and riparian ecology and groundwater quality requires a large scale spatially explicit model of groundwater- surface water interaction. In this study, we combine historical data on land use, stream flow, production well development and groundwater level observations with groundwater elevation modeling to support a geospatial framework for assessing changes in refugia for aquatic species in four rivers in western Kansas between 1965 and 2005. Decreased frequency and duration of streamflow occurred in all rivers, but the extent of change depended on the geomorphology of the river basin and the extent of groundwater development. In the absence of streamflow, refugia for aquatic species were defined as the stream reaches below the phreatic surface of the regional aquifer. Changes in extent, location and degree of fragmentation of gaining reaches was found to be a strong predictor of surface water occurrence during drought and a robust hydrological template for the analysis of changes in recharge to alluvial and regional aquifers and riparian and aquatic habitat.

Teasing apart the effects of natural and constructed green ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

National Hydrography Dataset Plus (NHDPlus)

EPA Pesticide Factsheets

The NHDPlus Version 1.0 is an integrated suite of application-ready geospatial data sets that incorporate many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,000-scale NHD), improved networking, naming, and value-added attributes (VAA's). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainageenforcement technique first broadly applied in New England, and thus dubbed The New-England Method. This technique involves burning-in the 1:100,000-scale NHD and when available building walls using the national WatershedBoundary Dataset (WBD). The resulting modified digital elevation model(HydroDEM) is used to produce hydrologic derivatives that agree with the NHDand WBD. An interdisciplinary team from the U. S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), and contractors, over the lasttwo years has found this method to produce the best quality NHD catchments using an automated process.The VAAs include greatly enhanced capabilities for upstream and downstream navigation, analysis and modeling. Examples include: retrieve all flowlines (predominantly confluence-to-confluence stream segments) and catchments upstream of a given flowline using queries rather than by slower flowline-by flowline navigation; retrieve flowlines by stream order; subset a stream level path sorted in hydrologic order for st

Increasingly complex representations of natural movies across the dorsal stream are shared between subjects.

PubMed

Güçlü, Umut; van Gerven, Marcel A J

2017-01-15

Recently, deep neural networks (DNNs) have been shown to provide accurate predictions of neural responses across the ventral visual pathway. We here explore whether they also provide accurate predictions of neural responses across the dorsal visual pathway, which is thought to be devoted to motion processing and action recognition. This is achieved by training deep neural networks to recognize actions in videos and subsequently using them to predict neural responses while subjects are watching natural movies. Moreover, we explore whether dorsal stream representations are shared between subjects. In order to address this question, we examine if individual subject predictions can be made in a common representational space estimated via hyperalignment. Results show that a DNN trained for action recognition can be used to accurately predict how dorsal stream responds to natural movies, revealing a correspondence in representations of DNN layers and dorsal stream areas. It is also demonstrated that models operating in a common representational space can generalize to responses of multiple or even unseen individual subjects to novel spatio-temporal stimuli in both encoding and decoding settings, suggesting that a common representational space underlies dorsal stream responses across multiple subjects. Copyright © 2015 Elsevier Inc. All rights reserved.

Mapping a lateralization gradient within the ventral stream for auditory speech perception.

PubMed

Specht, Karsten

2013-01-01

Recent models on speech perception propose a dual-stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend toward the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus. This article describes and reviews the results from a series of complementary functional magnetic resonance imaging studies that aimed to trace the hierarchical processing network for speech comprehension within the left and right hemisphere with a particular focus on the temporal lobe and the ventral stream. As hypothesized, the results demonstrate a bilateral involvement of the temporal lobes in the processing of speech signals. However, an increasing leftward asymmetry was detected from auditory-phonetic to lexico-semantic processing and along the posterior-anterior axis, thus forming a "lateralization" gradient. This increasing leftward lateralization was particularly evident for the left superior temporal sulcus and more anterior parts of the temporal lobe.

Mapping a lateralization gradient within the ventral stream for auditory speech perception

PubMed Central

Specht, Karsten

2013-01-01

Recent models on speech perception propose a dual-stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend toward the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus. This article describes and reviews the results from a series of complementary functional magnetic resonance imaging studies that aimed to trace the hierarchical processing network for speech comprehension within the left and right hemisphere with a particular focus on the temporal lobe and the ventral stream. As hypothesized, the results demonstrate a bilateral involvement of the temporal lobes in the processing of speech signals. However, an increasing leftward asymmetry was detected from auditory–phonetic to lexico-semantic processing and along the posterior–anterior axis, thus forming a “lateralization” gradient. This increasing leftward lateralization was particularly evident for the left superior temporal sulcus and more anterior parts of the temporal lobe. PMID:24106470

CNMM: a Catchment Environmental Model for Managing Water Quality and Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Li, Y.

2015-12-01

Mitigating agricultural diffuse pollution and greenhouse gas emissions is a complicated task due to tempo-spatial lags between the field practices and the watershed responses. Spatially-distributed modeling is essential to the implementation of cost-effective and best management practices (BMPs) to optimize land uses and nutrient applications as well as to project the impact of climate change on the watershed service functions. CNMM (the Catchment Nutrients Management Model) is a 3D spatially-distributed, grid-based and process-oriented biophysical model comprehensively developed to simulate energy balance, hydrology, plant/crop growth, biogeochemistry of life elements (e.g., C, N and P), waste treatment, waterway vegetation/purification, stream water quality and land management in agricultural watersheds as affected by land utilization strategies such as BMPs and by climate change. The CNMM is driven by a number of spatially-distributed data such as weather, topography (including DEM and shading), stream network, stream water, soil, vegetation and land management (including waste treatments), and runs at an hourly time step. It represents a catchment as a matrix of square uniformly-sized cells, where each cell is defined as a homogeneous hydrological response unit with all the hydrologically-significant parameters the same but varied at soil depths in fine intervals. Therefore, spatial variability is represented by allowing parameters to vary horizontally and vertically in space. A four-direction flux routing algorithm is applied to route water and nutrients across soils of cells governed by the gradients of either water head or elevation. A linear channel reservoir scheme is deployed to route water and nutrients in stream networks. The model is capable of computing CO2, CH4, NH3, NO, N2O and N2 emissions from soils and stream waters. The CNMM can serve as an idea modelling tool to investigate the overwhelming critical zone research at various catchment scales.

Landscape models of brook trout abundance and distribution in lotic habitat with field validation

USGS Publications Warehouse

McKenna, James E.; Johnson, James H.

2011-01-01

Brook trout Salvelinus fontinalis are native fish in decline owing to environmental changes. Predictions of their potential distribution and a better understanding of their relationship to habitat conditions would enhance the management and conservation of this valuable species. We used over 7,800 brook trout observations throughout New York State and georeferenced, multiscale landscape condition data to develop four regionally specific artificial neural network models to predict brook trout abundance in rivers and streams. Land cover data provided a general signature of human activity, but other habitat variables were resistant to anthropogenic changes (i.e., changing on a geological time scale). The resulting models predict the potential for any stream to support brook trout. The models were validated by holding 20% of the data out as a test set and by comparison with additional field collections from a variety of habitat types. The models performed well, explaining more than 90% of data variability. Errors were often associated with small spatial displacements of predicted values. When compared with the additional field collections (39 sites), 92% of the predictions were off by only a single class from the field-observed abundances. Among “least-disturbed” field collection sites, all predictions were correct or off by a single abundance class, except for one where brown trout Salmo trutta were present. Other degrading factors were evident at most sites where brook trout were absent or less abundant than predicted. The most important habitat variables included landscape slope, stream and drainage network sizes, water temperature, and extent of forest cover. Predicted brook trout abundances were applied to all New York streams, providing a synoptic map of the distribution of brook trout habitat potential. These fish models set benchmarks of best potential for streams to support brook trout under broad-scale human influences and can assist with planning and identification of protection or rehabilitation sites.

Rtop - an R package for interpolation along the stream network

NASA Astrophysics Data System (ADS)

Skøien, J. O.

2009-04-01

Rtop - an R package for interpolation along the stream network Geostatistical methods have been used to a limited extent for estimation along stream networks, with a few exceptions(Gottschalk, 1993; Gottschalk, et al., 2006; Sauquet, et al., 2000; Skøien, et al., 2006). Interpolation of runoff characteristics are more complicated than the traditional random variables estimated by geostatistical methods, as the measurements have a more complicated support, and many catchments are nested. Skøien et al. (2006) presented the model Top-kriging which takes these effects into account for interpolation of stream flow characteristics (exemplified by the 100 year flood). The method has here been implemented as a package in the statistical environment R (R Development Core Team, 2004). Taking advantage of the existing methods in R for working with spatial objects, and the extensive possibilities for visualizing the result, this makes it considerably easier to apply the method on new data sets, in comparison to earlier implementation of the method. Gottschalk, L. 1993. Interpolation of runoff applying objective methods. Stochastic Hydrology and Hydraulics, 7, 269-281. Gottschalk, L., I. Krasovskaia, E. Leblois, and E. Sauquet. 2006. Mapping mean and variance of runoff in a river basin. Hydrology and Earth System Sciences, 10, 469-484. R Development Core Team. 2004. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Sauquet, E., L. Gottschalk, and E. Leblois. 2000. Mapping average annual runoff: a hierarchical approach applying a stochastic interpolation scheme. Hydrological Sciences Journal, 45 (6), 799-815. Skøien, J. O., R. Merz, and G. Blöschl. 2006. Top-kriging - geostatistics on stream networks. Hydrology and Earth System Sciences, 10, 277-287.

AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

PubMed

Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

2018-05-01

The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging neuromorphic architectures.

Estimating water temperatures in small streams in western Oregon using neural network models

USGS Publications Warehouse

Risley, John C.; Roehl, Edwin A.; Conrads, Paul

2003-01-01

Artificial neural network models were developed to estimate water temperatures in small streams using data collected at 148 sites throughout western Oregon from June to September 1999. The sites were located on 1st-, 2nd-, or 3rd-order streams having undisturbed or minimally disturbed conditions. Data collected at each site for model development included continuous hourly water temperature and description of riparian habitat. Additional data pertaining to the landscape characteristics of the basins upstream of the sites were assembled using geographic information system (GIS) techniques. Hourly meteorological time series data collected at 25 locations within the study region also were assembled. Clustering analysis was used to partition 142 sites into 3 groups. Separate models were developed for each group. The riparian habitat, basin characteristic, and meteorological time series data were independent variables and water temperature time series were dependent variables to the models, respectively. Approximately one-third of the data vectors were used for model training, and the remaining two-thirds were used for model testing. Critical input variables included riparian shade, site elevation, and percentage of forested area of the basin. Coefficient of determination and root mean square error for the models ranged from 0.88 to 0.99 and 0.05 to 0.59 oC, respectively. The models also were tested and validated using temperature time series, habitat, and basin landscape data from 6 sites that were separate from the 142 sites that were used to develop the models. The models are capable of estimating water temperatures at locations along 1st-, 2nd-, and 3rd-order streams in western Oregon. The model user must assemble riparian habitat and basin landscape characteristics data for a site of interest. These data, in addition to meteorological data, are model inputs. Output from the models include simulated hourly water temperatures for the June to September period. Adjustments can be made to the shade input data to simulate the effects of minimum or maximum shade on water temperatures.

IN-STREAM AND WATERSHED PREDICTORS OF GENETIC DIVERSITY, EFFECTIVE POPULATION SIZE AND IMMIGRATION ACROSS RIVER-STREAM NETWORKS

EPA Science Inventory

The influence of spatial processes on population dynamics within river-stream networks is poorly understood. Utilizing spatially explicit analyses of temporal genetic variance, we examined whether persistence of Central Stonerollers (Campostoma anomalum) reflects differences in h...

Priority-based methods for reducing the impact of packet loss on HEVC encoded video streams

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2013-02-01

The rapid growth in the use of video streaming over IP networks has outstripped the rate at which new network infrastructure has been deployed. These bandwidth-hungry applications now comprise a significant part of all Internet traffic and present major challenges for network service providers. The situation is more acute in mobile networks where the available bandwidth is often limited. Work towards the standardisation of High Efficiency Video Coding (HEVC), the next generation video coding scheme, is currently on track for completion in 2013. HEVC offers the prospect of a 50% improvement in compression over the current H.264 Advanced Video Coding standard (H.264/AVC) for the same quality. However, there has been very little published research on HEVC streaming or the challenges of delivering HEVC streams in resource-constrained network environments. In this paper we consider the problem of adapting an HEVC encoded video stream to meet the bandwidth limitation in a mobile networks environment. Video sequences were encoded using the Test Model under Consideration (TMuC HM6) for HEVC. Network abstraction layers (NAL) units were packetized, on a one NAL unit per RTP packet basis, and transmitted over a realistic hybrid wired/wireless testbed configured with dynamically changing network path conditions and multiple independent network paths from the streamer to the client. Two different schemes for the prioritisation of RTP packets, based on the NAL units they contain, have been implemented and empirically compared using a range of video sequences, encoder configurations, bandwidths and network topologies. In the first prioritisation method the importance of an RTP packet was determined by the type of picture and the temporal switching point information carried in the NAL unit header. Packets containing parameter set NAL units and video coding layer (VCL) NAL units of the instantaneous decoder refresh (IDR) and the clean random access (CRA) pictures were given the highest priority followed by NAL units containing pictures used as reference pictures from which others can be predicted. The second method assigned a priority to each NAL unit based on the rate-distortion cost of the VCL coding units contained in the NAL unit. The sum of the rate-distortion costs of each coding unit contained in a NAL unit was used as the priority weighting. The preliminary results of extensive experiments have shown that all three schemes offered an improvement in PSNR, when comparing original and decoded received streams, over uncontrolled packet loss. Using the first method consistently delivered a significant average improvement of 0.97dB over the uncontrolled scenario while the second method provided a measurable, but less consistent, improvement across the range of testing conditions and encoder configurations.

Workflow-Oriented Cyberinfrastructure for Sensor Data Analytics

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

Sensor streams comprise an increasingly large part of Earth Science data. Analytics based on sensor data require an easy way to perform operations such as acquisition, conversion to physical units, metadata linking, sensor fusion, analysis and visualization on distributed sensor streams. Furthermore, embedding real-time sensor data into scientific workflows is of growing interest. We have implemented a scalable networked architecture that can be used to dynamically access packets of data in a stream from multiple sensors, and perform synthesis and analysis across a distributed network. Our system is based on the integrated Rule Oriented Data System (irods.org), which accesses sensor data from the Antelope Real Time Data System (brtt.com), and provides virtualized access to collections of data streams. We integrate real-time data streaming from different sources, collected for different purposes, on different time and spatial scales, and sensed by different methods. iRODS, noted for its policy-oriented data management, brings to sensor processing features and facilities such as single sign-on, third party access control lists ( ACLs), location transparency, logical resource naming, and server-side modeling capabilities while reducing the burden on sensor network operators. Rich integrated metadata support also makes it straightforward to discover data streams of interest and maintain data provenance. The workflow support in iRODS readily integrates sensor processing into any analytical pipeline. The system is developed as part of the NSF-funded Datanet Federation Consortium (datafed.org). APIs for selecting, opening, reaping and closing sensor streams are provided, along with other helper functions to associate metadata and convert sensor packets into NetCDF and JSON formats. Near real-time sensor data including seismic sensors, environmental sensors, LIDAR and video streams are available through this interface. A system for archiving sensor data and metadata in NetCDF format has been implemented and will be demonstrated at AGU.

On the usefulness of 'what' and 'where' pathways in vision.

PubMed

de Haan, Edward H F; Cowey, Alan

2011-10-01

The primate visual brain is classically portrayed as a large number of separate 'maps', each dedicated to the processing of specific visual cues, such as colour, motion or faces and their many features. In order to understand this fractionated architecture, the concept of cortical 'pathways' or 'streams' was introduced. In the currently prevailing view, the different maps are organised hierarchically into two major pathways, one involved in recognition and memory (the ventral stream or 'what' pathway) and the other in the programming of action (the dorsal stream or 'where' pathway). In this review, we question this heuristically influential but potentially misleading linear hierarchical pathway model and argue instead for a 'patchwork' or network model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Simulation of stream discharge and transport of nitrate and selected herbicides in the Mississippi River Basin

USGS Publications Warehouse

Broshears, R.E.; Clark, G.M.; Jobson, H.E.

2001-01-01

Stream discharge and the transport of nitrate, atrazine, and metolachlor in the Mississippi River Basin were simulated using the DAFLOW/BLTM hydrologic model. The simulated domain for stream discharge included river reaches downstream from the following stations in the National Stream Quality Accounting Network: Mississippi River at Clinton, IA; Missouri River at Hermann, MO: Ohio River at Grand Chain, IL: And Arkansas River at Little Rock, AR. Coefficients of hydraulic geometry were calibrated using data from water year 1996; the model was validated by favourable simulation of observed discharges in water years 1992-1994. The transport of nitrate, atrazine, and metolachlor was simulated downstream from the Mississippi River at Thebes, IL, and the Ohio River at Grand Chain. Simulated concentrations compared favourably with observed concentrations at Baton Rouge, LA. Development of this model is a preliminary step in gaining a more quantitative understanding of the sources and fate of nutrients and pesticides delivered from the Mississippi River Basin to the Gulf of Mexico.

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

USGS Publications Warehouse

Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

2001-01-01

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

Biotic Responses of Headwater Streams to Geophysical Alteration and Disturbance Related to Climate Change

NASA Astrophysics Data System (ADS)

Gresswell, R. E.; Sedell, E. R.; Cannon, S.; Hostetler, S. W.; Williams, J. E.; Haak, A. L.; Kershner, J. L.

2009-12-01

Climate change will potentially alter physical habitat availability for trout species (both native and nonnative) in the western USA, and ultimately affect population distribution and abundance in watersheds across the region. To understand the biological consequences of habitat alteration associated with climate change, we have developed models linking contemporary patterns of occurrence and abundance to geomorphic variables (e.g., aspect, elevation, and slope) and stream conditions derived from the habitat (e.g., temperature, discharge, and flood regimes). Because headwater streams may be especially susceptible to catastrophic disturbances in the form of debris flow torrents that have the potential to radically alter the physical structure of channels and sometimes extirpate local fish populations, we are focusing fine-scale spatial analyses in the high elevation systems. Risks of such disturbances increase exponentially in landscapes that have experienced recent wildfires when high-intensity precipitation or runoff events occur. Although predicting the timing, extent, and severity of future wildfires or subsequent precipitation and runoff events is difficult, it is possible to identify channels within stream networks that may be prone to debris flows. These channels can be identified using models based on characteristic storm and burn scenarios and geographic information describing topographic, soil, and vegetation characteristics. At-risk channels are being mapped throughout the stream networks within the study areas in the headwaters of the Colorado River to provide information about the potential for catastrophic population disturbance in response to variety of wildfire and post-wildfire storm scenarios.

A New Streamflow-Routing (SFR1) Package to Simulate Stream-Aquifer Interaction with MODFLOW-2000

USGS Publications Warehouse

Prudic, David E.; Konikow, Leonard F.; Banta, Edward R.

2004-01-01

The increasing concern for water and its quality require improved methods to evaluate the interaction between streams and aquifers and the strong influence that streams can have on the flow and transport of contaminants through many aquifers. For this reason, a new Streamflow-Routing (SFR1) Package was written for use with the U.S. Geological Survey's MODFLOW-2000 ground-water flow model. The SFR1 Package is linked to the Lake (LAK3) Package, and both have been integrated with the Ground-Water Transport (GWT) Process of MODFLOW-2000 (MODFLOW-GWT). SFR1 replaces the previous Stream (STR1) Package, with the most important difference being that stream depth is computed at the midpoint of each reach instead of at the beginning of each reach, as was done in the original Stream Package. This approach allows for the addition and subtraction of water from runoff, precipitation, and evapotranspiration within each reach. Because the SFR1 Package computes stream depth differently than that for the original package, a different name was used to distinguish it from the original Stream (STR1) Package. The SFR1 Package has five options for simulating stream depth and four options for computing diversions from a stream. The options for computing stream depth are: a specified value; Manning's equation (using a wide rectangular channel or an eight-point cross section); a power equation; or a table of values that relate flow to depth and width. Each stream segment can have a different option. Outflow from lakes can be computed using the same options. Because the wetted perimeter is computed for the eight-point cross section and width is computed for the power equation and table of values, the streambed conductance term no longer needs to be calculated externally whenever the area of streambed changes as a function of flow. The concentration of solute is computed in a stream network when MODFLOW-GWT is used in conjunction with the SFR1 Package. The concentration of a solute in a stream reach is based on a mass-balance approach and accounts for exchanges with (inputs from or losses to) ground-water systems. Two test examples are used to illustrate some of the capabilities of the SFR1 Package. The first test simulation was designed to illustrate how pumping of ground water from an aquifer connected to streams can affect streamflow, depth, width, and streambed conductance using the different options. The second test simulation was designed to illustrate solute transport through interconnected lakes, streams, and aquifers. Because of the need to examine time series results from the model simulations, the Gage Package first described in the LAK3 documentation was revised to include time series results of selected variables (streamflows, stream depth and width, streambed conductance, solute concentrations, and solute loads) for specified stream reaches. The mass-balance or continuity approach for routing flow and solutes through a stream network may not be applicable for all interactions between streams and aquifers. The SFR1 Package is best suited for modeling long-term changes (months to hundreds of years) in ground-water flow and solute concentrations using averaged flows in streams. The Package is not recommended for modeling the transient exchange of water between streams and aquifers when the objective is to examine short-term (minutes to days) effects caused by rapidly changing streamflows.

A simple metric to predict stream water quality from storm runoff in an urban watershed.

PubMed

Easton, Zachary M; Sullivan, Patrick J; Walter, M Todd; Fuka, Daniel R; Petrovic, A Martin; Steenhuis, Tammo S

2010-01-01

The contribution of runoff from various land uses to stream channels in a watershed is often speculated and used to underpin many model predictions. However, these contributions, often based on little or no measurements in the watershed, fail to appropriately consider the influence of the hydrologic location of a particular landscape unit in relation to the stream network. A simple model was developed to predict storm runoff and the phosphorus (P) status of a perennial stream in an urban watershed in New York State using the covariance structure of runoff from different landscape units in the watershed to predict runoff in time. One hundred and twenty-seven storm events were divided into parameterization (n = 85) and forecasting (n = 42) data sets. Runoff, dissolved P (DP), and total P (TP) were measured at nine sites distributed among three land uses (high maintenance, unmaintained, wooded), three positions in the watershed (near the outlet, midwatershed, upper watershed), and in the stream at the watershed outlet. The autocorrelation among runoff and P concentrations from the watershed landscape units (n = 9) and the covariance between measurements from the landscape units and measurements from the stream were calculated and used to predict the stream response. Models, validated using leave-one-out cross-validation and a forecasting method, were able to correctly capture temporal trends in streamflow and stream P chemistry (Nash-Sutcliffe efficiencies, 0.49-0.88). The analysis suggests that the covariance structure was consistent for all models, indicating that the physical processes governing runoff and P loss from these landscape units were stationary in time and that landscapes located in hydraulically active areas have a direct hydraulic link to the stream. This methodology provides insight into the impact of various urban landscape units on stream water quantity and quality.

High Resolution Flash Flood Forecasting Using a Wireless Sensor Network in the Dallas-Fort Worth Metroplex

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.

2017-12-01

In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation

EPA Science Inventory

Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Excep...

An Epidemiological Network Model for Disease Outbreak Detection

PubMed Central

Reis, Ben Y; Kohane, Isaac S; Mandl, Kenneth D

2007-01-01

Background Advanced disease-surveillance systems have been deployed worldwide to provide early detection of infectious disease outbreaks and bioterrorist attacks. New methods that improve the overall detection capabilities of these systems can have a broad practical impact. Furthermore, most current generation surveillance systems are vulnerable to dramatic and unpredictable shifts in the health-care data that they monitor. These shifts can occur during major public events, such as the Olympics, as a result of population surges and public closures. Shifts can also occur during epidemics and pandemics as a result of quarantines, the worried-well flooding emergency departments or, conversely, the public staying away from hospitals for fear of nosocomial infection. Most surveillance systems are not robust to such shifts in health-care utilization, either because they do not adjust baselines and alert-thresholds to new utilization levels, or because the utilization shifts themselves may trigger an alarm. As a result, public-health crises and major public events threaten to undermine health-surveillance systems at the very times they are needed most. Methods and Findings To address this challenge, we introduce a class of epidemiological network models that monitor the relationships among different health-care data streams instead of monitoring the data streams themselves. By extracting the extra information present in the relationships between the data streams, these models have the potential to improve the detection capabilities of a system. Furthermore, the models' relational nature has the potential to increase a system's robustness to unpredictable baseline shifts. We implemented these models and evaluated their effectiveness using historical emergency department data from five hospitals in a single metropolitan area, recorded over a period of 4.5 y by the Automated Epidemiological Geotemporal Integrated Surveillance real-time public health–surveillance system, developed by the Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology on behalf of the Massachusetts Department of Public Health. We performed experiments with semi-synthetic outbreaks of different magnitudes and simulated baseline shifts of different types and magnitudes. The results show that the network models provide better detection of localized outbreaks, and greater robustness to unpredictable shifts than a reference time-series modeling approach. Conclusions The integrated network models of epidemiological data streams and their interrelationships have the potential to improve current surveillance efforts, providing better localized outbreak detection under normal circumstances, as well as more robust performance in the face of shifts in health-care utilization during epidemics and major public events. PMID:17593895

Quantifying Stream-Aquifer Exchanges Over Scales: the Concept of Nested Interfaces

NASA Astrophysics Data System (ADS)

Flipo, N.; Mouhri, A.; Labarthe, B.; Saleh, F. S.

2013-12-01

Recent developments in hydrological modelling are based on a view of the interface being a single continuum through which water flows. These coupled hydrological-hydrogeological models, emphasizing the importance of the stream-aquifer interface (SAI), are more and more used in hydrological sciences for pluri-disciplinary studies aiming at questioning environmental issues. This notion of a single continuum comes from the historical modelling of hydrosystems based on the hypothesis of a homogeneous media that led to the Darcy law. Nowadays, there is a need to first bridge the gap between hydrological and eco-hydrological views of the SAIs, and, second, to rationalize the modelling of SAI within a consistent framework that fully takes into account the multi-dimensionality of the SAIs. We first define the concept of nested SAIs as a key transitional component of continental hydrosystem. We then demonstrate the usefulness of the concept for the multi-dimensional study of the SAI, with a special emphasis on the stream network which is identified as the key component for scaling hydrological processes occurring at the interface. Finally we focus on SAI modelling at various scales with up-to-date methodologies and give some guidance for the multi-dimensional modelling of the interface using the innovative methodology MIM (Measurements-Interpolation-Modelling), which is graphically developed. MIM scales in space three pools of methods needed to fully understand SAIs. The outcome of MIM is the localization in space of the type of SAI that can be studied by a given approach. The efficiency of the method is illustrated from the local (approx. 1m) to the regional scale (> 10 000 km2) with two examples from the Paris basin (France). The first one consists in the implementation of a sampling system of stream-aquifer exchanges, which is coupled with local 2D thermo-hydro models and a pseudo 3D hydro(geo)logical model at the watershed scale (40 km2). The quantification of monthly stream-aquifer exchanges over 14 000 km of river network in the Paris basin (74 000 km2) corresponds to a unique regional scale example.

Potential Improvements for HEC-HMS Automated Parameter Estimation

DTIC Science & Technology

2006-08-01

and is now a graduate student in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana /Champaign. Daniel...divided into 14 nested subwatersheds with a flow measuring flume constructed at each of the subwatershed outlets. The drainage areas above the...boundaries and stream network, and rain and stream gauge locations are shown in Figure 1. The first HEC-HMS model was applied to the 39.8-acre drainage

Longitudinal variability in streamwater chemistry and carbon and nitrogen fluxes in restored and degraded urban stream networks.

PubMed

Sivirichi, Gwendolyn M; Kaushal, Sujay S; Mayer, Paul M; Welty, Claire; Belt, Kenneth T; Newcomer, Tamara A; Newcomb, Katie D; Grese, Melissa M

2011-02-01

Stream restoration has increasingly been used as a best management practice for improving water quality in urbanizing watersheds, yet few data exist to assess restoration effectiveness. This study examined the longitudinal patterns in carbon and nitrogen concentrations and mass balance in two restored (Minebank Run and Spring Branch) and two unrestored (Powder Mill Run and Dead Run) stream networks in Baltimore, Maryland, USA. Longitudinal synoptic sampling showed that there was considerable reach-scale variability in biogeochemistry (e.g., total dissolved nitrogen (TDN), dissolved organic carbon (DOC), cations, pH, oxidation/reduction potential, dissolved oxygen, and temperature). TDN concentrations were typically higher than DOC in restored streams, but the opposite pattern was observed in unrestored streams. Mass balances in restored stream networks showed net uptake of TDN across subreaches (mean ± standard error net uptake rate of TDN across sampling dates for Minebank Run and Spring Branch was 420.3 ± 312.2 and 821.8 ± 570.3 mg m(-2) d(-1), respectively). There was net release of DOC in the restored streams (1344 ± 1063 and 1017 ± 944.5 mg m(-2) d(-1) for Minebank Run and Spring Branch, respectively). Conversely, degraded streams, Powder Mill Run and Dead Run showed mean net release of TDN across sampling dates (629.2 ± 167.5 and 327.1 ± 134.5 mg m(-2) d(-1), respectively) and net uptake of DOC (1642 ± 505.0 and 233.7 ± 125.1 mg m(-2) d(-1), respectively). There can be substantial C and N transformations in stream networks with hydrologically connected floodplain and pond features. Assessment of restoration effectiveness depends strongly on where monitoring is conducted along the stream network. Monitoring beyond the stream-reach scale is recommended for a complete perspective of evaluation of biogeochemical function in restored and degraded urban streams.

Beaver dams maintain fish biodiversity by increasing habitat heterogeneity throughout a low-gradient stream network

USGS Publications Warehouse

Smith, Joseph M.; Mather, Martha E.

2013-01-01

In summary, within a stream network, beaver dams maintained fish biodiversity by altering in-stream habitat and increasing habitat heterogeneity. Understanding the relationship between habitat heterogeneity and biodiversity can advance basic freshwater ecology and provide science-based support for applied aquatic conservation

Data Streams: An Overview and Scientific Applications

NASA Astrophysics Data System (ADS)

Aggarwal, Charu C.

In recent years, advances in hardware technology have facilitated the ability to collect data continuously. Simple transactions of everyday life such as using a credit card, a phone, or browsing the web lead to automated data storage. Similarly, advances in information technology have lead to large flows of data across IP networks. In many cases, these large volumes of data can be mined for interesting and relevant information in a wide variety of applications. When the volume of the underlying data is very large, it leads to a number of computational and mining challenges: With increasing volume of the data, it is no longer possible to process the data efficiently by using multiple passes. Rather, one can process a data item at most once. This leads to constraints on the implementation of the underlying algorithms. Therefore, stream mining algorithms typically need to be designed so that the algorithms work with one pass of the data. In most cases, there is an inherent temporal component to the stream mining process. This is because the data may evolve over time. This behavior of data streams is referred to as temporal locality. Therefore, a straightforward adaptation of one-pass mining algorithms may not be an effective solution to the task. Stream mining algorithms need to be carefully designed with a clear focus on the evolution of the underlying data. Another important characteristic of data streams is that they are often mined in a distributed fashion. Furthermore, the individual processors may have limited processing and memory. Examples of such cases include sensor networks, in which it may be desirable to perform in-network processing of data stream with limited processing and memory [1, 2]. This chapter will provide an overview of the key challenges in stream mining algorithms which arise from the unique setup in which these problems are encountered. This chapter is organized as follows. In the next section, we will discuss the generic challenges that stream mining poses to a variety of data management and data mining problems. The next section also deals with several issues which arise in the context of data stream management. In Sect. 3, we discuss several mining algorithms on the data stream model. Section 4 discusses various scientific applications of data streams. Section 5 discusses the research directions and conclusions.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks.

PubMed

Campbell Grant, Evan H; Nichols, James D; Lowe, Winsor H; Fagan, William F

2010-04-13

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks

USGS Publications Warehouse

Campbell, Grant E.H.; Nichols, J.D.; Lowe, W.H.; Fagan, W.F.

2010-01-01

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

Use of multiple dispersal pathways facilitates amphibian persistence in stream networks

PubMed Central

Campbell Grant, Evan H.; Nichols, James D.; Lowe, Winsor H.; Fagan, William F.

2010-01-01

Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines. PMID:20351269

Automated Guideway Network Traffic Modeling

DOT National Transportation Integrated Search

1972-02-01

In the literature concerning automated guideway transportation systems, such as dual mode, a great deal of effort has been expended on the use of deterministic reservation schemes and the problem of merging streams of vehicles. However, little attent...

Dynamic network expansion, contraction, and connectivity in the river corridor of mountain stream network

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.

2017-12-01

River networks are broadly recognized to expand and contract in response to hydrologic forcing. Additionally, the individual controls on river corridor dynamics of hydrologic forcing and geologic setting are well recognized. However, we currently lack tools to integrate our understanding of process dynamics in the river corridor and make predictions at the scale of river networks. In this study, we develop a perceptual model of the river corridor in mountain river networks, translate this into a reduced-complexity mechanistic model, and implement the model in a well-studied headwater catchment. We found that the river network was most sensitive to hydrologic dynamics under the lowest discharges (Qgauge < 1 L s-1). We also demonstrate a discharge-dependence on the dominant controls on network expansion, contraction, and river corridor exchange. Finally, we suggest this parsimonious model will be useful to managers of water resources who need to estimate connectivity and flow initiation location along the river corridor over broad, unstudied catchments.

Stream Intermittency Sensors Monitor the Onset and Duration of Stream Flow Along a Channel Network During Storms

NASA Astrophysics Data System (ADS)

Jensen, C.; McGuire, K. J.

2017-12-01

Headwater streams are spatially extensive, accounting for a majority of global stream length, and supply downstream water bodies with water, sediment, organic matter, and pollutants. Much of this transmission occurs episodically during storms when stream flow and connectivity are high. Many headwaters are temporary streams that expand and contract in length in response to storms and seasonality. Understanding where and when streams carry flow is critical for conserving headwaters and protecting downstream water quality, but storm events are difficult to study in small catchments. The rise and fall of stream flow occurs rapidly in headwaters, making observation of the entire stream network difficult. Stream intermittency sensors that detect the presence or absence of water can reveal wetting and drying patterns over short time scales. We installed 50 intermittency sensors along the channel network of a small catchment (35 ha) in the Valley and Ridge of southwest Virginia. Previous work shows stream length is highly variable in this shale catchment, as the drainage density spans two orders of magnitude. The sensors record data every 15 minutes for one year to capture different seasons, antecedent moisture conditions, and precipitation rates. We seek to determine whether hysteresis between stream flow and network length occurs on the rising and falling limbs of events and if reach-scale characteristics such as valley width explain spatial patterns of flow duration. Our results indicate reaches with a wide, sediment-filled valley floor carry water for shorter periods of time than confined channel segments with steep valley side slopes. During earlier field mapping surveys, we only observed flow in a few of the tributaries for the wettest conditions mapped. The sensors now show that these tributaries flow more frequently during much smaller storms, but only for brief periods of time (< 1 hour). The high temporal sampling resolution of the sensors permits a more realistic estimate of flow duration in temporary streams, which field surveys may, otherwise, underestimate. Such continuous datasets on stream network length will allow researchers to more accurately assess the value of headwater reaches for contributions to environmental services such as aquatic habitat, hyporheic exchange, and mass fluxes of solutes.

