scholarly journals Simulating river flow velocity on global scale

2005 ◽  
Vol 5 ◽  
pp. 133-136 ◽  
Author(s):  
K. Schulze ◽  
M. Hunger ◽  
P. Döll
Keyword(s):  
Flow Velocity ◽  
Cross Sections ◽  
Hydrological Modeling ◽  
River Flow ◽  
Simple Algorithm ◽  
Global Scale ◽  
Limited Information ◽  
Data Set ◽  
Measured Velocity ◽  
Test Flow

Abstract. Flow velocity in rivers has a major impact on residence time of water and thus on high and low water as well as on water quality. For global scale hydrological modeling only very limited information is available for simulating flow velocity. Based on the Manning-Strickler equation, a simple algorithm to model temporally and spatially variable flow velocity was developed with the objective of improving flow routing in the global hydrological model of WaterGAP. An extensive data set of flow velocity measurements in US rivers was used to test and to validate the algorithm before integrating it into WaterGAP. In this test, flow velocity was calculated based on measured discharge and compared to measured velocity. Results show that flow velocity can be modeled satisfactorily at selected river cross sections. It turned out that it is quite sensitive to river roughness, and the results can be optimized by tuning this parameter. After the validation of the approach, the tested flow velocity algorithm has been implemented into the WaterGAP model. A final validation of its effects on the model results is currently performed.

scholarly journals Evaluating Metagenomic Analysis for Pathogen Transmission in Healthcare Settings

2020 ◽  
Vol 41 (S1) ◽  
pp. s224-s224
Author(s):  
Curt Hewitt ◽  
Katharina Weber ◽  
Danielle LeSassier ◽  
Anthony Kappell ◽  
Kathleen Schulte ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Dna Analysis ◽  
Pathogen Transmission ◽  
Species Level ◽  
Metagenomic Analysis ◽  
Skin Microbiome ◽  
Limited Information ◽  
Culture Methods ◽  
Data Set ◽  
Skin Contact

Background: The prevalence of healthcare-acquired infections (HAIs) and rising levels of antimicrobial resistance place a significant burden on modern healthcare systems. Cultures are typically used to track HAIs; however, culture methods provide limited information and are not applicable to all pathogens. Next-generation sequencing (NGS) can detect and characterize pathogens present within a sample, but few research studies have explored how NGS could be used to detect pathogen transmission events under HAI-relevant scenarios. The objective of this CDC-funded project was to evaluate and correlate sequencing approaches for pathogen transmission with standard culture-based analysis. Methods: We modeled pathogen transfer via hand contact using synthetic skin. These skin coupons were seeded with a community of commensal organisms to mimic the human skin microbiome. Pathogens were added at physiologically relevant high or low levels prior to skin-to-skin contact. The ESKAPE pathogens: E. faecium, S. aureus, K. pneumoniae, A. baumannii, P. aeruginosa, and Enterobacter spp plus C. difficile were employed because they are the most common antibiotic resistant HAIs. Pathogen transfer between skin coupons was measured following direct skin contact and fomite surface transmission. The effects of handwashing or fomite decontamination were also evaluated. Transferred pathogens were enumerated via culture to establish a robust data set against which DNA and RNA sequence analyses of the same samples could be compared. These data also provide a quantitative assessment of individual ESKAPE+C pathogen transfer rates in skin contact scenarios. Results: Metagenomic and metatranscriptomic analysis using custom analysis pipelines and reference databases successfully identified the commensal and pathogenic organisms present in each sample at the species level. This analysis also identified antibiotic resistance genes and plasmids. Metatranscriptomic analysis permitted not only gene identification but also confirmation of gene expression, a critical factor in the evaluation of antibiotic resistance. DNA analysis does not require cell viability, a key differentiator between sequencing and culturing reflected in simulated handwashing data. Sensitivity remains a key limitation of metagenomic analysis, as shown by the poor species identification and gene content characterization of pathogens present at low abundance within the simulated microbial community. Species level identification typically failed as ratios fell below 1:1,000 pathogen CFU:total community CFU. Conclusions: These findings demonstrate the strengths and weaknesses of NGS for molecular epidemiology. The data sets produced for this study are publicly available so they can be employed for future metagenomic benchmarking studies.Funding: NoneDisclosures: None

scholarly journals Rapid multi-directed cholinergic transmission in the central nervous system

