A dynamic prediction model for time-to-peak

A simplified empirical equation is developed for widespread prediction of dynamic catchment response time. This model allows for time-to-peak prediction to evolve from static, lumped models, thereby providing a single value for any storm within a given catchment, using a single set of input parameters, that can be applied to a dynamic model, thus accounting for the variability between storm sizes and catchment moisture conditions. These dynamic prediction methods are translated to North America for the first time. This allows the concepts and prediction methods for catchment response time prediction previously established for the United Kingdom (UK), to be translated to a simple empirical equation for use in North America, through the use of selected study areas in Canada and the United States. This reconfigured model is statistically successful in both the UK and North America and allows for a straightforward implementation of dynamic time-to-peak prediction. Further, the reconfigured model introduces the use of a runoff coefficient (R_c) to encompass historical catchment wetness, increasing the ease of incorporating antecedent moisture condition into predictions.     

A new daily weather generator to preserve extremes and low-frequency variability

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series.     

An Analysis of Gsc0008.324, Newly Discovered Binary Star

A separate solution of the R *light curves was carried out using the 1998version of the Wilson's synthetic light curve code. In this paper we considered observations of Robb et al. (1999) for analysis. The photometry showed that star exhibits variable and asymmetric light curve. The asymmetric in the light curve is fitted with a spot on the surface of the hotter component. The fundamental orbital and physical parameters of this system have determined. The mass ratio is defined to be always q ≤ 1. The results indicate that the system is a late-type detached binary so that the components seem to be a very close pair of dwarfs. This revised version was published online in July 2006 with corrections to the Cover Date.     

Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models

ABSTRACT

Understanding streamflow patterns by incorporating climate signal information can contribute remarkably to the knowledge of future local environmental flows. Three machine learning models, the multivariate adaptive regression splines (MARS), the M5 Model Tree and the least squares support vector machine (LSSVM) are established to predict the streamflow pattern over the Mediterranean region of Turkey (Besiri and Baykan stations). The structure of the predictive models is built using synoptic-scale climate signal information and river flow data from antecedent records. The predictive models are evaluated and assessed using quantitative and graphical statistics. The correlation analysis demonstrates that the North Pacific (NP) and the East Central Tropical Pacific Sea Surface Temperature (Niño3.4) indices have a substantial influence on the streamflow patterns, in addition to the historical information obtained from the river flow data. The model results reveal the utility of the LSSVM model over the other models through incorporating climate signal information for modelling streamflow.     

Optimal design of flood-control multi-reservoir system on a watershed scale

Flood events have the highest damage costs and losses among natural hazards. There are different types of measures to mitigate flood damage costs and their negative consequences. Application of flood-control reservoirs or detention dams, as one of the main measures, may decrease devastating flood effects or even may cause to intensify flood damages in the watershed by a poor design with tremendous construction costs. Optimal design of a flood-control multi-reservoir system can simultaneously minimize investment costs of constructions and potential flood damage costs. This study proposes a simulation-based optimization approach to optimize the design of multi-reservoirs for flood control in the watershed by coupling the MIKE-11 hydrodynamic model and the NSGA-II multi-objective optimization model. The present approach provides the Pareto optimal solutions between two conflict objectives of minimizing total investment costs and the expected flood damage costs in the watershed. Application of the proposed model for a small watershed in central part of Iran as a case study shows that optimal designs of multi-reservoir systems can efficiently reduce construction costs, flood peaks and their corresponding damage costs at the downstream reaches of the basin.     

Input Selection Based on Information Theory for Constructing Predictor Models of Solar and Geomagnetic Activity Indices

Various phenomena with solar origin and their mutual dependence must be studied in order to predict behaviors in solar – terrestrial system. Linear statistical methods prevalent in analyzing natural systems may not be able to detect nonlinear dependencies among solar and geomagnetic processes. When relations, whether linear or nonlinear, between indices and their changes over time are revealed, better predictions can be made through appropriate modeling techniques. Selection of nonredundant input variables to build suitable models for prediction of solar and geomagnetic activity is of utmost importance. Mutual information is a tool that is capable of capturing all dependencies for detecting nonlinear relations and selecting the best subset of input variables by means of an applicable algorithm that maximizes information about the output and minimizes the shared information between inputs. High generalization power and improved interpretability of the selected inputs are the consequences of this analysis.     

Reanalysis of two eclipsing binaries: <Emphasis Type="Italic">EE</Emphasis> <Emphasis Type="Italic">Aqr</Emphasis> and <Emphasis Type="Italic">Z</Emphasis> <Emphasis Type="Italic">Vul</Emphasis>

We study the radial-velocity and light curves of the two eclipsing binaries EE Aqr and Z Vul. Using the latest version of the Wilson and Van Hamme (Computing Binary Star Observables, 2003) model, absolute parameters for the systems are determined. We find that EE Aqr and Z Vul are near-contact and semi-detached systems, respectively. The primary component of EE Aqr fills about 96% of its ‘Roche lobe’, while its secondary one appears close to completely filling this limiting volume. In a similar way, we find fill-out proportions of about 72 and 100% of these volumes for the primary and secondary components of Z Vul respectively. We compare our results with those of previous authors.     

Response surface methodology (RSM) optimization approach for degradation of Direct Blue 71 dye using CuO–ZnO nanocomposite

The present study highlights the synthesis of CuO–ZnO nanocomposite via facile hydrothermal method at 150 °C and autogenous pressure. The structural and textural features of prepared composite material was characterized by several characterization techniques such as X-ray powder diffraction, Fourier transform infrared spectroscopy, Scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The optimized prepared nanocomposite was utilized for photocatalytic degradation of aromatic Direct Blue 71 dye (DB71) under natural sunlight conditions. The catalytic activity results by CuO–ZnO nanocomposite were observed to be higher than the reagent-grade zinc oxide under visible light conditions. The response surface methodology protocol (RSM) with central composite design was optimized by different photodegradation operational parameters such as pH, dye concentration, catalyst amount, and reaction time. The optimized RSM results demonstrated that a quadratic polynomial model was found suitable to define the relation between the photocatalytic activity and operational parameters. Moreover, the observed high R ² value (0.9786) confirms a strong evaluation of experimental data. To achieve maximum DB71 degradation, optimized condition was found at 177.13 min of contact time, 3.93 solution pH, and 24.34 mg/L of dye concentration with 1.85 g/L of catalyst dose The identical optimum conditions resulted maximum 89.58% DB71 degradation.     

K- and Si-Metasomatism, Mineral Transformation and Formation of Granitoids from Basic Rocks in Qooshchi Area, NW Iran. A Mineralogical Context

The Qooshchi area lies to northwest of Orumieh Lake in western Azerbaijan, NW Iran. A basement metamorphic complex, consisting of Precambrian schists and gneisses, has been intruded by gabbres and diorites. Granitolds are grouped into five suites according to their mineralogy, texture and exposed features. The main body, pink Qooshchi granite, and apophyse-like, myrmekite-bearing granit-oids are discussed in this paper. On the basis of field observations and microscopic studies, an intensive metasonmtism has overprinted the country rocks, especially gabbros, transforming them into a more felsic composition. A prior event of intensive deformation and cataclasis preceded the metasonmtism, al-lowing the introduction of hydrothermal fluids. K-metasonmtism converted plagiuclase into K-feldspar (microdme), myrmekite, and sodic plagioclase as Si-metasomatism replaced the ferromagnesian silicates by quartz. Apophyse-like bodies within gabbros, called leucometasomatites, are formed during this process.