Watershed and Economic Data InterOperability (WEDO) ...

EPA Pesticide Factsheets

Watershed and Economic Data InterOperability (WEDO) is a system of information technologies designed to publish watershed modeling studies for reuse. WEDO facilitates three aspects of interoperability: discovery, evaluation and integration of data. This increased level of interoperability goes beyond the current practice of publishing modeling studies as reports or journal articles. Rather than summarized results, modeling studies can be published with their full complement of input data, calibration parameters and output with associated metadata for easy duplication by others. Reproducible science is possible only if researchers can find, evaluate and use complete modeling studies performed by other modelers. WEDO greatly increases transparency by making detailed data available to the scientific community.WEDO is a next generation technology, a Web Service linked to the EPA’s EnviroAtlas for discovery of modeling studies nationwide. Streams and rivers are identified using the National Hydrography Dataset network and stream IDs. Streams with modeling studies available are color coded in the EnviroAtlas. One can select streams within a watershed of interest to readily find data available via WEDO. The WEDO website is linked from the EnviroAtlas to provide a thorough review of each modeling study. WEDO currently provides modeled flow and water quality time series, designed for a broad range of watershed and economic models for nutrient trading market analysis. M

Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

Design tradeoffs in long-term research for stream salamanders

USGS Publications Warehouse

Brand, Adrianne B,; Grant, Evan H. Campbell

2017-01-01

Long-term research programs can benefit from early and periodic evaluation of their ability to meet stated objectives. In particular, consideration of the spatial allocation of effort is key. We sampled 4 species of stream salamanders intensively for 2 years (2010–2011) in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA to evaluate alternative distributions of sampling locations within stream networks, and then evaluated via simulation the ability of multiple survey designs to detect declines in occupancy and to estimate dynamic parameters (colonization, extinction) over 5 years for 2 species. We expected that fine-scale microhabitat variables (e.g., cobble, detritus) would be the strongest determinants of occupancy for each of the 4 species; however, we found greater support for all species for models including variables describing position within the stream network, stream size, or stream microhabitat. A monitoring design focused on headwater sections had greater power to detect changes in occupancy and the dynamic parameters in each of 3 scenarios for the dusky salamander (Desmognathus fuscus) and red salamander (Pseudotriton ruber). Results for transect length were more variable, but across all species and scenarios, 25-m transects are most suitable as a balance between maximizing detection probability and describing colonization and extinction. These results inform sampling design and provide a general framework for setting appropriate goals, effort, and duration in the initial planning stages of research programs on stream salamanders in the eastern United States.

Apply network coding for H.264/SVC multicasting

NASA Astrophysics Data System (ADS)

Wang, Hui; Kuo, C.-C. Jay

2008-08-01

In a packet erasure network environment, video streaming benefits from error control in two ways to achieve graceful degradation. The first approach is application-level (or the link-level) forward error-correction (FEC) to provide erasure protection. The second error control approach is error concealment at the decoder end to compensate lost packets. A large amount of research work has been done in the above two areas. More recently, network coding (NC) techniques have been proposed for efficient data multicast over networks. It was shown in our previous work that multicast video streaming benefits from NC for its throughput improvement. An algebraic model is given to analyze the performance in this work. By exploiting the linear combination of video packets along nodes in a network and the SVC video format, the system achieves path diversity automatically and enables efficient video delivery to heterogeneous receivers in packet erasure channels. The application of network coding can protect video packets against the erasure network environment. However, the rank defficiency problem of random linear network coding makes the error concealment inefficiently. It is shown by computer simulation that the proposed NC video multicast scheme enables heterogenous receiving according to their capacity constraints. But it needs special designing to improve the video transmission performance when applying network coding.

Contraction driven flow in the extended vein networks of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Alim, Karen; Amselem, Gabriel; Peaudecerf, Francois; Pringle, Anne; Brenner, Michael P.

2011-11-01

The true slime mold Physarum polycephalum is a basal organism that forms an extended network of veins to forage for food. P. polycephalum is renown for its adaptive changes of vein structure and morphology in response to food sources. These rearrangements presumably occur to establish an efficient transport and mixing of resources throughout the networks thus presenting a prototype to design transport networks under the constraints of laminar flow. The physical flows of cytoplasmic fluid enclosed by the veins exhibit an oscillatory flow termed ``shuttle streaming.'' The flow exceed by far the volume required for growth at the margins suggesting that the additional energy cost for generating the flow is spent for efficient and/or targeted redistribution of resources. We show that the viscous shuttle flow is driven by the radial contractions of the veins that accompany the streaming. We present a model for the fluid flow and resource dispersion arising due to radial contractions. The transport and mixing properties of the flow are discussed.

Describing spatial pattern in stream networks: A practical approach

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

A geostatistical approach for describing spatial pattern in stream networks

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

Predicting fine-scale distributions of peripheral aquatic species in headwater streams.

PubMed

DeRolph, Christopher R; Nelson, Stacy A C; Kwak, Thomas J; Hain, Ernie F

2015-01-01

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.

Predicting fine-scale distributions of peripheral aquatic species in headwater streams

USGS Publications Warehouse

DeRolph, Christopher R.; Nelson, S.; Kwak, Thomas J.; Hain, Ernie F.

2015-01-01

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.

Predicting fine-scale distributions of peripheral aquatic species in headwater streams

DOE PAGES

DeRolph, Christopher R.; Nelson, Stacy A. C.; Kwak, Thomas J.; ...

2014-12-09

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. In this paper, we predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistancemore » and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Finally and additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.« less

Predicting fine-scale distributions of peripheral aquatic species in headwater streams

PubMed Central

DeRolph, Christopher R; Nelson, Stacy A C; Kwak, Thomas J; Hain, Ernie F

2015-01-01

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients. PMID:25628872

The NorWeST Summer Stream Temperature Model and Scenarios for the Western U.S.: A Crowd-Sourced Database and New Geospatial Tools Foster a User Community and Predict Broad Climate Warming of Rivers and Streams

NASA Astrophysics Data System (ADS)

Isaak, Daniel J.; Wenger, Seth J.; Peterson, Erin E.; Ver Hoef, Jay M.; Nagel, David E.; Luce, Charles H.; Hostetler, Steven W.; Dunham, Jason B.; Roper, Brett B.; Wollrab, Sherry P.; Chandler, Gwynne L.; Horan, Dona L.; Parkes-Payne, Sharon

2017-11-01

Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency-specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial-stream-network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site-years to develop accurate temperature models (r2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993-2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976-2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user-friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vardoyan, G.; Rao, Nageswara S; Towlsey, D.

In recent years, the computer networking community has seen a steady growth in bandwidth-delay products (BDPs). Several TCP variants were created to combat the shortcomings of legacy TCP when it comes to operation in high-BDP environments. These variants, among which are CUBIC, STCP, and H-TCP, have been extensively studied in some empirical contexts, and some analytical models exist for CUBIC and STCP. However, since these studies have been conducted, BDPs have risen even more, and new bulk data transfer tools have emerged that utilize multiple parallel TCP streams. In view of these new developments, it is imperative to revisit themore » question: Which congestion control algorithms are best adapted to current networking environments? In order to help resolve this question, we contribute the following: (i) using first principles, we develop a general throughput-prediction framework that takes into account buffer sizes and maximum window constraints; (ii) we validate the models using measurements and achieve low prediction errors; (iii) we note differences in TCP dynamics between two experimental configurations and find one of them to be significantly more deterministic than the other; we also find that CUBIC and H-TCP outperform STCP, especially when multiple streams are used; and (iv) we present preliminary results for modelling multiple TCP streams for CUBIC and STCP.« less

Monitoring Ephemeral Streams Using Airborne Very High Resolution Multispectral Remote Sensing in Arid Environments

NASA Astrophysics Data System (ADS)

Hamada, Y.; O'Connor, B. L.

2012-12-01

Development in arid environments often results in the loss and degradation of the ephemeral streams that provide habitat and critical ecosystem functions such as water delivery, sediment transport, and groundwater recharge. Quantification of these ecosystem functions is challenging because of the episodic nature of runoff events in desert landscapes and the large spatial scale of watersheds that potentially can be impacted by large-scale development. Low-impact development guidelines and regulatory protection of ephemeral streams are often lacking due to the difficulty of accurately mapping and quantifying the critical functions of ephemeral streams at scales larger than individual reaches. Renewable energy development in arid regions has the potential to disturb ephemeral streams at the watershed scale, and it is necessary to develop environmental monitoring applications for ephemeral streams to help inform land management and regulatory actions aimed at protecting and mitigating for impacts related to large-scale land disturbances. This study focuses on developing remote sensing methodologies to identify and monitor impacts on ephemeral streams resulting from the land disturbance associated with utility-scale solar energy development in the desert southwest of the United States. Airborne very high resolution (VHR) multispectral imagery is used to produce stereoscopic, three-dimensional landscape models that can be used to (1) identify and map ephemeral stream channel networks, and (2) support analyses and models of hydrologic and sediment transport processes that pertain to the critical functionality of ephemeral streams. Spectral and statistical analyses are being developed to extract information about ephemeral channel location and extent, micro-topography, riparian vegetation, and soil moisture characteristics. This presentation will demonstrate initial results and provide a framework for future work associated with this project, for developing the necessary field measurements necessary to verify remote sensing landscape models, and for generating hydrologic models and analyses.

Ecohydrological and subsurface controls on drought-induced contraction and disconnection of stream networks

NASA Astrophysics Data System (ADS)

Godsey, S.; Kirchner, J. W.; Whiting, J. A.

2016-12-01

Temporary headwater streams - both intermittent and ephemeral waterways - supply water to approximately 1/3 of the US population, and 60% of streams used for drinking water are temporary. Stream ecologists increasingly recognize that a gradient of processes across the drying continuum affect ecosystems at dynamic terrestrial-aquatic interfaces. Understanding the hydrological controls across that gradient of drying may improve management of these sensitive systems. One possible control on surface flows includes transpiration losses from either the riparian zone or the entire watershed. We mapped several stream networks under extreme low flow conditions brought on by severe drought in central Idaho and California in 2015. Compared to previous low-flow stream length estimates, the active drainage network had generally decreased by a very small amount across these sites, perhaps because stored water buffered the precipitation decrease, or because flowing channel heads are fixed by focused groundwater flow emerging at springs. We also examined the apparent sources of water for both riparian and hillslope trees using isotopic techniques. During drought conditions, we hypothesized that riparian trees - but not those far from flowing streams - would be sustained by streamflow recharging riparian aquifers, and thus would transpire water that was isotopically similar to streamflow because little soil water would remain available below the wilting point and stream water would be sustain those trees. We found a more complex pattern, but in most places stream water and water transpired by trees were isotopically distinct regardless of flow intermittency or tree location. We also found that hillslope trees outside of the riparian zone appeared to be using different waters from those used by riparian trees. Finally, we explore subsurface controls on network extent, showing that bedrock characteristics can influence network stability and contraction patterns.

Stream Splitting in Support of Intrusion Detection

DTIC Science & Technology

2003-06-01

increased. Every computer on the Internet has no need to see the traffic of every other computer on the Internet. Indeed if this was so, nothing would get ...distinguishes the stream splitter from other network analysis tools. B. HIGH LEVEL DESIGN To get the desired level of performance, a multi-threaded...of greater concern than added accuracy of a Bayesian model. This is a case where close is good enough . b. PassiveSensors Though similar to active

Temperature coefficient for modeling denitrification in surface water sediments using the mass transfer coefficient

Treesearch

T.W. Appelboom; G.M. Chescheir; F. Birgand; R.W. Skaggs; J.W. Gilliam; D. Amatya

2010-01-01

Watershed modeling has become an important tool for researchers. Modeling nitrate transport within drainage networks requires quantifying the denitrification within the sediments in canals and streams. In a previous study, several of the authors developed an equation using a term called a mass transfer coefficient to mathematically describe sediment denitrification....

Temperature coefficient for modeling denitrification in surface water sediments using the mass transfer coefficient.

Treesearch

T.W. Appelboom; G.M. Chescheir; F. Birgand; R.W. Skaggs; J.W. Gilliam; D. Amatya

2010-01-01

Watershed modeling has become an important tool for researchers. Modeling nitrate transport within drainage networks requires quantifying the denitrification within the sediments in canals and streams. In a previous study, several of the authors developed an equation using a term called a mass transfer coefficient to mathematically describe sediment denitrification....

Testing the dual-pathway model for auditory processing in human cortex.

PubMed

Zündorf, Ida C; Lewald, Jörg; Karnath, Hans-Otto

2016-01-01

Analogous to the visual system, auditory information has been proposed to be processed in two largely segregated streams: an anteroventral ("what") pathway mainly subserving sound identification and a posterodorsal ("where") stream mainly subserving sound localization. Despite the popularity of this assumption, the degree of separation of spatial and non-spatial auditory information processing in cortex is still under discussion. In the present study, a statistical approach was implemented to investigate potential behavioral dissociations for spatial and non-spatial auditory processing in stroke patients, and voxel-wise lesion analyses were used to uncover their neural correlates. The results generally provided support for anatomically and functionally segregated auditory networks. However, some degree of anatomo-functional overlap between "what" and "where" aspects of processing was found in the superior pars opercularis of right inferior frontal gyrus (Brodmann area 44), suggesting the potential existence of a shared target area of both auditory streams in this region. Moreover, beyond the typically defined posterodorsal stream (i.e., posterior superior temporal gyrus, inferior parietal lobule, and superior frontal sulcus), occipital lesions were found to be associated with sound localization deficits. These results, indicating anatomically and functionally complex cortical networks for spatial and non-spatial auditory processing, are roughly consistent with the dual-pathway model of auditory processing in its original form, but argue for the need to refine and extend this widely accepted hypothesis. Copyright © 2015 Elsevier Inc. All rights reserved.

Concentrations and annual fluxes for selected water-quality constituents from the USGS National Stream Quality Accounting Network (NASQAN) 1996-2000

USGS Publications Warehouse

Kelly, Valerie J.; Hooper, Richard P.; Aulenbach, Brent T.; Janet, Mary

2001-01-01

This report contains concentrations and annual mass fluxes (loadings) for a broad range of water-quality constituents measured during 1996-2000 as part of the U.S. Geological Survey National Stream Quality Accounting Network (NASQAN). During this period, NASQAN operated a network of 40-42 stations in four of the largest river basins of the USA: the Colorado, the Columbia, the Mississippi (including the Missouri and Ohio), and the Rio Grande. The report contains surface-water quality data, streamflow data, field measurements (e.g. water temperature and pH), sediment-chemistry data, and quality-assurance data; interpretive products include annual and average loads, regression parameters for models used to estimate loads, sub-basin yield maps, maps depicting percent detections for censored constituents, and diagrams depicting flow-weighted average concentrations. Where possible, a regression model relating concentration to discharge and season was used for flux estimation. The interpretive context provided by annual loads includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean.

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

Risk Assessment and Mapping of Fecal Contamination in the Ohio River Basin

NASA Astrophysics Data System (ADS)

Cabezas, A.; Morehead, D.; Teklitz, A.; Yeghiazarian, L.

2014-12-01

Decisions in many problems in engineering planning are invariably made under conditions of uncertainty imposed by the inherent randomness of natural phenomena. Water quality is one such problem. For example, the leading cause of surface-water impairment in the US is fecal microbial contamination, which can potentially trigger massive outbreaks of gastrointestinal disease. It is well known that the difficulty in prediction of water contamination is rooted in the stochastic variability of microbes in the environment, and in the complexity of environmental systems.To address these issues, we employ a risk-based design format to compute the variability in microbial concentrations and the probability of exceeding the E. Coli target in the Ohio River Basin (ORB). This probability is then mapped onto the basin's stream network within the ArcGIS environment. We demonstrate how spatial risk maps can be used in support of watershed management decisions, in particular in the assessment of best management practices for reduction of E. Coli load in surface water. The modeling environment selected for the analysis is the Schematic Processor (SP), a suite of geoprocessing ArcGIS tools. SP operates on a schematic, link-and-node network model of the watershed. The National Hydrography Dataset (NHD) is used as the basis for this representation, as it provides the stream network, lakes, and catchment definitions. Given the schematic network of the watershed, SP adds the capability to perform mathematical computations along the links and at the nodes. This enables modeling fate and transport of any entity over the network. Data from various sources have been integrated for this analysis. Catchment boundaries, lake locations, the stream network and flow data have been retrieved from the NHDPlus. Land use data come from the National Land Cover Database (NLCD), and microbial observations data from the Ohio River Sanitation Committee. The latter dataset is a result of a 2003-2007 longitudinal study. Samples for E. coli analysis were collected approximately every five miles along the entire length of the Ohio River, with additional samples collected at the mouths of over 125 direct tributaries to the Ohio River.

International Virtual Observatory System for Water Resources Information

NASA Astrophysics Data System (ADS)

Leinenweber, Lewis; Bermudez, Luis

2013-04-01

Sharing, accessing, and integrating hydrologic and climatic data have been identified as a critical need for some time. The current state of data portals, standards, technologies, activities, and expertise can be leverage to develop an initial operational capability for a virtual observatory system. This system will allow to link observations data with stream networks and models, and to solve semantic inconsistencies among communities. Prototyping a virtual observatory system is an inter-disciplinary, inter-agency and international endeavor. The Open Geospatial Consortium (OGC) within the OGC Interoperability Program provides the process and expertise to run such collaborative effort. The OGC serves as a global forum for the collaboration of developers and users of spatial data products and services, and to advance the development of international standards for geospatial interoperability. The project coordinated by OGC that is advancing an international virtual observatory system for water resources information is called Climatology-Hydrology Information Sharing Pilot, Phase 1 (CHISP-1). It includes observations and forecasts in the U.S. and Canada levering current networks and capabilities. It is designed to support the following use cases: 1) Hydrologic modeling for historical and near-future stream flow and groundwater conditions. Requires the integration of trans-boundary stream flow and groundwater well data, as well as national river networks (US NHD and Canada NHN) from multiple agencies. Emphasis will be on time series data and real-time flood monitoring. 2) Modeling and assessment of nutrient load into the lakes. Requires accessing water-quality data from multiple agencies and integrating with stream flow information for calculating loads. Emphasis on discrete sampled water quality observations, linking those to specific NHD stream reaches and catchments, and additional metadata for sampled data. The key objectives of these use cases are: 1) To link observations data to the stream network, enabling queries of conditions upstream from a given location to return all relevant gages and well locations. This is currently not practical with the data sources available. 2) To bridge differences in semantics across information models and processes used by the various data producers, to improve the hydrologic and water quality modeling capabilities. Other expected benefits to be derived from this project include: - Leverage a large body of existing data holdings and related activities of multiple agencies in the US and Canada. - Influence data and metadata standards used internationally for web-based information sharing, through multiple agency cooperation and OGC standards setting process. - Reduction of procurement risk through partnership-based development of an initial operating capability verses the cost for building a fully operational system using a traditional "waterfall approach". - Identification and clarification of what is possible, and of the key technical and non-technical barriers to continued progress in sharing and integrating hydrologic and climatic information. - Promote understanding and strengthen ties within the hydro-climatic community. This is anticipated to be the first phase of a multi-phase project, with future work on forecasting the hydrologic consequences of extreme weather events, and enabling more sophisticated water quality modeling.

A coupled surface-water and ground-water flow model (MODBRANCH) for simulation of stream-aquifer interaction

USGS Publications Warehouse

Swain, Eric D.; Wexler, Eliezer J.

1996-01-01

Ground-water and surface-water flow models traditionally have been developed separately, with interaction between subsurface flow and streamflow either not simulated at all or accounted for by simple formulations. In areas with dynamic and hydraulically well-connected ground-water and surface-water systems, stream-aquifer interaction should be simulated using deterministic responses of both systems coupled at the stream-aquifer interface. Accordingly, a new coupled ground-water and surface-water model was developed by combining the U.S. Geological Survey models MODFLOW and BRANCH; the interfacing code is referred to as MODBRANCH. MODFLOW is the widely used modular three-dimensional, finite-difference ground-water model, and BRANCH is a one-dimensional numerical model commonly used to simulate unsteady flow in open- channel networks. MODFLOW was originally written with the River package, which calculates leakage between the aquifer and stream, assuming that the stream's stage remains constant during one model stress period. A simple streamflow routing model has been added to MODFLOW, but is limited to steady flow in rectangular, prismatic channels. To overcome these limitations, the BRANCH model, which simulates unsteady, nonuniform flow by solving the St. Venant equations, was restructured and incorporated into MODFLOW. Terms that describe leakage between stream and aquifer as a function of streambed conductance and differences in aquifer and stream stage were added to the continuity equation in BRANCH. Thus, leakage between the aquifer and stream can be calculated separately in each model, or leakages calculated in BRANCH can be used in MODFLOW. Total mass in the coupled models is accounted for and conserved. The BRANCH model calculates new stream stages for each time interval in a transient simulation based on upstream boundary conditions, stream properties, and initial estimates of aquifer heads. Next, aquifer heads are calculated in MODFLOW based on stream stages calculated by BRANCH, aquifer properties, and stresses. This process is repeated until convergence criteria are met for head and stage. Because time steps used in ground-water modeling can be much longer than time intervals used in surface- water simulations, provision has been made for handling multiple BRANCH time intervals within one MODFLOW time step. An option was also added to BRANCH to allow the simulation of channel drying and rewetting. Testing of the coupled model was verified by using data from previous studies; by comparing results with output from a simpler, four-point implicit, open-channel flow model linked with MODFLOW; and by comparison to field studies of L-31N canal in southern Florida.

The contribution of headwater streams to biodiversity in river networks

Treesearch

Judy L. Meyer; David L. Strayer; J. Bruce Wallace; Sue L. Eggert; Gene S. Helfman; Norman E. Leonard

2007-01-01

The diversity of life in headwater streams (intermittent, first and second order) contributes to the biodiversity of a river system and its riparian network. Small streams differ widely in physical, chemical, and biotic attributes, thus providing habitats for a range of unique species. Headwater species include permanent residents as well as migrants that travel to...

Valley segments, stream reaches, and channel units [Chapter 2

Treesearch

Peter A. Bisson; David R. Montgomery; John M. Buffington

2006-01-01

Valley segments, stream reaches, and channel units are three hierarchically nested subdivisions of the drainage network (Frissell et al. 1986), falling in size between landscapes and watersheds (see Chapter 1) and individual point measurements made along the stream network (Table 2.1; also see Chapters 3 and 4). These three subdivisions compose the habitat for large,...

Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.

PubMed

Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad

2018-05-25

IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.

Benthic invertebrate fauna, small streams

Treesearch

J. Bruce Wallace; S.L. Eggert

2009-01-01

Small streams (first- through third-order streams) make up >98% of the total number of stream segments and >86% of stream length in many drainage networks. Small streams occur over a wide array of climates, geology, and biomes, which influence temperature, hydrologic regimes, water chemistry, light, substrate, stream permanence, a basin's terrestrial plant...

Recognition of degraded handwritten digits using dynamic Bayesian networks

NASA Astrophysics Data System (ADS)

Likforman-Sulem, Laurence; Sigelle, Marc

2007-01-01

We investigate in this paper the application of dynamic Bayesian networks (DBNs) to the recognition of handwritten digits. The main idea is to couple two separate HMMs into various architectures. First, a vertical HMM and a horizontal HMM are built observing the evolving streams of image columns and image rows respectively. Then, two coupled architectures are proposed to model interactions between these two streams and to capture the 2D nature of character images. Experiments performed on the MNIST handwritten digit database show that coupled architectures yield better recognition performances than non-coupled ones. Additional experiments conducted on artificially degraded (broken) characters demonstrate that coupled architectures better cope with such degradation than non coupled ones and than discriminative methods such as SVMs.

Anatomy of aphasia revisited.

PubMed

Fridriksson, Julius; den Ouden, Dirk-Bart; Hillis, Argye E; Hickok, Gregory; Rorden, Chris; Basilakos, Alexandra; Yourganov, Grigori; Bonilha, Leonardo

2018-01-17

In most cases, aphasia is caused by strokes involving the left hemisphere, with more extensive damage typically being associated with more severe aphasia. The classical model of aphasia commonly adhered to in the Western world is the Wernicke-Lichtheim model. The model has been in existence for over a century, and classification of aphasic symptomatology continues to rely on it. However, far more detailed models of speech and language localization in the brain have been formulated. In this regard, the dual stream model of cortical brain organization proposed by Hickok and Poeppel is particularly influential. Their model describes two processing routes, a dorsal stream and a ventral stream, that roughly support speech production and speech comprehension, respectively, in normal subjects. Despite the strong influence of the dual stream model in current neuropsychological research, there has been relatively limited focus on explaining aphasic symptoms in the context of this model. Given that the dual stream model represents a more nuanced picture of cortical speech and language organization, cortical damage that causes aphasic impairment should map clearly onto the dual processing streams. Here, we present a follow-up study to our previous work that used lesion data to reveal the anatomical boundaries of the dorsal and ventral streams supporting speech and language processing. Specifically, by emphasizing clinical measures, we examine the effect of cortical damage and disconnection involving the dorsal and ventral streams on aphasic impairment. The results reveal that measures of motor speech impairment mostly involve damage to the dorsal stream, whereas measures of impaired speech comprehension are more strongly associated with ventral stream involvement. Equally important, many clinical tests that target behaviours such as naming, speech repetition, or grammatical processing rely on interactions between the two streams. This latter finding explains why patients with seemingly disparate lesion locations often experience similar impairments on given subtests. Namely, these individuals' cortical damage, although dissimilar, affects a broad cortical network that plays a role in carrying out a given speech or language task. The current data suggest this is a more accurate characterization than ascribing specific lesion locations as responsible for specific language deficits.awx363media15705668782001. © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Upper Washita River Experimental Watersheds: Physiography Data

USDA-ARS?s Scientific Manuscript database

Physiographic data such as digital elevation models (DEMs), soils, geology, stream channel network characteristics, and channel stability data are essential for understanding the complex hydrologic cycle and chemical transport processes of any given study area. This paper describes physiographic dat...

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification

USGS Publications Warehouse

Carlisle, Daren M.; Wolock, David M.; Howard, Jeannette K.; Grantham, Theodore E.; Fesenmyer, Kurt; Wieczorek, Michael

2016-12-12

Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.

Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Simulation of stream discharge and transport of nitrate and selected herbicides in the Mississippi River Basin

NASA Astrophysics Data System (ADS)

Broshears, Robert E.; Clark, Gregory M.; Jobson, Harvey E.

2001-05-01

Stream discharge and the transport of nitrate, atrazine, and metolachlor in the Mississippi River Basin were simulated using the DAFLOW/BLTM hydrologic model. The simulated domain for stream discharge included river reaches downstream from the following stations in the National Stream Quality Accounting Network: Mississippi River at Clinton, IA; Missouri River at Hermann, MO; Ohio River at Grand Chain, IL; and Arkansas River at Little Rock, AR. Coefficients of hydraulic geometry were calibrated using data from water year 1996; the model was validated by favourable simulation of observed discharges in water years 1992-1994. The transport of nitrate, atrazine, and metolachlor was simulated downstream from the Mississippi River at Thebes, IL, and the Ohio River at Grand Chain. Simulated concentrations compared favourably with observed concentrations at Baton Rouge, LA. Development of this model is a preliminary step in gaining a more quantitative understanding of the sources and fate of nutrients and pesticides delivered from the Mississippi River Basin to the Gulf of Mexico. Published in 2001 by John Wiley & Sons, Ltd.

Evaluation of Topographic wetness index and catchment characteristics on spatially and temporally variable streams across an elevation gradient

NASA Astrophysics Data System (ADS)

Martin, C.

2017-12-01

Topography can be used to delineate streams and quantify the topographic control on hydrological processes of a watershed because geomorphologic processes have shaped the topography and streams of a catchment over time. Topographic Wetness index (TWI) is a common index used for delineating stream networks by predicting location of saturation excess overland flow, but is also used for other physical attributes of a watershed such as soil moisture, groundwater level, and vegetation patterns. This study evaluates how well TWI works across an elevation gradient and the relationships between the active drainage network of four headwater watersheds at various elevations in the Colorado Front Range to topography, geology, climate, soils, elevation, and vegetation in attempt to determine the controls on streamflow location and duration. The results suggest that streams prefer to flow along a path of least resistance which including faults and permeable lithology. Permeable lithologies created more connectivity of stream networks during higher flows but during lower flows dried up. Streams flowing over impermeable lithologies had longer flow duration. Upslope soil hydraulic conductivity played a role on stream location, where soils with low hydraulic conductivity had longer flow duration than soils with higher hydraulic conductivity.Finally TWI thresholds ranged from 5.95 - 10.3 due to changes in stream length and to factors such as geology and soil. TWI had low accuracy for the lowest elevation site due to the greatest change of stream length. In conclusion, structural geology, upslope soil texture, and the permeability of the underlying lithology influenced where the stream was flowing and for how long. Elevation determines climate which influences the hydrologic processes occurring at the watersheds and therefore affects the duration and timing of streams at different elevations. TWI is an adequate tool for delineating streams because results suggest topography has a primary control on the stream locations, but because intermittent streams change throughout the year a algorithm needs to be created to correspond to snow melt and rain events. Also geology indices and soil indices need be considered in addition to topography to have the most accurate derived stream network.

Evaluation Study of a Wireless Multimedia Traffic-Oriented Network Model

NASA Astrophysics Data System (ADS)

Vasiliadis, D. C.; Rizos, G. E.; Vassilakis, C.

2008-11-01

In this paper, a wireless multimedia traffic-oriented network scheme over a fourth generation system (4-G) is presented and analyzed. We conducted an extensive evaluation study for various mobility configurations in order to incorporate the behavior of the IEEE 802.11b standard over a test-bed wireless multimedia network model. In this context, the Quality of Services (QoS) over this network is vital for providing a reliable high-bandwidth platform for data-intensive sources like video streaming. Therefore, the main issues concerned in terms of QoS were the metrics for bandwidth of both dropped and lost packets and their mean packet delay under various traffic conditions. Finally, we used a generic distance-vector routing protocol which was based on an implementation of Distributed Bellman-Ford algorithm. The performance of the test-bed network model has been evaluated by using the simulation environment of NS-2.

Introduction to stream network habitat analysis

USGS Publications Warehouse

Bartholow, John M.; Waddle, Terry J.

1986-01-01

Increasing demands on stream resources by a variety of users have resulted in an increased emphasis on studies that evaluate the cumulative effects of basinwide water management programs. Network habitat analysis refers to the evaluation of an entire river basin (or network) by predicting its habitat response to alternative management regimes. The analysis principally focuses on the biological and hydrological components of the riv er basin, which include both micro- and macrohabitat. (The terms micro- and macrohabitat are further defined and discussed later in this document.) Both conceptual and analytic models are frequently used for simplifying and integrating the various components of the basin. The model predictions can be used in developing management recommendations to preserve, restore, or enhance instream fish habitat. A network habitat analysis should begin with a clear and concise statement of the study objectives and a thorough understanding of the institutional setting in which the study results will be applied. This includes the legal, social, and political considerations inherent in any water management setting. The institutional environment may dictate the focus and level of detail required of the study to a far greater extent than the technical considerations. After the study objectives, including species on interest, and institutional setting are collectively defined, the technical aspects should be scoped to determine the spatial and temporal requirements of the analysis. A macro level approach should be taken first to identify critical biological elements and requirements. Next, habitat availability is quantified much as in a "standard" river segment analysis, with the likely incorporation of some macrohabitat components, such as stream temperature. Individual river segments may be aggregated to represent the networkwide habitat response of alternative water management schemes. Things learned about problems caused or opportunities generated may be fed back to the design of new alternatives, which themselves may be similarly tested. One may get as sophisticated an analysis as the decisionmaking process demands. Figure 1 shows a decision point that asks whether the results from the micro- or macrohabitat models display cumulative or synergistic effects. If they do, then network habitat analysis is the appropriate tool. We are left, however, in a difficult bind. We may not know a priori whether the effects are cumulative or synergistic unless some network-type questions are investigated as part of the scoping process. The next several sections raise issues designed to alert the modeler to relevant questions necessary to address this paradox.

In-network adaptation of SHVC video in software-defined networks

NASA Astrophysics Data System (ADS)

Awobuluyi, Olatunde; Nightingale, James; Wang, Qi; Alcaraz Calero, Jose Maria; Grecos, Christos

2016-04-01

Software Defined Networks (SDN), when combined with Network Function Virtualization (NFV) represents a paradigm shift in how future networks will behave and be managed. SDN's are expected to provide the underpinning technologies for future innovations such as 5G mobile networks and the Internet of Everything. The SDN architecture offers features that facilitate an abstracted and centralized global network view in which packet forwarding or dropping decisions are based on application flows. Software Defined Networks facilitate a wide range of network management tasks, including the adaptation of real-time video streams as they traverse the network. SHVC, the scalable extension to the recent H.265 standard is a new video encoding standard that supports ultra-high definition video streams with spatial resolutions of up to 7680×4320 and frame rates of 60fps or more. The massive increase in bandwidth required to deliver these U-HD video streams dwarfs the bandwidth requirements of current high definition (HD) video. Such large bandwidth increases pose very significant challenges for network operators. In this paper we go substantially beyond the limited number of existing implementations and proposals for video streaming in SDN's all of which have primarily focused on traffic engineering solutions such as load balancing. By implementing and empirically evaluating an SDN enabled Media Adaptation Network Entity (MANE) we provide a valuable empirical insight into the benefits and limitations of SDN enabled video adaptation for real time video applications. The SDN-MANE is the video adaptation component of our Video Quality Assurance Manager (VQAM) SDN control plane application, which also includes an SDN monitoring component to acquire network metrics and a decision making engine using algorithms to determine the optimum adaptation strategy for any real time video application flow given the current network conditions. Our proposed VQAM application has been implemented and evaluated on an SDN allowing us to provide important benchmarks for video streaming over SDN and for SDN control plane latency.