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Santhosh Sethuramanujam ◽  
Akihiro Matsumoto ◽  
Geoff deRosenroll ◽  
Benjamin Murphy-Baum ◽  
J Michael McIntosh ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Ganglion Cells ◽  
Release Site ◽  
Amacrine Cells ◽  
Global Scale ◽  
Cholinergic Transmission ◽  
Data Set ◽  
The Central Nervous System ◽  
Synaptic Mechanisms

AbstractIn many parts of the central nervous system, including the retina, it is unclear whether cholinergic transmission is mediated by rapid, point-to-point synaptic mechanisms, or slower, broad-scale ‘non-synaptic’ mechanisms. Here, we characterized the ultrastructural features of cholinergic connections between direction-selective starburst amacrine cells and downstream ganglion cells in an existing serial electron microscopy data set, as well as their functional properties using electrophysiology and two-photon acetylcholine (ACh) imaging. Correlative results demonstrate that a ‘tripartite’ structure facilitates a ‘multi-directed’ form of transmission, in which ACh released from a single vesicle rapidly (~1 ms) co-activates receptors expressed in multiple neurons located within ~1 µm of the release site. Cholinergic signals are direction-selective at a local, but not global scale, and facilitate the transfer of information from starburst to ganglion cell dendrites. These results suggest a distinct operational framework for cholinergic signaling that bears the hallmarks of synaptic and non-synaptic forms of transmission.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

scholarly journals Evaluation of coral reef carbonate production models at a global scale

2015 ◽  
Vol 12 (5) ◽  
pp. 1339-1356 ◽  
Author(s):  
N. S. Jones ◽  
A. Ridgwell ◽  
E. J. Hendy
Keyword(s):  
Coral Reef ◽  
Predictive Power ◽  
Numerical Models ◽  
Coral Cover ◽  
Light Availability ◽  
Global Scale ◽  
Data Set ◽  
Carbonate Production ◽  
Future Global Warming ◽  
Atmospheric Co2 Concentrations

Abstract. Calcification by coral reef communities is estimated to account for half of all carbonate produced in shallow water environments and more than 25% of the total carbonate buried in marine sediments globally. Production of calcium carbonate by coral reefs is therefore an important component of the global carbon cycle; it is also threatened by future global warming and other global change pressures. Numerical models of reefal carbonate production are needed for understanding how carbonate deposition responds to environmental conditions including atmospheric CO2 concentrations in the past and into the future. However, before any projections can be made, the basic test is to establish model skill in recreating present-day calcification rates. Here we evaluate four published model descriptions of reef carbonate production in terms of their predictive power, at both local and global scales. We also compile available global data on reef calcification to produce an independent observation-based data set for the model evaluation of carbonate budget outputs. The four calcification models are based on functions sensitive to combinations of light availability, aragonite saturation (Ωa) and temperature and were implemented within a specifically developed global framework, the Global Reef Accretion Model (GRAM). No model was able to reproduce independent rate estimates of whole-reef calcification, and the output from the temperature-only based approach was the only model to significantly correlate with coral-calcification rate observations. The absence of any predictive power for whole reef systems, even when consistent at the scale of individual corals, points to the overriding importance of coral cover estimates in the calculations. Our work highlights the need for an ecosystem modelling approach, accounting for population dynamics in terms of mortality and recruitment and hence calcifier abundance, in estimating global reef carbonate budgets. In addition, validation of reef carbonate budgets is severely hampered by limited and inconsistent methodology in reef-scale observations.

Glaciological Problems Set by the Control of Dangerous Lakes in Cordillera Blanca, Peru. II. Movement of a Covered Glacier Embedded within a Rock Glacier

1977 ◽  
Vol 18 (79) ◽  
pp. 255-274 ◽  
Author(s):  
Louis Lliboutry
Keyword(s):  
Cross Sections ◽  
Rock Glacier ◽  
Measured Velocity ◽  
Elliptical Cross ◽  
Cordillera Blanca ◽  
The Holocene ◽  
Glacier Tongue ◽  
Proglacial Lake

AbstractIn front of Laguna Parón there is a huge moraine which turns through 90° in the middle of the valley and with a narrow covered glacier on the top. It has been studied by electrical exploration, and using the displacements of 43 marked boulders on the glacier. Assuming a uniform balance on the glacier tongue and semi-elliptical cross-sections, it has been possible to estimate this balance and the glacier thickness. A great amount of the measured velocity comes from the creep of the moraine itself, which seems 10 be a kind of rock glacier, probably without interstitial ire. It must have taken all the Holocene to be formed. During its complex history a proglacial lake must have formed at some time, the rupture of which explains the crooked form.

