M. Khalaji Pirbalouty, A.r. Sepaskhah,
Volume 6, Issue 1 (4-2002)
Abstract
Probable Maximum Precipitation (PMP) is the maximum possible amount of precipitation which could occur in a gauging station, a region, or in a watershed. Probable maximum precipitation is usually estimated by two general methods: the first is synoptic method in which short period (hourly) meteorological parameters such as dew point, wind speed and air pressure are used. The second is statistical method which is based on the statistical analysis of the 24-h maximum precipitations. In this study, the amount of 24-h PMP was estimated by Hershfield, Bethlahmy and modified Bethlahmy methods using date obtained from meteorological and Ministry of Energy over 15 or more years.
The results showed that there exist large differences between statistical and synoptic methods however, there are rather smaller differences between Bethlahmy and synoptic methods. For modified Bethlahmy method, the results were multiplied by a coefficient of relative humidity. Then the calibrated 24-h PMP values were estimated for all meteorological stations of Iran and a contour map of 24-h PMP for the country was developed.
Results showed that a minimum value of 24-h PMP (110 mm) occurred in the central part of country and a maximum amount (260 mm) was found in both south and north parts of Iran.
S. Soltani , L. Yaghmaei , M. Khodagholi , R. Saboohi ,
Volume 14, Issue 54 (1-2011)
Abstract
The temporal and spatial vegetation dynamics is highly dependent on many different environmental and biophysical factors. Among these, climate is one of the most important factors that influence the growth and condition of vegetation. Of the abiotic factors affecting the geographic distribution of vegetation type, climate is probably the most important. Ecological research has traditionally aimed to generalize vegetation types that are assumed to be homogenous. Most of climatic classifications related to bioclimate are focused on limited climatic factors such as temperatue, precipitation and combination of them. As climate is a compound phenomena using limited factors cannot show the climate of a region, and as a result most climatic factors must be considered in bioclimatic classification. Therefore, a climatic study using various climatic factors could reveal the effective factors in distribution of vegetation. In order to determine bioclimatic zones in Chahar-Mahal & Bakhtiari province using multivariate statistical method, 71 climatic variables, which were more important in plant ecological conditions, were selected and evaluated by the factor analysis. The factor analysis revealed that the first three factors which explain %91.8 of total variance among the selected variables were temperature, precipitation, and radiation. According to results and using hierarchical cluster analysis in Ward’s method, bioclimatic classification in Chahar-Mahal province was carried out and 5 bioclimatic zones were found. In addition, Chahar-Mahal province was classified by 4 traditional climatic classification methods (Koppen, Gaussen, Emberger and De Martonne) and those classes were compared to climatic classes obtained by multivariate statistical method. The latter comparison was suggestive of the fact that multivariate statistical method provides a more appropriate classification in comparison to the traditional methods, specially because more dominant vegetation species could be defined for each of the newly described climatic classes. Furthermore, dominant species were determined for each climatic region.
S. H. Sadeghi, A. Allbuali, R. Ghazavi,
Volume 20, Issue 76 (8-2016)
Abstract
Nowadays, the increasing population and water demand in various sectors of agriculture, industry, drinking and sanitation has brought about tremendous pressure on groundwater resources. Changes in groundwater quality and salinity of the water resources are currently major threats to development, especially in the dry and too dry lands. The aim of this study is evaluation of the trend of changes in groundwater quality, both temporally and spatially, in Kashan plain over a period of 12 years (2002-2013) using geostatistical methods and classification methods namely Shouler and Wilcox. Thereby, Export Choice has been used and each parameter has been weighted according to its effect on water quality changes. Then, the weighted average of water quality parameters was used for zoning the drinking and agriculture water. The results showed that among the geostatistical methods, circular Kriging based on the correlation coefficient has more acceptable performance. Moreover, the results of spatial and temporal changes in water quality based on Shouler and Wilcox indicate a decrease of drink and agriculture water quality in the study area. Besides, 1.75 km2 of high quality drinkable water was annually decreased between 2002 and 2013 and replaced with moderate or poor quality water. Also, the same but more remarkable decline happened in agriculture water so that 11.06 km2 of high quality agriculture water annually diminished from 2002 to 2009 and plunged zero by 2009.