Dimensions and dynamics of citizen observatories: The case of online amateur weather networks

NASA Astrophysics Data System (ADS)

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2016-04-01

Crowd-sourced environmental observations are being increasingly considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public (so-called citizen science) and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated citizen observatories as one of the oldest and most widely practiced citizen science activities. The objective of this paper is to introduce a conceptual framework that enables a systematic review of different dimensions of these mushrooming/expanding networks. These dimensions include the geographic scope and types of network participants; the network's establishment mechanism, revenue stream(s) and existing communication paradigm; efforts required by citizens and support offered by platform providers; and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run these networks, sustainability of the platforms, data ownership and level of transparency of each network. This framework is then utilized to perform a critical and normative review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) There are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks. (2) The revenue stream(s) of online amateur weather networks is one of the least discussed but most important dimensions that is crucial for the sustainability of these networks. (3) Although all of the networks included in this study have one or more explicit pattern of two-way communications, there is no sign (yet) of interactive information exchange among the triangle of weather observers, data aggregators and policy makers. KEYWORDS Citizen Science, Citizen Observatories, ICT-enabled citizen participation, online amateur weather networks

Stochastic cycle selection in active flow networks.

PubMed

Woodhouse, Francis G; Forrow, Aden; Fawcett, Joanna B; Dunkel, Jörn

2016-07-19

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.

Stochastic cycle selection in active flow networks

NASA Astrophysics Data System (ADS)

Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn

2016-11-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.

Stochastic cycle selection in active flow networks

PubMed Central

Woodhouse, Francis G.; Forrow, Aden; Fawcett, Joanna B.; Dunkel, Jörn

2016-01-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. PMID:27382186

77 FR 36305 - Stream Communications Network & Media, Inc.; Order of Suspension of Trading

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-18

... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] Stream Communications Network & Media, Inc.; Order of Suspension of Trading June 14, 2012. It appears to the Securities and Exchange Commission that... Network & Media, Inc. because it has not filed any periodic reports since the period ended December 31...

Introduction to Parallel Computing

DTIC Science & Technology

1992-05-01

Instruction Stream, Multiple Data Stream Machines .................... 19 2.4 Networks of M achines...independent memory units and connecting them to the processors by an interconnection network . Many different interconnection schemes have been considered, and...connected to the same processor at the same time. Crossbar switching networks are still too expensive to be practical for connecting large numbers of

An expanded role for river networks

Treesearch

Jonathan P. Benstead; David S. Leigh

2012-01-01

Estimates of stream and river area have relied on observations at coarse resolution. Consideration of the smallest and most dynamic streams could reveal a greater role for river networks in global biogeochemical cycling than previously thought.

Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams

USGS Publications Warehouse

Johnson, Zachary C.; Snyder, Craig D.; Hitt, Nathaniel P.

2017-01-01

Headwater stream responses to climate change will depend in part on groundwater‐surface water exchanges. We used linear modeling techniques to partition likely effects of shallow groundwater seepage and air temperature on stream temperatures for 79 sites in nine focal watersheds using hourly air and water temperature measurements collected during summer months from 2012 to 2015 in Shenandoah National Park, Virginia, USA. Shallow groundwater effects exhibited more variation within watersheds than between them, indicating the importance of reach‐scale assessments and the limited capacity to extrapolate upstream groundwater influences from downstream measurements. Boosted regression tree (BRT) models revealed intricate interactions among geomorphological landform features (stream slope, elevation, network length, contributing area, and channel confinement) and seasonal precipitation patterns (winter, spring, and summer months) that together were robust predictors of spatial and temporal variation in groundwater influence on stream temperatures. The final BRT model performed well for training data and cross‐validated samples (correlation = 0.984 and 0.760, respectively). Geomorphological and precipitation predictors of groundwater influence varied in their importance between watersheds, suggesting differences in spatial and temporal controls of recharge dynamics and the depth of the groundwater source. We demonstrate an application of the final BRT model to predict groundwater effects from landform and precipitation covariates at 1075 new sites distributed at 100 m increments within focal watersheds. Our study provides a framework to estimate effects of groundwater seepage on stream temperature in unsampled locations. We discuss applications for climate change research to account for groundwater‐surface water interactions when projecting future thermal thresholds for stream biota.

Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams

NASA Astrophysics Data System (ADS)

Johnson, Zachary C.; Snyder, Craig D.; Hitt, Nathaniel P.

2017-07-01

Headwater stream responses to climate change will depend in part on groundwater-surface water exchanges. We used linear modeling techniques to partition likely effects of shallow groundwater seepage and air temperature on stream temperatures for 79 sites in nine focal watersheds using hourly air and water temperature measurements collected during summer months from 2012 to 2015 in Shenandoah National Park, Virginia, USA. Shallow groundwater effects exhibited more variation within watersheds than between them, indicating the importance of reach-scale assessments and the limited capacity to extrapolate upstream groundwater influences from downstream measurements. Boosted regression tree (BRT) models revealed intricate interactions among geomorphological landform features (stream slope, elevation, network length, contributing area, and channel confinement) and seasonal precipitation patterns (winter, spring, and summer months) that together were robust predictors of spatial and temporal variation in groundwater influence on stream temperatures. The final BRT model performed well for training data and cross-validated samples (correlation = 0.984 and 0.760, respectively). Geomorphological and precipitation predictors of groundwater influence varied in their importance between watersheds, suggesting differences in spatial and temporal controls of recharge dynamics and the depth of the groundwater source. We demonstrate an application of the final BRT model to predict groundwater effects from landform and precipitation covariates at 1075 new sites distributed at 100 m increments within focal watersheds. Our study provides a framework to estimate effects of groundwater seepage on stream temperature in unsampled locations. We discuss applications for climate change research to account for groundwater-surface water interactions when projecting future thermal thresholds for stream biota.

Performance Evaluation of Peer-to-Peer Progressive Download in Broadband Access Networks

NASA Astrophysics Data System (ADS)

Shibuya, Megumi; Ogishi, Tomohiko; Yamamoto, Shu

P2P (Peer-to-Peer) file sharing architectures have scalable and cost-effective features. Hence, the application of P2P architectures to media streaming is attractive and expected to be an alternative to the current video streaming using IP multicast or content delivery systems because the current systems require expensive network infrastructures and large scale centralized cache storage systems. In this paper, we investigate the P2P progressive download enabling Internet video streaming services. We demonstrated the capability of the P2P progressive download in both laboratory test network as well as in the Internet. Through the experiments, we clarified the contribution of the FTTH links to the P2P progressive download in the heterogeneous access networks consisting of FTTH and ADSL links. We analyzed the cause of some download performance degradation occurred in the experiment and discussed about the effective methods to provide the video streaming service using P2P progressive download in the current heterogeneous networks.

Fish everywhere, all the time: modeling fish in the riverscape

EPA Science Inventory

From 2002-2006, EPA’s Western Ecology Division conducted innovative research on the population dynamics of fish within an entire stream network. Employing individual tagging and tracking technology, we examined spatial patterns of juvenile coho salmon (Oncorhynchus kisutch...

Landscape control on the hydrogeochemistry of As, Co and Pb in a boreal stream network

NASA Astrophysics Data System (ADS)

Wällstedt, Teresia; Björkvald, Louise; Laudon, Hjalmar; Borg, Hans; Mörth, Carl-Magnus

2017-08-01

In a boreal stream network, stream water concentrations of As, Co and Pb (filtered, <0.4 μm) of 10 nested streams were studied during two consecutive years in order to evaluate the influence of land cover on the temporal and spatial variability of metal concentrations and speciation. Mean concentrations of Co and Pb showed significant but contrasting relationship to landscape type, while As concentrations were not related to landscape type. Highest concentrations of Pb were found in the wetland dominated streams (>30% wetland), which was suggested to be controlled by atmospheric deposition in combination with high DOC release from the wetlands. For Co, the highest concentrations were found in the forest dominated sites (>98% forest), which were attributed to the weathering of minerogenic sources. Contrasting response to runoff events could also be related to landscape type; during the spring flood, decreasing concentrations of As, Co and Pb were observed in the wetland dominated catchments due to dilution, while increasing concentrations during spring flood were observed in the mixed catchments (2-30% wetland) and to some degree in the forested catchments, probably due to flushing of the organic-rich riparian sources. Further, metal speciation was calculated using the geochemical equilibrium model Visual MINTEQ. This suggests that dissolved inorganic species of As and Co dominated in headwater streams with low pH while DOC had a major influencing role for Pb. In the larger mixed streams where pH was higher and precipitation of e.g. colloidal Fe and Mn (hydr)oxides was favoured, the major influencing factor was instead adsorption to colloidal Fe for As and Pb, while association to organic matter and colloids of e.g. Mn influenced the concentrations of Co. We thus conclude that landscape type and the magnitude of the runoff events are of great importance for the spatial and temporal variations of As, Co and Pb in this boreal stream network. Projected climate change, with increasing runoff, may therefore influence riverine concentrations and fluxes differently, depending on the prevailing landscape type.

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.

2013-01-01

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

SPARROW modeling of nitrogen sources and transport in rivers and streams of California and adjacent states, U.S.

USGS Publications Warehouse

Saleh, Dina; Domagalski, Joseph L.

2015-01-01

The SPARROW (SPAtially Referenced Regressions On Watershed attributes) model was used to evaluate the spatial distribution of total nitrogen (TN) sources, loads, watershed yields, and factors affecting transport and decay in the stream network of California and portions of adjacent states for the year 2002. The two major TN sources to local catchments on a mass basis were fertilizers and manure (51.7%) and wastewater discharge (15.9%). Other sources contributed < 12%. Fertilizer use is widespread in the Central Valley region of California, and also important in several other regions because of the diversity of California agriculture. Precipitation, sand content of surficial soils, wetlands, and tile drains were important for TN movement to stream reaches. Median streamflow in the study area is about 0.04 m3/s. Aquatic losses of nitrogen were found to be most important in intermittent and small to medium sized streams (0.2-14 m3/s), while larger streams showed less loss, and therefore are important for TN transport. Nitrogen loss in reservoirs was found to be insignificant, possibly because most of the larger ones are located upstream of nitrogen sources. The model was used to show loadings, sources, and tributary inputs to several major rivers. The information provided by the SPARROW model is useful for determining both the major sources contributing nitrogen to streams and the specific tributaries that transport the load.

Evaluating changes in stream fish species richness over a 50-year time-period within a landscape context

USGS Publications Warehouse

Midway, Stephen R.; Wagner, Tyler; Tracy, Bryn H.; Hogue, Gabriela M.; Starnes, Wayne C.

2015-01-01

Worldwide, streams and rivers are facing a suite of pressures that alter water quality and degrade physical habitat, both of which can lead to changes in the composition and richness of fish populations. These potential changes are of particular importance in the Southeast USA, home to one of the richest stream fish assemblages in North America. Using data from 83 stream sites in North Carolina sampled in the 1960’s and the past decade, we used hierarchical Bayesian models to evaluate relationships between species richness and catchment land use and land cover (e.g., agriculture and forest cover). In addition, we examined how the rate of change in species richness over 50 years was related to catchment land use and land cover. We found a negative and positive correlation between forest land cover and agricultural land use and average species richness, respectively. After controlling for introduced species, most (66 %) stream sites showed an increase in native fish species richness, and the magnitude of the rate of increase was positively correlated to the amount of forested land cover in the catchment. Site-specific trends in species richness were not positive, on average, until the percentage forest cover in the network catchment exceeded about 55 %. These results suggest that streams with catchments that have moderate to high (>55 %) levels of forested land in upstream network catchments may be better able to increase the number of native species at a faster rate compared to less-forested catchments.

Deformation and evolution of an experimental drainage network subjected to oblique deformation: Insight from chi-maps

NASA Astrophysics Data System (ADS)

Guerit, Laure; Goren, Liran; Dominguez, Stéphane; Malavieille, Jacques; Castelltort, Sébastien

2017-04-01

The morphology of a fluvial landscape reflects a balance between its own dynamics and external forcings, and therefore holds the potential to reveal local or large-scale tectonic patterns. Commonly, particular focus has been cast on the longitudinal profiles of rivers as they constitute sensitive recorders of vertical movements, that can be recovered based on models of bedrock incision. However, several recent studies have suggested that maps of rescaled distance along channel called chi (χ), derived from the commonly observed power law relation between the slope and the drainage area , could reveal transient landscapes in state of reorganization of basin geometry and location of water divides. If river networks deforms in response to large amount of distributed strain, then they might be used to reconstruct the mode and rate of horizontal deformation away from major active structures through the use of the parameter χ. To explore how streams respond to tectonic horizontal deformation, we develop an experimental model for studying river pattern evolution over a doubly-vergent orogenic wedge growing in a context of oblique convergence. We use a series of sprinklers located about the experimental table to activate erosion, sediment transport and river development on the surface of the experimental wedge. At the end of the experiment, the drainage network is statistically rotated clockwise, confirming that rivers can record the distribution of motion along the wedge. However, the amount of rotation does not match with the imposed deformation, and thus we infer that stream networks are not purely passive markers. Based on the comparison between the observed evolution of the fluvial system and the predictions made from χ maps, we show that the plan-view morphology of the streams results from the competition between the imposed deformation and fluvial processes of drainage reorganization.

Estimating occurrence and detection probabilities for stream-breeding salamanders in the Gulf Coastal Plain

USGS Publications Warehouse

Lamb, Jennifer Y.; Waddle, J. Hardin; Qualls, Carl P.

2017-01-01

Large gaps exist in our knowledge of the ecology of stream-breeding plethodontid salamanders in the Gulf Coastal Plain. Data describing where these salamanders are likely to occur along environmental gradients, as well as their likelihood of detection, are important for the prevention and management of amphibian declines. We used presence/absence data from leaf litter bag surveys and a hierarchical Bayesian multispecies single-season occupancy model to estimate the occurrence of five species of plethodontids across reaches in headwater streams in the Gulf Coastal Plain. Average detection probabilities were high (range = 0.432–0.942) and unaffected by sampling covariates specific to the use of litter bags (i.e., bag submergence, sampling season, in-stream cover). Estimates of occurrence probabilities differed substantially between species (range = 0.092–0.703) and were influenced by the size of the upstream drainage area and by the maximum proportion of the reach that dried. The effects of these two factors were not equivalent across species. Our results demonstrate that hierarchical multispecies models successfully estimate occurrence parameters for both rare and common stream-breeding plethodontids. The resulting models clarify how species are distributed within stream networks, and they provide baseline values that will be useful in evaluating the conservation statuses of plethodontid species within lotic systems in the Gulf Coastal Plain.

ASSESSING HEADWATER STREAMS: LINKING LANDSCAPES TO STREAM NETWORKS

EPA Science Inventory

Headwater streams represent a significant land-water boundary and drain 70-80% of the landscape. Headwater streams are vital components to drainage systems and are directly linked to our downstream rivers and lakes. However, alteration and loss of headwater streams have occurre...

Analysis of streamflow-gaging network for monitoring stormwater in small streams in the Puget Sound Basin, Washington

USGS Publications Warehouse

Konrad, Christopher P.; Voss, Frank D.

2012-01-01

The streamflow-gaging network in the Puget Sound basin was analyzed for its capacity to monitor stormwater in small streams. The analysis consisted of an inventory of active and inactive gages and an evaluation of the coverage and resolution of the gaging network with an emphasis on lowland areas. The active gaging network covers much of the Puget Lowland largely by gages located at sites on larger streams and rivers. Assessments of stormwater impacts and management will likely require streamflow information with higher spatial resolution than provided by the current gaging network. Monitoring that emphasizes small streams in combination with approaches for estimating streamflow at ungaged sites provides an alternative to expanding the current gaging network that can improve the spatial resolution of streamflow information in the region. The highest priority gaps in the gaging network are low elevation basins close to the Puget Sound shoreline and sites that share less than 10 percent of the drainage area of an active gage. Although small, lowland sites with long records of streamflow are particularly valuable to maintain in the region, other criteria for prioritizing sites in the gaging network should be based on the specific questions that stormwater managers need to answer.

How and Why Does Stream Water Temperature Vary at Small Spatial Scales in a Headwater Stream?

NASA Astrophysics Data System (ADS)

Morgan, J. C.; Gannon, J. P.; Kelleher, C.

2017-12-01

The temperature of stream water is controlled by climatic variables, runoff/baseflow generation, and hyporheic exchange. Hydrologic conditions such as gaining/losing reaches and sources of inflow can vary dramatically along a stream on a small spatial scale. In this work, we attempt to discern the extent that the factors of air temperature, groundwater inflow, and precipitation influence stream temperature at small spatial scales along the length of a stream. To address this question, we measured stream temperature along the perennial stream network in a 43 ha catchment with a complex land use history in Cullowhee, NC. Two water temperature sensors were placed along the stream network on opposite sides of the stream at 100-meter intervals and at several locations of interest (i.e. stream junctions). The forty total sensors recorded the temperature every 10 minutes for one month in the spring and one month in the summer. A subset of sampling locations where stream temperature was consistent or varied from one side of the stream to the other were explored with a thermal imaging camera to obtain a more detailed representation of the spatial variation in temperature at those sites. These thermal surveys were compared with descriptions of the contributing area at the sample sites in an effort to discern specific causes of differing flow paths. Preliminary results suggest that on some branches of the stream stormflow has less influence than regular hyporheic exchange, while other tributaries can change dramatically with stormflow conditions. We anticipate this work will lead to a better understanding of temperature patterns in stream water networks. A better understanding of the importance of small-scale differences in flow paths to water temperature may be able to inform watershed management decisions in the future.

Groundwater-Surface water interaction in agricultural watershed that encompasses dense network of High Capacity wells

NASA Astrophysics Data System (ADS)

Talib, A.; Desai, A. R.

2017-12-01

The Central Sands region of Wisconsin is characterized by productive trout streams, lakes, farmland and forest. However, stream channelization, past wetland drainage, and ground water withdrawals have disrupted the hydrology of this Central Sands region. Climatically driven conditions in last decade (2000-2008) alone are unable to account for the severely depressed water levels. Increased interception and evapotranspiration from afforested areas in central sand Wisconsin may also be culprit for reduced water recharge. Hence, there is need to study the cumulative effects of changing precipitation patterns, groundwater withdrawals, and forest evapotranspiration to improve projections of the future of lake levels and water availability in this region. Here, the SWAT-MODFLOW coupled model approach was applied at large spatio-temporal scale. The coupled model fully integrates a watershed model (SWAT) with a groundwater flow model (MODFLOW). Surface water and ground water flows were simulated integratively at daily time step to estimate the groundwater discharge to the stream network in Central Sands that encompasses high capacity wells. The model was calibrated (2010-2013) and validated (2014-2017) based on streamflow, groundwater extraction, and water table elevation. As the long-term trends in some of the primary drivers is presently ambiguous in Central Sands under future climate, as is the case for total precipitation or timing of precipitation, we relied on a sensitivity student to quantitatively access how primary and secondary drivers may influence future net groundwater recharge. We demonstrate how such an approach could then be coupled with decision-making models to evaluate the effectiveness of groundwater withdrawal policies under a changing climate.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Quality of experience enhancement of high efficiency video coding video streaming in wireless packet networks using multiple description coding

NASA Astrophysics Data System (ADS)

Boumehrez, Farouk; Brai, Radhia; Doghmane, Noureddine; Mansouri, Khaled

2018-01-01

Recently, video streaming has attracted much attention and interest due to its capability to process and transmit large data. We propose a quality of experience (QoE) model relying on high efficiency video coding (HEVC) encoder adaptation scheme, in turn based on the multiple description coding (MDC) for video streaming. The main contributions of the paper are (1) a performance evaluation of the new and emerging video coding standard HEVC/H.265, which is based on the variation of quantization parameter (QP) values depending on different video contents to deduce their influence on the sequence to be transmitted, (2) QoE support multimedia applications in wireless networks are investigated, so we inspect the packet loss impact on the QoE of transmitted video sequences, (3) HEVC encoder parameter adaptation scheme based on MDC is modeled with the encoder parameter and objective QoE model. A comparative study revealed that the proposed MDC approach is effective for improving the transmission with a peak signal-to-noise ratio (PSNR) gain of about 2 to 3 dB. Results show that a good choice of QP value can compensate for transmission channel effects and improve received video quality, although HEVC/H.265 is also sensitive to packet loss. The obtained results show the efficiency of our proposed method in terms of PSNR and mean-opinion-score.

The significance of small streams

NASA Astrophysics Data System (ADS)

Wohl, Ellen

2017-09-01

Headwaters, defined here as first- and secondorder streams, make up 70%‒80% of the total channel length of river networks. These small streams exert a critical influence on downstream portions of the river network by: retaining or transmitting sediment and nutrients; providing habitat and refuge for diverse aquatic and riparian organisms; creating migration corridors; and governing connectivity at the watershed-scale. The upstream-most extent of the channel network and the longitudinal continuity and lateral extent of headwaters can be difficult to delineate, however, and people are less likely to recognize the importance of headwaters relative to other portions of a river network. Consequently, headwaters commonly lack the legal protections accorded to other portions of a river network and are more likely to be significantly altered or completely obliterated by land use.

Research to inform policy on headwater streams: ongoing and future directions

EPA Science Inventory

Headwater streams are the exterior links of stream networks and represent a substantial proportion of U.S. stream miles. Alteration and loss of headwater streams have occurred without an understanding of the potential consequences to larger downstream waterbodies. Recent court ca...

A stochastic population model to evaluate Moapa dace (Moapa coriacea) population growth under alternative management scenarios

USGS Publications Warehouse

Perry, Russell W.; Jones, Edward; Scoppettone, G. Gary

2015-07-14

Increasing or decreasing the total carrying capacity of all stream segments resulted in changes in equilibrium population size that were directly proportional to the change in capacity. However, changes in carrying capacity to some stream segments but not others could result in disproportionate changes in equilibrium population sizes by altering density-dependent movement and survival in the stream network. These simulations show how our IBM can provide a useful management tool for understanding the effect of restoration actions or reintroductions on carrying capacity, and, in turn, how these changes affect Moapa dace abundance. Such tools are critical for devising management strategies to achieve recovery goals.

Comparison of Stream Temperature Modeling Approaches: The Case of a High Alpine Watershed in the Context of Climate Change

NASA Astrophysics Data System (ADS)

Gallice, A.

2015-12-01

Stream temperature controls important aspects of the riverine habitat, such as the rate of spawning or death of many fish species, or the concentration of numerous dissolved substances. In the current context of accelerating climate change, the future evolution of stream temperature is regarded as uncertain, particularly in the Alps. This uncertainty fostered the development of many prediction models, which are usually classified in two categories: mechanistic models and statistical models. Based on the numerical resolution of physical conservation laws, mechanistic models are generally considered to provide more reliable long-term estimates than regression models. However, despite their physical basis, these models are observed to differ quite significantly in some aspects of their implementation, notably (1) the routing of water in the river channel and (2) the estimation of the temperature of groundwater discharging into the stream. For each one of these two aspects, we considered several of the standard modeling approaches reported in the literature and implemented them in a new modular framework. The latter is based on the spatially-distributed snow model Alpine3D, which is essentially used in the framework to compute the amount of water infiltrating in the upper soil layer. Starting from there, different methods can be selected for the computation of the water and energy fluxes in the hillslopes and in the river network. We relied on this framework to compare the various methodologies for river channel routing and groundwater temperature modeling. We notably assessed the impact of each these approaches on the long-term stream temperature predictions of the model under a typical climate change scenario. The case study was conducted over a high Alpine catchment in Switzerland, whose hydrological and thermal regimes are expected to be markedly affected by climate change. The results show that the various modeling approaches lead to significant differences in the model predictions, and that these differences may be larger than the uncertainties in future air temperature. It is also shown that the temperature of groundwater discharging into the stream has a marked impact on the modeled stream temperature at the catchment outlet.

Performance Evaluation of the NASA/KSC Transmission System

NASA Technical Reports Server (NTRS)

Christensen, Kenneth J.

2000-01-01

NASA-KSC currently uses three bridged 100-Mbps FDDI segments as its backbone for data traffic. The FDDI Transmission System (FTXS) connects the KSC industrial area, KSC launch complex 39 area, and the Cape Canaveral Air Force Station. The report presents a performance modeling study of the FTXS and the proposed ATM Transmission System (ATXS). The focus of the study is on performance of MPEG video transmission on these networks. Commercial modeling tools - the CACI Predictor and Comnet tools - were used. In addition, custom software tools were developed to characterize conversation pairs in Sniffer trace (capture) files to use as input to these tools. A baseline study of both non-launch and launch day data traffic on the FTXS is presented. MPEG-1 and MPEG-2 video traffic was characterized and the shaping of it evaluated. It is shown that the characteristics of a video stream has a direct effect on its performance in a network. It is also shown that shaping of video streams is necessary to prevent overflow losses and resulting poor video quality. The developed models can be used to predict when the existing FTXS will 'run out of room' and for optimizing the parameters of ATM links used for transmission of MPEG video. Future work with these models can provide useful input and validation to set-top box projects within the Advanced Networks Development group in NASA-KSC Development Engineering.

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

PubMed

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

USGS Publications Warehouse

Alexander, R.B.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.

1996-01-01

Data from two U.S. Geological Survey (USGS) national stream water-quality monitoring networks, the National Stream Quality Accounting Network (NASQAN) and the Hydrologic Benchmark Network (HBN), are now available in a two CD-ROM set. These data on CD-ROM are collectively referred to as WQN, water-quality networks. Data from these networks have been used at the national, regional, and local levels to estimate the rates of chemical flux from watersheds, quantify changes in stream water quality for periods during the past 30 years, and investigate relations between water quality and streamflow as well as the relations of water quality to pollution sources and various physical characteristics of watersheds. The networks include 679 monitoring stations in watersheds that represent diverse climatic, physiographic, and cultural characteristics. The HBN includes 63 stations in relatively small, minimally disturbed basins ranging in size from 2 to 2,000 square miles with a median drainage basin size of 57 square miles. NASQAN includes 618 stations in larger, more culturally-influenced drainage basins ranging in size from one square mile to 1.2 million square miles with a median drainage basin size of about 4,000 square miles. The CD-ROMs contain data for 63 physical, chemical, and biological properties of water (122 total constituents including analyses of dissolved and water suspended-sediment samples) collected during more than 60,000 site visits. These data approximately span the periods 1962-95 for HBN and 1973-95 for NASQAN. The data reflect sampling over a wide range of streamflow conditions and the use of relatively consistent sampling and analytical methods. The CD-ROMs provide ancillary information and data-retrieval tools to allow the national network data to be properly and efficiently used. Ancillary information includes the following: descriptions of the network objectives and history, characteristics of the network stations and water-quality data, historical records of important changes in network sample collection and laboratory analytical methods, water reference sample data for estimating laboratory measurement bias and variability for 34 dissolved constituents for the period 1985-95, discussions of statistical methods for using water reference sample data to evaluate the accuracy of network stream water-quality data, and a bibliography of scientific investigations using national network data and other publications relevant to the networks. The data structure of the CD-ROMs is designed to allow users to efficiently enter the water-quality data to user-supplied software packages including statistical analysis, modeling, or geographic information systems. On one disc, all data are stored in ASCII form accessible from any computer system with a CD-ROM driver. The data also can be accessed using DOS-based retrieval software supplied on a second disc. This software supports logical queries of the water-quality data based on constituent concentrations, sample- collection date, river name, station name, county, state, hydrologic unit number, and 1990 population and 1987 land-cover characteristics for station watersheds. User-selected data may be output in a variety of formats including dBASE, flat ASCII, delimited ASCII, or fixed-field for subsequent use in other software packages.

Live streaming video for medical education: a laboratory model.

PubMed

Gandsas, Alejandro; McIntire, Katherine; Palli, Guillermo; Park, Adrian

2002-10-01

At the University of Kentucky (UK), we applied streaming video technology to develop a webcast model that will allow institutions to broadcast live and prerecorded surgeries, conferences, and courses in real time over networks (the Internet or an intranet). We successfully broadcast a prerecorded laparoscopic paraesophageal hernia repair to domestic and international clients by using desktop computers equipped with off-the-shelf, streaming-enabled software and standard hardware and operating systems. A web-based user interface made accessing the educational material as simple as a mouse click and allowed clients to participate in the broadcast event via an embedded e-mail/chat module. Three client computers (two connected to the Internet and a third connected to the UK intranet) requested and displayed the surgical film by means of seven common network connection configurations. Significantly, no difference in image resolution was detected with the use of a connection speed faster than 128 kilobytes per second (kbps). At this connection speed, an average bandwidth of 32.7 kbps was used, and although a 15-second delay was experienced from the time of data request to data display, the surgical film streamed continuously from beginning to end at a mean rate of 14.4 frames per second (fps). The clients easily identified all anatomic structures in full color motion, clearly followed all steps of the surgical procedure, and successfully asked questions and made comments by using the e-mail/chat module while viewing the surgery. With minimal financial investment, we have created an interactive virtual classroom with the potential to attract a global audience. Our webcast model represents a simple and practical method for institutions to supplement undergraduate and graduate surgical education and offer continuing medical education credits in a way that is convenient for clients (surgeons, students, residents, others). In the future, physicians may access streaming webcast material wirelessly with hand-held computers, so that they will be freed from computer stations.

Mapping Active Stream Lengths as a Tool for Understanding Spatial Variations in Runoff Generation

NASA Astrophysics Data System (ADS)

Erwin, E. G.; Gannon, J. P.; Zimmer, M. A.

2016-12-01

Recent studies have shown temporary stream channels respond in complex ways to precipitation. By investigating how stream networks expand and recede throughout rain events, we may further develop our understanding of runoff generation. This study focused on mapping the expansion and contraction of the stream network in two headwater catchments characterized by differing soil depths and slopes, located in North Carolina, USA. The first is a 43 ha catchment located in the Southern Appalachian region, characterized by incised, steep slopes and soils of varying thickness. The second is a 3.3 ha catchment located in the Piedmont region, characterized as low relief with deep, highly weathered soils. Over a variety of flow conditions, surveys of the entire stream network were conducted at 10 m intervals to determine presence or absence of surface water. These surveys revealed several reaches within the networks that were intermittent, with perennial flow upstream and downstream. Furthermore, in some tributaries, the active stream head moved up the channel in response to precipitation and at others it remained anchored in place. Moreover, when repeat surveys were performed during the same storm, hysteresis was observed in active stream length variations: stream length was not the same on the rising limb and falling limb of the hydrograph. These observations suggest there are different geomorphological controls or runoff generation processes occurring spatially throughout these catchments. Observations of wide spatial and temporal variability of active stream length over a variety of flow conditions suggest runoff dynamics, generation mechanisms, and contributing flowpath depths producing streamflow may be highly variable and not easily predicted from streamflow observations at a fixed point. Finally, the observation of similar patterns in differing geomorphic regions suggests these processes extend beyond unique site characterizations.

MODELING NITRATE CONCENTRATION IN NATURAL STREAMS BY USING ARTIFICIAL NEURAL NETWORKS. (R827451)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Where and why hyporheic exchange is important: Inferences from a parsimonious, physically-based river network model

NASA Astrophysics Data System (ADS)

Gomez-Velez, J. D.; Harvey, J. W.

2014-12-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data as well as models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically-based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). At the core of NEXSS is a characterization of the channel geometry, geomorphic features, and related hydraulic drivers based on scaling equations from the literature and readily accessible information such as river discharge, bankfull width, median grain size, sinuosity, channel slope, and regional groundwater gradients. Multi-scale hyporheic flow is computed based on combining simple but powerful analytical and numerical expressions that have been previously published. We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bedforms dominates hyporheic fluxes and turnover rates along the river corridor. Moreover, the hyporheic zone's potential for biogeochemical transformations is comparable across stream orders, but the abundance of lower-order channels results in a considerably higher cumulative effect for low-order streams. Thus, vertical exchange beneath submerged bedforms has more potential for biogeochemical transformations than lateral exchange beneath banks, although lateral exchange through meanders may be important in large rivers. These results have implications for predicting outcomes of river and basin management practices.

Towards benchmarking citizen observatories: Features and functioning of online amateur weather networks.

PubMed

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2017-05-15

Crowd-sourced environmental observations are increasingly being considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated observatories that are rooted in one of the oldest and most widely practiced citizen science activities, namely amateur weather observation. The objective of this paper is to introduce a conceptual framework that enables a systematic review of the features and functioning of these expanding networks. This is done by considering distinct dimensions, namely the geographic scope and types of participants, the network's establishment mechanism, revenue stream(s), existing communication paradigm, efforts required by data sharers, support offered by platform providers, and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run the networks, and their sustainability. This framework is then utilized to perform a critical review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) there are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks; (2) the revenue stream(s) of online amateur weather networks is one of the least discussed but arguably most important dimensions that is crucial for the sustainability of these networks; and (3) all of the networks included in this study have one or more explicit modes of bi-directional communication, however, this is limited to feedback mechanisms that are mainly designed to educate the data sharers. Copyright © 2017 Elsevier Ltd. All rights reserved.

A simple-harmonic model for depicting the annual cycle of seasonal temperatures of streams

USGS Publications Warehouse

Steele, Timothy Doak

1978-01-01

Due to economic or operational constraints, stream-temperature records cannot always be collected at all sites where information is desired or at frequencies dictated by continuous or near-continuous surveillance requirements. For streams where only periodic measurements are made during the year, and that are not appreciably affected by regulation or by thermal loading , a simple harmonic function may adequately depict the annual seasonal cycle of stream temperature at any given site. Resultant harmonic coefficients obtained from available stream-temperature records may be used in the following ways: (1) To interpolate between discrete measurements by solving the harmonic function at specified times, thereby filling in estimates of stream-temperature values; (2) to characterize areal or regional patterns of natural stream-temperature values; (2) to characterize areal or regional patterns of natural stream-temperature conditions; and (3) to detect and to assess any significant at a site brought about by streamflow regulation or basin development. Moreover, less-than-daily or sampling frequencies at a given site may give estimates of annual variation of stream temperatures that are statistically comparable to estimates obtained from a daily or continuous sampling scheme. The latter procedure may result in potential savings of resources in network operations, with negligible loss in information on annual stream-temperature variations. (Woodard -USGS)

Summer temperature patterns in the headwater streams of the Oregon coast range

Treesearch

Liz Dent; Danielle Vick; Kyle Abraham; Stephen Schoenholtz; Sherri Johnson

2008-01-01

Cool summertime stream temperature is an important component of high-quality aquatic habitat in Oregon coastal streams. Within the Oregon Coast Range, small headwater streams make up a majority of the stream network, yet little information is available on temperature patterns and the longitudinal variability for these streams. In this paper we describe preharvest...

