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Showing 5 results for Multiple Regression

S. S. Eslamian, A. Zarei, A. Abrishamchi,
Volume 8, Issue 1 (4-2004)
Abstract

An approach for regional low flow frequency analysis is to use multiple regression techniques for obtaining relationships between low flows with specific return periods and catchments characteristics. In this paper, this method has been used. After single-site frequency analysis for 20 stream gauging stations, homogeneity test was performed. Regional relationships between low flows with return periods 2 , 5 , 10, and 20 years and catchments characteristics were derived. For this purpose, catchment area, mean elevation, minimum elevation, shape factor, main channel length, length of main chanel from catchment centroid to outlet, forest area, mean annual rainfall, and mean catchment slope as model inputs were examined and cachment area, mean elevation, and mean catchment slope entered to the models. Finally, the mean relative error of models for different return period, 2, 5, 10, and 20 years, was computed 41.1, 41.3, 45.0, 47.2 percent, respectively that in comparison with other studies, it displays smaller errors.
M. Khalili Mahani, B. Hatami, H. Seyedoleslami, A. M. Rezaei, B. Heidari,
Volume 8, Issue 4 (1-2005)
Abstract

Elm leaf beetle were reared under controlled conditions (25± 2 oC, 70± 5%R.H. and 16L: 8D) to determine relationship between biological traits and the number of eggs per female on different hosts and to evaluate correlation between traits. U. carpinifolia, U .c. var. umbraculifera, U. glabra var. pendula and Celtis caucasica were examined as hosts. The biological traits consisted of 1st, 2nd and 3rd larval developmental times first, second, and third larval percent mortality rates prepupal and pupal developmental times male and female longevity and pre-ovipositional period recorded during experiments. The relationships between traits and the number of eggs per female were determined by multiple regression (Foreward selection and stepwise). The correlation between traits was evaluated, too. The results showed that the number of eggs per female were mostly affected by certain special traits such as 2nd and 3rd larval developmental time, pre-ovipositional period and male longevity which are distinct in different hosts and seasons.
M. J. Nazemosadat, A. Shirvani,
Volume 9, Issue 3 (10-2005)
Abstract

Since the fluctuations of the Persian Gulf Sea Surface Temperature (PGSST) have a significant effect on the winter precipitation and water resources and agricultural productions of the south western parts of Iran, the possibility of the Winter SST prediction was evaluated by multiple regression model. The time series of PGSSTs for all seasons, during 1947-1992, were considered as predictors, and the time series of MSSTs during 1948-1993, as the prrdictand. For the purpose of data reduction and principal components extraction, the principal components analysis was applied. Just the scores of the first four PCs (PC1 to PC4) that accounted for the total variance in predictor field were considered as the input file for the regression analysis. For finding the dependency of each principal component to the first time series of the PGSST, the Varimax rotation analysis was applied. The results have indicated that PC1 to PC4 respectively are the indicator of temperature changes during winter, autumn, Spring and Summer. According to the regression model, the components of PC1, PC2 and PC4 were significant at 5% level. But the components of PC3 was insignificant. The results indicated that the significant variables are held accountable for the 33.5% of the total variance in the winter PGSSTs. It became obvious that for the prediction of the winter PGSST, the PGSST during the winter of the last year has a particular importance. At the next stage, autumn and summer temperature have also a role in prediction of winter PGSST.
H. Jalilvand,
Volume 11, Issue 42 (1-2008)
Abstract

  This study was down in Forest Park of Noor. In order to determination of tree ring response to climatic variations, 35 cores were taken from dominant natural stand of common ash (Fraxinus excelsior L.). The guide of this study was finding which climatic variables are effective in the ring width growth of ash in current growing year and previous years (one, two and three years before current growing year) by multiple regression models at the North of IR-Iran. Totally, 85 annually, monthly seasons and seasonal growth climatic variations of precipitation, temperature, heat index, evapotranspiration and water balance were analyzed. The best multiple regression models were explained 83 percent of total variance of the growth of common ash. The results show that the growth of common ash was related to the previous year's climatic variations than that of the current year. The most effective role of climatic variations was due to the first and second preceding years (55%). Evapotranspiration of July and September, and precipitation of May in the second and precipitation of March in the third previous years, all were positively affected the growth of this species. This study revealed that ash is interested in warmer condition on early and middle of seasonal growth in present of available humid, and precipitation in the months of early growing season (Ordibehesht-Khordad of two previous years).


M. Shamaeizadeh, S. Soltani,
Volume 18, Issue 70 (3-2015)
Abstract

Hydrologic drought which usually affects wide regions can be studied through Low flow index. In this study, to predict hydrologic drought in North Karoon watershed, 14 stations with suitable and long enough duration data were recorded in the 1387-88 water year. Then 13 physiographic and climatic characteristics of the chosen stations were used to perform homogeneity test for cluster analysis. 7 day low flow series were calculated in each station and according to chi-square and Kolomogragh smirnov tests and parameter, 2 parameter gamma distribution was selected as the best regional distribution for this region. Therefore, a seven day low flow index was estimated using FREQ for 5,10,20,50,100 return periods. Regional analysis was performed using a multiple regression method. Moreover, flow duration curves were delineated to obtain Q95 index. Then, zoning maps for Q95، Q7,2 ،Q7,10, Q7,100 were prepared. The results of regional analysis indicated that the averages of height and slope were the two most effective parameters in low flow in this watershed. The investigation of zoning maps showed that southeastern part of this watershed experiences severe droughts compared with other parts.



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