in this research prediction methods of artificial neural network and chaos theory are employed to predict daily, weekly and monthly runoff. for this, runoff series data observed at pole-kohneh located in the qareh-soo river. the nonlinear predictions of chaos are found to be in close agreement with the observed runoff, with high correlation coefficient for daily and weekly time scales. predicte...

the solar radiation received by earth surface is one of the most applicable parameter that is so important in hydrology, agriculture, meteorology and climatological modeling. because of very expensive instrument for measuring the radiation, researchers suggested many different experimental equations to estimate this parameter in different climate. seven models which are calibrated for semi-arid...

abstract angstrom-prescott equation is one of the most commonly used methods for the estimation of global solar radiation (rs) based on sunshine hours. the critical step in the application of this method's is the calibration of its coefficients for each region. although the coefficients of the equation have been calibrated in different parts of the world, the effect of different time scales has...

in this research the chaocity of precipitation time series in daily, weekly and monthly scales in the pole-kohneh and ghourbaghestan stations located in qarah-soo watershed is investigated. in order to reassure about the absence of stochastic behavior of the time series, method of surrogate data is applied. thereafter, the aperiodicity of the time series is investigated using power spectrum ana...

extended abstract introduction rainfall prediction at regional and global scales is mostly as principle component of hydro-meteorological studies in un-gauged regions. ground-based measurements of precipitation are available with high accuracy in synoptic stations. spatial distribution of operational stations is now as one of the biggest problems in the developing countries such as iran, which ...