Adaptive Video Streaming Using Bandwidth Estimation for 3.5G Mobile Network

NASA Astrophysics Data System (ADS)

Nam, Hyeong-Min; Park, Chun-Su; Jung, Seung-Won; Ko, Sung-Jea

Currently deployed mobile networks including High Speed Downlink Packet Access (HSDPA) offer only best-effort Quality of Service (QoS). In wireless best effort networks, the bandwidth variation is a critical problem, especially, for mobile devices with small buffers. This is because the bandwidth variation leads to packet losses caused by buffer overflow as well as picture freezing due to high transmission delay or buffer underflow. In this paper, in order to provide seamless video streaming over HSDPA, we propose an efficient real-time video streaming method that consists of the available bandwidth (AB) estimation for the HSDPA network and the transmission rate control to prevent buffer overflows/underflows. In the proposed method, the client estimates the AB and the estimated AB is fed back to the server through real-time transport control protocol (RTCP) packets. Then, the server adaptively adjusts the transmission rate according to the estimated AB and the buffer state obtained from the RTCP feedback information. Experimental results show that the proposed method achieves seamless video streaming over the HSDPA network providing higher video quality and lower transmission delay.

Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design

NASA Astrophysics Data System (ADS)

Kaminski, Thomas; Rayner, Peter Julian

2017-10-01

Various observational data streams have been shown to provide valuable constraints on the state and evolution of the global carbon cycle. These observations have the potential to reduce uncertainties in past, current, and predicted natural and anthropogenic surface fluxes. In particular such observations provide independent information for verification of actions as requested by the Paris Agreement. It is, however, difficult to decide which variables to sample, and how, where, and when to sample them, in order to achieve an optimal use of the observational capabilities. Quantitative network design (QND) assesses the impact of a given set of existing or hypothetical observations in a modelling framework. QND has been used to optimise in situ networks and assess the benefit to be expected from planned space missions. This paper describes recent progress and highlights aspects that are not yet sufficiently addressed. It demonstrates the advantage of an integrated QND system that can simultaneously evaluate a multitude of observational data streams and assess their complementarity and redundancy.

Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling

USGS Publications Warehouse

Lee, Casey; Foster, Guy

2013-01-01

In-stream sensors are increasingly deployed as part of ambient water quality-monitoring networks. Temporally dense data from these networks can be used to better understand the transport of constituents through streams, lakes or reservoirs. Data from existing, continuously recording in-stream flow and water quality monitoring stations were coupled with the two-dimensional hydrodynamic CE-QUAL-W2 model to assess the potential of altered reservoir outflow management to reduce sediment trapping in John Redmond Reservoir, located in east-central Kansas. Monitoring stations upstream and downstream from the reservoir were used to estimate 5.6 million metric tons of sediment transported to John Redmond Reservoir from 2007 through 2010, 88% of which was trapped within the reservoir. The two-dimensional model was used to estimate the residence time of 55 equal-volume releases from the reservoir; sediment trapping for these releases varied from 48% to 97%. Smaller trapping efficiencies were observed when the reservoir was maintained near the normal operating capacity (relative to higher flood pool levels) and when average residence times were relatively short. An idealized, alternative outflow management scenario was constructed, which minimized reservoir elevations and the length of time water was in the reservoir, while continuing to meet downstream flood control end points identified in the reservoir water control manual. The alternative scenario is projected to reduce sediment trapping in the reservoir by approximately 3%, preventing approximately 45 000 metric tons of sediment from being deposited within the reservoir annually. This article presents an approach to quantify the potential of reservoir management using existing in-stream data; actual management decisions need to consider the effects on other reservoir benefits, such as downstream flood control and aquatic life.

Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

NASA Astrophysics Data System (ADS)

Jaeger, K. L.

2017-12-01

The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the landscape that may be resilient or sensitive to drought conditions, allowing for targeted management efforts to protect critical reaches.

The stream segment and stream network temperature models: A self-study course

USGS Publications Warehouse

Bartholow, John M.

2000-01-01

I am pleased to have had the opportunity to revise the first version of this set of course notes for the stream temperature models. In some ways, there have been many changes and in some ways the notes have stayed much the same. Generally, I was satisfied that the notes were both comprehensive and fairly easy to read. The exercises using SSTEMP have been upgraded to reflect advances in the software. Some additional material was added to better cover contemporary thremistors, and some, but not all, weak transitions and incomplete sentences have been corrected. A comprehensive index was added in an attempt to make these notes as useful as possible, and a few telling quotes have been added for spice. The goal has been to make this set of notes as stand-alone as possible and keep the file size down to something that is easily downloadable over the Internet today (March 2000).

Running key mapping in a quantum stream cipher by the Yuen 2000 protocol

NASA Astrophysics Data System (ADS)

Shimizu, Tetsuya; Hirota, Osamu; Nagasako, Yuki

2008-03-01

A quantum stream cipher by Yuen 2000 protocol (so-called Y00 protocol or αη scheme) consisting of linear feedback shift register of short key is very attractive in implementing secure 40 Gbits/s optical data transmission, which is expected as a next-generation network. However, a basic model of the Y00 protocol with a very short key needs a careful design against fast correlation attacks as pointed out by Donnet This Brief Report clarifies an effectiveness of irregular mapping between running key and physical signals in the driver for selection of M -ary basis in the transmitter, and gives a design method. Consequently, quantum stream cipher by the Y00 protocol with our mapping has immunity against the proposed fast correlation attacks on a basic model of the Y00 protocol even if the key is very short.

An unexpected truth: increasing nitrate loading can decrease nitrate export from watersheds

NASA Astrophysics Data System (ADS)

Askarizadeh Bardsiri, A.; Grant, S. B.; Rippy, M.

2015-12-01

The discharge of anthropogenic nitrate (e.g., from partially treated sewage, return flows from agricultural irrigation, and runoff from animal feeding operations) to streams can negatively impact both human and ecosystem health. Managing these many point and non-point sources to achieve some specific end-point—for example, reducing the annual mass of nitrate exported from a watershed—can be a challenge, particularly in rapidly growing urban areas. Adding to this complexity is the fact that streams are not inert: they too can add or remove nitrate through assimilation (e.g., by stream-associated plants and animals) and microbially-mediated biogeochemical reactions that occur in streambed sediments (e.g., respiration, ammonification, nitrification, denitrification). By coupling a previously published correlation for in-stream processing of nitrate [Mulholland et al., Nature, 2008, 452, 202-205] with a stream network model of the Jacksons Creek watershed (Victoria, Australia) I demonstrate that managing anthropogenic sources of stream nitrate without consideration of in-stream processing can result in a number of non-intuitive "surprises"; for example, wastewater effluent discharges that increase nitrate loading but decrease in-stream nitrate concentrations can reduce the mass of nitrate exported from a watershed.

Georgia's Stream-Water-Quality Monitoring Network, 2006

USGS Publications Warehouse

Nobles, Patricia L.; ,

2006-01-01

The USGS stream-water-quality monitoring network for Georgia is an aggregation of smaller networks and individual monitoring stations that have been established in cooperation with Federal, State, and local agencies. These networks collectively provide data from 130 sites, 62 of which are monitored continuously in real time using specialized equipment that transmits these data via satellite to a centralized location for processing and storage. These data are made available on the Web in near real time at http://waterdata.usgs.gov/ga/nwis/ Ninety-eight stations are sampled periodically for a more extensive suite of chemical and biological constituents that require laboratory analysis. Both the continuous and the periodic water-quality data are archived and maintained in the USGS National Water Information System and are available to cooperators, water-resource managers, and the public. The map at right shows the USGS stream-water-quality monitoring network for Georgia and major watersheds. The network represents an aggregation of smaller networks and individual monitoring stations that collectively provide data from 130 sites.

Riparian influences on stream fish assemblage structure in urbanizing streams

USGS Publications Warehouse

Roy, A.H.; Freeman, B.J.; Freeman, Mary C.

2007-01-01

We assessed the influence of land cover at multiple spatial extents on fish assemblage integrity, and the degree to which riparian forests can mitigate the negative effects of catchment urbanization on stream fish assemblages. Riparian cover (urban, forest, and agriculture) was determined within 30 m buffers at longitudinal distances of 200 m, 1 km, and the entire network upstream of 59 non-nested fish sampling locations. Catchment and riparian land cover within the upstream network were highly correlated, so we were unable to distinguish between those variables. Most fish assemblage variables were related to % forest and % urban land cover, with the strongest relations at the largest spatial extent of land cover (catchment), followed by riparian land cover in the 1-km and 200-m reach, respectively. For fish variables related to urban land cover in the catchment, we asked whether the influence of riparian land cover on fish assemblages was dependent on the amount of urban development in the catchment. Several fish assemblage metrics (endemic richness, endemic:cosmopolitan abundance, insectivorous cyprinid richness and abundance, and fluvial specialist richness) were all best predicted by single variable models with % urban land cover. However, endemic:cosmopolitan richness, cosmopolitan abundance, and lentic tolerant abundance were related to % forest cover in the 1-km stream reach, but only in streams that had <15% catchment urban land cover. In these cases, catchment urbanization overwhelmed the potential mitigating effects of riparian forests on stream fishes. Together, these results suggest that catchment land cover is an important driver of fish assemblages in urbanizing catchments, and riparian forests are important but not sufficient for protecting stream ecosystems from the impacts of high levels of urbanization.

Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.

PubMed

Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter

2017-07-11

The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Predicting and generalizing the refuge function of intermittent and ephemeral streams

EPA Science Inventory

Intermittent and ephemeral streams can provide important functions within stream networks. For fish, intermittent and ephemeral streams can contribute energy and materials to downstream perennial waters, serve as seasonal habitats, and/or provide refuge functions. Understanding t...

Communication System and Method

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Strawser, Philip A. (Inventor)

2014-01-01

A communication system for communicating over high-latency, low bandwidth networks includes a communications processor configured to receive a collection of data from a local system, and a transceiver in communication with the communications processor. The transceiver is configured to transmit and receive data over a network according to a plurality of communication parameters. The communications processor is configured to divide the collection of data into a plurality of data streams; assign a priority level to each of the respective data streams, where the priority level reflects the criticality of the respective data stream; and modify a communication parameter of at least one of the plurality of data streams according to the priority of the at least one data stream.

Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network

USGS Publications Warehouse

Letcher, Benjamin H.; Schueller, Paul; Bassar, Ronald D.; Nislow, Keith H.; Coombs, Jason A.; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B.; Whiteley, Andrew R.; O'Donnell, Matthew J.; Dubreuil, Todd L.

2015-01-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall.These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.

Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network.

PubMed

Letcher, Benjamin H; Schueller, Paul; Bassar, Ronald D; Nislow, Keith H; Coombs, Jason A; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B; Whiteley, Andrew R; O'Donnell, Matthew J; Dubreuil, Todd L

2015-03-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses. We developed an integrated capture-recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival. We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature. Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall. These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

A coupled upland-erosion and instream hydrodynamic-sediment transport model for evaluating sediment transport in forested watersheds

Treesearch

W. J. Conroy; R. H. Hotchkiss; W. J. Elliot

2006-01-01

This article describes a prototype modeling system for assessing forest management-related erosion at its source and predicting sediment transport from hillslopes to stream channels and through channel networks to a watershed outlet. We demonstrate that it is possible to develop a land management tool capable of accurately assessing the primary impacts of...

Application of a DRAINMOD-based watershed model to a lower coastal plain watershed

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2003-01-01

This is a case study for applying DRAINMOD-GIS, a DRAINMOD based lumped parameter watershed model to Chicod Creek, a 11300 ha coastal plain watershed in North Carolina which is not intensively instrumented or documented. The study utilized the current database of land-use, topography, stream network, soil, and weather data available to the State and Federal agencies....

Integration of Watershed Model AnnAGNPS and Stream Network Model CCHE1D for the Development of a New GIS-Based BMP Planning Tool

USDA-ARS?s Scientific Manuscript database

This paper presents a new GIS-based Best Management Practice (BMP) Tool developed for watershed managers to assist in the decision making process by simulating various scenarios using various combinations of Best Management Practices (BMPs). The development of this BMPTool is based on the integratio...

An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation

Treesearch

F. Pan; M. Stieglitz; R.B. McKane

2012-01-01

Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow...

System and method for anomaly detection

DOEpatents

Scherrer, Chad

2010-06-15

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

Regional Monitoring Networks (RMN) to Detect Changing Baselines in Freshwater Wadeable Streams (Final Report)

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA) is working with its regional offices, states, tribes, and other entities to establish Regional Monitoring Networks (RMNs) at which biological, thermal, and hydrologic data are collected from freshwater wadeable streams ...

Predicting Thermal Regimes of Stream Networks Across New England: Natural and Anthropogenic Influences

EPA Science Inventory

Thermal regime is a critical factor in models predicting joint effects of watershed management activities and climate change on habitat suitability for fish. We used a database of lotic temperature time series across New England (> 7000 station-year combinations) from state a...

An incremental community detection method for social tagging systems using locality-sensitive hashing.

PubMed

Wu, Zhenyu; Zou, Ming

2014-10-01

An increasing number of users interact, collaborate, and share information through social networks. Unprecedented growth in social networks is generating a significant amount of unstructured social data. From such data, distilling communities where users have common interests and tracking variations of users' interests over time are important research tracks in fields such as opinion mining, trend prediction, and personalized services. However, these tasks are extremely difficult considering the highly dynamic characteristics of the data. Existing community detection methods are time consuming, making it difficult to process data in real time. In this paper, dynamic unstructured data is modeled as a stream. Tag assignments stream clustering (TASC), an incremental scalable community detection method, is proposed based on locality-sensitive hashing. Both tags and latent interactions among users are incorporated in the method. In our experiments, the social dynamic behaviors of users are first analyzed. The proposed TASC method is then compared with state-of-the-art clustering methods such as StreamKmeans and incremental k-clique; results indicate that TASC can detect communities more efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cost-effectiveness of the U.S. Geological Survey stream-gaging program in Indiana

USGS Publications Warehouse

Stewart, J.A.; Miller, R.L.; Butch, G.K.

1986-01-01

Analysis of the stream gaging program in Indiana was divided into three phases. The first phase involved collecting information concerning the data need and the funding source for each of the 173 surface water stations in Indiana. The second phase used alternate methods to produce streamflow records at selected sites. Statistical models were used to generate stream flow data for three gaging stations. In addition, flow routing models were used at two of the sites. Daily discharges produced from models did not meet the established accuracy criteria and, therefore, these methods should not replace stream gaging procedures at those gaging stations. The third phase of the study determined the uncertainty of the rating and the error at individual gaging stations, and optimized travel routes and frequency of visits to gaging stations. The annual budget, in 1983 dollars, for operating the stream gaging program in Indiana is $823,000. The average standard error of instantaneous discharge for all continuous record gaging stations is 25.3%. A budget of $800,000 could maintain this level of accuracy if stream gaging stations were visited according to phase III results. A minimum budget of $790,000 is required to operate the gaging network. At this budget, the average standard error of instantaneous discharge would be 27.7%. A maximum budget of $1 ,000,000 was simulated in the analysis and the average standard error of instantaneous discharge was reduced to 16.8%. (Author 's abstract)

Flood-hazard analysis of four headwater streams draining the Argonne National Laboratory property, DuPage County, Illinois

USGS Publications Warehouse

Soong, David T.; Murphy, Elizabeth A.; Straub, Timothy D.; Zeeb, Hannah L.

2016-11-22

Results of a flood-hazard analysis conducted by the U.S. Geological Survey, in cooperation with the Argonne National Laboratory, for four headwater streams within the Argonne National Laboratory property indicate that the 1-percent and 0.2-percent annual exceedance probability floods would cause multiple roads to be overtopped. Results indicate that most of the effects on the infrastructure would be from flooding of Freund Brook. Flooding on the Northeast and Southeast Drainage Ways would be limited to overtopping of one road crossing for each of those streams. The Northwest Drainage Way would be the least affected with flooding expected to occur in open grass or forested areas.The Argonne Site Sustainability Plan outlined the development of hydrologic and hydraulic models and the creation of flood-plain maps of the existing site conditions as a first step in addressing resiliency to possible climate change impacts as required by Executive Order 13653 “Preparing the United States for the Impacts of Climate Change.” The Hydrological Simulation Program-FORTRAN is the hydrologic model used in the study, and the Hydrologic Engineering Center‒River Analysis System (HEC–RAS) is the hydraulic model. The model results were verified by comparing simulated water-surface elevations to observed water-surface elevations measured at a network of five crest-stage gages on the four study streams. The comparison between crest-stage gage and simulated elevations resulted in an average absolute difference of 0.06 feet and a maximum difference of 0.19 feet.In addition to the flood-hazard model development and mapping, a qualitative stream assessment was conducted to evaluate stream channel and substrate conditions in the study reaches. This information can be used to evaluate erosion potential.

Links between riparian landcover, instream environment and fish assemblages in headwater streams of south-eastern Brazil

USGS Publications Warehouse

Cruz, Bruna B.; Miranda, Leandro E.; Cetra, Mauricio

2013-01-01

We hypothesised and tested a hierarchical organisation model where riparian landcover would influence bank composition and light availability, which in turn would influence instream environments and control fish assemblages. The study was conducted during the dry season in 11 headwater tributaries of the Sorocaba River in the upper Paraná River Basin, south-eastern Brazil. We focused on seven environmental factors each represented by one or multiple environmental variables and seven fish functional traits each represented by two or more classes. Multivariate direct gradient analyses suggested that riparian zone landcover can be considered a higher level causal factor in a network of relations that control instream characteristics and fish assemblages. Our results provide a framework for a hierarchical conceptual model that identifies singular and collective influences of variables from different scales on each other and ultimately on different aspects related to stream fish functional composition. This conceptual model is focused on the relationships between riparian landcover and instream variables as causal factors on the organisation of stream fish assemblages. Our results can also be viewed as a model for headwater stream management in that landcover can be manipulated to influence factors such as bank composition, substrates and water quality, whereas fish assemblage composition can be used as indicators to monitor the success of such efforts.

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

PubMed

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

PubMed Central

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN). PMID:27907113

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks.

PubMed

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

Stream Width Dynamics in a Small Headwater Catchment

NASA Astrophysics Data System (ADS)

Barefoot, E. A.; Pavelsky, T.; Allen, G. H.; Zimmer, M. A.; McGlynn, B. L.

2016-12-01

Changing streamflow conditions cause small, ephemeral and intermittent stream networks to expand and contract, while simultaneously driving widening and narrowing of streams. The resulting dynamic surface area of ephemeral streams impacts critical hydrological and biogeochemical processes, including air-water gas exchange, solute transport, and sediment transport. Despite the importance of these dynamics, to our knowledge there exists no complete study of how stream widths vary throughout an entire catchment in response to changing streamflow conditions. Here we present the first characterization of how variable hydrologic conditions impact the distribution of stream widths in a 48 ha headwater catchment in the Stony Creek Research Watershed, NC, USA. We surveyed stream widths longitudinally every 5 m on 12 occasions over a range of stream discharge from 7 L/s to 128 L/s at the catchment outlet. We hypothesize that the shape and location of the stream width distribution are driven by the action of two interrelated mechanisms, network extension and at-a-station widening, both of which increase with discharge. We observe that during very low flow conditions, network extension more significantly influences distribution location, and during high flow conditions stream widening is the dominant driver. During moderate flows, we observe an approximately 1 cm rightward shift in the distribution peak with every additional 10 L/s of increased discharge, which we attribute to a greater impact of at-a-station widening on distribution location. Aside from this small shift, the qualitative location and shape of the stream width distribution are largely invariant with changing streamflow. We suggest that the basic characteristics of stream width distributions constitute an equilibrium between the two described mechanisms across variable hydrologic conditions.

Determination of trunk streams via using flow accumulation values

NASA Astrophysics Data System (ADS)

Farek, Vladimir

2013-04-01

There is often a problem, with schematisation of catchments and a channel networks in a broken relief like sandstone landscape (with high vertical segmentation, narrow valley lines, crags, sheer rocks, endorheic hollows etc.). Usual hydrological parameters (subcatchment areas, altitude of highest point of subcatchment, water discharge), which are mostly used for determination of trunk stream upstream the junction, are frequently not utilizable very well in this kind of relief. We found, that for small, relatively homogeneous catchments (within the meaning of land-use, geological subsurface, anthropogenic influence etc.), which are extremely shaped, the value called "flow accumulation" (FA) could be very useful. This value gives the number of cells of the Digital Elevation Model (DEM) grid, which are drained to each cell of the catchment. We can predict that the stream channel with higher values of flow accumulation represents the main stream. There are three crucial issues with this theory. At first it is necessary to find the most suitable algorithm for calculation flow accumulation in a broken relief. Various algorithms could have complications with correct flow routing (representation of divergent or convergent character of the flow), or with keeping the flow paths uninterrupted. Relief with high curvature changes (alternating concave/convex shapes, high steepness changes) causes interrupting of flow lines in many algorithms used for hydrological computing. Second - set down limits of this theory (e.g. the size and character of a surveyed catchment). Third - verify this theory in reality. We tested this theory on sandstone landscape of National park Czech Switzerland. The main data source were high-resolution LIDAR (Light Detection and Ranging) DEM snapshots of surveyed area. This data comes from TU Dresden project called Genesis (Geoinformation Networks For The Cross- Border National Park Region Saxon- Bohemian Switzerland). In order to solve these issues GIS applications (e. g. GIS GRASS and its hydrological modules like r.terraflow, r.watershed, r.flow etc.) are very useful. Key words: channel network, flow accumulation, Digital Elevation Model, LIDAR, broken relief, GIS GRASS

Patterns in CH4 and CO2 concentrations across boreal rivers: Major drivers and implications for fluvial greenhouse emissions under climate change scenarios.

PubMed

Campeau, Audrey; Del Giorgio, Paul A

2014-04-01

It is now widely accepted that boreal rivers and streams are regionally significant sources of carbon dioxide (CO2), yet their role as methane (CH4) emitters, as well as the sensitivity of these greenhouse gas (GHG) emissions to climate change, are still largely undefined. In this study, we explore the large-scale patterns of fluvial CO2 and CH4 partial pressure (pCO2 , pCH4) and gas exchange (k) relative to a set of key, climate-sensitive river variables across 46 streams and rivers in two distinct boreal landscapes of Northern Québec. We use the resulting models to determine the direction and magnitude of C-gas emissions from these boreal fluvial networks under scenarios of climate change. River pCO2 and pCH4 were positively correlated, although the latter was two orders of magnitude more variable. We provide evidence that in-stream metabolism strongly influences the dynamics of surface water pCO2 and pCH4 , but whereas pCO2 is not influenced by temperature in the surveyed streams and rivers, pCH4 appears to be strongly temperature-dependent. The major predictors of ambient gas concentrations and exchange were water temperature, velocity, and DOC, and the resulting models indicate that total GHG emissions (C-CO2 equivalent) from the entire network may increase between by 13 to 68% under plausible scenarios of climate change over the next 50 years. These predicted increases in fluvial GHG emissions are mostly driven by a steep increase in the contribution of CH4 (from 36 to over 50% of total CO2 -equivalents). The current role of boreal fluvial networks as major landscape sources of C is thus likely to expand, mainly driven by large increases in fluvial CH4 emissions. © 2013 John Wiley & Sons Ltd.

The HomePlanet project: a HAVi multi-media network over POF

NASA Astrophysics Data System (ADS)

Roycroft, Brendan; Corbett, Brian; Kelleher, Carmel; Lambkin, John; Bareel, Baudouin; Goudeau, Jacques; Skiczuk, Peter

2005-06-01

This project has developed a low cost in-home network compatible with network standard IEEE1394b. We have developed all components of the network, from the red resonant cavity LEDs and VCSELs as light sources, the driver circuitry, plastic optical fibres for transmission, up to the network management software. We demonstrate plug-and-play operation of S100 and S200 (125 and 250Mbps) data streams using 650nm RCLEDs, and S400 (500 Mbps) data streams using VCSELs. The network software incorporates Home Audio Video interoperability (HAVi), which allows any HAVi device to be hot-plugged into the network and be instantly recognised and controllable over the network.

A regional neural network model for predicting mean daily river water temperature

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

Coupling Self-Organizing Maps with a Naïve Bayesian classifier: A case study for classifying Vermont streams using geomorphic, habitat and biological assessment data

NASA Astrophysics Data System (ADS)

Fytilis, N.; Rizzo, D. M.

2012-12-01

Environmental managers are increasingly required to forecast the long-term effects and the resilience or vulnerability of biophysical systems to human-generated stresses. Mitigation strategies for hydrological and environmental systems need to be assessed in the presence of uncertainty. An important aspect of such complex systems is the assessment of variable uncertainty on the model response outputs. We develop a new classification tool that couples a Naïve Bayesian Classifier with a modified Kohonen Self-Organizing Map to tackle this challenge. For proof-of-concept, we use rapid geomorphic and reach-scale habitat assessments data from over 2500 Vermont stream reaches (~1371 stream miles) assessed by the Vermont Agency of Natural Resources (VTANR). In addition, the Vermont Department of Environmental Conservation (VTDEC) estimates stream habitat biodiversity indices (macro-invertebrates and fish) and a variety of water quality data. Our approach fully utilizes the existing VTANR and VTDEC data sets to improve classification of stream-reach habitat and biological integrity. The combined SOM-Naïve Bayesian architecture is sufficiently flexible to allow for continual updates and increased accuracy associated with acquiring new data. The Kohonen Self-Organizing Map (SOM) is an unsupervised artificial neural network that autonomously analyzes properties inherent in a given a set of data. It is typically used to cluster data vectors into similar categories when a priori classes do not exist. The ability of the SOM to convert nonlinear, high dimensional data to some user-defined lower dimension and mine large amounts of data types (i.e., discrete or continuous, biological or geomorphic data) makes it ideal for characterizing the sensitivity of river networks in a variety of contexts. The procedure is data-driven, and therefore does not require the development of site-specific, process-based classification stream models, or sets of if-then-else rules associated with expert systems. This has the potential to save time and resources, while enabling a truly adaptive management approach using existing knowledge (expressed as prior probabilities) and new information (expressed as likelihood functions) to update estimates (i.e., in this case, improved stream classifications expressed as posterior probabilities). The distribution parameters of these posterior probabilities are used to quantify uncertainty associated with environmental data. Since classification plays a leading role in the future development of data-enabled science and engineering, such a computational tool is applicable to a variety of engineering applications. The ability of the new classification neural network to characterize streams with high environmental risk is essential for a proactive adaptive watershed management approach.

Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

NASA Astrophysics Data System (ADS)

SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

2013-12-01

Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

Influence of multi-scale hydrologic controls on river network connectivity and riparian function

EPA Science Inventory

The ecological functions of rivers and streams and their associated riparian zones are strongly influenced by surface and subsurface hydrologic routing of water within river basins and river networks. Hydrologic attributes of the riparian area for a given stream reach are typica...

Hydrologic landscape regions for predicting and generalizing the refuge function of intermittent and ephemeral streams

EPA Science Inventory

Intermittent and ephemeral (IE) streams can provide important functions within stream networks. Understanding the relative benefit provided to downstream waters is needed to better inform watershed management. Although the potential functions of IE streams are relatively well kn...

Estimating the sources and transport of nutrients in the Waikato River Basin, New Zealand

USGS Publications Warehouse

Alexander, Richard B.; Elliott, Alexander H.; Shankar, Ude; McBride, Graham B.

2002-01-01

We calibrated SPARROW (Spatially Referenced Regression on Watershed Attributes) surface water‐quality models using measurements of total nitrogen and total phosphorus from 37 sites in the 13,900‐km2 Waikato River Basin, the largest watershed on the North Island of New Zealand. This first application of SPARROW outside of the United States included watersheds representative of a wide range of natural and cultural conditions and water‐resources data that were well suited for calibrating and validating the models. We applied the spatially distributed model to a drainage network of nearly 5000 stream reaches and 75 lakes and reservoirs to empirically estimate the rates of nutrient delivery (and their levels of uncertainty) from point and diffuse sources to streams, lakes, and watershed outlets. The resulting models displayed relatively small errors; predictions of stream yield (kg ha−1 yr−1) were typically within 30% or less of the observed values at the monitoring sites. There was strong evidence of the accuracy of the model estimates of nutrient sources and the natural rates of nutrient attenuation in surface waters. Estimated loss rates for streams, lakes, and reservoirs agreed closely with experimental measurements and empirical models from New Zealand, North America, and Europe as well as with previous U.S. SPARROW models. The results indicate that the SPARROW modeling technique provides a reliable method for relating experimental data and observations from small catchments to the transport of nutrients in the surface waters of large river basins.

Path selection in the growth of rivers

DOE PAGES

Cohen, Yossi; Devauchelle, Olivier; Seybold, Hansjörg F.; ...

2015-11-02

River networks exhibit a complex ramified structure that has inspired decades of studies. But, an understanding of the propagation of a single stream remains elusive. In this paper, we invoke a criterion for path selection from fracture mechanics and apply it to the growth of streams in a diffusion field. We show that, as it cuts through the landscape, a stream maintains a symmetric groundwater flow around its tip. The local flow conditions therefore determine the growth of the drainage network. We use this principle to reconstruct the history of a network and to find a growth law associated withmore » it. Finally, our results show that the deterministic growth of a single channel based on its local environment can be used to characterize the structure of river networks.« less

Multivariate Spatial Condition Mapping Using Subtractive Fuzzy Cluster Means

PubMed Central

Sabit, Hakilo; Al-Anbuky, Adnan

2014-01-01

Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining. PMID:25313495

Predicting thermal regimes of stream networks across the Chesapeake Bay Watershed: Natural and anthropogenic influences

EPA Science Inventory

Thermal regimes are a critical factor in models predicting joint effects of watershed management activities and climate change on fish habitat suitability. We have compiled a database of lotic temperature time series across the Chesapeake Bay Watershed (725 station-year combinat...

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

PubMed Central

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

USGS Publications Warehouse

Yang, X.; Jin, W.

2010-01-01

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

The burial of headwater streams in drainage pipes reduces in-stream nitrate retention: results from two US metropolitan areas

EPA Science Inventory

Nitrogen (N) retention in stream networks is an important ecosystem service that may be affected by the widespread burial of headwater streams in urban watersheds. Stream burial occurs when segments of a channel are encased in drainage pipe and buried beneath the land surface to...

Coding for Parallel Links to Maximize the Expected Value of Decodable Messages

NASA Technical Reports Server (NTRS)

Klimesh, Matthew A.; Chang, Christopher S.

2011-01-01

When multiple parallel communication links are available, it is useful to consider link-utilization strategies that provide tradeoffs between reliability and throughput. Interesting cases arise when there are three or more available links. Under the model considered, the links have known probabilities of being in working order, and each link has a known capacity. The sender has a number of messages to send to the receiver. Each message has a size and a value (i.e., a worth or priority). Messages may be divided into pieces arbitrarily, and the value of each piece is proportional to its size. The goal is to choose combinations of messages to send on the links so that the expected value of the messages decodable by the receiver is maximized. There are three parts to the innovation: (1) Applying coding to parallel links under the model; (2) Linear programming formulation for finding the optimal combinations of messages to send on the links; and (3) Algorithms for assisting in finding feasible combinations of messages, as support for the linear programming formulation. There are similarities between this innovation and methods developed in the field of network coding. However, network coding has generally been concerned with either maximizing throughput in a fixed network, or robust communication of a fixed volume of data. In contrast, under this model, the throughput is expected to vary depending on the state of the network. Examples of error-correcting codes that are useful under this model but which are not needed under previous models have been found. This model can represent either a one-shot communication attempt, or a stream of communications. Under the one-shot model, message sizes and link capacities are quantities of information (e.g., measured in bits), while under the communications stream model, message sizes and link capacities are information rates (e.g., measured in bits/second). This work has the potential to increase the value of data returned from spacecraft under certain conditions.

Layer-based buffer aware rate adaptation design for SHVC video streaming

NASA Astrophysics Data System (ADS)

Gudumasu, Srinivas; Hamza, Ahmed; Asbun, Eduardo; He, Yong; Ye, Yan

2016-09-01

This paper proposes a layer based buffer aware rate adaptation design which is able to avoid abrupt video quality fluctuation, reduce re-buffering latency and improve bandwidth utilization when compared to a conventional simulcast based adaptive streaming system. The proposed adaptation design schedules DASH segment requests based on the estimated bandwidth, dependencies among video layers and layer buffer fullness. Scalable HEVC video coding is the latest state-of-art video coding technique that can alleviate various issues caused by simulcast based adaptive video streaming. With scalable coded video streams, the video is encoded once into a number of layers representing different qualities and/or resolutions: a base layer (BL) and one or more enhancement layers (EL), each incrementally enhancing the quality of the lower layers. Such layer based coding structure allows fine granularity rate adaptation for the video streaming applications. Two video streaming use cases are presented in this paper. The first use case is to stream HD SHVC video over a wireless network where available bandwidth varies, and the performance comparison between proposed layer-based streaming approach and conventional simulcast streaming approach is provided. The second use case is to stream 4K/UHD SHVC video over a hybrid access network that consists of a 5G millimeter wave high-speed wireless link and a conventional wired or WiFi network. The simulation results verify that the proposed layer based rate adaptation approach is able to utilize the bandwidth more efficiently. As a result, a more consistent viewing experience with higher quality video content and minimal video quality fluctuations can be presented to the user.

OVER-WINTER JUVENILE COHO SALMON GROWTH AND SURVIVAL IN A COASTAL OREGON STREAM NETWORK

EPA Science Inventory

Winter habitat has the potential to be a limiting factor for the production and condition of coho salmon (Oncorhynchus kisutch) smolts, but little is known about how the variation of habitat throughout whole stream networks influences coho smolts. Over a four year period (2002 - ...

The National Stream Quality Accounting Network (NASQAN) - Some questions and answers

USGS Publications Warehouse

Ficke, John F.; Hawkinson, Richard O.

1975-01-01

One of the major new efforts of the U.S. Geological Survey is the National Stream Quality Accounting Network (NASQAN). This circular is intended to answer some of the frequently asked questions concerning concepts used in establishing NASQAN, its purposes, design, value, and future plans.

VARIATION IN JUVENILE COHO SALMON SUMMER ABUNDANCE: HIERARCHICAL ANALYSIS OF HABITAT EFFECTS

EPA Science Inventory

Varying habitat conditions found across a stream network during the summer months may limit the abundance of salmonids such as coho (Oncorhynchus kisutch). We examined the abundance of juvenile coho salmon across a stream network in an Oregon coast range basin from 2002 through ...

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.

A new traffic control design method for large networks with signalized intersections

NASA Technical Reports Server (NTRS)

Leininger, G. G.; Colony, D. C.; Seldner, K.

1979-01-01

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

Exploring storage and runoff generation processes for urban flooding through a physically based watershed model

NASA Astrophysics Data System (ADS)

Smith, B. K.; Smith, J. A.; Baeck, M. L.; Miller, A. J.

