scholarly journals Hydrodynamic simulation of the effects of stable in-channel large wood on the flood hydrographs of a low mountain range creek, Ore Mountains, Germany

2019 ◽  
Vol 23 (10) ◽  
pp. 4349-4365 ◽  
Author(s):  
Daniel Rasche ◽  
Christian Reinhardt-Imjela ◽  
Achim Schulte ◽  
Robert Wenzel
Keyword(s):  
Goodness Of Fit ◽  
Field Experiments ◽  
Ecological Impacts ◽  
Mountain Range ◽  
Two Dimensional ◽  
Large Wood ◽  
Hydrodynamic Models ◽  
Small Streams ◽  
The Mean ◽  
Best Fit

Abstract. Large wood (LW) can alter the hydromorphological and hydraulic characteristics of rivers and streams and may act positively on a river's ecology by i.e. leading to increased habitat availability. On the contrary, floating as well as stable LW is a potential threat for anthropogenic goods and infrastructure during flood events. Concerning the contradiction of potential risks and positive ecological impacts, addressing the physical effects of stable large wood is highly important. Hydrodynamic models offer the possibility of investigating the hydraulic effects of anchored large wood. However, the work and time involved varies between approaches that incorporate large wood in hydrodynamic models. In this study, a two-dimensional hydraulic model is set up for a mountain creek to simulate the hydraulic effects of stable LW and to compare multiple methods of accounting for LW-induced roughness. LW is implemented by changing in-channel roughness coefficients and by adding topographic elements to the model; this is carried out in order to determine which method most accurately simulates observed hydrographs and to provide guidance for future hydrodynamic modelling of stable large wood with two-dimensional models. The study area comprises a 282 m long reach of the Ullersdorfer Teichbächel, a creek in the Ore Mountains (south-eastern Germany). Discharge time series from field experiments allow for a validation of the model outputs with field observations with and without stable LW. We iterate in-channel roughness coefficients to best fit the mean simulated and observed flood hydrographs with and without LW at the downstream reach outlet. As an alternative approach for modelling LW-induced effects, we use simplified discrete topographic elements representing individual LW elements in the channel. In general, the simulations reveal a high goodness of fit between the observed flood hydrographs and the model results without and with stable in-channel LW. The best fit of the simulation and mean observed hydrograph with in-channel LW can be obtained when increasing in-channel roughness coefficients throughout the reach instead of an increase at LW positions only. The best fit in terms of the hydrograph's general shape can be achieved by integrating discrete elements into the calculation mesh. The results illustrate that the mean observed hydrograph can be satisfactorily modelled using an adjustment of roughness coefficients. In conclusion, a time-consuming and work-intensive mesh manipulation is suitable for analysing the more detailed effects of stable LW on a small spatio-temporal scale where high precision is required. In contrast, the reach-wise adjustment of in-channel roughness coefficients seems to provide similarly accurate results on the reach scale and, thus, could be helpful for practical applications of model-based impact assessments of stable LW on flood hydrographs of small streams and rivers.

scholarly journals Hydrodynamic simulation of the effects of in-channel large woody debris on the flood hydrographs of a low mountain range creek, Ore Mountains, Germany

2019 ◽  
Author(s):  
Daniel Rasche ◽  
Christian Reinhardt-Imjela ◽  
Achim Schulte ◽  
Robert Wenzel
Keyword(s):  
Field Experiments ◽  
Woody Debris ◽  
Ecological Impacts ◽  
Large Woody Debris ◽  
Scale Model ◽  
Mountain Range ◽  
Flood Events ◽  
Discrete Elements ◽  
Temporal Shift ◽  
Best Fit

