In this study, long-term annual and monthly trends in rainfall amount, number of rainy days and maximum precipitation in 24 h are investigated based on the data collected at 33 synoptic stations in Iran. The statistical significance of trend and climate variability is assessed by the Mann-Kendall test. The Linear trend analysis and the Mann-Kendall test indicate that there are no significant linear trends in monthly rainfall at most of the synoptic stations in Iran.

ABSTRACT:The purpose of the present study is to determine bioclimatic zones in Isfahan province using multivariate statistical method. Thirty-nine climatic variables, which were more important in plant ecological conditions (especially Artemisia sieberi and Artemisia aucheri that include more than half of rangeland surface in Isfahan province), were selected and investigated with factor analysis. Results of factor analysis showed the first three factors that explain 92.3% of total variance in selected variables were precipitation, temperature and radiation and wind with 41.91, 40.18 and 10.23% of variance, respectively. According to results and using hierarchical cluster analysis in Ward's method, bioclimatic classification in Isfahan province was performed and seven bioclimatic zones were found. In addition, to compare the results of this study with the other climatic classification methods, Isfahan province was classified by four traditional climatic classification methods (Koppen, Gaussen, Emberger and De Martonne) and its results were compared to climatic classification by multivariate statistical method. It showed that multivariate statistical method gives better classification in comparison with other methods. Beside that precipitation is the most important factor in vegetation distribution of humid and cold and sub-humid and cold regions in west and south parts of Isfahan province. In addition, temperature is the most important factor in vegetation distribution of hyper warm-arid and warm-arid climatic regions in eastern low elevation parts of province. Furthermore, dominant species were determined for each climatic region.

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This study aimed to investigate the vegetation production changes in Khuzestan province, Iran using MODIS data production, meteorological data, vegetation maps as well as topographic and field monitoring data in CASA model. The study area was divided into different climatic classes based on multivariate statistical method, so the vegetation of each climatic region was examined separately for changes in NPP values. Production changes due to degradation were calculated using the Miami model and subsequently, the rain use efficiency (RUE) and the light use efficiency (LUE) and correlation indices between the CASA model and ground data were determined. The results of this study (R2) showed that the accuracy of this model varies depending on the type of climatic regions (R2 = 80 to R2 = 15). In different climatic regions, the rate of NPP changes (very humid 68 gC/m2 to ultra-dry 15 gC/m2) varies in rangeland types. The highest rate of vegetation production is observed seasonally in May. Degradation conditions also reduced RUE and LUE. However, in hyper-arid regions, adaptations of plants in some different species (Hammada sp.) increase their efficiency compared to other vegetation types. The results showed the importance of vegetation and climate classification in vegetation production studies.