2015-03-01

A physically based model of the 14 km2 Dead Run watershed in Baltimore County, MD was created to test the impacts of detention basin storage and soil storage on the hydrologic response of a small urban watershed during flood events. The Dead Run model was created using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) algorithms and validated using U.S. Geological Survey stream gaging observations for the Dead Run watershed and 5 subbasins over the largest 21 warm season flood events during 2008-2012. Removal of the model detention basins resulted in a median peak discharge increase of 11% and a detention efficiency of 0.5, which was defined as the percent decrease in peak discharge divided by percent detention controlled area. Detention efficiencies generally decreased with increasing basin size. We tested the efficiency of detention basin networks by focusing on the "drainage network order," akin to the stream order but including storm drains, streams, and culverts. The detention efficiency increased dramatically between first-order detention and second-order detention but was similar for second and third-order detention scenarios. Removal of the soil compacted layer, a common feature in urban soils, resulted in a 7% decrease in flood peak discharges. This decrease was statistically similar to the flood peak decrease caused by existing detention. Current soil storage within the Dead Run watershed decreased flood peak discharges by a median of 60%. Numerical experiment results suggested that detention basin storage and increased soil storage have the potential to substantially decrease flood peak discharges.

Hydrodynamic effects of kinetic power extraction by in-stream tidal turbines

NASA Astrophysics Data System (ADS)

Polagye, Brian L.

The hydrodynamic effects of extracting kinetic power from tidal streams presents unique challenges to the development of in-stream tidal power. In-stream tidal turbines superficially resemble wind turbines and extract kinetic power from the ebb and flood of strong tidal currents. Extraction increases the resistance to flow, leading to changes in tidal range, transport, mixing, and the kinetic resource itself. These far-field changes have environmental, social, and economic implications that must be understood to develop the in-stream resource. This dissertation describes the development of a one-dimensional numerical channel model and its application to the study of these effects. The model is applied to determine the roles played by site geometry, network topology, tidal regime, and device dynamics. A comparison is also made between theoretical and modeled predictions for the maximum amount of power which could be extracted from a tidal energy site. The model is extended to a simulation of kinetic power extraction from Puget Sound, Washington. In general, extracting tidal energy will have a number of far-field effects, in proportion to the level of power extraction. At the theoretical limit, these effects can be very significant (e.g., 50% reduction in transport), but are predicted to be immeasurably small for pilot-scale projects. Depending on the specifics of the site, far-field effects may either augment or reduce the existing tidal regime. Changes to the tide, in particular, have significant spatial variability. Since tidal streams are generally subcritical, effects are felt throughout the estuary, not just at the site of extraction. The one dimensional numerical modeling is supported by a robust theory for predicting the performance characteristics of in-stream devices. The far-field effects of tidal power depend on the total power dissipated by turbines, rather than the power extracted. When the low-speed wake downstream of a turbine mixes with the free-stream, power is lost, such that the total power dissipated by the turbine is significantly greater than the power extracted. This dissertation concludes with a framework for three-dimensional numerical modeling of near-field extraction effects.

Modifying Bagnold's Sediment Transport Equation for Use in Watershed-Scale Channel Incision Models

NASA Astrophysics Data System (ADS)

Lammers, R. W.; Bledsoe, B. P.

2016-12-01

Destabilized stream channels may evolve through a sequence of stages, initiated by bed incision and followed by bank erosion and widening. Channel incision can be modeled using Exner-type mass balance equations, but model accuracy is limited by the accuracy and applicability of the selected sediment transport equation. Additionally, many sediment transport relationships require significant data inputs, limiting their usefulness in data-poor environments. Bagnold's empirical relationship for bedload transport is attractive because it is based on stream power, a relatively straightforward parameter to estimate using remote sensing data. However, the equation is also dependent on flow depth, which is more difficult to measure or estimate for entire drainage networks. We recast Bagnold's original sediment transport equation using specific discharge in place of flow depth. Using a large dataset of sediment transport rates from the literature, we show that this approach yields similar predictive accuracy as other stream power based relationships. We also explore the applicability of various critical stream power equations, including Bagnold's original, and support previous conclusions that these critical values can be predicted well based solely on sediment grain size. In addition, we propagate error in these sediment transport equations through channel incision modeling to compare the errors associated with our equation to alternative formulations. This new version of Bagnold's bedload transport equation has utility for channel incision modeling at larger spatial scales using widely available and remote sensing data.

Neural correlates of consciousness: a definition of the dorsal and ventral streams and their relation to phenomenology.

PubMed

Vakalopoulos, Costa

2005-01-01

The paper presents a hypothesis for a neural correlate of consciousness. A proposal is made that both the dorsal and ventral streams must be concurrently active to generate conscious awareness and that V1 (striate cortex) provides a serial link between them. An argument is presented against a true extrastriate communication between the dorsal and ventral streams. Secondly, a detailed theory is developed for the structure of the visual hierarchy. Premotor theory states that each organism-object interaction can be described by the two quantitative measures of torque and change in joint position served by the basal ganglia and cerebellum, respectively. This leads to a component theory of motor efference copy providing a fundamental tool for categorizing dorsal and ventral stream networks. The rationale for this is that the dorsal stream specifies spatial coordinates of the external world, which can be coded by the reafference of changes in joint position. The ventral stream is concerned with object recognition and is coded for by forces exerted on the world during a developmental exploratory phase of the organism. The proposed pathways for a component motor efference copy from both the cerebellum and basal ganglia converge on the thalamus and modulate thalamocortical projections via the thalamic reticular nucleus. The origin of the corticopontine projections, which are a massive pathway for cortical information to reach the cerebellum, coincides with the area typically considered as part of the dorsal stream, whereas the entire cortex projects to the striatum. This adds empirical support for a new conceptualization of the visual streams. The model also presents a solution to the binding problem of a neural correlate of consciousness, that is, how a distributed neural network synchronizes its activity during a cognitive event. It represents a reinterpretation of the current status of the visual hierarchy.

Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

2015-12-01

One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

PubMed Central

Liu, Yiming; Huang, Nai-Lun; Zeng, Fufu; Lin, Fang-Ying

2014-01-01

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment. PMID:25032231

Design and implementation of streaming media server cluster based on FFMpeg.

PubMed

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system.

Design and Implementation of Streaming Media Server Cluster Based on FFMpeg

PubMed Central

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system. PMID:25734187

Spatial and temporal patterns of stream burial and its effect on habitat connectivity across headwater stream communities of the Potomac River Basin, USA

NASA Astrophysics Data System (ADS)

Weitzell, R.; Guinn, S. M.; Elmore, A. J.

2012-12-01

The process of directing streams into culverts, pipes, or concrete-lined ditches during urbanization, known as stream burial, alters the primary physical, chemical, and biological processes of streams. Knowledge of the cumulative impacts of reduced structure and ecological function within buried stream networks is crucial for informing management of stream ecosystems, in light of continued growth in urban areas, and the uncertain response of freshwater ecosystems to the stresses of global climate change. To address this need, we utilized recently improved stream maps for the Potomac River Basin (PRB) to describe the extent and severity of stream burial across the basin. Observations of stream burial made from high resolution aerial photographs (>1% of total basin area) and a decision tree using spatial statistics from impervious cover data were used to predict stream burial at 4 time-steps (1975, 1990, 2001, 2006). Of the roughly 95,500 kilometers (km) of stream in the PRB, approximately 4551 km (4.76%) were buried by urban development as of 2001. Analysis of county-level burial trends shows differential patterns in the timing and rates of headwater stream burial, which may be due to local development policies, topographical constraints, and/or time since development. Consistently higher rates of stream burial were observed for small streams, decreasing with stream order. Headwater streams (1st-2nd order) are disproportionately affected, with burial rates continuing to increase over time in relation to larger stream orders. Beyond simple habitat loss, headwater burial decreases connectivity among headwater populations and habitats, with potential to affect a wide range of important ecological processes. To quantify changes to regional headwater connectivity we applied a connectivity model based on electrical circuit theory. Circuit-theoretical models function by treating the landscape as a resistance surface, representing hypothesized relationships between landscape features and their differential "resistance" to movement by organisms. A landscape resistance layer was developed and fine-tuned in terms of the habitat use/needs of aquatic invertebrates with terrestrial adult stages, organisms of critical importance to riparian and aquatic ecosystem health. Initial results show significant increases in landscape resistance (isolation) among headwater systems, and corresponding decreases in current flow (movement of organisms) across the increasingly urbanized PRB landscape. Of particular interest, the circuit model highlighted the importance of stream confluences and zero-order (non-channel) headwater areas for movement of organisms between headwater systems that are otherwise highly disconnected, and for which the latter currently receives no legal protection from development.

Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, George; Choudhury, Sutanay; Feo, John T.

2014-06-30

The number and sophistication of cyberattacks on industries and governments have dramatically grown in recent years. To counter this movement, new advanced tools and techniques are needed to detect cyberattacks in their early stages such that defensive actions may be taken to avert or mitigate potential damage. From a cybersecurity analysis perspective, detecting cyberattacks may be cast as a problem of identifying patterns in computer network traffic. Logically and intuitively, these patterns may take on the form of a directed graph that conveys how an attack or intrusion propagates through the computers of a network. Such cyberattack graphs could providemore » cybersecurity analysts with powerful conceptual representations that are natural to express and analyze. We have been researching and developing graph-centric approaches and algorithms for dynamic cyberattack detection. The advanced dynamic graph algorithms we are developing will be packaged into a streaming network analysis framework known as StreamWorks. With StreamWorks, a scientist or analyst may detect and identify precursor events and patterns as they emerge in complex networks. This analysis framework is intended to be used in a dynamic environment where network data is streamed in and is appended to a large-scale dynamic graph. Specific graphical query patterns are decomposed and collected into a graph query library. The individual decomposed subpatterns in the library are continuously and efficiently matched against the dynamic graph as it evolves to identify and detect early, partial subgraph patterns. The scalable emerging subgraph pattern algorithms will match on both structural and semantic network properties.« less

Maximizing Resource Utilization in Video Streaming Systems

ERIC Educational Resources Information Center

Alsmirat, Mohammad Abdullah

2013-01-01

Video streaming has recently grown dramatically in popularity over the Internet, Cable TV, and wire-less networks. Because of the resource demanding nature of video streaming applications, maximizing resource utilization in any video streaming system is a key factor to increase the scalability and decrease the cost of the system. Resources to…

Burial affects the biogeochemistry of headwater streams in a midwestern US metropolitan area

EPA Science Inventory

Nitrogen (N) retention in stream networks is an important ecosystem service that may be affected by the widespread burial of headwater streams in urban basins. Urban stream burial has only recently been recognized by ecologists and little research has addressed the extent to whi...

Burial affects the biogeochemistry of headwater streams in a midwestern US metropolitan area - slides

EPA Science Inventory

Nitrogen (N) retention in stream networks is an important ecosystem service that may be affected by the widespread burial of headwater streams in urban basins. Urban stream burial has only recently been recognized by ecologists as a regional environmental impact and little resea...

Formation and evolution of a drainage network during the Pleistocene through a process of homoclinal shifting initiated by headward erosion.

NASA Astrophysics Data System (ADS)

Castelltort, F. Xavier; Carles Balasch, J.; Cirés, Jordi; Colombo, Ferran

2017-04-01

A homoclinal shifting process in NE of the Ebro basin, NE Iberian Peninsula, reorganized an old flow network into a new one. This process was initiated by the reactivation of a major normal fault (Amer Fault). An anaclinal stream, flowing to the hanging wall block, incised in the fault-line scarp, accessing by headward erosion the less resistant Paleogene units. The result was the formation of a sequence of strike valleys. The first valleys are situated in a more elevated topographical position than the valleys formed later. The last and the most important valley is La Plana de Vic, which is being emptied by differential erosion in front of the resistant base layer. The study of the lateral migration of a drainage basin since its initial stages has allowed the recognition of the layout of a drainage network and its model of evolution. The new drainage network includes three different subsystems. The main subsystem consists of stream courses flowing along the strike valley. While the other two subsystems flow into the main or can flow directly to the basin sink. These are the anaclinal subsystem, which drains the scarp face of the asymmetric valley, and the cataclinal subsystem, which drains the cuesta. The process of homoclinal shifting makes the strike streams migrate laterally and dip in the less resistant unit. This migration implies the reorganization of the other two tributary subsystems. The sequence of reorganizations may be preserved on the resistant bedrock of the cuesta. This allows the reconstruction of the route of the headward erosion of the initial anaclinal stream course through remnants of ancient strike streams flowing into former basin sinks, and its cataclinal tributaries draining the cuesta. In the case study of La Plana de Vic the migration route of the basin sink can be reconstructed from its initial position, Early Pleistocene, until present day. Besides, reorganization of the cataclinal network can also be recognized. During the lateral migration three incisions were made in a large anticlinal structure in the north (Bellmunt Anticline) and one incision was made in a crystalline massif (Montseny) in the south. The last of the incisions into the Bellmunt Anticline captured by headward erosion an older drainage network with headwaters in the axial Pyrenees. The result of the homoclinal shifting process was the capture of older drainage basins and the formation of the current drainage basin of the river Ter.

Green Cloud on the Horizon

NASA Astrophysics Data System (ADS)

Ali, Mufajjul

This paper proposes a Green Cloud model for mobile Cloud computing. The proposed model leverage on the current trend of IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service), and look at new paradigm called "Network as a Service" (NaaS). The Green Cloud model proposes various Telco's revenue generating streams and services with the CaaS (Cloud as a Service) for the near future.

New England SPARROW Water-Quality Modeling to Assist with the Development of Total Maximum Daily Loads in the Connecticut River Basin

NASA Astrophysics Data System (ADS)

Moore, R. B.; Robinson, K. W.; Simcox, A. C.; Johnston, C. M.

2002-05-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEWIPCC), is currently preparing a water-quality model, called SPARROW, to assist in the regional total maximum daily load (TMDL) studies in New England. A model is required to provide estimates of nutrient loads and confidence intervals at unmonitored stream reaches. SPARROW (Spatially Referenced Regressions on Watershed Attributes) is a spatially detailed, statistical model that uses regression equations to relate total phosphorus and nitrogen (nutrient) stream loads to pollution sources and watershed characteristics. These statistical relations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW model is based on a hydrologic network of 42,000 stream reaches and associated watersheds. Point source data are derived from USEPA's Permit Compliance System (PCS). Information about nonpoint sources is derived from data such as fertilizer use, livestock wastes, and atmospheric deposition. Watershed characteristics include land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. Preliminary SPARROW results are expected in Spring 2002. The New England SPARROW model is proposed for use in the TMDL determination for nutrients in the Connecticut River Basin, upstream of Connecticut. The model will be used to estimate nitrogen loads from each of the upstream states to Long Island Sound. It will provide estimates and confidence intervals of phosphorus and nitrogen loads, area-weighted yields of nutrients by watershed, sources of nutrients, and the downstream movement of nutrients. This information will be used to (1) understand ranges in nutrient levels in surface waters, (2) identify the environmental factors that affect nutrient levels in streams, (3) evaluate monitoring efforts for better determination of nutrient loads, and (4) evaluate management options for reducing nutrient loads to achieve water-quality goals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

A. M. Sexton,; A. M. Sadeghi,; X. Zhang,

The value of watershed-scale, hydrologic and water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropriate application of watershed models. In small watersheds, where no dense rain gauge network is available, modelers are faced with a dilemma to choose between different data sets. In this study, we used the German Branch (GB) watershed (~50 km 2), which is included in the USDA Conservation Effects Assessment Project (CEAP), to examine the implications of usingmore » surface rain gauge and next-generation radar (NEXRAD) precipitation data sets on the performance of the Soil and Water Assessment Tool (SWAT). The GB watershed is located in the Coastal Plain of Maryland on the eastern shore of Chesapeake Bay. Stream flow estimation results using surface rain gauge data seem to indicate the importance of using rain gauges within the same direction as the storm pattern with respect to the watershed. In the absence of a spatially representative network of rain gauges within the watershed, NEXRAD data produced good estimates of stream flow at the outlet of the watershed. Three NEXRAD datasets, including (1)*non-corrected (NC), (2) bias-corrected (BC), and (3) inverse distance weighted (IDW) corrected NEXRAD data, were produced. Nash-Sutcliffe efficiency coefficients for daily stream flow simulation using these three NEXRAD data ranged from 0.46 to 0.58 during calibration and from 0.68 to 0.76 during validation. Overall, correcting NEXRAD with rain gauge data is promising to produce better hydrologic modeling results. Given the multiple precipitation datasets and corresponding simulations, we explored the combination of the multiple simulations using Bayesian model averaging.« less

The Functional Neuroanatomy of Human Face Perception.

PubMed

Grill-Spector, Kalanit; Weiner, Kevin S; Kay, Kendrick; Gomez, Jesse

2017-09-15

Face perception is critical for normal social functioning and is mediated by a network of regions in the ventral visual stream. In this review, we describe recent neuroimaging findings regarding the macro- and microscopic anatomical features of the ventral face network, the characteristics of white matter connections, and basic computations performed by population receptive fields within face-selective regions composing this network. We emphasize the importance of the neural tissue properties and white matter connections of each region, as these anatomical properties may be tightly linked to the functional characteristics of the ventral face network. We end by considering how empirical investigations of the neural architecture of the face network may inform the development of computational models and shed light on how computations in the face network enable efficient face perception.

Character recognition from trajectory by recurrent spiking neural networks.

PubMed

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.

Assessment of groundwater response to droughts in a complex runoff-dominated watershed by using an integrated hydrologic model

NASA Astrophysics Data System (ADS)

Woolfenden, L. R.; Hevesi, J. A.; Nishikawa, T.

2014-12-01

Groundwater is an important component of the water supply, especially during droughts, within the Santa Rosa Plain watershed (SRPW), California, USA. The SRPW is 680 km2 and includes a network of natural and engineered stream channels. Streamflow is strongly seasonal, with high winter flows, predominantly intermittent summer flows, and comparatively rapid response time to larger storms. Groundwater flow is influenced primarily by complex geology, spatial and temporal variation in recharge, and pumping for urban, agricultural, and rural demands. Results from an integrated hydrologic model (GSFLOW) for the SRPW were analyzed to assess the effect of droughts on groundwater resources during water years 1976-2010. Model results indicate that, in general, below-average precipitation during historical drought periods reduced groundwater recharge (focused within stream channels and diffuse outside of channels on alluvial plains), groundwater evapotranspiration (ET), and groundwater discharge to streams (baseflow). In addition, recharge during wet periods was not sufficient to replenish groundwater-storage losses caused by drought and groundwater pumping, resulting in an overall 150 gigaliter loss in groundwater storage for water years 1976-2010. During drought periods, lower groundwater levels from reduced recharge broadly increased the number and length of losing-stream reaches, and seepage losses in streams became a higher percentage of recharge relative to the diffuse recharge outside of stream channels (for example, seepage losses in streams were 36% of recharge in 2006 and 57% at the end of the 2007-09 drought). Reductions in groundwater storage during drought periods resulted in decreased groundwater ET (loss of riparian habitat) and baseflow, especially during the warmer and dryer months (May through September) when groundwater is the dominant component of streamflow.

A linked spatial and temporal model of the chemical and biological status of a large, acid-sensitive river network.

PubMed

Evans, Chris D; Cooper, David M; Juggins, Steve; Jenkins, Alan; Norris, Dave

2006-07-15

Freshwater sensitivity to acidification varies according to geology, soils and land-use, and consequently it remains difficult to quantify the current extent of acidification, or its biological impacts, based on limited spot samples. The problem is particularly acute for river systems, where the transition from acid to circum-neutral conditions can occur within short distances. This paper links an established point-based long-term acidification model (MAGIC) with a landscape-based mixing model (PEARLS) to simulate spatial and temporal variations in acidification for a 256 km(2) catchment in North Wales. Empirical relationships are used to predict changes in the probability of occurrence of an indicator invertebrate species, Baetis rhodani, across the catchment as a function of changing chemical status. Results suggest that, at present, 27% of the river network has a mean acid neutralising capacity (ANC) below a biologically-relevant threshold of 20 microeq l(-1). At high flows, this proportion increases to 45%. The model suggests that only around 16% of the stream network had a mean ANC < 20 microeq l(-1) in 1850, but that this increased to 42% at the sulphur deposition peak around 1970. By 2050 recovery is predicted, but with some persistence of acid conditions in the most sensitive, peaty headwaters. Stream chemical suitability for Baetis rhodani is also expected to increase in formerly acidified areas, but for overall abundance to remain below that simulated in 1850. The approach of linking plot-scale process-based models to catchment mixing models provides a potential means of predicting the past and future spatial extent of acidification within large, heterogeneous river networks and regions. Further development of ecological response models to include other chemical predictor variables and the effects of acid episodes would allow more realistic simulation of the temporal and spatial dynamics of ecosystem recovery from acidification.

Effects of riparian buffer width on wood loading in headwater streams after repeated forest thinning

Treesearch

Julia I. Burton; Deanna H. Olson; Klaus J. Puettmann

2016-01-01

Forested riparian buffer zones are used in conjunction with upland forest management, in part, to provide for the recruitment for large wood to streams. Small headwater streams account for the majority of stream networks in many forested regions. Yet, our understanding of how riparian buffer width influences wood dynamics in headwater streams is relatively less...

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

Empirical evaluation of H.265/HEVC-based dynamic adaptive video streaming over HTTP (HEVC-DASH)

NASA Astrophysics Data System (ADS)

Irondi, Iheanyi; Wang, Qi; Grecos, Christos

2014-05-01

Real-time HTTP streaming has gained global popularity for delivering video content over Internet. In particular, the recent MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard enables on-demand, live, and adaptive Internet streaming in response to network bandwidth fluctuations. Meanwhile, emerging is the new-generation video coding standard, H.265/HEVC (High Efficiency Video Coding) promises to reduce the bandwidth requirement by 50% at the same video quality when compared with the current H.264/AVC standard. However, little existing work has addressed the integration of the DASH and HEVC standards, let alone empirical performance evaluation of such systems. This paper presents an experimental HEVC-DASH system, which is a pull-based adaptive streaming solution that delivers HEVC-coded video content through conventional HTTP servers where the client switches to its desired quality, resolution or bitrate based on the available network bandwidth. Previous studies in DASH have focused on H.264/AVC, whereas we present an empirical evaluation of the HEVC-DASH system by implementing a real-world test bed, which consists of an Apache HTTP Server with GPAC, an MP4Client (GPAC) with open HEVC-based DASH client and a NETEM box in the middle emulating different network conditions. We investigate and analyze the performance of HEVC-DASH by exploring the impact of various network conditions such as packet loss, bandwidth and delay on video quality. Furthermore, we compare the Intra and Random Access profiles of HEVC coding with the Intra profile of H.264/AVC when the correspondingly encoded video is streamed with DASH. Finally, we explore the correlation among the quality metrics and network conditions, and empirically establish under which conditions the different codecs can provide satisfactory performance.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Ramification of Channel Networks Incised by Groundwater Flow

NASA Astrophysics Data System (ADS)

Yi, R. S.; Seybold, H. F.; Petroff, A. P.; Devauchelle, O.; Rothman, D.

2011-12-01

The geometry of channel networks has been a source of fascination since at least Leonardo da Vinci's time. Yet a comprehensive understanding of ramification---the mechanism of branching by which a stream network acquires its geometric complexity---remains elusive. To investigate the mechanisms of ramification and network growth, we consider channel growth driven by groundwater flow as a model system, analogous to a medical scientist's laboratory rat. We test our theoretical predictions through analysis of a particularly compelling example found on the Florida Panhandle north of Bristol. As our ultimate goal is to understand ramification and growth dynamics of the entire network, we build a computational model based on the following growth hypothesis: Channels grow in the direction that captures the maximum water flux. When there are two such directions, tips bifurcate. The direction of growth can be determined from the expansion of the ground water field around each tip, where each coefficient in this expansion has a physical interpretation. The first coefficient in the expansion determines the ground water discharge, leading to a straight growth of the channel. The second term describes the asymmetry in the water field leading to a bending of the stream in the direction of maximal water flux. The ratio between the first and the third coefficient determines a critical distance rc over which the tip feels inhomogeneities in the ground water table. This initiates then the splitting of the tip. In order to test our growth hypothesis and to determine rc, we grow the Florida network backward. At each time step we calculate the solution of the ground water field and determine the appropriate expansion coefficients around each tip. Comparing this simulation result to the predicted values provides us with a stringent measure for rc and the significance of our growth hypothesis.

An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow

NASA Astrophysics Data System (ADS)

Hicks, S.; Damiano, S. G.; Smith, K. M.; Olexy, J.; Horsburgh, J. S.; Mayorga, E.; Aufdenkampe, A. K.

2013-12-01

Implementing a large-scale streaming environmental sensor network has previously been limited by the high cost of the datalogging and data communication infrastructure. The Christina River Basin Critical Zone Observatory (CRB-CZO) is overcoming the obstacles to large near-real-time data collection networks by using Arduino, an open source electronics platform, in combination with XBee ZigBee wireless radio modules. These extremely low-cost and easy-to-use open source electronics are at the heart of the new DIY movement and have provided solutions to countless projects by over half a million users worldwide. However, their use in environmental sensing is in its infancy. At present a primary limitation to widespread deployment of open-source electronics for environmental sensing is the lack of a simple, open-source software stack to manage streaming data from heterogeneous sensor networks. Here we present a functioning prototype software stack that receives sensor data over a self-meshing ZigBee wireless network from over a hundred sensors, stores the data locally and serves it on demand as a CUAHSI Water One Flow (WOF) web service. We highlight a few new, innovative components, including: (1) a versatile open data logger design based the Arduino electronics platform and ZigBee radios; (2) a software library implementing SDI-12 communication protocol between any Arduino platform and SDI12-enabled sensors without the need for additional hardware (https://github.com/StroudCenter/Arduino-SDI-12); and (3) 'midStream', a light-weight set of Python code that receives streaming sensor data, appends it with metadata on the fly by querying a relational database structured on an early version of the Observations Data Model version 2.0 (ODM2), and uses the WOFpy library to serve the data as WaterML via SOAP and REST web services.

Network Structure as a Modulator of Disturbance Impacts in Streams

NASA Astrophysics Data System (ADS)

Warner, S.; Tullos, D. D.

2017-12-01

This study examines how river network structure affects the propagation of geomorphic and anthropogenic disturbances through streams. Geomorphic processes such as debris flows can alter channel morphology and modify habitat for aquatic biota. Anthropogenic disturbances such as road construction can interact with the geomorphology and hydrology of forested watersheds to change sediment and water inputs to streams. It was hypothesized that the network structure of streams within forested watersheds would influence the location and magnitude of the impacts of debris flows and road construction on sediment size and channel width. Longitudinal surveys were conducted every 50 meters for 11 kilometers of third-to-fifth order streams in the H.J. Andrews Experimental Forest in the Western Cascade Range of Oregon. Particle counts and channel geometry measurements were collected to characterize the geomorphic impacts of road crossings and debris flows as disturbances. Sediment size distributions and width measurements were plotted against the distance of survey locations through the network to identify variations in longitudinal trends of channel characteristics. Thresholds for the background variation in sediment size and channel width, based on the standard deviations of sample points, were developed for sampled stream segments characterized by location as well as geomorphic and land use history. Survey locations were classified as "disturbed" when they deviated beyond the reference thresholds in expected sediment sizes and channel widths, as well as flow-connected proximity to debris flows and road crossings. River network structure was quantified by drainage density and centrality of nodes upstream of survey locations. Drainage density and node centrality were compared between survey locations with similar channel characteristic classifications. Cluster analysis was used to assess the significance of survey location, proximity of survey location to debris flows and road crossings, drainage density and node centrality in predicting sediment size and channel width classifications for locations within the watershed. Results contribute to the understanding of susceptibility and responses of streams supporting critical habitat for aquatic species to debris flows and forest road disturbances.

A biological assessment of streams in the eastern United States using a predictive model for macroinvertebrate assemblages

USGS Publications Warehouse

Carlisle, D.M.; Meador, M.R.

2007-01-01

A predictive model (RIVPACS-type) for benthic macroinvertebrates was constructed to assess the biological condition of 1,087 streams sampled throughout the eastern United States from 1993-2003 as part of the U.S. Geological Survey's National Water-Quality Assessment Program. A subset of 338 sites was designated as reference quality, 28 of which were withheld from model calibration and used to independently evaluate model precision and accuracy. The ratio of observed (O) to expected (E) taxa richness was used as a continuous measure of biological condition, and sites with O/E values <0.8 were classified as biologically degraded. Spatiotemporal variability of O/E values was evaluated with repeated annual and within-site samples at reference sites. Values of O/E were regressed on a measure of urbanization in three regions and compared among streams in different land-use settings. The model accurately predicted the expected taxa at validation sites with high precision (SD = 0.11). Within-site spatial variability in O/E values was much larger than annual and among-site variation at reference sites and was likely caused by environmental differences among sampled reaches. Values of O/E were significantly correlated with basin road density in the Boston, Massachusetts (p < 0.001), Birmingham, Alabama (p = 0.002), and Green Bay, Wisconsin (p = 0.034) metropolitan areas, but the strength of the relations varied among regions. Urban streams were more depleted of taxa than streams in other land-use settings, but larger networks of riparian forest appeared to mediate biological degradation. Taxa that occurred less frequently than predicted by the model were those known to be generally intolerant of a variety of anthropogenic stressors. ?? 2007 American Water Resources Association.

Putting newborn hearing screening on the political agenda in Belgium: local initiatives toward a community programme - a qualitative study.

PubMed

Vos, Bénédicte; Lagasse, Raphaël; Levêque, Alain

2014-07-01

The Kingdon model, based on the convergence of three streams (problem, policy, and politics) and the opening of a policy window, analyses the process by which a health issue is placed on the political agenda. We used this model to document the political agenda-setting process of the newborn hearing screening programme in Belgium. A qualitative study based on a document review and on semi-directed interviews was carried out. The interviews were conducted with nine people who had played a role in putting the issue in question on the political agenda, and the documents reviewed included scientific literature and internal reports and publications from the newborn hearing screening programme. The thematic analysis of the data collected was carried out on the basis of the Kingdon model's three streams. The political agenda-setting of this screening programme was based on many factors. The problem stream included factors external to the context under study, such as the technological developments and the contribution of the scientific literature which led to the recommendation to provide newborn hearing screening. The two other streams (policy and politics) covered factors internal to the Belgian context. The fact that it was locally feasible with financial support, the network of doctors convinced of the need for newborn hearing screening, the drafting of various proposals, and the search for financing were all part of the policy stream. The Belgian political context and the policy opportunities concerning preventive medicine were identified as significant factors in the third stream. When these three streams converged, a policy window opened, allowing newborn hearing screening onto the political agenda and enabling the policy decision for its introduction. The advantage of applying the Kingdon model in our approach was the ability to demonstrate the political agenda-setting process, using the three streams. This made it possible to identify the many factors involved in the process. However, the roles of the stakeholders and of the context were somewhat inexplicit in this model.

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

USGS Publications Warehouse

Hay, Lauren E.; LaFontaine, Jacob H.; Markstrom, Steven

2014-01-01

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

Privacy Preserving Sequential Pattern Mining in Data Stream

NASA Astrophysics Data System (ADS)

Huang, Qin-Hua

The privacy preserving data mining technique researches have gained much attention in recent years. For data stream systems, wireless networks and mobile devices, the related stream data mining techniques research is still in its' early stage. In this paper, an data mining algorithm dealing with privacy preserving problem in data stream is presented.

Statistical Analysis of Regional Surface Water Quality in Southeastern Ontario.

ERIC Educational Resources Information Center

Bodo, Byron A.

1992-01-01

Historical records from Ontario's Provincial Water Quality Monitoring Network for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario, spanning the Precambrian Shield and the St. Lawrence Lowlands. The study served as a model for much of Ontario. (54 references) (Author/MDH)

Hydrogeomorphic connectivity on roads crossing in rural headwaters and its effect on stream dynamics.

PubMed

Thomaz, Edivaldo L; Peretto, Gustavo T

2016-04-15

Unpaved roads are ubiquitous features that have been transforming the landscape through human history. Unpaved roads affect the water and sediment pathways through a catchment and impacts the aquatic ecosystem. In this study, we describe the effect of unpaved road on the hydrogeomorphic connectivity at the rural headwater scale. Measurement was based on the stream crossing approach, i.e., road superimposing the drainage system. We installed a Parshall flume coupled with single-stage suspended sediment sampler at each stream crossing. In addition, we displayed our monitoring scheme with an upscaling perspective from second-order to third-order stream. We concluded that the road-stream coupling dramatically changed the stream dynamic. The increase of discharge caused by roads at the headwater was 50% larger compared to unaffected streams. Additionally, suspended sediment concentration enhancement at stream crossings ranged from to 413% at second-order streams to 145% at third-order streams. The landform characteristics associated with the road network produced an important hydrogeomorphic disruption in the landscape. As a result, the sediment filter function of the riparian zone was reduced dramatically. Therefore, we recommend that projects for aquatic system restoration or conservation in rural landscape consider the role of the road network on stream dynamics. Copyright © 2016 Elsevier B.V. All rights reserved.

Opinion dynamics on interacting networks: media competition and social influence.

PubMed

Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

2014-05-27

The inner dynamics of the multiple actors of the informations systems - i.e, T.V., newspapers, blogs, social network platforms, - play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.

Opinion dynamics on interacting networks: media competition and social influence

NASA Astrophysics Data System (ADS)

Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

2014-05-01

The inner dynamics of the multiple actors of the informations systems - i.e, T.V., newspapers, blogs, social network platforms, - play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.

No Snow No Flow: How Montane Stream Networks Respond to Drought

NASA Astrophysics Data System (ADS)

Grant, G.; Nolin, A. W.; Selker, J. S.; Lewis, S.; Hempel, L. A.; Jefferson, A.; Walter, C.; Roques, C.

2015-12-01

Hydrologic extremes, such as drought, offer an exceptional opportunity to explore how runoff generation mechanisms and stream networks respond to changing precipitation regimes. The winter of 2014-2015 was the warmest on record in western Oregon, US, with record low snowpacks, and was followed by an anomalously warm, dry spring, resulting in historically low streamflows. But a year like 2015 is more than an outlier meteorological year. It provides a unique opportunity to test fundamental hypotheses for how montane hydrologic systems will respond to anticipated changes in amount and timing of recharge. In particular, the volcanic Cascade Mountains represent a "landscape laboratory" comprised of two distinct runoff regimes: the surface-flow dominated Western Cascade watersheds, with flashy streamflow regimes, rapid baseflow recession, and very low summer flows; and (b) the spring-fed High Cascade watersheds, with a slow-responding streamflow regime, and a long and sustained baseflow recession that maintains late summer streamflow through deep-groundwater contributions to high volume, coldwater springs. We hypothesize that stream network response to the extremely low snowpack and recharge varies sharply in these two regions. In surface flow dominated streams, the location of channel heads can migrate downstream, contracting the network longitudinally; wetted channel width and depth contract laterally as summer recession proceeds and flows diminish. In contrast, in spring-fed streams, channel heads "jump" to the next downstream spring when upper basin spring flow diminishes to zero. Downstream of flowing springs, wetted channel width and depth contract laterally as flows recede. To test these hypotheses, we conducted a field campaign to measure changing discharge, hydraulic geometry, and channel head location in both types of watersheds throughout the summer and early fall. Multiple cross-section sites were established on 6 streams representing both flow regime types on either side of the Cascade crest. We also took Isotopic water samples to determine recharge elevations of receding streams. Taken together these measurements reveal the processes by which drainage networks contract as flows diminish - a fundamental property of montane stream systems both now and in the future.