Abstract. Fifteen years after introducing the European Union's water framework directive (WFD), most of the German surface water bodies are still far away from having the targeted good ecological status or potential. One reason are insufficient hydromorphological diversities such as riverbed structure including the absence of natural woody debris in the channels. The presence of large woody debris (LWD) in river channels can improve the hydromorphological and hydraulic characteristics of rivers and streams and therefore act positively on a river’s ecology. On the contrary, floating LWD is a potential threat for anthropogenic goods and infrastructure during flood events. Concerning the contradiction of potential risks as well as positive ecological impacts, addressing the physical effects of large woody debris is highly important, for example to identify river sections in which large woody debris can remain or can be reintroduced. Hydrodynamic models offer the possibility of investigating the hydraulic effects of fastened large woody debris. In such models roughness coefficients are commonly used to implement LWD, however, because of the complexity of the shape of LWD elements this approach seems to be too simple and not appropriate to simulate its diverse effects especially on flood hydrographs. Against this background a two-dimensional hydraulic model is set up for a mountain creek to simulate the hydraulic effects of LWD and to test different methods of LWD implementation. The study area comprises a 282 m long reach of the Ullersdorfer Teichbächel, a creek in the Ore Mountains (South-eastern Germany). In previous studies, field experiments with artificially generated flood events have been performed with and without LWD in the channel. Discharge time series from the experiments allow a validation of the model outputs with field observations. Methodically, in-channel roughness coefficients are changed iteratively for retrieving the best fit between mean simulated and observed flood hydrographs with and without LWD at the downstream reach outlet. In addition, roughness values are modified at LWD positions only and, simplified discrete elements representing LWD were incorporated into the calculation mesh. In general, the model results reveal a good simulation of the observed flood hydrographs of the field experiments without in-channel large woody debris. This indicates the applicability of the model used in the studied reach of a creek in low mountain ranges. The best fit of simulation and mean observed hydrograph with in-channel LWD can be obtained when increasing in-channel roughness through decreasing Strickler coefficients by 30 % in the entire reach or 55 % at LWD positions only. However, the increase of roughness in the entire reach shows a better simulation of the observed hydrograph, indicating that LWD elements affect sections beyond their own dimensions i.e. by forming downstream wake fields. The best fit in terms of the hydrograph's general shape can be achieved by integrating discrete elements into the calculation mesh. The emerging temporal shift between simulation and observation can be attributed to mesh impermeability and element dimensions causing too intense water retention and flow alteration. The results illustrate that the mean observed hydrograph can be satisfactorily modelled using roughness coefficients. Nevertheless, discrete elements result in a better fitting shape of the simulated hydrograph. In conclusion, a time-consuming and work-intensive mesh manipulation is suitable for analysing detailed flow conditions using computational fluid dynamics (CFD) on small spatio-temporal scale. Here, a close-to-nature design of discrete LWD objects is essential to retrieve accurate results. In contrast, the reach-wise adjustment of in-channel roughness coefficients is useful in larger scale model applications such as 1D-hydrodynamic or rainfall-runoff simulations on catchment scale.

scholarly journals Statistical models for the number of successful cyber intrusions

2017 ◽  
Vol 15 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Nandi O Leslie ◽  
Richard E Harang ◽  
Lawrence P Knachel ◽  
Alexander Kott
Keyword(s):  
Network Security ◽  
Count Data ◽  
Security Policy ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Negative Binomial ◽  
Computer Network ◽  
Educational Institution ◽  
The Mean ◽  
Best Fit

We propose several generalized linear models (GLMs) to predict the number of successful cyber intrusions (or “intrusions”) into an organization’s computer network, where the rate at which intrusions occur is a function of the following observable characteristics of the organization: (i) domain name system (DNS) traffic classified by their top-level domains (TLDs); (ii) the number of network security policy violations; and (iii) a set of predictors that we collectively call the “cyber footprint” that is comprised of the number of hosts on the organization’s network, the organization’s similarity to educational institution behavior, and its number of records on scholar.google.com . In addition, we evaluate the number of intrusions to determine whether these events follow a Poisson or negative binomial (NB) probability distribution. We reveal that the NB GLM provides the best fit model for the observed count data, number of intrusions per organization, because the NB model allows the variance of the count data to exceed the mean. We also show that there are restricted and simpler NB regression models that omit selected predictors and improve the goodness-of-fit of the NB GLM for the observed data. With our model simulations, we identify certain TLDs in the DNS traffic as having a significant impact on the number of intrusions. In addition, we use the models and regression results to conclude that the number of network security policy violations is consistently predictive of the number of intrusions.

The ‘best fit’ to the truncated Poisson distribution

1982 ◽  
Vol 109 (3) ◽  
pp. 453-457
Author(s):  
J. G. Spain
Keyword(s):  
Finite Number ◽  
Poisson Distribution ◽  
Degrees Of Freedom ◽  
Goodness Of Fit ◽  
Scaling Factor ◽  
Factor H ◽  
Reasonable Belief ◽  
Chi Squared ◽  
The Mean ◽  
Best Fit

Suppose we have a finite number N of observed frequencies [a(i)], and suppose further that we have a ‘reasonable belief’ that the (truncated) Poisson distribution could be used to describe those frequencies. The parameter μ (which represents both the mean and the variance of the entire unit Poisson distribution) and a suitable scaling-factor H would, in some way, be estimated from the data. In the normal course of events, the chi-squared test would probably be used to test for ‘goodness of fit’, and the number of ‘degrees of freedom’ would reflect the extent to which μ and H had been directly estimated from the data. Depending upon the degree of significance considered appropriate, the test would be used to decide whether or not a ‘reasonable fit’ had been obtained, and whether or not a particular formally-defined hypothesis should be accepted or rejected.

