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Showing 2 results for balyani

Yadollah Balyani, Mohammad Saligheh, Hossein Asakereh, Mohammad Hossein Nasserzadeh,
Volume 15, Issue 37 (9-2015)
Abstract

Precipitation is one of the most intractable elements. The oscillating behavior of the crucial environmental planning (explicit and tacit knowledge of the behavior), is the key variable. Spectrum analysis techniques to understand the behavior of overt or covert methods suitable for the extraction and analysis of climate oscillations with different wave lengths. The size range of the distribution variance across all wave lengths may provide time series. In this study, data from 37 stations Heleh and Mond watershed (both rain and synoptic) from its inception until 2011,  who had over 30 years of data, to analyze the cycle of annual rainfall, interest has been taken. So that the space is 3-2 year cycles in every area of study, the highest annual rainfall events are returned. On this basis, the Story of annual precipitation 95 percent for each of the stations under study and cycle meaningful estimate of the time series of basin data were extracted.
Saeed Balyani,
Volume 16, Issue 43 (16 2016)
Abstract

Knowing of precipitation values in different regions is always of main and strategic issues of human which has important role in short- term and long-term decisions. In order to determine of precipitation model and forecasting it, there are different models, but given that the precipitation data have a spatial autocorrelation, the spatial statistic is a powerful tool to recognition of spatial behaviors. In this research, for determine of precipitation model and predicting of it with geographical factors e.g. altitude, slope and view shade and latitude- longitude by using spatial regressions analysis such as ordinary least squares (OLS) and geographical weighted regressions(GWR), 13 synoptic stations of Khuzestan province from establishment to 2010 were used. Results showed a powerful correlation between precipitations with geographical factors. Also results of modeling through OLS and GWR representative that forecasting of GWR is close to reality, so that in GWR, the sum of errors of residuals is less, the AWT IMAGE is more and there aren't any spatial autocorrelation in residuals and the residuals are normal. The AWT IMAGEof OLS can only justify 75 percent of precipitation variations with spatial factors while in GWR this quantity is 82- 97 percent. Accordingly, it was found that, in east, northeast and north of province the altitudes, in east and northeast and Zagros Mountains the view shade and slope are the most important spatial factors, respectively.



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