Stream Tracker: Crowd sourcing and remote sensing to monitor stream flow intermittence

NASA Astrophysics Data System (ADS)

Puntenney, K.; Kampf, S. K.; Newman, G.; Lefsky, M. A.; Weber, R.; Gerlich, J.

2017-12-01

Streams that do not flow continuously in time and space support diverse aquatic life and can be critical contributors to downstream water supply. However, these intermittent streams are rarely monitored and poorly mapped. Stream Tracker is a community powered stream monitoring project that pairs citizen contributed observations of streamflow presence or absence with a network of streamflow sensors and remotely sensed data from satellites to track when and where water is flowing in intermittent stream channels. Citizens can visit sites on roads and trails to track flow and contribute their observations to the project site hosted by CitSci.org. Data can be entered using either a mobile application with offline capabilities or an online data entry portal. The sensor network provides a consistent record of streamflow and flow presence/absence across a range of elevations and drainage areas. Capacitance, resistance, and laser sensors have been deployed to determine the most reliable, low cost sensor that could be mass distributed to track streamflow intermittence over a larger number of sites. Streamflow presence or absence observations from the citizen and sensor networks are then compared to satellite imagery to improve flow detection algorithms using remotely sensed data from Landsat. In the first two months of this project, 1,287 observations have been made at 241 sites by 24 project members across northern and western Colorado.

Patterns in stream longitudinal profiles and implications for hyporheic exchange flow at the H.J. Andrews Experimental Forest, Oregon, USA.

Treesearch

Justin K. Anderson; Steven M. Wondzell; Michael N. Gooseff; Roy Haggerty

2005-01-01

There is a need to identify measurable characteristics of stream channel morphology that vary predictably throughout stream networks and that influence patterns of hyporheic exchange flow in mountain streams. In this paper we characterize stream longitudinal profiles according to channel unit spacing and the concavity of the water surface profile. We demonstrate that...

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

USGS Publications Warehouse

Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

2018-01-01

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

Nitrate removal in deep sediments of a nitrogen-rich river network: A test of a conceptual model

USGS Publications Warehouse

Stelzer, Robert S.; Bartsch, Lynn

2012-01-01

Many estimates of nitrogen removal in streams and watersheds do not include or account for nitrate removal in deep sediments, particularly in gaining streams. We developed and tested a conceptual model for nitrate removal in deep sediments in a nitrogen-rich river network. The model predicts that oxic, nitrate-rich groundwater will become depleted in nitrate as groundwater upwelling through sediments encounters a zone that contains buried particulate organic carbon, which promotes redox conditions favorable for nitrate removal. We tested the model at eight sites in upwelling reaches of lotic ecosystems in the Waupaca River Watershed that varied by three orders of magnitude in groundwater nitrate concentration. We measured denitrification potential in sediment core sections to 30 cm and developed vertical nitrate profiles to a depth of about 1 m with peepers and piezometer nests. Denitrification potential was higher, on average, in shallower core sections. However, core sections deeper than 5 cm accounted for 70%, on average, of the depth-integrated denitrification potential. Denitrification potential increased linearly with groundwater nitrate concentration up to 2 mg NO3-N/L but the relationship broke down at higher concentrations (> 5 mg NO3-N/L), a pattern that suggests nitrate saturation. At most sites groundwater nitrate declined from high concentrations at depth to much lower concentrations prior to discharge into the surface water. The profiles suggested that nitrate removal occurred at sediment depths between 20 and 40 cm. Dissolved oxygen concentrations were much higher in deep sediments than in pore water at 5 cm sediment depth at most locations. The substantial denitrification potential in deep sediments coupled with the declines in nitrate and dissolved oxygen concentrations in upwelling groundwater suggest that our conceptual model for nitrate removal in deep sediments is applicable to this river network. Our results suggest that nitrate removal rates can be high in deep sediments of upwelling stream reaches, which may have implications for efforts to understand and quantify nitrogen transport and removal at larger scales.

Multimodal Speaker Diarization.

PubMed

Noulas, A; Englebienne, G; Krose, B J A

2012-01-01

We present a novel probabilistic framework that fuses information coming from the audio and video modality to perform speaker diarization. The proposed framework is a Dynamic Bayesian Network (DBN) that is an extension of a factorial Hidden Markov Model (fHMM) and models the people appearing in an audiovisual recording as multimodal entities that generate observations in the audio stream, the video stream, and the joint audiovisual space. The framework is very robust to different contexts, makes no assumptions about the location of the recording equipment, and does not require labeled training data as it acquires the model parameters using the Expectation Maximization (EM) algorithm. We apply the proposed model to two meeting videos and a news broadcast video, all of which come from publicly available data sets. The results acquired in speaker diarization are in favor of the proposed multimodal framework, which outperforms the single modality analysis results and improves over the state-of-the-art audio-based speaker diarization.

Assessing sufficiency of thermal riverscapes for resilient ...

EPA Pesticide Factsheets

Resilient salmon populations require river networks that provide water temperature regimes sufficient to support a diversity of salmonid life histories across space and time. Efforts to protect, enhance and restore watershed thermal regimes for salmon may target specific locations and features within stream networks hypothesized to provide disproportionately high-value functional resilience to salmon populations. These include relatively small-scale features such as thermal refuges, and larger-scale features such as entire watersheds or aquifers that support thermal regimes buffered from local climatic conditions. Quantifying the value of both small and large scale thermal features to salmon populations has been challenged by both the difficulty of mapping thermal regimes at sufficient spatial and temporal resolutions, and integrating thermal regimes into population models. We attempt to address these challenges by using newly-available datasets and modeling approaches to link thermal regimes to salmon populations across scales. We will describe an individual-based modeling approach for assessing sufficiency of thermal refuges for migrating salmon and steelhead in large rivers, as well as a population modeling approach for assessing large-scale climate refugia for salmon in the Pacific Northwest. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Environment-dependent morphology in plasmodium of true slime mold Physarum polycephalum and a network growth model.

PubMed

Takamatsu, Atsuko; Takaba, Eri; Takizawa, Ginjiro

2009-01-07

Branching network growth patterns, depending on environmental conditions, in plasmodium of true slime mold Physarum polycephalum were investigated. Surprisingly, the patterns resemble those in bacterial colonies even though the biological mechanisms differ greatly. Bacterial colonies are collectives of microorganisms in which individual organisms have motility and interact through nutritious and chemical fields. In contrast, the plasmodium is a giant amoeba-like multinucleated unicellular organism that forms a network of tubular structures through which protoplasm streams. The cell motility of the plasmodium is generated by oscillation phenomena observed in the partial bodies, which interact through the tubular structures. First, we analyze characteristics of the morphology quantitatively, then we abstract local rules governing the growing process to construct a simple network growth model. This model is independent of specific systems, in which only two rules are applied. Finally, we discuss the mechanism of commonly observed biological pattern formations through comparison with the system of bacterial colonies.

Modular GIS Framework for National Scale Hydrologic and Hydraulic Modeling Support

NASA Astrophysics Data System (ADS)

Djokic, D.; Noman, N.; Kopp, S.

2015-12-01

Geographic information systems (GIS) have been extensively used for pre- and post-processing of hydrologic and hydraulic models at multiple scales. An extensible GIS-based framework was developed for characterization of drainage systems (stream networks, catchments, floodplain characteristics) and model integration. The framework is implemented as a set of free, open source, Python tools and builds on core ArcGIS functionality and uses geoprocessing capabilities to ensure extensibility. Utilization of COTS GIS core capabilities allows immediate use of model results in a variety of existing online applications and integration with other data sources and applications.The poster presents the use of this framework to downscale global hydrologic models to local hydraulic scale and post process the hydraulic modeling results and generate floodplains at any local resolution. Flow forecasts from ECMWF or WRF-Hydro are downscaled and combined with other ancillary data for input into the RAPID flood routing model. RAPID model results (stream flow along each reach) are ingested into a GIS-based scale dependent stream network database for efficient flow utilization and visualization over space and time. Once the flows are known at localized reaches, the tools can be used to derive the floodplain depth and extent for each time step in the forecast at any available local resolution. If existing rating curves are available they can be used to relate the flow to the depth of flooding, or synthetic rating curves can be derived using the tools in the toolkit and some ancillary data/assumptions. The results can be published as time-enabled spatial services to be consumed by web applications that use floodplain information as an input. Some of the existing online presentation templates can be easily combined with available online demographic and infrastructure data to present the impact of the potential floods on the local community through simple, end user products. This framework has been successfully used in both the data rich environments as well as in locales with minimum available spatial and hydrographic data.

Kinesthetic working memory and action control within the dorsal stream.

PubMed

Fiehler, Katja; Burke, Michael; Engel, Annerose; Bien, Siegfried; Rösler, Frank

2008-02-01

There is wide agreement that the "dorsal (action) stream" processes visual information for movement control. However, movements depend not only on vision but also on tactile and kinesthetic information (=haptics). Using functional magnetic resonance imaging, the present study investigates to what extent networks within the dorsal stream are also utilized for kinesthetic action control and whether they are also involved in kinesthetic working memory. Fourteen blindfolded participants performed a delayed-recognition task in which right-handed movements had to be encoded, maintained, and later recognized without any visual feedback. Encoding of hand movements activated somatosensory areas, superior parietal lobe (dorsodorsal stream), anterior intraparietal sulcus (aIPS) and adjoining areas (ventrodorsal stream), premotor cortex, and occipitotemporal cortex (ventral stream). Short-term maintenance of kinesthetic information elicited load-dependent activity in the aIPS and adjacent anterior portion of the superior parietal lobe (ventrodorsal stream) of the left hemisphere. We propose that the action representation system of the dorsodorsal and ventrodorsal stream is utilized not only for visual but also for kinesthetic action control. Moreover, the present findings demonstrate that networks within the ventrodorsal stream, in particular the left aIPS and closely adjacent areas, are also engaged in working memory maintenance of kinesthetic information.

Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network

Treesearch

Daniel J. Isaak; Charles H. Luce; Bruce E. Rieman; David E. Nagel; Erin E. Peterson; Dona L. Horan; Sharon Parkes; Gwynne L. Chandler

2010-01-01

Mountain streams provide important habitats for many species, but their faunas are especially vulnerable to climate change because of ectothermic physiologies and movements that are constrained to linear networks that are easily fragmented. Effectively conserving biodiversity in these systems requires accurate downscaling of climatic trends to local habitat conditions...

Quantity is nothing without quality: automated QA/QC for streaming sensor networks

Treesearch

John L. Campbell; Lindsey E. Rustad; John H. Porter; Jeffrey R. Taylor; Ethan W. Dereszynski; James B. Shanley; Corinna Gries; Donald L. Henshaw; Mary E. Martin; Wade. M. Sheldon; Emery R. Boose

2013-01-01

Sensor networks are revolutionizing environmental monitoring by producing massive quantities of data that are being made publically available in near real time. These data streams pose a challenge for ecologists because traditional approaches to quality assurance and quality control are no longer practical when confronted with the size of these data sets and the...

Regional statistical assessment of WRF-Hydro and IFC Model stream Flow uncertainties over the State of Iowa

NASA Astrophysics Data System (ADS)

ElSaadani, M.; Quintero, F.; Goska, R.; Krajewski, W. F.; Lahmers, T.; Small, S.; Gochis, D. J.

2015-12-01

This study examines the performance of different Hydrologic models in estimating peak flows over the state of Iowa. In this study I will compare the output of the Iowa Flood Center (IFC) hydrologic model and WRF-Hydro (NFIE configuration) to the observed flows at the USGS stream gauges. During the National Flood Interoperability Experiment I explored the performance of WRF-Hydro over the state of Iowa using different rainfall products and the resulting hydrographs showed a "flashy" behavior of the model output due to lack of calibration and bad initial flows due to short model spin period. I would like to expand this study by including a second well established hydrologic model and include more rain gauge vs. radar rainfall direct comparisons. The IFC model is expected to outperform WRF-Hydro's out of the box results, however, I will test different calibration options for both the Noah-MP land surface model and RAPID, which is the routing component of the NFIE-Hydro configuration, to see if this will improve the model results. This study will explore the statistical structure of model output uncertainties across scales (as a function of drainage areas and/or stream orders). I will also evaluate the performance of different radar-based Quantitative Precipitation Estimation (QPE) products (e.g. Stage IV, MRMS and IFC's NEXRAD based radar rainfall product. Different basins will be evaluated in this study and they will be selected based on size, amount of rainfall received over the basin area and location. Basin location will be an important factor in this study due to our prior knowledge of the performance of different NEXRAD radars that cover the region, this will help observe the effect of rainfall biases on stream flows. Another possible addition to this study is to apply controlled spatial error fields to rainfall inputs and observer the propagation of these errors through the stream network.

A modeling assessment of the thermal regime for an urban sport fishery

USGS Publications Warehouse

Bartholow, John M.

1991-01-01

Water temperature is almost certainly a limiting factor in the maintenance of a self-sustaining rainbow trout (Oncorhynchus mykiss, formerly Salmo gairdneri) and brown trout (Salmo trutta) fishery in the lower reaches of the Cache la Poudre River near Fort Collins, Colorado, USA. Irrigation diversions dewater portions of the river, but cold reservoir releases moderate water temperatures during some periods. The US Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP) was applied to a 31-km segment of the river using readily available stream geometry and hydrological and meteorological data. The calibrated model produced satisfactory water temperature predictions (R2=0.88,P3/sec would be needed to maintain suitable summer temperatures throughout most of the study area. Such flows would be especially beneficial during weekends when current irrigation patterns reduce flows. The model indicated that increasing the riparian shade would result in little improvement in water temperatures but that decreasing the stream width would result in significant temperature reductions. Introduction of a more thermally tolerant redband trout (Oncorhynchus sp.), or smallmouth bass (Micropterus dolomieui) might prove beneficial to the fishery. Construction of deep pools for thermal refugia might also be helpful.

Sediment carbon fate in phreatic karst (Part 1): Conceptual model development

NASA Astrophysics Data System (ADS)

Husic, A.; Fox, J.; Agouridis, C.; Currens, J.; Ford, W.; Taylor, C.

2017-06-01

Recent research has paid increased attention to quantifying the fate of carbon pools within fluvial networks, but few, if any, studies consider the fate of sediment organic carbon in fluviokarst systems despite that karst landscapes cover 12% of the earth's land surface. The authors develop a conceptual model of sediment carbon fate in karst terrain with specific emphasis upon phreatic karst conduits, i.e., those located below the groundwater table that have the potential to trap surface-derived sediment and turnover carbon. To assist with their conceptual model development, the authors study a phreatic system and apply a mixture of methods traditional and novel to karst studies, including electrical resistivity imaging, well drilling, instantaneous velocimetry, dye tracing, stage recording, discrete and continuous sediment and water quality sampling, and elemental and stable carbon isotope fingerprinting. Results show that the sediment transport carrying capacity of the phreatic karst water is orders of magnitude less than surface streams during storm-activated periods promoting deposition of fine sediments in the phreatic karst. However, the sediment transport carrying capacity is sustained long after the hydrologic event has ended leading to sediment resuspension and prolonged transport. The surficial fine grained laminae occurs in the subsurface karst system; but unlike surface streams, the light-limited conditions of the subsurface karst promotes constant heterotrophy leading to carbon turnover. The coupling of the hydrological processes leads to a conceptual model that frames phreatic karst as a biologically active conveyor of sediment carbon that recharges degraded organic carbon back to surface streams. For example, fluvial sediment is estimated to lose 30% of its organic carbon by mass during a one year temporary residence within the phreatic karst. It is recommended that scientists consider karst pathways when attempting to estimate organic matter stocks and carbon transformation in fluvial networks.

The role of the hyporheic zone across stream networks

Treesearch

Steven M. Wondzell

2011-01-01

Many hyporheic papers state that the hyporheic zone is a critical component of stream ecosystems, and many of these papers focus on the biogeochemical effects of the hyporheic zone on stream solute loads. However, efforts to show such relationships have proven elusive, prompting several questions: Are the effects of the hyporheic zone on stream ecosystems so highly...

Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing

NASA Astrophysics Data System (ADS)

Jansen, Peter A.; Watter, Scott

2012-03-01

Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.

Comparison of Mercury Mass Loading in Streams to Wet and Dry Atmospheric Deposition in Watersheds of the Western US: Evidence for Non-Atmospheric Mercury Sources

NASA Astrophysics Data System (ADS)

Domagalski, J. L.; Majewski, M. S.; Alpers, C. N.; Eckley, C.

2015-12-01

Many streams in the western United States (US) are listed as impaired by mercury (Hg), and it is important to understand the magnitudes of the various sources in order to implement management strategies. Atmospheric deposition of Hg and can be a major source of aquatic contamination, along with mine wastes, and other sources. Prior studies in the eastern US have shown that streams deliver less than 50% of the atmospherically deposited Hg on an annual basis. In this study, we compared annual stream Hg loads for 20 watersheds in the western US to measured wet and modeled dry deposition. Land use varies from undisturbed to mixed (agricultural, urban, forested, mining). Data from the Mercury Deposition Network was used to estimate Hg input from precipitation. Dry deposition was not directly measured, but can be modeled using the Community Multi-scale Air Quality model. At an undeveloped watershed in the Rocky Mountains, the ratio of stream Hg load to atmospheric deposition was 0.2 during a year of average precipitation. In contrast, at the Carson River in Nevada, with known Hg contamination from historical silver mining with Hg amalgamation, stream export exceeded atmospheric deposition by a factor of 60, and at a small Sierran watershed with gold mining, the ratio was 70. Larger watersheds with mixed land uses, tend to have lower ratios of stream export relative to atmospheric deposition suggesting storage of Hg. The Sacramento River was the largest watershed for which Hg riverine loads were available with an average ratio of stream Hg export to atmospheric deposition of 0.10. Although Hg was used in upstream historical mining operations, the downstream river Hg load is partially mitigated by reservoirs, which trap sediment. This study represents the first compilation of riverine Hg loads in comparison to atmospheric deposition on a regional scale; the approach may be useful in assessing the relative importance of atmospheric and non-atmospheric Hg sources.

Stream network geomorphology mediates predicted vulnerability of anadromous fish habitat to hydrologic change in southeast Alaska.

PubMed

Sloat, Matthew R; Reeves, Gordon H; Christiansen, Kelly R

2017-02-01

In rivers supporting Pacific salmon in southeast Alaska, USA, regional trends toward a warmer, wetter climate are predicted to increase mid- and late-21st-century mean annual flood size by 17% and 28%, respectively. Increased flood size could alter stream habitats used by Pacific salmon for reproduction, with negative consequences for the substantial economic, cultural, and ecosystem services these fish provide. We combined field measurements and model simulations to estimate the potential influence of future flood disturbance on geomorphic processes controlling the quality and extent of coho, chum, and pink salmon spawning habitat in over 800 southeast Alaska watersheds. Spawning habitat responses varied widely across watersheds and among salmon species. Little variation among watersheds in potential spawning habitat change was explained by predicted increases in mean annual flood size. Watershed response diversity was mediated primarily by topographic controls on stream channel confinement, reach-scale geomorphic associations with spawning habitat preferences, and complexity in the pace and mode of geomorphic channel responses to altered flood size. Potential spawning habitat loss was highest for coho salmon, which spawn over a wide range of geomorphic settings, including steeper, confined stream reaches that are more susceptible to streambed scour during high flows. We estimated that 9-10% and 13-16% of the spawning habitat for coho salmon could be lost by the 2040s and 2080s, respectively, with losses occurring primarily in confined, higher-gradient streams that provide only moderate-quality habitat. Estimated effects were lower for pink and chum salmon, which primarily spawn in unconfined floodplain streams. Our results illustrate the importance of accounting for valley and reach-scale geomorphic features in watershed assessments of climate vulnerability, especially in topographically complex regions. Failure to consider the geomorphic context of stream networks will hamper efforts to understand and mitigate the vulnerability of anadromous fish habitat to climate-induced hydrologic change. © 2016 John Wiley & Sons Ltd.

Hydrogeomorphic controls on hyporheic and riparian transport in two headwater mountain streams during base flow recession

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.; Harman, Ciaran; Gooseff, Michael N.; Singha, Kamini

2016-02-01

Solute transport along riparian and hyporheic flow paths is broadly expected to respond to dynamic hydrologic forcing by streams, aquifers, and hillslopes. However, direct observation of these dynamic responses is lacking, as is the relative control of geologic setting as a control on responses to dynamic hydrologic forcing. We conducted a series of four stream solute tracer injections through base flow recession in each of two watersheds with contrasting valley morphology in the H.J. Andrews Experimental Forest, monitoring tracer concentrations in the stream and in a network of shallow riparian wells in each watershed. We found hyporheic mean arrival time, temporal variance, and fraction of stream water in the bedrock-constrained valley bottom and near large roughness elements in the wider valley bottom were not variable with discharge, suggesting minimal control by hydrologic forcing. Conversely, we observed increases in mean arrival time and temporal variance and decreasing fraction stream water with decreasing discharge near the hillslopes in the wider valley bottom. This may indicate changes in stream discharge and valley bottom hydrology control transport in less constrained locations. We detail five hydrogeomorphic responses to base flow recession to explain observed spatial and temporal patterns in the interactions between streams and their valley bottoms. Models able to account for the transition from geologically dominated processes in the near-stream subsurface to hydrologically dominated processes near the hillslope will be required to predict solute transport and fate in valley bottoms of headwater mountain streams.

Reconciling records of ice streaming and ice margin retreat to produce a palaeogeographic reconstruction of the deglaciation of the Laurentide Ice Sheet

NASA Astrophysics Data System (ADS)

Margold, Martin; Stokes, Chris R.; Clark, Chris D.

2018-06-01

This paper reconstructs the deglaciation of the Laurentide Ice Sheet (LIS; including the Innuitian Ice Sheet) from the Last Glacial Maximum (LGM), with a particular focus on the spatial and temporal variations in ice streaming and the associated changes in flow patterns and ice divides. We build on a recent inventory of Laurentide ice streams and use an existing ice margin chronology to produce the first detailed transient reconstruction of the ice stream drainage network in the LIS, which we depict in a series of palaeogeographic maps. Results show that the drainage network at the LGM was similar to modern-day Antarctica. The majority of the ice streams were marine terminating and topographically-controlled and many of these continued to function late into the deglaciation, until the ice sheet lost its marine margin. Ice streams with a terrestrial ice margin in the west and south were more transient and ice flow directions changed with the build-up, peak-phase and collapse of the Cordilleran-Laurentide ice saddle. The south-eastern marine margin in Atlantic Canada started to retreat relatively early and some of the ice streams in this region switched off at or shortly after the LGM. In contrast, the ice streams draining towards the north-western and north-eastern marine margins in the Beaufort Sea and in Baffin Bay appear to have remained stable throughout most of the Late Glacial, and some of them continued to function until after the Younger Dryas (YD). The YD influenced the dynamics of the deglaciation, but there remains uncertainty about the response of the ice sheet in several sectors. We tentatively ascribe the switching-on of some major ice streams during this period (e.g. M'Clintock Channel Ice Stream at the north-west margin), but for other large ice streams whose timing partially overlaps with the YD, the drivers are less clear and ice-dynamical processes, rather than effects of climate and surface mass balance are viewed as more likely drivers. Retreat rates markedly increased after the YD and the ice sheet became limited to the Canadian Shield. This hard-bed substrate brought a change in the character of ice streaming, which became less frequent but generated much broader terrestrial ice streams. The final collapse of the ice sheet saw a series of small ephemeral ice streams that resulted from the rapidly changing ice sheet geometry in and around Hudson Bay. Our reconstruction indicates that the LIS underwent a transition from a topographically-controlled ice drainage network at the LGM to an ice drainage network characterised by less frequent, broad ice streams during the later stages of deglaciation. These deglacial ice streams are mostly interpreted as a reaction to localised ice-dynamical forcing (flotation and calving of the ice front in glacial lakes and transgressing sea; basal de-coupling due to large amount of meltwater reaching the bed, debuttressing due to rapid changes in ice sheet geometry) rather than as conveyors of excess mass from the accumulation area of the ice sheet. At an ice sheet scale, the ice stream drainage network became less widespread and less efficient with the decreasing size of the deglaciating ice sheet, the final elimination of which was mostly driven by surface melt.

Low latency adaptive streaming of HD H.264 video over 802.11 wireless networks with cross-layer feedback

NASA Astrophysics Data System (ADS)

Patti, Andrew; Tan, Wai-tian; Shen, Bo

2007-09-01

Streaming video in consumer homes over wireless IEEE 802.11 networks is becoming commonplace. Wireless 802.11 networks pose unique difficulties for streaming high definition (HD), low latency video due to their error-prone physical layer and media access procedures which were not designed for real-time traffic. HD video streaming, even with sophisticated H.264 encoding, is particularly challenging due to the large number of packet fragments per slice. Cross-layer design strategies have been proposed to address the issues of video streaming over 802.11. These designs increase streaming robustness by imposing some degree of monitoring and control over 802.11 parameters from application level, or by making the 802.11 layer media-aware. Important contributions are made, but none of the existing approaches directly take the 802.11 queuing into account. In this paper we take a different approach and propose a cross-layer design allowing direct, expedient control over the wireless packet queue, while obtaining timely feedback on transmission status for each packet in a media flow. This method can be fully implemented on a media sender with no explicit support or changes required to the media client. We assume that due to congestion or deteriorating signal-to-noise levels, the available throughput may drop substantially for extended periods of time, and thus propose video source adaptation methods that allow matching the bit-rate to available throughput. A particular H.264 slice encoding is presented to enable seamless stream switching between streams at multiple bit-rates, and we explore using new computationally efficient transcoding methods when only a high bit-rate stream is available.

Dynamic Resource Adjustment to Provide Seamless Streaming Services on Multimedia Mobile Cellular Networks

NASA Astrophysics Data System (ADS)

Lin, Chow-Sing; Yen, Fang-Zhi

With the rapid advances in wireless network communication, multimedia presentation has become more applicable. However, due to the limited wireless network resource and the mobility of Mobile Host (MH), QoS for wireless streaming is much more difficult to maintain. How to decrease Call Dropping Probability (CDP) in multimedia traffic while still keeping acceptable Call Block Probability (CBP) without sacrificing QoS has become an significant issue in providing wireless streaming services. In this paper, we propose a novel Dynamic Resources Adjustment (DRA) algorithm, which can dynamically borrow idle reserved resources in the serving cell or the target cell for handoffing MHs to compensate the shortage of bandwidth in media streaming. The experimental simulation results show that compared with traditional No Reservation (NR), and Resource Reservation in the six neighboring cells (RR-nb), and Resource Reservation in the target cell (RR-t), our proposed DRA algorithm can fully utilize unused reserved resources to effectively decrease the CDP while still keeping acceptable CBP with high bandwidth utilization.

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

PubMed

Pecevski, Dejan; Maass, Wolfgang

2016-01-01

Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

PubMed Central

Pecevski, Dejan

2016-01-01

Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

Integrated Water Flow Model (IWFM), A Tool For Numerically Simulating Linked Groundwater, Surface Water And Land-Surface Hydrologic Processes

NASA Astrophysics Data System (ADS)

Dogrul, E. C.; Brush, C. F.; Kadir, T. N.

2006-12-01

The Integrated Water Flow Model (IWFM) is a comprehensive input-driven application for simulating groundwater flow, surface water flow and land-surface hydrologic processes, and interactions between these processes, developed by the California Department of Water Resources (DWR). IWFM couples a 3-D finite element groundwater flow process and 1-D land surface, lake, stream flow and vertical unsaturated-zone flow processes which are solved simultaneously at each time step. The groundwater flow system is simulated as a multilayer aquifer system with a mixture of confined and unconfined aquifers separated by semiconfining layers. The groundwater flow process can simulate changing aquifer conditions (confined to unconfined and vice versa), subsidence, tile drains, injection wells and pumping wells. The land surface process calculates elemental water budgets for agricultural, urban, riparian and native vegetation classes. Crop water demands are dynamically calculated using distributed soil properties, land use and crop data, and precipitation and evapotranspiration rates. The crop mix can also be automatically modified as a function of pumping lift using logit functions. Surface water diversions and groundwater pumping can each be specified, or can be automatically adjusted at run time to balance water supply with water demand. The land-surface process also routes runoff to streams and deep percolation to the unsaturated zone. Surface water networks are specified as a series of stream nodes (coincident with groundwater nodes) with specified bed elevation, conductance and stage-flow relationships. Stream nodes are linked to form stream reaches. Stream inflows at the model boundary, surface water diversion locations, and one or more surface water deliveries per location are specified. IWFM routes stream flows through the network, calculating groundwater-surface water interactions, accumulating inflows from runoff, and allocating available stream flows to meet specified or calculated deliveries. IWFM utilizes a very straight-forward input file structure, allowing rapid development of complex simulations. A key feature of IWFM is a new algorithm for computation of groundwater flow across element faces. Enhancements to version 3.0 include automatic time-tracking of input and output data sets, linkage with the HEC-DSS database, and dynamic crop allocation using logit functions. Utilities linking IWFM to the PEST automated calibration suite are also available. All source code, executables and documentation are available for download from the DWR web site. IWFM is currently being used to develop hydrologic simulations of California's Central Valley (C2VSIM); the west side of California's San Joaquin Valley (WESTSIM); Butte County, CA; Solano County, CA; Merced County, CA; and the Oregon side of the Walla Walla River Basin.

Simulating the Effects of Drainage and Agriculture on Hydrology and Sediment in the Minnesota River Basin

NASA Astrophysics Data System (ADS)

Downer, C. W.; Pradhan, N. R.; Skahill, B. E.; Banitt, A. M.; Eggers, G.; Pickett, R. E.

2014-12-01

Throughout the Midwest region of the United States, slopes are relatively flat, soils tend to have low permeability, and local water tables are high. In order to make the region suitable for agriculture, farmers have installed extensive networks of ditches to drain off excess surface water and subsurface tiles to lower the water table and remove excess soil water in the root zone that can stress common row crops, such as corn and soybeans. The combination of tiles, ditches, and intensive agricultural land practices radically alters the landscape and hydrology. Within the watershed, tiles have outlets to both the ditch/stream network as well as overland locations, where the tile discharge appears to initiate gullies and exacerbate overland erosion. As part of the Minnesota River Basin Integrated Study we are explicitly simulating the tile and drainage systems in the watershed at multiple scales using the physics-based watershed model GSSHA (Gridded Surface Subsurface Hydrologic Analysis). The tile drainage system is simulated as a network of pipes that collect water from the local water table. Within the watershed, testing of the methods on smaller basins shows the ability of the model to simulate tile flow, however, application at the larger scale is hampered by the computational burden of simulating the flow in the complex tile drain networks that drain the agricultural fields. Modeling indicates the subsurface drains account for approximately 40% of the stream flow in the Seven Mile Creek sub-basin account in the late spring and early summer when the tile is flowing. Preliminary results indicate that agricultural tile drains increase overland erosion in the Seven Mile Creek watershed.

Characterization and classification of invertebrates as indicators of flow permanence in headwater streams

EPA Science Inventory

Headwater streams represent a large proportion of river networks and many have temporary flow. Litigation has questioned whether these streams are jurisdictional under the Clean Water Act. Our goal was to identify indicators of flow permanence by comparing invertebrate assemblage...

Watershed-based survey designs

USGS Publications Warehouse

Detenbeck, N.E.; Cincotta, D.; Denver, J.M.; Greenlee, S.K.; Olsen, A.R.; Pitchford, A.M.

2005-01-01

Watershed-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification of impaired water bodies or watersheds to meet Section 303(d), and development of empirical relationships between causes or sources of impairment and biological responses. Creation of GIS databases for hydrography, hydrologically corrected digital elevation models, and hydrologic derivatives such as watershed boundaries and upstream–downstream topology of subcatchments would provide a consistent seamless nationwide framework for these designs. The elements of a watershed-based sample framework can be represented either as a continuous infinite set defined by points along a linear stream network, or as a discrete set of watershed polygons. Watershed-based designs can be developed with existing probabilistic survey methods, including the use of unequal probability weighting, stratification, and two-stage frames for sampling. Case studies for monitoring of Atlantic Coastal Plain streams, West Virginia wadeable streams, and coastal Oregon streams illustrate three different approaches for selecting sites for watershed-based survey designs.

Effect of Culverts on Predator-Prey Interactions in a Tropical Stream.

NASA Astrophysics Data System (ADS)

Hein, C. L.; Kikkert, D. A.; Crowl, T. A.

2005-05-01

As part of a biocomplexity project in Puerto Rico, we use river and road networks as a platform to understand the interactions between stream biota, the physical environment, and human activity. Specifically, we ask if humans affect aquatic organisms through road building and recreational activities. Culverts have been documented to impede or slow migration of aquatic biota. This is especially important in these streams because all of the freshwater, stream species have diadramous life cycles. If culverts do act as bottlenecks to shrimp migrations, we expect altered predator-prey interactions downstream through density-dependent predation dynamics. In order to determine how roads may affect predation rates on upstream migrating shrimp, we parameterized functional response curves for mountain mullet (Agonostomus monticola) consuming shrimp (Xiphocaris sp.) using artificial mesocosm experiments. We then used data obtained from underwater videography to determine how culverts decrease the rate and number of shrimp moving upstream. These data were combined in a predator-prey model to quantify the effects of culverts on localized shrimp densities and fish predation.

Method and apparatus for distributed intrusion protection system for ultra high bandwidth networks

DOEpatents

Goranson, Craig A.; Burnette, John R.; Greitzer, Frank L.; McMillan, Bryan H.

2013-10-15

A method for providing security to a network having a data stream with a plurality of portions of data, each having differing levels of sensitivity. The data stream is interrogated to determine the presence of predetermined characteristics associated with at least one of the portions of data within the data stream. At least one of the portions of data is then characterized, based upon the portion of data exhibiting a predetermined combination of characteristics, wherein the predetermined combination of characteristics is related to the sensitivity of the portion of data. The portions of the data stream are then distributed into a plurality of different channels, each of the channels associated with different level of sensitivity.

Learning a Continuous-Time Streaming Video QoE Model.

PubMed

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

WEPP FuME Analysis for a North Idaho Site

Treesearch

William Elliot; Ina Sue Miller; David Hall

2007-01-01

A computer interface has been developed to assist with analyzing soil erosion rates associated with fuel management activities. This interface uses the Water Erosion Prediction Project (WEPP) model to predict sediment yields from hillslopes and road segments to the stream network. The simple interface has a large database of climates, vegetation files and forest soil...