New Transboundary Hydrographic Data Set for Advancing Regional Hydrological Modeling and Water Resources Management

2019 ◽  
Vol 145 (6) ◽  
pp. 06019004 ◽  
Author(s):  
Lacey A. Mason ◽  
Andrew D. Gronewold ◽  
Michael Laitta ◽  
David Gochis ◽  
Kevin Sampson ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Hydrological Modeling ◽  
Hydrographic Data ◽  
Data Set ◽  
Resources Management

scholarly journals An improved glyoxal retrieval from OMI measurements

2014 ◽  
Vol 7 (12) ◽  
pp. 4133-4150 ◽  
Author(s):  
L. M. A. Alvarado ◽  
A. Richter ◽  
M. Vrekoussis ◽  
F. Wittrock ◽  
A. Hilboll ◽  
...  
Keyword(s):  
Cross Sections ◽  
Anthropogenic Activities ◽  
Absorption Cross ◽  
Fire Event ◽  
Data Set ◽  
Polynomial Degree ◽  
Temperature Boundary ◽  
Sensitivity Tests ◽  
Radiative Power ◽  
The Impact

Abstract. Satellite observations from the SCIAMACHY, GOME-2 and OMI spectrometers have been used to retrieve atmospheric columns of glyoxal (CHOCHO) with the DOAS method. High CHOCHO levels were found over regions with large biogenic and pyrogenic emissions, and hot-spots have been identified over areas of anthropogenic activities. This study focuses on the development of an improved retrieval for CHOCHO from measurements by the OMI instrument. From sensitivity tests, a fitting window and a polynomial degree are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high-temperature (boundary layer ambient: 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences of NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. A comparison with vertical CHOCHO columns retrieved from GOME-2 and SCIAMACHY measurements over continental regions is performed, showing overall good consistency. However, SCIAMACHY CHOCHO columns are systematically higher than those obtained from the other instruments. Using the new OMI CHOCHO data set, the link between fires and glyoxal columns is investigated for two selected regions in Africa. In addition, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. In both cases, enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of MODIS fire radiative power, demonstrating that pyrogenic emissions can be clearly identified in the new OMI CHOCHO product.

scholarly journals Supplementary material to "Global-scale evaluation of 23 precipitation datasets using gauge observations and hydrological modeling"

2017 ◽  
Author(s):  
Hylke E. Beck ◽  
Noemi Vergopolan ◽  
Ming Pan ◽  
Vincenzo Levizzani ◽  
Albert I. J. M. van Dijk ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Global Scale ◽  
Scale Evaluation ◽  
Supplementary Material

scholarly journals Artificial Intelligence Techniques for river flow forecasting in the Seyhan River Catchment, Turkey

2007 ◽  
Vol 4 (3) ◽  
pp. 1369-1406 ◽  
Author(s):  
M. Firat
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
River Flow ◽  
Fuzzy Inference ◽  
Flow Data ◽  
Data Set ◽  
Inference System ◽  
Forecasting Models ◽  
River Flow Forecasting ◽  
Best Fit

Abstract. The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN), for forecasting of daily river flow is investigated and the Seyhan catchment, located in the south of Turkey, is chosen as a case study. Totally, 5114 daily river flow data are obtained from river flow gauges station of Üçtepe (1818) on Seyhan River between the years 1986 and 2000. The data set are divided into three subgroups, training, testing and verification. The training and testing data set include totally 5114 daily river flow data and the number of verification data points is 731. The river flow forecasting models having various input structures are trained and tested to investigate the applicability of ANFIS and ANN methods. The results of ANFIS, GRNN and FFNN models for both training and testing are evaluated and the best fit forecasting model structure and method is determined according to criteria of performance evaluation. The best fit model is also trained and tested by traditional statistical methods and the performances of all models are compared in order to get more effective evaluation. Moreover ANFIS, GRNN and FFNN models are also verified by verification data set including 731 daily river flow data at the time period 1998–2000 and the results of models are compared. The results demonstrate that ANFIS model is superior to the GRNN and FFNN forecasting models, and ANFIS can be successfully applied and provide high accuracy and reliability for daily River flow forecasting.

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