A one-dimensional self-gravitating stellar gas

1966 ◽  
Vol 25 ◽  
pp. 46-48 ◽  
Author(s):  
M. Lecar
Keyword(s):  
Gravitational Field ◽  
Phase Space ◽  
Motion Picture ◽  
Space Distribution ◽  
Two Dimensional ◽  
One Dimensional ◽  
Phase Space Distribution ◽  
Dimensional Phase Space ◽  
The Mean

“Dynamical mixing”, i.e. relaxation of a stellar phase space distribution through interaction with the mean gravitational field, is numerically investigated for a one-dimensional self-gravitating stellar gas. Qualitative results are presented in the form of a motion picture of the flow of phase points (representing homogeneous slabs of stars) in two-dimensional phase space.

Prediction of Haemoglobin Level by Some Probability Distribution

2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Continuous Variable ◽  
Hemoglobin Level ◽  
Chi Square ◽  
Chi Square Test ◽  
Log Normal ◽  
Two Parameters ◽  
Best Fit

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.

The Influence of Blade Wakes on the Performance of Interturbine Diffusers

1996 ◽  
Vol 118 (2) ◽  
pp. 347-352 ◽  
Author(s):  
R. G. Dominy ◽  
D. A. Kirkham
Keyword(s):  
Performance Modeling ◽  
Three Dimensional ◽  
Secondary Flows ◽  
Two Dimensional ◽  
Correct Performance ◽  
Analysis Methods ◽  
Flow Factor ◽  
The Mean ◽  
Lp Turbine

Interturbine diffusers provide continuity between HP and LP turbines while diffusing the flow upstream of the LP turbine. Increasing the mean turbine diameter offers the potential advantage of reducing the flow factor in the following stages, leading to increased efficiency. The flows associated with these interturbine diffusers differ from those in simple annular diffusers both as a consequence of their high-curvature S-shaped geometry and of the presence of wakes created by the upstream turbine. It is shown that even the simplest two-dimensional wakes result in significantly modified flows through such ducts. These introduce strong secondary flows demonstrating that fully three-dimensional, viscous analysis methods are essential for correct performance modeling.

scholarly journals Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 314
Author(s):  
Andrew Revill ◽  
Vasileios Myrgiotis ◽  
Anna Florence ◽  
Stephen Hoad ◽  
Robert Rees ◽  
...  
Keyword(s):  
Field Experiments ◽  
Process Models ◽  
Agricultural Technologies ◽  
N Application ◽  
Area Index ◽  
Complex Process ◽  
C Cycle ◽  
The Mean ◽  
Leaf N Content ◽  
Leaf N

Climate, nitrogen (N) and leaf area index (LAI) are key determinants of crop yield. N additions can enhance yield but must be managed efficiently to reduce pollution. Complex process models estimate N status by simulating soil-crop N interactions, but such models require extensive inputs that are seldom available. Through model-data fusion (MDF), we combine climate and LAI time-series with an intermediate-complexity model to infer leaf N and yield. The DALEC-Crop model was calibrated for wheat leaf N and yields across field experiments covering N applications ranging from 0 to 200 kg N ha−1 in Scotland, UK. Requiring daily meteorological inputs, this model simulates crop C cycle responses to LAI, N and climate. The model, which includes a leaf N-dilution function, was calibrated across N treatments based on LAI observations, and tested at validation plots. We showed that a single parameterization varying only in leaf N could simulate LAI development and yield across all treatments—the mean normalized root-mean-square-error (NRMSE) for yield was 10%. Leaf N was accurately retrieved by the model (NRMSE = 6%). Yield could also be reasonably estimated (NRMSE = 14%) if LAI data are available for assimilation during periods of typical N application (April and May). Our MDF approach generated robust leaf N content estimates and timely yield predictions that could complement existing agricultural technologies. Moreover, EO-derived LAI products at high spatial and temporal resolutions provides a means to apply our approach regionally. Testing yield predictions from this approach over agricultural fields is a critical next step to determine broader utility.

scholarly journals Helium, [Fe/H] Abundances and the HR (Log TEFF, MBol) Diagram With Hipparcos Data of The Four Nearest Open Clusters: Hyades, Coma Berenices, The Pleiades and Praesepe

1998 ◽  
Vol 11 (1) ◽  
pp. 565-565
Author(s):  
G. Cayrel de Strobel ◽  
R. Cayrel ◽  
Y. Lebreton
Keyword(s):  
Main Sequence ◽  
Open Clusters ◽  
Main Sequence Stars ◽  
Spectroscopic Analyses ◽  
Solar Metallicity ◽  
Metal Abundances ◽  
The Mean ◽  
The Moment ◽  
The One ◽  
Best Fit

