Refinements on a GIS-Based, Spatially Distributed Rainfall-Runoff Model for a Small Watershed

This research addresses the problem of predicting the direct runoff generated by precipitation falling over a small watershed using an existing rainfall-runoff model. The model consists of several separate modules, which process data describing the spatial variation of watershed properties, and compute the runoff time series at the watershed outlet. Data processing and visualization is handled primarily by GIS software, while computer programs perform the bulk of the computations. The model is designed to operate a simply and generally as possible, requiring only four external data sets as input (Digital Elevation Model (DEM), land coverage, soil coverage, and incremental precipitation depths) to create all other data needed to compute the direct runoff for the watershed under study. Our goal is to improve the model by refining the existing programs and increasing the level of spatial distribution.To achieve this goal, we focus our research on the following three objectives: testing and refining the existing model; developing a hydraulic flow routing module using the Kinematic Wave model; and exploring the possibility of calibrating the model results to the actual soil moisture conditions present in the watershed during the time of interest by modifying the SCS curve number values across the watershed. We consider Little Pine Creek watershed located in Allegheny County as our case study, and compare the model's predictions for two separate precipitation events with the direct runoff hydrographs given by a USGS stream gauge located at the outlet of the Little Pine Creek watershed. Based on the results of our investigation we identify and correct several problems with the existing model, and provide a better understanding of how the model responds under varying conditions and assumptions. We show that the Kinematic Wave flow routing model does not work well with our model because is cannot account for storage within the watershed. We also develop an effective method for calibrating the volume of runoff predicted by the model to that given by the USGS stream gauge by adjusting the SCS curve number values in the watershed to reflect that actual soil moisture conditions present at the time of interest, guaranteeing that fluid mass is conserved between our model predictions and reality

Trends in International Maths and Science Study (TIMSS) 2019 National Report for England

The Trends in International Mathematics and Science Study (TIMSS) is a survey of the educational achievement of pupils in years 5 and 9 organised by the International Association for the Evaluation of Educational Achievement (IEA). The report provides analysis of the TIMSS 2019 findings for England and compares England’s performance to performance in other participating countries

Modelling the light variability of the Ap star epsilon Ursae Majoris

We simulate the light variability of the Ap star epsUMa using the observed surface distributions of Fe, Cr, Ca, Mn, Mg, Sr and Ti obtained with the help of Doppler Imaging technique. Using all photometric data available we specified light variations of epsUMa modulated by its rotation from far UV to IR. We employed the LLmodels stellar model atmosphere code to predict the light variability in different photometric systems. The rotational period of epsUMa is refined to 5d088631(18). It is shown that the observed light variability can be explained as a result of the redistribution of radiative flux from the UV spectral region to the visual caused by the inhomogeneous surface distribution of chemical elements. Among seven mapped elements, only Fe and Cr significantly contribute to the amplitude of the observed light variability. In general, we find a very good agreement between theory and observations. We confirm the important role of Fe and Cr to the magnitude of the well-known depression around 5200 \AA\ through the analysis of the peculiar $a$-parameter. Finally, we show that the abundance spots of considered elements cannot explain the observed variability in near UV and $\beta$ index which are likely due to some other causes. The inhomogeneous surface distribution of chemical elements can explain most of the observed light variability of the A-type CP star epsUMa.Comment: Accepted in A&A, 10 pages, 9 figures, 3 table

Carbon Stars in the Hamburg/ESO Survey: Abundances

We have carried out a detailed abundance analysis for a sample of 16 carbon stars found among candidate extremely metal-poor (EMP) stars from the Hamburg/ESO Survey. We find that the Fe-metallicities for the cooler C-stars (Teff ~ 5100K) have been underestimated by a factor of ~10 by the standard HES survey tools. The results presented here provided crucial supporting data used by Cohen et al (2006) to derive the frequency of C-stars among EMP stars. C-enhancement in these EMP C-stars appears to be independent of Fe-metallicity and approximately constant at ~1/5 the solar C/H. The mostly low C12/C13 ratios (~4) and the high N abundances in many of these stars suggest that material which has been through proton burning via the CN cycle comprises most of the stellar envelope. C-enhancement is associated with strong enrichment of heavy nuclei beyond the Fe-peak for 12 of the 16 stars. The remaining C-stars from the HES, which tend to be the most Fe-metal poor, show no evidence for enhancement of the heavy elements. Very high enhancements of lead are detected in some of the C-stars with highly enhanced Ba. (We show that) the s-process is responsible for the enhancement of the heavy elements for the majority of the C-stars in our sample. We suggest that both the s-process rich and Ba-normal C-stars result from phenomena associated with mass transfer in binary systems. This leads directly to the progression from C-stars to CH stars and then to Ba stars as the Fe-metallicity increases. (abridged and slightly edited to shorten)Comment: AJ, in press, submitted 13 Dec, 2005, accepted 21 March 200

A Comprehensive Spectral and Variability Study of Narrow-Line Seyfert 1 Galaxies Observed by ASCA: II. Spectral Analysis and Correlations

(Abridged) I present a comprehensive and uniform analysis of 25 {\it ASCA} observations from 23 Narrow-line Seyfert 1 galaxies. The spectral analysis and correlations are presented in this paper, Part 2; the reduction and time series analysis is presented in the companion paper, Part 1.Comment: 73 pages, 31 figures, accepted for publication in ApJS. Report also available at http://www.astro.columbia.edu/~leighly/research.htm

On the Internal Structure of Relativistic Jets

A magnetohydrodynamic model is constructed for a cylindrical jet immersed in an external uniform magnetic field. It is shown that, as in the force-free case, the total electric current within the jet can be zero. The particle energetics and the magnetic field structure are determined in a self-consistent way; all jet parameters depend on the physical conditions in the external medium. In particular, we show that a region with subsonic flow can exist in the central jet regions. In actual relativistic jets, most of the energy is transferred by the electromagnetic field only when the magnetization parameter is sufficiently large, $\sigma>10^6$. We also show that, in general, the well-known solution with a central core, $B_z = B_0/(1+\varpi^2/\varpi_c^2)$, can not be realized in the presence of an external medium.Comment: 19 pages, 2 figure

Of monkeys and men:Impatience in perceptual decision-making

For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set decision standard throughout the decision process. Based on the theoretical argument of reward rate maximization, some authors have recently suggested that decision makers become increasingly impatient as time passes and therefore lower their decision standard. Indeed, a number of studies show that computational models with an impatience component provide a good fit to human and monkey decision behavior. However, many of these studies lack quantitative model comparisons and systematic manipulations of rewards. Moreover, the often-cited evidence from single-cell recordings is not unequivocal and complimentary data from human subjects is largely missing. We conclude that, despite some enthusiastic calls for the abandonment of the standard model, the idea of an impatience component has yet to be fully established; we suggest a number of recently developed tools that will help bring the debate to a conclusive settlement

Adaptation and visual search in mammographic images

Abstract Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the im-ages. The stimuli were randomly selected sections from nor-mal mammograms previously classified with BIRADS Den-sity scores of Bfatty ^ versus Bdense, ^ corresponding to differ-ences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in vi-sual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corre-sponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was random-ly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background tex-ture. Our results are consistent with the hypothesis that adap-tation allows observers to more effectively suppress the spe-cific structure of the background, thereby heightening visual salience and search efficiency