Stream denitrification across biomes and its response to anthropogenic nitrate loading

USGS Publications Warehouse

Mulholland, P.J.; Helton, A.M.; Poole, G.C.; Hall, R.O.; Hamilton, S.K.; Peterson, B.J.; Tank, J.L.; Ashkenas, L.R.; Cooper, L.W.; Dahm, Clifford N.; Dodds, W.K.; Findlay, S.E.G.; Gregory, S.V.; Grimm, N. B.; Johnson, S.L.; McDowell, W.H.; Meyer, J.L.; Valett, H.M.; Webster, J.R.; Arango, C.P.; Beaulieu, J.J.; Bernot, M.J.; Burgin, A.J.; Crenshaw, C.L.; Johnson, L.T.; Niederlehner, B.R.; O'Brien, J. M.; Potter, J.D.; Sheibley, R.W.; Sobota, D.J.; Thomas, S.M.

2008-01-01

Anthropogenic addition of bioavailable nitrogen to the biosphere is increasing and terrestrial ecosystems are becoming increasingly nitrogen-saturated, causing more bioavailable nitrogen to enter groundwater and surface waters. Large-scale nitrogen budgets show that an average of about 20-25 per cent of the nitrogen added to the biosphere is exported from rivers to the ocean or inland basins, indicating that substantial sinks for nitrogen must exist in the landscape. Streams and rivers may themselves be important sinks for bioavailable nitrogen owing to their hydrological connections with terrestrial systems, high rates of biological activity, and streambed sediment environments that favour microbial denitrification. Here we present data from nitrogen stable isotope tracer experiments across 72 streams and 8 regions representing several biomes. We show that total biotic uptake and denitrification of nitrate increase with stream nitrate concentration, but that the efficiency of biotic uptake and denitrification declines as concentration increases, reducing the proportion of in-stream nitrate that is removed from transport. Our data suggest that the total uptake of nitrate is related to ecosystem photosynthesis and that denitrification is related to ecosystem respiration. In addition, we use a stream network model to demonstrate that excess nitrate in streams elicits a disproportionate increase in the fraction of nitrate that is exported to receiving waters and reduces the relative role of small versus large streams as nitrate sinks. ??2008 Nature Publishing Group.

A stream-gaging network analysis for the 7-day, 10-year annual low flow in New Hampshire streams

USGS Publications Warehouse

Flynn, Robert H.

2003-01-01

The 7-day, 10-year (7Q10) low-flow-frequency statistic is a widely used measure of surface-water availability in New Hampshire. Regression equations and basin-characteristic digital data sets were developed to help water-resource managers determine surface-water resources during periods of low flow in New Hampshire streams. These regression equations and data sets were developed to estimate streamflow statistics for the annual and seasonal low-flow-frequency, and period-of-record and seasonal period-of-record flow durations. generalized-least-squares (GLS) regression methods were used to develop the annual 7Q10 low-flow-frequency regression equation from 60 continuous-record stream-gaging stations in New Hampshire and in neighboring States. In the regression equation, the dependent variables were the annual 7Q10 flows at the 60 stream-gaging stations. The independent (or predictor) variables were objectively selected characteristics of the drainage basins that contribute flow to those stations. In contrast to ordinary-least-squares (OLS) regression analysis, GLS-developed estimating equations account for differences in length of record and spatial correlations among the flow-frequency statistics at the various stations.A total of 93 measurable drainage-basin characteristics were candidate independent variables. On the basis of several statistical parameters that were used to evaluate which combination of basin characteristics contribute the most to the predictive power of the equations, three drainage-basin characteristics were determined to be statistically significant predictors of the annual 7Q10: (1) total drainage area, (2) mean summer stream-gaging station precipitation from 1961 to 90, and (3) average mean annual basinwide temperature from 1961 to 1990.To evaluate the effectiveness of the stream-gaging network in providing regional streamflow data for the annual 7Q10, the computer program GLSNET (generalized-least-squares NETwork) was used to analyze the network by application of GLS regression between streamflow and the climatic and basin characteristics of the drainage basin upstream from each stream-gaging station. Improvement to the predictive ability of the regression equations developed for the network analyses is measured by the reduction in the average sampling-error variance, and can be achieved by collecting additional streamflow data at existing stations. The predictive ability of the regression equations is enhanced even further with the addition of new stations to the network. Continued data collection at unregulated stream-gaging stations with less than 14 years of record resulted in the greatest cost-weighted reduction to the average sampling-error variance of the annual 7Q10 regional regression equation. The addition of new stations in basins with underrepresented values for the independent variables of the total drainage area, average mean annual basinwide temperature, or mean summer stream-gaging station precipitation in the annual 7Q10 regression equation yielded a much greater cost-weighted reduction to the average sampling-error variance than when more data were collected at existing unregulated stations. To maximize the regional information obtained from the stream-gaging network for the annual 7Q10, ranking of the streamflow data can be used to determine whether an active station should be continued or if a new or discontinued station should be activated for streamflow data collection. Thus, this network analysis can help determine the costs and benefits of continuing the operation of a particular station or activating a new station at another location to predict the 7Q10 at ungaged stream reaches. The decision to discontinue an existing station or activate a new station, however, must also consider its contribution to other water-resource analyses such as flood management, water quality, or trends in land use or climatic change.

Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

USGS Publications Warehouse

Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

2011-01-01

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Interaction between dorsal and ventral processing streams: where, when and how?

PubMed

Cloutman, Lauren L

2013-11-01

The execution of complex visual, auditory, and linguistic behaviors requires a dynamic interplay between spatial ('where/how') and non-spatial ('what') information processed along the dorsal and ventral processing streams. However, while it is acknowledged that there must be some degree of interaction between the two processing networks, how they interact, both anatomically and functionally, is a question which remains little explored. The current review examines the anatomical, temporal, and behavioral evidence regarding three potential models of dual stream interaction: (1) computations along the two pathways proceed independently and in parallel, reintegrating within shared target brain regions; (2) processing along the separate pathways is modulated by the existence of recurrent feedback loops; and (3) information is transferred directly between the two pathways at multiple stages and locations along their trajectories. Copyright © 2012 Elsevier Inc. All rights reserved.

Estimating westslope cutthroat trout (Oncorhynchus clarkii lewisi) movements in a river network using strontium isoscapes

USGS Publications Warehouse

Muhlfeld, Clint C.; Simon R. Thorrold,; Thomas E. McMahon,; Marotz, Brian

2012-01-01

We used natural variation in the strontium concentration (Sr:Ca) and isotope composition (87Sr:86Sr) of stream waters and corresponding values recorded in otoliths of westslope cutthroat trout (Oncorhynchus clarkii lewisi) to examine movements during their life history in a large river network. We found significant spatial differences in Sr:Ca and 87Sr:86Sr values (strontium isoscapes) within and among numerous spawning and rearing streams that remained relatively constant seasonally. Both Sr:Ca and 87Sr:86Sr values in the otoliths of juveniles collected from nine natal streams were highly correlated with those values in the ambient water. Strontium isoscapes measured along the axis of otolith growth revealed that almost half of the juveniles had moved at least some distance from their natal streams. Finally, otolith Sr profiles from three spawning adults confirmed homing to natal streams and use of nonoverlapping habitats over their migratory lifetimes. Our study demonstrates that otolith geochemistry records movements of cutthroat trout through Sr isoscapes and therefore provides a method that complements and extends the utility of conventional tagging techniques in understanding life history strategies and conservation needs of freshwater fishes in river networks.

Potential interaction between transport and stream networks over the lowland rivers in Eastern India.

PubMed

Roy, Suvendu; Sahu, Abhay Sankar

2017-07-15

Extension of transport networks supports good accessibility and associated with the development of a region. However, transport lines have fragmented the regional landscape and disturbed the natural interplay between rivers and their floodplains. Spatial analysis using multiple buffers provides information about the potential interaction between road and stream networks and their impact on channel morphology of a small watershed in the Lower Gangetic Plain. Present study is tried to understand the lateral and longitudinal disconnection in headwater stream by rural roads with the integration of geoinformatics and field survey. Significant (p < 0.001) growth of total road length and number of road-stream crossing in the last five decades (1970s-2010s) contribute to making longitudinal and lateral disconnection in the fluvial system of Kunur River Basin. Channel geometry from ten road-stream crossings shows significant (p = 0.01) differences between upstream and downstream of crossing structure and created problems like downstream scouring, increased drop height at outlet, formation of stable bars, severe bank erosion, and make barriers for river biota. The hydro-geomorphic processes are also adversely affected due to lateral disconnection and input of fine to coarse sediments from the river side growth of unpaved road (1922%). Limited streamside development, delineation of stream corridor, regular monitoring and engineering efficiency for the construction of road and road-stream crossing might be effective in managing river geomorphology and riverine landscape. Copyright © 2017 Elsevier Ltd. All rights reserved.

The role of headwater streams in downstream water quality

USGS Publications Warehouse

Alexander, R.B.; Boyer, E.W.; Smith, R.A.; Schwarz, G.E.; Moore, R.B.

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters. ?? 2007 American Water Resources Association.

The Role of Headwater Streams in Downstream Water Quality1

PubMed Central

Alexander, Richard B; Boyer, Elizabeth W; Smith, Richard A; Schwarz, Gregory E; Moore, Richard B

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters. PMID:22457565

Putting newborn hearing screening on the political agenda in Belgium: local initiatives toward a community programme – a qualitative study

PubMed Central

2014-01-01

Background The Kingdon model, based on the convergence of three streams (problem, policy, and politics) and the opening of a policy window, analyses the process by which a health issue is placed on the political agenda. We used this model to document the political agenda-setting process of the newborn hearing screening programme in Belgium. Methods A qualitative study based on a document review and on semi-directed interviews was carried out. The interviews were conducted with nine people who had played a role in putting the issue in question on the political agenda, and the documents reviewed included scientific literature and internal reports and publications from the newborn hearing screening programme. The thematic analysis of the data collected was carried out on the basis of the Kingdon model’s three streams. Results The political agenda-setting of this screening programme was based on many factors. The problem stream included factors external to the context under study, such as the technological developments and the contribution of the scientific literature which led to the recommendation to provide newborn hearing screening. The two other streams (policy and politics) covered factors internal to the Belgian context. The fact that it was locally feasible with financial support, the network of doctors convinced of the need for newborn hearing screening, the drafting of various proposals, and the search for financing were all part of the policy stream. The Belgian political context and the policy opportunities concerning preventive medicine were identified as significant factors in the third stream. When these three streams converged, a policy window opened, allowing newborn hearing screening onto the political agenda and enabling the policy decision for its introduction. Conclusions The advantage of applying the Kingdon model in our approach was the ability to demonstrate the political agenda-setting process, using the three streams. This made it possible to identify the many factors involved in the process. However, the roles of the stakeholders and of the context were somewhat inexplicit in this model. PMID:24986647

Network Characteristics of Video Streaming Traffic

DTIC Science & Technology

2011-11-01

Silverlight, Flash, or HTML5 ) used for video streaming. In particular, we identify three different streaming strategies that produce traffic... HTML5 , Flash. 1. INTRODUCTION The popularity of video streaming has considerably increased in the last decade. Indeed, recent studies have shown...applications for mobile devices), and the container (Flash [10], HTML5 [18], Silverlight [4]), on the charac- teristics of the traffic between the

Where Does Wood Most Effectively Enhance Storage? Network-Scale Distribution of Sediment and Organic Matter Stored by Instream Wood

NASA Astrophysics Data System (ADS)

Pfeiffer, Andrew; Wohl, Ellen

2018-01-01

We used 48 reach-scale measurements of large wood and wood-associated sediment and coarse particulate organic matter (CPOM) storage within an 80 km2 catchment to examine spatial patterns of storage relative to stream order. Wood, sediment, and CPOM are not distributed uniformly across the drainage basin. Third- and fourth-order streams (23% of total stream length) disproportionately store wood and coarse and fine sediments: 55% of total wood volume, 78% of coarse sediment, and 49% of fine sediment, respectively. Fourth-order streams store 0.8 m3 of coarse sediment and 0.2 m3 of fine sediment per cubic meter of wood. CPOM storage is highest in first-order streams (60% of storage in 47% of total network stream length). First-order streams can store up to 0.3 m3 of CPOM for each cubic meter of wood. Logjams in third- and fourth-order reaches are primary sediment storage agents, whereas roots in small streams may be more important for storage of CPOM. We propose the large wood particulate storage index to quantify average volume of sediment or CPOM stored by a cubic meter of wood.

Streaming data analytics via message passing with application to graph algorithms

DOE PAGES

Plimpton, Steven J.; Shead, Tim

2014-05-06

The need to process streaming data, which arrives continuously at high-volume in real-time, arises in a variety of contexts including data produced by experiments, collections of environmental or network sensors, and running simulations. Streaming data can also be formulated as queries or transactions which operate on a large dynamic data store, e.g. a distributed database. We describe a lightweight, portable framework named PHISH which enables a set of independent processes to compute on a stream of data in a distributed-memory parallel manner. Datums are routed between processes in patterns defined by the application. PHISH can run on top of eithermore » message-passing via MPI or sockets via ZMQ. The former means streaming computations can be run on any parallel machine which supports MPI; the latter allows them to run on a heterogeneous, geographically dispersed network of machines. We illustrate how PHISH can support streaming MapReduce operations, and describe streaming versions of three algorithms for large, sparse graph analytics: triangle enumeration, subgraph isomorphism matching, and connected component finding. Lastly, we also provide benchmark timings for MPI versus socket performance of several kernel operations useful in streaming algorithms.« less

Review of amateur meteor research

NASA Astrophysics Data System (ADS)

Rendtel, Jürgen

2017-09-01

Significant amounts of meteor astronomical data are provided by amateurs worldwide, using various methods. This review concentrates on optical data. Long-term meteor shower analyses based on consistent data are possible over decades (Orionids, Geminids, κ-Cygnids) and allow combination with modelling results. Small and weak structures related to individual stream filaments of cometary dust have been analysed in both major and minor showers (Quadrantids, September ε-Perseids), providing feedback to meteoroid ejection and stream evolution processes. Meteoroid orbit determination from video meteor networks contributes to the improvement of the IAU meteor data base. Professional-amateur cooperation also concerns observations and detailed analysis of fireball data, including meteorite ground searches.

Neural network retuning and neural predictors of learning success associated with cello training.

PubMed

Wollman, Indiana; Penhune, Virginia; Segado, Melanie; Carpentier, Thibaut; Zatorre, Robert J

2018-06-26

The auditory and motor neural systems are closely intertwined, enabling people to carry out tasks such as playing a musical instrument whose mapping between action and sound is extremely sophisticated. While the dorsal auditory stream has been shown to mediate these audio-motor transformations, little is known about how such mapping emerges with training. Here, we use longitudinal training on a cello as a model for brain plasticity during the acquisition of specific complex skills, including continuous and many-to-one audio-motor mapping, and we investigate individual differences in learning. We trained participants with no musical background to play on a specially designed MRI-compatible cello and scanned them before and after 1 and 4 wk of training. Activation of the auditory-to-motor dorsal cortical stream emerged rapidly during the training and was similarly activated during passive listening and cello performance of trained melodies. This network activation was independent of performance accuracy and therefore appears to be a prerequisite of music playing. In contrast, greater recruitment of regions involved in auditory encoding and motor control over the training was related to better musical proficiency. Additionally, pre-supplementary motor area activity and its connectivity with the auditory cortex during passive listening before training was predictive of final training success, revealing the integrative function of this network in auditory-motor information processing. Together, these results clarify the critical role of the dorsal stream and its interaction with auditory areas in complex audio-motor learning.

Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams

USGS Publications Warehouse

Azamathulla, H. Md.; Jarrett, Robert D.

2013-01-01

Manning’s roughness coefficient (n) has been widely used in the estimation of flood discharges or depths of flow in natural channels. Therefore, the selection of appropriate Manning’s nvalues is of paramount importance for hydraulic engineers and hydrologists and requires considerable experience, although extensive guidelines are available. Generally, the largest source of error in post-flood estimates (termed indirect measurements) is due to estimates of Manning’s n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for estimating n values. The objective of this study was to develop a soft computing model in the estimation of the Manning’s n values using 75 discharge measurements on 21 high gradient streams in Colorado, USA. The data are from high gradient (S > 0.002 m/m), cobble- and boulder-bed streams for within bank flows. This study presents Gene-Expression Programming (GEP), an extension of Genetic Programming (GP), as an improved approach to estimate Manning’s roughness coefficient for high gradient streams. This study uses field data and assessed the potential of gene-expression programming (GEP) to estimate Manning’s n values. GEP is a search technique that automatically simplifies genetic programs during an evolutionary processes (or evolves) to obtain the most robust computer program (e.g., simplify mathematical expressions, decision trees, polynomial constructs, and logical expressions). Field measurements collected by Jarrett (J Hydraulic Eng ASCE 110: 1519–1539, 1984) were used to train the GEP network and evolve programs. The developed network and evolved programs were validated by using observations that were not involved in training. GEP and ANN-RBF (artificial neural network-radial basis function) models were found to be substantially more effective (e.g., R2 for testing/validation of GEP and RBF-ANN is 0.745 and 0.65, respectively) than Jarrett’s (J Hydraulic Eng ASCE 110: 1519–1539, 1984) equation (R2 for testing/validation equals 0.58) in predicting the Manning’s n.

Digital hydrologic networks supporting applications related to spatially referenced regression modeling

USGS Publications Warehouse

Brakebill, John W.; Wolock, David M.; Terziotti, Silvia

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based ⁄ statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

Evaluation of a landscape evolution model to simulate stream piracies: Insights from multivariable numerical tests using the example of the Meuse basin, France

NASA Astrophysics Data System (ADS)

Benaïchouche, Abed; Stab, Olivier; Tessier, Bruno; Cojan, Isabelle

2016-01-01

In landscapes dominated by fluvial erosion, the landscape morphology is closely related to the hydrographic network system. In this paper, we investigate the hydrographic network reorganization caused by a headward piracy mechanism between two drainage basins in France, the Meuse and the Moselle. Several piracies occurred in the Meuse basin during the past one million years, and the basin's current characteristics are favorable to new piracies by the Moselle river network. This study evaluates the consequences over the next several million years of a relative lowering of the Moselle River (and thus of its basin) with respect to the Meuse River. The problem is addressed with a numerical modeling approach (landscape evolution model, hereafter LEM) that requires empirical determinations of parameters and threshold values. Classically, fitting of the parameters is based on analysis of the relationship between the slope and the drainage area and is conducted under the hypothesis of equilibrium. Application of this conventional approach to the capture issue yields incomplete results that have been consolidated by a parametric sensitivity analysis. The LEM equations give a six-dimensional parameter space that was explored with over 15,000 simulations using the landscape evolution model GOLEM. The results demonstrate that stream piracies occur in only four locations in the studied reach near the city of Toul. The locations are mainly controlled by the local topography and are model-independent. Nevertheless, the chronology of the captures depends on two parameters: the river concavity (given by the fluvial advection equation) and the hillslope erosion factor. Thus, the simulations lead to three different scenarios that are explained by a phenomenon of exclusion or a string of events.

Mobile Transactional Modelling: From Concepts to Incremental Knowledge

NASA Astrophysics Data System (ADS)

Launders, Ivan; Polovina, Simon; Hill, Richard

In 1988, Robert T. Morris exploited a so-called buffer-overflow bug in finger (a dæmon whose job it is to return information on local users) to mount a denial-of-service attack on hundreds of VAX and Sun-3 computers [159]. He created what is nowadays called a worm; that is, a crafted stream of bytes that, when sent to a computer over the network, utilises a buffer-overflow bug in the software of that computer to execute code encoded in the byte stream. In the case of a worm, this code will send the very same byte stream to other computers on the network, thereby creating an avalanche of network traffic that ultimately renders the network and all computers involved in replicating the worm inaccessible. Besides duplicating themselves, worms can alter data on the host that they are running on. The most famous example in recent years was the MSBlaster32 worm, which altered the configuration database on many Microsoft Windows machines, thereby forcing the computers to reboot incessantly. Although this worm was rather benign, it caused huge damage to businesses who were unable to use their IT infrastructure for hours or even days after the appearance of the worm. A more malicious worm is certainly conceivable [187] due to the fact that worms are executed as part of a dæmon (also known as "service" on Windows machines) and thereby run at a privileged level, allowing access to any data stored on the remote computer. While the deletion of data presents a looming threat to valuable information, even more serious uses are espionage and theft, in particular because worms do not have to affect the running system and hence may be impossible to detect.

Solute transport in streams of varying morphology inferred from a high resolution network of potentiometric wireless chloride sensors

NASA Astrophysics Data System (ADS)

Klaus, Julian; Smettem, Keith; Pfister, Laurent; Harris, Nick

2017-04-01

There is ongoing interest in understanding and quantifying the travel times and dispersion of solutes moving through stream environments, including the hyporheic zone and/or in-channel dead zones where retention affects biogeochemical cycling processes that are critical to stream ecosystem functioning. Modelling these transport and retention processes requires acquisition of tracer data from injection experiments where the concentrations are recorded downstream. Such experiments are often time consuming and costly, which may be the reason many modelling studies of chemical transport have tended to rely on relatively few well documented field case studies. This leads to the need of fast and cheap distributed sensor arrays that respond instantly and record chemical transport at points of interest on timescales of seconds at various locations in the stream environment. To tackle this challenge we present data from several tracer experiments carried out in the Attert river catchment in Luxembourg employing low-cost (in the order of a euro per sensor) potentiometric chloride sensors in a distributed array. We injected NaCl under various baseflow conditions in streams of different morphologies and observed solute transport at various distances and locations. This data is used to benchmark the sensors to data obtained from more expensive electrical conductivity meters. Furthermore, the data allowed spatial resolution of hydrodynamic mixing processes and identification of chemical 'dead zones' in the study reaches.

Stream ecosystem response to limestone treatment in acid impacted watersheds of the allegheny plateau

USGS Publications Warehouse

McClurg, S.E.; Petty, J.T.; Mazik, P.M.; Clayton, J.L.

2007-01-01

Restoration programs are expanding worldwide, but assessments of restoration effectiveness are rare. The objectives of our study were to assess current acid-precipitation remediation programs in streams of the Allegheny Plateau ecoregion of West Virginia (USA), identify specific attributes that could and could not be fully restored, and quantify temporal trends in ecosystem recovery. We sampled water chemistry, physical habitat, periphyton biomass, and benthic macroinvertebrate and fish community structure in three stream types: acidic (four streams), naturally circumneutral (eight streams), and acidic streams treated with limestone sand (eight streams). We observed no temporal trends in ecosystem recovery in treated streams despite sampling streams that ranged from 2 to 20 years since initial treatment. Our results indicated that the application of limestone sand to acidic streams was effective in fully recovering some characteristics, such as pH, alkalinity, Ca2+, Ca:H ratios, trout biomass and density, and trout reproductive success. However, recovery of many other characteristics was strongly dependent upon spatial proximity to treatment, and still others were never fully recovered. For example, limestone treatment did not restore dissolved aluminum concentrations, macroinvertebrate taxon richness, and total fish biomass to circumneutral reference conditions. Full recovery may not be occurring because treated streams continue to drain acidic watersheds and remain isolated in a network of acidic streams. We propose a revised stream restoration plan for the Allegheny Plateau that includes restoring stream ecosystems as connected networks rather than isolated reaches and recognizes that full recovery of acidified watersheds may not be possible. ?? 2007 by the Ecological Society of America.

Interpolation of Water Quality Along Stream Networks from Synoptic Data

NASA Astrophysics Data System (ADS)

Lyon, S. W.; Seibert, J.; Lembo, A. J.; Walter, M. T.; Gburek, W. J.; Thongs, D.; Schneiderman, E.; Steenhuis, T. S.

2005-12-01

Effective catchment management requires water quality monitoring that identifies major pollutant sources and transport and transformation processes. While traditional monitoring schemes involve regular sampling at fixed locations in the stream, there is an interest synoptic or `snapshot' sampling to quantify water quality throughout a catchment. This type of sampling enables insights to biogeochemical behavior throughout a stream network at low flow conditions. Since baseflow concentrations are temporally persistence, they are indicative of the health of the ecosystems. A major problem with snapshot sampling is the lack of analytical techniques to represent the spatially distributed data in a manner that is 1) easily understood, 2) representative of the stream network, and 3) capable of being used to develop land management scenarios. This study presents a kriging application using the landscape composition of the contributing area along a stream network to define a new distance metric. This allows for locations that are more `similar' to stay spatially close together while less similar locations `move' further apart. We analyze a snapshot sampling campaign consisting of 125 manually collected grab samples during a summer recession flow period in the Townbrook Research Watershed. The watershed is located in the Catskill region of New York State and represents the mixed forest-agriculture land uses of the region. Our initial analysis indicated that stream nutrients (nitrogen and phosphorus) and chemical (major cations and anions) concentrations are controlled by the composition of landscape characteristics (landuse classes and soil types) surrounding the stream. Based on these relationships, an intuitively defined distance metric is developed by combining the traditional distance between observations and the relative difference in composition of contributing area. This metric is used to interpolate between the sampling locations with traditional geostatistic techniques (semivariograms and ordinary kriging). The resulting interpolations provide continuous stream nutrient and chemical concentrations with reduced kriging RMSE (i.e., the interpolation fits the actual data better) performed without path restriction to the stream channel (i.e., the current default for most geostatistical packages) or performed with an in-channel, Euclidean distance metric (i.e., `as the fish swims' distance). In addition to being quantifiably better, the new metric also produces maps of stream concentrations that match expected continuous stream concentrations based on expert knowledge of the watershed. This analysis and its resulting stream concentration maps provide a representation of spatially distributed synoptic data that can be used to quantify water quality for more effective catchment management that focuses on pollutant sources and transport and transformation processes.

Evaluation of stream chemistry trends in US Geological Survey reference watersheds, 1970-2010.

PubMed

Mast, M Alisa

2013-11-01

The Hydrologic Benchmark Network (HBN) is a long-term monitoring program established by the US Geological Survey in the 1960s to track changes in the streamflow and stream chemistry in undeveloped watersheds across the USA. Trends in stream chemistry were tested at 15 HBN stations over two periods (1970-2010 and 1990-2010) using the parametric Load Estimator (LOADEST) model and the nonparametric seasonal Kendall test. Trends in annual streamflow and precipitation chemistry also were tested to help identify likely drivers of changes in stream chemistry. At stations in the northeastern USA, there were significant declines in stream sulfate, which were consistent with declines in sulfate deposition resulting from the reductions in SO₂ emissions mandated under the Clean Air Act Amendments. Sulfate declines in stream water were smaller than declines in deposition suggesting sulfate may be accumulating in watershed soils and thereby delaying the stream response to improvements in deposition. Trends in stream chemistry at stations in other part of the country generally were attributed to climate variability or land disturbance. Despite declines in sulfate deposition, increasing stream sulfate was observed at several stations and appeared to be linked to periods of drought or declining streamflow. Falling water tables might have enhanced oxidation of organic matter in wetlands or pyrite in mineralized bedrock thereby increasing sulfate export in surface water. Increasing sulfate and nitrate at a station in the western USA were attributed to release of soluble salts and nutrients from soils following a large wildfire in the watershed.

Urban infrastructure influences dissolved organic matter quality and bacterial metabolism in an urban stream network

EPA Science Inventory

Urban streams are degraded by a suite of factors, including burial beneath urban infrastructure (i.e., roads, parking lots) that eliminates light and reduces direct organic matter inputs to streams, with likely consequences for organic matter metabolism by microbes and carbon lim...

LAND USE AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL AND TEMPORAL ASSESSMENT

EPA Science Inventory

We assessed the effects of land-use at multiple spatial scales (e.g., catchment, stream network, and stream reach) on periphyton from 25 wadeable streams along a land-use gradient in the Willamette River Basin, Oregon, in a dry season. Additional water chemistry samples were col...

Multi-scale streambed topographic and discharge effects on hyporheic at the stream network scale in confined streams

Treesearch

Alessandra Marzadri; Daniele Tonina; James A. McKean; Matthew G. Tiedemann; Rohan M. Benjankar

2014-01-01

The hyporheic zone is the volume of the streambed sediment mostly saturated with stream water. It is the transitional zone between stream and shallow-ground waters and an important ecotone for benthic species, including macro-invertebrates, microorganisms, and some fish species that dwell in the hyporheic zone for parts of their lives. Most hyporheic analyses are...

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

The simultaneous evolution of author and paper networks

PubMed Central

Börner, Katy; Maru, Jeegar T.; Goldstone, Robert L.

2004-01-01

There has been a long history of research into the structure and evolution of mankind's scientific endeavor. However, recent progress in applying the tools of science to understand science itself has been unprecedented because only recently has there been access to high-volume and high-quality data sets of scientific output (e.g., publications, patents, grants) and computers and algorithms capable of handling this enormous stream of data. This article reviews major work on models that aim to capture and recreate the structure and dynamics of scientific evolution. We then introduce a general process model that simultaneously grows coauthor and paper citation networks. The statistical and dynamic properties of the networks generated by this model are validated against a 20-year data set of articles published in PNAS. Systematic deviations from a power law distribution of citations to papers are well fit by a model that incorporates a partitioning of authors and papers into topics, a bias for authors to cite recent papers, and a tendency for authors to cite papers cited by papers that they have read. In this TARL model (for topics, aging, and recursive linking), the number of topics is linearly related to the clustering coefficient of the simulated paper citation network. PMID:14976254

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

NASA Astrophysics Data System (ADS)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

Variable weight spectral amplitude coding for multiservice OCDMA networks

NASA Astrophysics Data System (ADS)

Seyedzadeh, Saleh; Rahimian, Farzad Pour; Glesk, Ivan; Kakaee, Majid H.

2017-09-01

The emergence of heterogeneous data traffic such as voice over IP, video streaming and online gaming have demanded networks with capability of supporting quality of service (QoS) at the physical layer with traffic prioritisation. This paper proposes a new variable-weight code based on spectral amplitude coding for optical code-division multiple-access (OCDMA) networks to support QoS differentiation. The proposed variable-weight multi-service (VW-MS) code relies on basic matrix construction. A mathematical model is developed for performance evaluation of VW-MS OCDMA networks. It is shown that the proposed code provides an optimal code length with minimum cross-correlation value when compared to other codes. Numerical results for a VW-MS OCDMA network designed for triple-play services operating at 0.622 Gb/s, 1.25 Gb/s and 2.5 Gb/s are considered.

Occurrence of maize detritus and a transgenic insecticidal protein (Cry1Ab) within the stream network of an agricultural landscape

PubMed Central

Tank, Jennifer L.; Rosi-Marshall, Emma J.; Royer, Todd V.; Whiles, Matt R.; Griffiths, Natalie A.; Frauendorf, Therese C.; Treering, David J.

2010-01-01

Widespread planting of maize throughout the agricultural Midwest may result in detritus entering adjacent stream ecosystems, and 63% of the 2009 US maize crop was genetically modified to express insecticidal Cry proteins derived from Bacillus thuringiensis. Six months after harvest, we conducted a synoptic survey of 217 stream sites in Indiana to determine the extent of maize detritus and presence of Cry1Ab protein in the stream network. We found that 86% of stream sites contained maize leaves, cobs, husks, and/or stalks in the active stream channel. We also detected Cry1Ab protein in stream-channel maize at 13% of sites and in the water column at 23% of sites. We found that 82% of stream sites were adjacent to maize fields, and Geographical Information Systems analyses indicated that 100% of sites containing Cry1Ab-positive detritus in the active stream channel had maize planted within 500 m during the previous crop year. Maize detritus likely enters streams throughout the Corn Belt; using US Department of Agriculture land cover data, we estimate that 91% of the 256,446 km of streams/rivers in Iowa, Illinois, and Indiana are located within 500 m of a maize field. Maize detritus is common in low-gradient stream channels in northwestern Indiana, and Cry1Ab proteins persist in maize leaves and can be measured in the water column even 6 mo after harvest. Hence, maize detritus, and associated Cry1Ab proteins, are widely distributed and persistent in the headwater streams of a Corn Belt landscape. PMID:20876106

Occurrence of maize detritus and a transgenic insecticidal protein (Cry1Ab) within the stream network of an agricultural landscape.

PubMed

Tank, Jennifer L; Rosi-Marshall, Emma J; Royer, Todd V; Whiles, Matt R; Griffiths, Natalie A; Frauendorf, Therese C; Treering, David J

2010-10-12

Widespread planting of maize throughout the agricultural Midwest may result in detritus entering adjacent stream ecosystems, and 63% of the 2009 US maize crop was genetically modified to express insecticidal Cry proteins derived from Bacillus thuringiensis. Six months after harvest, we conducted a synoptic survey of 217 stream sites in Indiana to determine the extent of maize detritus and presence of Cry1Ab protein in the stream network. We found that 86% of stream sites contained maize leaves, cobs, husks, and/or stalks in the active stream channel. We also detected Cry1Ab protein in stream-channel maize at 13% of sites and in the water column at 23% of sites. We found that 82% of stream sites were adjacent to maize fields, and Geographical Information Systems analyses indicated that 100% of sites containing Cry1Ab-positive detritus in the active stream channel had maize planted within 500 m during the previous crop year. Maize detritus likely enters streams throughout the Corn Belt; using US Department of Agriculture land cover data, we estimate that 91% of the 256,446 km of streams/rivers in Iowa, Illinois, and Indiana are located within 500 m of a maize field. Maize detritus is common in low-gradient stream channels in northwestern Indiana, and Cry1Ab proteins persist in maize leaves and can be measured in the water column even 6 mo after harvest. Hence, maize detritus, and associated Cry1Ab proteins, are widely distributed and persistent in the headwater streams of a Corn Belt landscape.

Retro-Future

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferrell, Paul; Hanson, Paige; Ardi, Calvin

2016-11-04

A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.

GIS as a tool for efficient management of transport streams

NASA Astrophysics Data System (ADS)

Zatserkovnyi, V. I.; Kobrin, O. V.

2015-10-01

The transport network, which is an ideal object for the automation and the increase of efficiency using geographic information systems (GIS), is considered. The transport problems, which have a lot of mathematical models of the traffic flow for their solution, are enumerated. GIS analysis tools that allow one to build optimal routes in the real road network with its capabilities and limitations are presented. They can solve the extremely important problem of modern Ukraine - the rapid increase of the number of cars and the glut of road network vehicles. The intelligent transport systems, which are created and developed on the basis of GPS, GIS, modern communications and telecommunications facilities, are considered.