After having studied in great detail the observational HR diagram (log Teff, Mbol) composed by 40 main sequence stars of the Hyades (Perryman et al.,1997, A&A., in press), we have tried to apply the same method to the observational main sequences of the three next nearest open clusters: Coma Berenices, the Pleiades, and Praesepe. This method consists in comparing the observational main sequence of the clusters with a grid of theoretical ZAMSs. The stars composing the observational main sequences had to have reliable absolute bolometric magnitudes, coming all from individual Hipparcos parallaxes, precise bolometric corrections, effective temperatures and metal abundances from high resolution detailed spectroscopic analyses. If we assume, following the work by Fernandez et al. (1996, A&A,311,127), that the mixing-lenth parameter is solar, the position of a theoretical ZAMS, in the (log Teff, Mbol) plane, computed with given input physics, only depends on two free parameters: the He content Y by mass, and the metallicity Z by mass. If effective temperature and metallicity of the constituting stars of the 4 clusters are previously known by means of detailed analyses, one can deduce their helium abundances by means of an appropriate grid of theoretical ZAMS’s. The comparison between the empirical (log Teff, Mbol) main sequence of the Hyades and the computed ZAMS corresponding to the observed metallicity Z of the Hyades (Z= 0.0240 ± 0.0085) gives a He abundance for the Hyades, Y= 0.26 ± 0.02. Our interpretation, concerning the observational position of the main sequence of the three nearest clusters after the Hyades, is still under way and appears to be greatly more difficult than for the Hyades. For the moment we can say that: ‒ The 15 dwarfs analysed in detailed in Coma have a solar metallicity: [Fe/H] = -0.05 ± 0.06. However, their observational main sequence fit better with the Hyades ZAMS. ‒ The mean metallicity of 13 Pleiades dwarfs analysed in detail is solar. A metal deficient and He normal ZAMS would fit better. But, a warning for absorption in the Pleiades has to be recalled. ‒ The upper main sequence of Praesepe, (the more distant cluster: 180 pc) composed by 11 stars, analysed in detail, is the one which has the best fit with the Hyades ZAMS. The deduced ‘turnoff age’ of the cluster is slightly higher than that of the Hyades: 0.8 Gyr instead of 0.63 Gyr.

scholarly journals Crystal structure of 2-nitro-N-(5-nitro-1,3-thiazol-2-yl)benzamide

2014 ◽  
Vol 70 (12) ◽  
pp. o1252-o1252 ◽  
Author(s):  
Rodolfo Moreno-Fuquen ◽  
Diego F. Sánchez ◽  
Javier Ellena
Keyword(s):  
Crystal Structure ◽  
Hydrogen Bonds ◽  
Title Compound ◽  
Dihedral Angles ◽  
Two Dimensional ◽  
Compound C ◽  
Dimensional Network ◽  
Benzene Rings ◽  
The Mean ◽  
Amide Fragment

In the title compound, C10H6N4O5S, the mean plane of the non-H atoms of the central amide fragment C—N—C(=O)—C [r.m.s. deviation = 0.0294 Å] forms dihedral angles of 12.48 (7) and 46.66 (9)° with the planes of the thiazole and benzene rings, respectively. In the crystal, molecules are linked by N—H...O hydrogen bonds, forming chains along [001]. In addition, weak C—H...O hydrogen bonds link these chains, forming a two-dimensional network, containingR44(28) ring motifs parallel to (100).

PARAMETER ESTIMATION ON HURDLE POISSON REGRESSION MODEL WITH CENSORED DATA

2012 ◽  
Vol 57 (1) ◽  
Author(s):  
SEYED EHSAN SAFFAR ◽  
ROBIAH ADNAN ◽  
WILLIAM GREENE
Keyword(s):  
Regression Model ◽  
Count Data ◽  
Poisson Regression ◽  
Goodness Of Fit ◽  
Poisson Model ◽  
Likelihood Method ◽  
Poisson Regression Model ◽  
Response Variable ◽  
The Mean ◽  
Over Dispersion

A Poisson model typically is assumed for count data. In many cases, there are many zeros in the dependent variable and because of these many zeros, the mean and the variance values of the dependent variable are not the same as before. In fact, the variance value of the dependent variable will be much more than the mean value of the dependent variable and this is called over–dispersion. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, it is suggested to use a hurdle Poisson regression model to overcome over–dispersion problem. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle Poisson regression model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness–of–fit for the regression model is examined. We study the effects of right censoring on estimated parameters and their standard errors via an example.

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