introduction rainfall is considered as one of the most important factures in water cycle. prediction of monthly rainfall is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins. rainfall prediction in each area is mediated by punctual data measured as humidity, temperature, wind speed and etc. as iran i...

BACKGROUND The relationship between traffic emissions and mobile-source air pollutant concentrations is highly variable over space and time and therefore difficult to model accurately, especially in urban settings with complex terrain. Regression-based approaches using continuous real-time mobile measurements may be able to characterize spatiotemporal variability in traffic-related pollutant co...

Background: Brucellosis (Malta fever) is a major contagious zoonotic disease, with economic and public health importance. Methods: To assess the effect of meteorological (temperature, rainfall, humidity, and wind) and climate parameters on incidence of brucellosis, brucellosis distribution and meteorological zoning maps of Zanjan Province were prepared using Inverse Distance Weighting (IDW) an...

Introduction Knowledge of snow parameters is important for climatology, meteorology, hydrology, flood prevention and hydropower industry. Liquid water in a snow pack shows a dominant effect on reflection, absorption and transmission of electromagnetic waves especially in microwave region. Liquid water in snow plays a major role in metamorphism, mechanics and hydrology of snow, and in soil engin...

Analysing tree susceptibility to uprooting one has to compare external power acting on a tree with its resistance to uprooting (critical moment). The critical uprooting moment for a tree depends on both plant parameters and substratum. Results of an assessment of critical moments of studied pine and black alder tree stands are presented in this paper. Field studies consisted of uprooting trees ...

Hidden Markov models form an extension of mixture models providing a ex-ible class of models exhibiting dependence and a possibly large degree of variability. In this paper we show how reversible jump Markov chain Monte Carlo techniques can be used to estimate the parameters as well as the number of components of a hidden Markov model in a Bayesian framework. We employ a mixture of zero mean no...