Supporting Seamless Mobility for P2P Live Streaming

PubMed Central

Kim, Eunsam; Kim, Sangjin; Lee, Choonhwa

2014-01-01

With advent of various mobile devices with powerful networking and computing capabilities, the users' demand to enjoy live video streaming services such as IPTV with mobile devices has been increasing rapidly. However, it is challenging to get over the degradation of service quality due to data loss caused by the handover. Although many handover schemes were proposed at protocol layers below the application layer, they inherently suffer from data loss while the network is being disconnected during the handover. We therefore propose an efficient application-layer handover scheme to support seamless mobility for P2P live streaming. By simulation experiments, we show that the P2P live streaming system with our proposed handover scheme can improve the playback continuity significantly compared to that without our scheme. PMID:24977171

Protection of HEVC Video Delivery in Vehicular Networks with RaptorQ Codes

PubMed Central

Martínez-Rach, Miguel; López, Otoniel; Malumbres, Manuel Pérez

2014-01-01

With future vehicles equipped with processing capability, storage, and communications, vehicular networks will become a reality. A vast number of applications will arise that will make use of this connectivity. Some of them will be based on video streaming. In this paper we focus on HEVC video coding standard streaming in vehicular networks and how it deals with packet losses with the aid of RaptorQ, a Forward Error Correction scheme. As vehicular networks are packet loss prone networks, protection mechanisms are necessary if we want to guarantee a minimum level of quality of experience to the final user. We have run simulations to evaluate which configurations fit better in this type of scenarios. PMID:25136675

Addressing Hydro-economic Modeling Limitations - A Limited Foresight Sacramento Valley Model and an Open-source Modeling Platform

NASA Astrophysics Data System (ADS)

Harou, J. J.; Hansen, K. M.

2008-12-01

Increased scarcity of world water resources is inevitable given the limited supply and increased human pressures. The idea that "some scarcity is optimal" must be accepted for rational resource use and infrastructure management decisions to be made. Hydro-economic systems models are unique at representing the overlap of economic drivers, socio-political forces and distributed water resource systems. They demonstrate the tangible benefits of cooperation and integrated flexible system management. Further improvement of models, quality control practices and software will be needed for these academic policy tools to become accepted into mainstream water resource practice. Promising features include: calibration methods, limited foresight optimization formulations, linked simulation-optimization approaches (e.g. embedding pre-existing calibrated simulation models), spatial groundwater models, stream-aquifer interactions and stream routing, etc.. Conventional user-friendly decision support systems helped spread simulation models on a massive scale. Hydro-economic models must also find a means to facilitate construction, distribution and use. Some of these issues and model features are illustrated with a hydro-economic optimization model of the Sacramento Valley. Carry-over storage value functions are used to limit hydrologic foresight of the multi- period optimization model. Pumping costs are included in the formulation by tracking regional piezometric head of groundwater sub-basins. To help build and maintain this type of network model, an open-source water management modeling software platform is described and initial project work is discussed. The objective is to generically facilitate the connection of models, such as those developed in a modeling environment (GAMS, MatLab, Octave, "), to a geographic user interface (drag and drop node-link network) and a database (topology, parameters and time series). These features aim to incrementally move hydro- economic models in the direction of more practical implementation.

Runoff generation through ephemeral streams in south-east Italy

NASA Astrophysics Data System (ADS)

Doglioni, A.; Simeone, V.; Giustolisi, O.

2012-04-01

Ephemeral streams are morphological elements, typical of karst areas, characterized by relatively large and flat bottom transects (Camarasa & Tilford, 2002). These occasionally drain runoff generated by extreme rainfall events, characterized by high return periods. The activation of these streams was investigated by several authors for the Mediterranean regions, and in particular for south Spain and north Africa (Camarasa & Segura, 2001; De Vera, 1984). However, there are few analyses for karst areas of south-east of Italy (Cotecchia, 2006; Polemio, 2010). South-east of Italy, in particular the central part of Apulia, is characterized by a karst morphology, with a moderately elevated plateau, namely Murgia, which is drained by a network of ephemeral streams. These are normally dry, relatively short-length and straights, and their main outlets are on the coast. They normally drain water after extraordinary rainfall events, which can generate very high discharges, which can potentially flood the areas close to the streams. For this reason, the definition of an activation threshold for ephemeral streams is a paramount problem, even if this constitutes a complex problem, since the dynamics of the catchment drained by these streams in highly non-linear and biased by multiple variables (e.g. urbanization, land use, etc.). The main problem affecting the analysis and prediction of flood events in karst semi-arid regions is the almost complete absence of discharge time-series, measured at the outlets of the ephemeral streams. This prevents from the identification of accurate statistics of flood events and on the determination of rainfall events, which may potentially generate floods. Indeed, floods and in general flash floods are relatively rare events for semi-arid karst regions, however they can be really severe and disruptive, causing serious damages to people and infrastructures. This work presents an analysis of the ephemeral stream activation in karst semi-arid areas, in a partially urbanized catchment located in Apulia (south east of Italy). The analysis is based on full 2D simulation of the behaviour of a network of ephemeral streams. A full 2D approach integrates the hydrological and hydraulic models, in order to account first for the dynamic of catchment response to rainfall and activation of the streams, and then for the hydraulic behaviour of the streams. This analysis entails the simulation of extreme events corresponding to low, medium and high return periods, in order to identify which event presumably activate the ephemeral streams. Camarasa, A.M. and Tilford, K.A. (2002). "Rainfall-runoff modelling of ephemeral streams in the Valencia region (eastern Spain)". Hydrological Processes, 16: 3329-3344. Camarasa Belmonte, A.M, and Segura Beltran, F. (2001). "Flood events in Mediterranean ephemeral stream (ramblas) in Valencia Region, Spain". Catena, 45: 229-249. Cotecchia, V. (2006). "Il disordine idraulico evidenziato in Bari dall'evento pluviometrico dell'Ottobre 2005 e il caso dell' ex cava di Maso". Continuità - Rassegna Tecnica Pugliese, 1-2.2006: 25-76. De Vera M. (1984). "Rainfall-Runoff relationship of some catchments with karstic geomorphology under arid to semi-arid conditions". Journal of Hydrology, 68(1-4): 85-93. Polemio, M., (2010). "Historical floods and a recent extreme rainfall event in the Murgia karstic environment (Southern Italy)". Zeitschrift für Geomorphologie, 54(2): 195-219.

Application of the Hydroecological Integrity Assessment Process for Missouri Streams

USGS Publications Warehouse

Kennen, Jonathan G.; Henriksen, James A.; Heasley, John; Cade, Brian S.; Terrell, James W.

2009-01-01

Natural flow regime concepts and theories have established the justification for maintaining or restoring the range of natural hydrologic variability so that physiochemical processes, native biodiversity, and the evolutionary potential of aquatic and riparian assemblages can be sustained. A synthesis of recent research advances in hydroecology, coupled with stream classification using hydroecologically relevant indices, has produced the Hydroecological Integrity Assessment Process (HIP). HIP consists of (1) a regional classification of streams into hydrologic stream types based on flow data from long-term gaging-station records for relatively unmodified streams, (2) an identification of stream-type specific indices that address 11 subcomponents of the flow regime, (3) an ability to establish environmental flow standards, (4) an evaluation of hydrologic alteration, and (5) a capacity to conduct alternative analyses. The process starts with the identification of a hydrologic baseline (reference condition) for selected locations, uses flow data from a stream-gage network, and proceeds to classify streams into hydrologic stream types. Concurrently, the analysis identifies a set of non-redundant and ecologically relevant hydrologic indices for 11 subcomponents of flow for each stream type. Furthermore, regional hydrologic models for synthesizing flow conditions across a region and the development of flow-ecology response relations for each stream type can be added to further enhance the process. The application of HIP to Missouri streams identified five stream types ((1) intermittent, (2) perennial runoff-flashy, (3) perennial runoff-moderate baseflow, (4) perennial groundwater-stable, and (5) perennial groundwater-super stable). Two Missouri-specific computer software programs were developed: (1) a Missouri Hydrologic Assessment Tool (MOHAT) which is used to establish a hydrologic baseline, provide options for setting environmental flow standards, and compare past and proposed hydrologic alterations; and (2) a Missouri Stream Classification Tool (MOSCT) designed for placing previously unclassified streams into one of the five pre-defined stream types.

Predicting spatial distribution of postfire debris flows and potential consequences for native trout in headwater streams

USGS Publications Warehouse

Sedell, Edwin R; Gresswell, Bob; McMahon, Thomas E.

2015-01-01

Habitat fragmentation and degradation and invasion of nonnative species have restricted the distribution of native trout. Many trout populations are limited to headwater streams where negative effects of predicted climate change, including reduced stream flow and increased risk of catastrophic fires, may further jeopardize their persistence. Headwater streams in steep terrain are especially susceptible to disturbance associated with postfire debris flows, which have led to local extirpation of trout populations in some systems. We conducted a reach-scale spatial analysis of debris-flow risk among 11 high-elevation watersheds of the Colorado Rocky Mountains occupied by isolated populations of Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus). Stream reaches at high risk of disturbance by postfire debris flow were identified with the aid of a qualitative model based on 4 primary initiating and transport factors (hillslope gradient, flow accumulation pathways, channel gradient, and valley confinement). This model was coupled with a spatially continuous survey of trout distributions in these stream networks to assess the predicted extent of trout population disturbances related to debris flows. In the study systems, debris-flow potential was highest in the lower and middle reaches of most watersheds. Colorado River Cutthroat Trout occurred in areas of high postfire debris-flow risk, but they were never restricted to those areas. Postfire debris flows could extirpate trout from local reaches in these watersheds, but trout populations occupy refugia that should allow recolonization of interconnected, downstream reaches. Specific results of our study may not be universally applicable, but our risk assessment approach can be applied to assess postfire debris-flow risk for stream reaches in other watersheds.

Engineering rules for evaluating the efficiency of multiplexing traffic streams

NASA Astrophysics Data System (ADS)

Klincewicz, John G.

2004-09-01

It is common, either for a telecommunications service provider or for a corporate enterprise, to have multiple data networks. For example, both an IP network and an ATM or Frame Relay network could be in operation to serve different applications. This can result in parallel transport links between the same two locations, each carrying data traffic under a different protocol. In this paper, we consider some practical engineering rules, for particular situations, to evaluate whether or not it is advantageous to combine these parallel traffic streams onto a single transport link. Combining the streams requires additional overhead (a so-called "cell tax" ) but, in at least some situations, can result in more efficient use of modular transport capacity. Simple graphs can be used to summarize the analysis. Some interesting, and perhaps unexpected, observations can be made.

Estimating Escherichia coli loads in streams based on various physical, chemical, and biological factors

PubMed Central

Dwivedi, Dipankar; Mohanty, Binayak P.; Lesikar, Bruce J.

2013-01-01

Microbes have been identified as a major contaminant of water resources. Escherichia coli (E. coli) is a commonly used indicator organism. It is well recognized that the fate of E. coli in surface water systems is governed by multiple physical, chemical, and biological factors. The aim of this work is to provide insight into the physical, chemical, and biological factors along with their interactions that are critical in the estimation of E. coli loads in surface streams. There are various models to predict E. coli loads in streams, but they tend to be system or site specific or overly complex without enhancing our understanding of these factors. Hence, based on available data, a Bayesian Neural Network (BNN) is presented for estimating E. coli loads based on physical, chemical, and biological factors in streams. The BNN has the dual advantage of overcoming the absence of quality data (with regards to consistency in data) and determination of mechanistic model parameters by employing a probabilistic framework. This study evaluates whether the BNN model can be an effective alternative tool to mechanistic models for E. coli loads estimation in streams. For this purpose, a comparison with a traditional model (LOADEST, USGS) is conducted. The models are compared for estimated E. coli loads based on available water quality data in Plum Creek, Texas. All the model efficiency measures suggest that overall E. coli loads estimations by the BNN model are better than the E. coli loads estimations by the LOADEST model on all the three occasions (three-fold cross validation). Thirteen factors were used for estimating E. coli loads with the exhaustive feature selection technique, which indicated that six of thirteen factors are important for estimating E. coli loads. Physical factors included temperature and dissolved oxygen; chemical factors include phosphate and ammonia; biological factors include suspended solids and chlorophyll. The results highlight that the LOADEST model estimates E. coli loads better in the smaller ranges, whereas the BNN model estimates E. coli loads better in the higher ranges. Hence, the BNN model can be used to design targeted monitoring programs and implement regulatory standards through TMDL programs. PMID:24511166

Mass balances of dissolved gases at river network scales across biomes.

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.; Sheehan, K.

2016-12-01

Estimating aquatic metabolism and gas fluxes at broad spatial scales is needed to evaluate the role of aquatic ecosystems in continental carbon cycles. We applied a river network model, FrAMES, to quantify the mass balances of dissolved oxygen at river network scales across five river networks in different biomes. The model accounts for hydrology; spatially varying re-aeration rates due to flow, slope, and water temperature; gas inputs via terrestrial runoff; variation in light due to canopy cover and water depth; benthic gross primary production; and benthic respiration. The model was parameterized using existing groundwater information and empirical relationships of GPP, R, and re-aeration, and was tested using dissolved oxygen patterns measured throughout river networks. We found that during summers, internal aquatic production dominates the river network mass balance of Kings Cr., Konza Prairie, KS (16.3 km2), whereas terrestrial inputs and aeration dominate the network mass balance at Coweeta Cr., Coweeta Forest, NC (15.7 km2). At network scales, both river networks are net heterotrophic, with Coweeta more so than Kings Cr. (P:R 0.6 vs. 0.7, respectively). The river network of Kings Creek showed higher network-scale GPP and R compared to Coweeta, despite having a lower drainage density because streams are on average wider so cumulative benthic surface areas are similar. Our findings suggest that the role of aquatic systems in watershed carbon balances will depend on interactions of drainage density, channel hydraulics, terrestrial vegetation, and biological activity.

How old is streamwater? Open questions in catchment transit time conceptualization, modeling and analysis

Treesearch

J.J. McDonnell; K. McGuire; P. Aggarwal; K.J. Beven; D. Biondi; G. Destouni; S. Dunn; A. James; J. Kirchner; P. Kraft; S. Lyon; P. Maloszewski; B. Newman; L. Pfister; A. Rinaldo; A. Rodhe; T. Sayama; J. Seibert; K. Solomon; C. Soulsby; M. Stewart; D. Tetzlaff; C. Tobin; P. Troch; M. Weiler; A. Western; A. Wörman; S. Wrede

2010-01-01

The time water spends travelling subsurface through a catchment to the stream network (i.e. the catchment water transit time) fundamentally describes the storage, flow pathway heterogeneity and sources of water in a catchment. The distribution of transit times reflects how catchments retain and release water and solutes that in turn set biogeochemical conditions and...

Unifying research on the fragmentation of terrestrial and aquatic habitats: patches, connectivity and the matrix in riverscapes

USGS Publications Warehouse

Eros, Tibor; Grant, Evan H. Campbell

2015-01-01

Fragmentation of habitats is a critical issue in the conservation and management of stream networks across spatial scales. Although the effects of individual barriers (e.g. dams) are well documented, we argue that a more comprehensive patch–matrix landscape model will improve our understanding of fragmentation effects and improve management in riverscapes.

A Dual-Stream Neuroanatomy of Singing

PubMed Central

Loui, Psyche

2015-01-01

Singing requires effortless and efficient use of auditory and motor systems that center around the perception and production of the human voice. Although perception and production are usually tightly coupled functions, occasional mismatches between the two systems inform us of dissociable pathways in the brain systems that enable singing. Here I review the literature on perception and production in the auditory modality, and propose a dual-stream neuroanatomical model that subserves singing. I will discuss studies surrounding the neural functions of feedforward, feedback, and efference systems that control vocal monitoring, as well as the white matter pathways that connect frontal and temporal regions that are involved in perception and production. I will also consider disruptions of the perception-production network that are evident in tone-deaf individuals and poor pitch singers. Finally, by comparing expert singers against other musicians and nonmusicians, I will evaluate the possibility that singing training might offer rehabilitation from these disruptions through neuroplasticity of the perception-production network. Taken together, the best available evidence supports a model of dorsal and ventral pathways in auditory-motor integration that enables singing and is shared with language, music, speech, and human interactions in the auditory environment. PMID:26120242

A Dual-Stream Neuroanatomy of Singing.

PubMed

Loui, Psyche

2015-02-01

Singing requires effortless and efficient use of auditory and motor systems that center around the perception and production of the human voice. Although perception and production are usually tightly coupled functions, occasional mismatches between the two systems inform us of dissociable pathways in the brain systems that enable singing. Here I review the literature on perception and production in the auditory modality, and propose a dual-stream neuroanatomical model that subserves singing. I will discuss studies surrounding the neural functions of feedforward, feedback, and efference systems that control vocal monitoring, as well as the white matter pathways that connect frontal and temporal regions that are involved in perception and production. I will also consider disruptions of the perception-production network that are evident in tone-deaf individuals and poor pitch singers. Finally, by comparing expert singers against other musicians and nonmusicians, I will evaluate the possibility that singing training might offer rehabilitation from these disruptions through neuroplasticity of the perception-production network. Taken together, the best available evidence supports a model of dorsal and ventral pathways in auditory-motor integration that enables singing and is shared with language, music, speech, and human interactions in the auditory environment.

Opinion dynamics on interacting networks: media competition and social influence

PubMed Central

Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

2014-01-01

The inner dynamics of the multiple actors of the informations systems – i.e, T.V., newspapers, blogs, social network platforms, – play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist. PMID:24861995

From Shoestring Rills to Dendritic River Networks: Documenting the Evolution of River Basins Towards Geometric Similarity Through Divide Migration, Stream Capture and Lateral Branching

NASA Astrophysics Data System (ADS)

Beeson, H. W.; McCoy, S. W.; Willett, S.

2016-12-01

Erosional river networks dissect much of Earth's surface into drainage basins. Global scaling laws such as Hack's Law suggest that river basins trend toward a particular scale-invariant shape. While erosional instabilities arising from competition between advective and diffusive processes can explain why headwaters branch, the erosional mechanics linking larger scale network branching with evolution towards a characteristic river basin shape remain poorly constrained. We map river steepness and a proxy for the steady-state elevation of river networks, χ, in simulated and real landscapes with a large range in spatial scale (102 -106 m) but with similar inclined, planar surfaces at the time of incipient network formation. We document that the evolution from narrow rill-like networks to dendritic, leaf-shaped river basins follows from drainage area differences between catchments. These serve as instabilities that grow, leading to divide migration, stream capture, lateral branching and network reorganization. As Horton hypothesized, incipient networks formed down gradient on an inclined, planar surface have an unequal distribution of drainage area and nonuniformity in response times such that larger basins erode more rapidly and branch laterally via capture of adjacent streams with lower erosion rates. Positive feedback owing to increase in drainage area furthers the process of branching at the expense of neighboring rivers. We show that drainage area exchange and the degree of network reorganization has a significant effect on river steepness in the Dragon's Back Pressure Ridge, CA, the Sierra Nevada, CA, and the Rocky Mountain High Plains, USA. Similarly, metrics of basin shape reveal that basins are evolving from narrow basins towards more common leaf shapes. Our results suggest that divide migration and stream capture driven by erosional disequilibrium could be fundamental processes by which river basins reach their characteristic geometry and dendritic form.

Policy entrepreneurship in the development of public sector strategy: the case of London health reform.

PubMed

Oborn, Eivor; Barrett, Michael; Exworthy, Mark

2011-01-01

The development of health policy is recognized as complex; however, there has been little development of the role of agency in this process. Kingdon developed the concept of policy entrepreneur (PE) within his ‘windows’ model. He argued inter-related ‘policy streams' must coincide for important issues to become addressed. The conjoining of these streams may be aided by a policy entrepreneur. We contribute by clarifying the role of the policy entrepreneur and highlighting the translational processes of key actors in creating and aligning policy windows. We analyse the work in London of Professor Sir Ara Darzi as a policy entrepreneur. An important aspect of Darzi's approach was to align a number of important institutional networks to conjoin related problems. Our findings highlight how a policy entrepreneur not only opens policy windows but also yokes together a network to make policy agendas happen. Our contribution reveals the role of clinical leadership in health reform.

Photoacoustic microscopy using Evans Blue dye as a contrast agent

NASA Astrophysics Data System (ADS)

Yao, Junjie; Maslov, Konstantin I.; Hu, Song; Wang, Lihong V.

2010-02-01

Complete and continuous imaging of microvascular networks is crucial for a wide variety of biomedical applications. Photoacoustic tomography can provide high resolution microvascular imaging using hemoglobin within red blood cells (RBC) as an endogenous contrast agent. However, intermittent RBC flow in capillaries results in discontinuous and fragmentary capillary images. To overcome this problem, we used Evans Blue (EB) dye as a contrast agent for in vivo photoacoustic imaging. EB has strong optical absorption at 610 nm and distributes uniformly in the blood stream by chemically binding to albumin. By intravenous injection of EB (6%, 200 μL), complete and continuous microvascular networks-especially capillaries-of the ears of nude mice were imaged. The diffusion of EB (3%, 100 μL) leaving the blood stream was monitored for 2 hours. At lower administration dose of EB (3%, 50 μL), the clearance of the EB-albumin complex was imaged for 10 days and quantitatively investigated using a two-compartment model.

JPL Earth Science Center Visualization Multitouch Table

NASA Astrophysics Data System (ADS)

Kim, R.; Dodge, K.; Malhotra, S.; Chang, G.

2014-12-01

JPL Earth Science Center Visualization table is a specialized software and hardware to allow multitouch, multiuser, and remote display control to create seamlessly integrated experiences to visualize JPL missions and their remote sensing data. The software is fully GIS capable through time aware OGC WMTS using Lunar Mapping and Modeling Portal as the GIS backend to continuously ingest and retrieve realtime remote sending data and satellite location data. 55 inch and 82 inch unlimited finger count multitouch displays allows multiple users to explore JPL Earth missions and visualize remote sensing data through very intuitive and interactive touch graphical user interface. To improve the integrated experience, Earth Science Center Visualization Table team developed network streaming which allows table software to stream data visualization to near by remote display though computer network. The purpose of this visualization/presentation tool is not only to support earth science operation, but specifically designed for education and public outreach and will significantly contribute to STEM. Our presentation will include overview of our software, hardware, and showcase of our system.

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhury, Sutanay; Holder, Larry; Chin, George

2015-05-27

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving networks spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with prominent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in amore » continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a ``Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named ``Relative Selectivity" that is used to select between different query processing strategies. Our experiments performed on real online news, network traffic stream and a synthetic social network benchmark demonstrate 10-100x speedups over non-incremental, selectivity agnostic approaches.« less

Wastewater treatment plant effluent introduces recoverable shifts in microbial community composition in urban streams

NASA Astrophysics Data System (ADS)

Ledford, S. H.; Price, J. R.; Ryan, M. O.; Toran, L.; Sales, C. M.

2017-12-01

New technologies are allowing for intense scrutiny of the impact of land use on microbial communities in stream networks. We used a combination of analytical chemistry, real-time polymerase chain reaction (qPCR) and targeted amplicon sequencing for a preliminary study on the impact of wastewater treatment plant effluent discharge on urban streams. Samples were collected on two dates above and below treatment plants on the Wissahickon Creek, and its tributary, Sandy Run, in Montgomery County, PA, USA. As expected, effluent was observed to be a significant source of nutrients and human and non-specific fecal associated taxa. There was an observed increase in the alpha diversity at locations immediately below effluent outflows, which contributed many taxa involved in wastewater treatment processes and nutrient cycling to the stream's microbial community. Unexpectedly, modeling of microbial community shifts along the stream was not controlled by concentrations of measured nutrients. Furthermore, partial recovery, in the form of decreasing abundances of bacteria and nutrients associated with wastewater treatment plant processes, nutrient cycling bacteria, and taxa associated with fecal and sewage sources, was observed between effluent sources. Antecedent moisture conditions impacted overall microbial community diversity, with higher diversity occurring after rainfall. These findings hint at resilience in stream microbial communities to recover from wastewater treatment plant effluent and are vital to understanding the impacts of urbanization on microbial stream communities.

The legacy of lead (Pb) in fluvial bed sediments of an urban drainage basin, Oahu, Hawaii.

PubMed

Hotton, Veronica K; Sutherland, Ross A

2016-03-01

The study of fluvial bed sediments is essential for deciphering the impact of anthropogenic activities on water quality and drainage basin integrity. In this study, a systematic sampling design was employed to characterize the spatial variation of lead (Pb) concentrations in bed sediment of urban streams in the Palolo drainage basin, southeastern Oahu, Hawaii. Potentially bioavailable Pb was assessed with a dilute 0.5 N HCl extraction of the <63 μm grain-size fraction from the upper bed sediment layer of 169 samples from Palolo, Pukele, and Waiomao streams. Contamination of bed sediments was associated with the direct transport of legacy Pb from the leaded gasoline era to stream channels via a dense network of storm drains linked to road surfaces throughout the basin. The Palolo Stream had the highest median Pb concentration (134 mg/kg), and the greatest road and storm drain densities, the greatest population, and the most vehicle numbers. Lower median Pb concentrations were associated with the less impacted Pukele Stream (24 mg/kg), and Waiomao Stream (7 mg/kg). The median Pb enrichment ratio values followed the sequence of Palolo (68) > Pukele (19) > Waiomao (8). Comparisons to sediment quality guidelines and potential toxicity estimates using a logistic regression model (LRM) indicated a significant potential risk of Palolo Stream bed sediments to bottom-dwelling organisms.

Improving Data Transfer Throughput with Direct Search Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balaprakash, Prasanna; Morozov, Vitali; Kettimuthu, Rajkumar

2016-01-01

Improving data transfer throughput over high-speed long-distance networks has become increasingly difficult. Numerous factors such as nondeterministic congestion, dynamics of the transfer protocol, and multiuser and multitask source and destination endpoints, as well as interactions among these factors, contribute to this difficulty. A promising approach to improving throughput consists in using parallel streams at the application layer.We formulate and solve the problem of choosing the number of such streams from a mathematical optimization perspective. We propose the use of direct search methods, a class of easy-to-implement and light-weight mathematical optimization algorithms, to improve the performance of data transfers by dynamicallymore » adapting the number of parallel streams in a manner that does not require domain expertise, instrumentation, analytical models, or historic data. We apply our method to transfers performed with the GridFTP protocol, and illustrate the effectiveness of the proposed algorithm when used within Globus, a state-of-the-art data transfer tool, on productionWAN links and servers. We show that when compared to user default settings our direct search methods can achieve up to 10x performance improvement under certain conditions. We also show that our method can overcome performance degradation due to external compute and network load on source end points, a common scenario at high performance computing facilities.« less

Neural Integration in Body Perception.

PubMed

Ramsey, Richard

2018-06-19

The perception of other people is instrumental in guiding social interactions. For example, the appearance of the human body cues a wide range of inferences regarding sex, age, health, and personality, as well as emotional state and intentions, which influence social behavior. To date, most neuroscience research on body perception has aimed to characterize the functional contribution of segregated patches of cortex in the ventral visual stream. In light of the growing prominence of network architectures in neuroscience, the current article reviews neuroimaging studies that measure functional integration between different brain regions during body perception. The review demonstrates that body perception is not restricted to processing in the ventral visual stream but instead reflects a functional alliance between the ventral visual stream and extended neural systems associated with action perception, executive functions, and theory of mind. Overall, these findings demonstrate how body percepts are constructed through interactions in distributed brain networks and underscore that functional segregation and integration should be considered together when formulating neurocognitive theories of body perception. Insight from such an updated model of body perception generalizes to inform the organizational structure of social perception and cognition more generally and also informs disorders of body image, such as anorexia nervosa, which may rely on atypical integration of body-related information.

Channel erosion in a rapidly urbanizing region of Tijuana, Mexico: Enlargement downstream of channel hardpoints

NASA Astrophysics Data System (ADS)

Taniguchi, Kristine; Biggs, Trent; Langendoen, Eddy; Castillo, Carlos; Gudiño, Napoleon; Yuan, Yongping; Liden, Douglas

2016-04-01

Urban-induced erosion in Tijuana, Mexico, has led to excessive sediment deposition in the Tijuana Estuary in the United States. Urban areas in developing countries, in contrast to developed countries, are characterized by much lower proportions of vegetation and impervious surfaces due to limited access to urban services such as road paving and landscaping, and larger proportions of exposed soils. In developing countries, traditional watershed scale variables such as impervious surfaces may not be good predictors of channel enlargement. In this research, we surveyed the stream channel network of an erodible tributary of the Tijuana River Watershed, Los Laureles Canyon, at 125 locations, including repeat surveys from 2008. Structure from Motion (SfM) and 3D photo-reconstruction techniques were used to create digital terrain models of stream reaches upstream and downstream of channel hardpoints. Channels are unstable downstream of hardpoints, with incision up to 2 meters and widening up to 12 meters. Coordinated channelization is essential to avoid piece-meal approaches that lead to channel degradation. Watershed impervious area is not a good predictor of channel erosion due to the overriding importance of hardpoints and likely to the high sediment supply from the unpaved roads which prevents channel erosion throughout the stream network.

The concept of entropy in landscape evolution

USGS Publications Warehouse

Leopold, Luna Bergere; Langbein, Walter Basil

1962-01-01

The concept of entropy is expressed in terms of probability of various states. Entropy treats of the distribution of energy. The principle is introduced that the most probable condition exists when energy in a river system is as uniformly distributed as may be permitted by physical constraints. From these general considerations equations for the longitudinal profiles of rivers are derived that are mathematically comparable to those observed in the field. The most probable river profiles approach the condition in which the downstream rate of production of entropy per unit mass is constant. Hydraulic equations are insufficient to determine the velocity, depths, and slopes of rivers that are themselves authors of their own hydraulic geometries. A solution becomes possible by introducing the concept that the distribution of energy tends toward the most probable. This solution leads to a theoretical definition of the hydraulic geometry of river channels that agrees closely with field observations. The most probable state for certain physical systems can also be illustrated by random-walk models. Average longitudinal profiles and drainage networks were so derived and these have the properties implied by the theory. The drainage networks derived from random walks have some of the principal properties demonstrated by the Horton analysis; specifically, the logarithms of stream length and stream numbers are proportional to stream order.

Seasonally-Dynamic SPARROW Modeling of Nitrogen Flux Using Earth Observation Data

NASA Astrophysics Data System (ADS)

Smith, R. A.; Schwarz, G. E.; Brakebill, J. W.; Hoos, A. B.; Moore, R. B.; Shih, J.; Nolin, A. W.; Macauley, M.; Alexander, R. B.

2013-12-01

SPARROW models are widely used to identify and quantify the sources of contaminants in watersheds and to predict their flux and concentration at specified locations downstream. Conventional SPARROW models describe the average relationship between sources and stream conditions based on long-term water quality monitoring data and spatially-referenced explanatory information. But many watershed management issues stem from intra- and inter-annual changes in contaminant sources, hydrologic forcing, or other environmental conditions which cause a temporary imbalance between inputs and stream water quality. Dynamic behavior of the system relating to changes in watershed storage and processing then becomes important. In this study, we describe dynamically calibrated SPARROW models of total nitrogen flux in three sub-regional watersheds: the Potomac River Basin, Long Island Sound drainage, and coastal South Carolina drainage. The models are based on seasonal water quality and watershed input data for a total 170 monitoring stations for the period 2001 to 2008. Frequently-reported, spatially-detailed input data on the phenology of agricultural production, terrestrial vegetation growth, and snow melt are often challenging requirements of seasonal modeling of reactive nitrogen. In this NASA-funded research, we use Enhanced Vegetation Index (EVI), gross primary production and snow/ice cover data from MODIS to parameterize seasonal uptake and release of nitrogen from vegetation and snowpack. The spatial reference frames of the models are 1:100,000-scale stream networks, and the computational time steps are 0.25-year seasons. Precipitation and temperature data are from PRISM. The model formulation accounts for storage of nitrogen from nonpoint sources including fertilized cropland, pasture, urban land, and atmospheric deposition. Model calibration is by non-linear regression. Once calibrated, model source terms based on previous season export allow for recursive dynamic simulation of stream flux: gradual increases or decreases in export occur as source supply rates and hydrologic forcing change. Based on an assumption that removal of nitrogen from watershed storage to stream channels and to 'permanent' sinks (e.g. the atmosphere and deep groundwater) occur as parallel first-order processes, the models can be used to estimate the approximate residence times of nonpoint source nitrogen in the watersheds.

Application of Artificial Neural Network to Optical Fluid Analyzer

NASA Astrophysics Data System (ADS)

Kimura, Makoto; Nishida, Katsuhiko

1994-04-01

A three-layer artificial neural network has been applied to the presentation of optical fluid analyzer (OFA) raw data, and the accuracy of oil fraction determination has been significantly improved compared to previous approaches. To apply the artificial neural network approach to solving a problem, the first step is training to determine the appropriate weight set for calculating the target values. This involves using a series of data sets (each comprising a set of input values and an associated set of output values that the artificial neural network is required to determine) to tune artificial neural network weighting parameters so that the output of the neural network to the given set of input values is as close as possible to the required output. The physical model used to generate the series of learning data sets was the effective flow stream model, developed for OFA data presentation. The effectiveness of the training was verified by reprocessing the same input data as were used to determine the weighting parameters and then by comparing the results of the artificial neural network to the expected output values. The standard deviation of the expected and obtained values was approximately 10% (two sigma).

Morphology and channel evolution of small streams in the southern Blue Ridge mountains of western North Carolina

Treesearch

David Leigh

2010-01-01

Small streams are understudied in the Southern Blue Ridge Mountains, yet they constitute a huge portion of the drainage network and are relevant with respect to human impact on the landscape and stream restoration efforts. Morphologies of 44 streams (0.01 to 20 km2 watersheds) from western North Carolina are characterized and couched in the context of historical...

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

NASA Astrophysics Data System (ADS)

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-09-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002-2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970-2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

USGS Publications Warehouse

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-01-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Delivering Instruction via Streaming Media: A Higher Education Perspective.

ERIC Educational Resources Information Center

Mortensen, Mark; Schlieve, Paul; Young, Jon

2000-01-01

Describes streaming media, an audio/video presentation that is delivered across a network so that it is viewed while being downloaded onto the user's computer, including a continuous stream of video that can be pre-recorded or live. Discusses its use for nontraditional students in higher education and reports on implementation experiences. (LRW)

Distribution of Amphipods (Gammarus nipponensis Ueno) Among Mountain Headwater Streams with Different Legacies of Debris Flow Occurrence

EPA Science Inventory

To understand the impacts of debris flows on the distribution of an amphipod with limited dispersal ability in the context of stream networks, we surveyed the presence of Gammarus nipponensis in 87 headwater streams with different legacies of debris flow occurrence within an 8.5-...

Geography of invasion in mountain streams: consequences of headwater lake fish introductions

Treesearch

Susan B. Adams; Christopher A. Frissell; Bruce E. Rieman

2001-01-01

The introduction of fish into high-elevation lakes can provide a geographic and demographic boost to their invasion of stream networks, thereby further endangering the native stream fauna. Increasingly, remaining populations of native salmonids are concentrated in fragmented headwater refugia that are protected by physical or biological barriers from introduced fishes...