Studied potash-bearing evaporites are situated in the northern parts of the GREAT KAVIR desert, south of Semnan city. These deposits, which could be classified as Mg-SO4 poor salts, belong to the lower parts of the Miocene Upper Red Formation. As well as halite, which is the main mineral, they contain primary sylvite and carnallite, and some secondary K-Mg bittern salts such as polyhalite, d'ansite and langbeinite. Surface and bottom nucleated chevron, cornet and cumulative textures in halite and sylvite indicates their early crystallization from parent brines in the shallow evaporitic ponds. Secondary K-bearing salts, which have been formed during shallow burial diagenesis, are polyhalite, d'ansite and langbeinite. High bromine contents, simple mineralogical paragenesis of these salts and their association with marine carbonates indicate their marine origin. Accordingly, a subsidizing relatively shallow marginal marine BASIN, under domination of arid climate, could be suggested for sedimentary environment of these evaporites.

GREAT KAVIR BASIN is the largest inner BASIN in Iran that extended about 90000 km2.This BASIN is situated in the centre of Iran, to the south from Alborz mountain range and elongated in the sub latitudinal trend and its construction is asymmetric. The BASIN cover consists generally of complicated sequence of continental - marine Oligocene - Miocene molasses. According to drainage systems conditions, molassoid cycles, alluvial, alluvial- deltaic and lacustrine sediments, climate, morphological conditions and metallogenic and structural features, GREAT KAVIR depression generally is favorable for exogenic and surficial uranium deposits (vally-fill, flood plain, deltaic and playa). Uranium occurrences that are known in the southern and north eastern part of the margent GREAT KAVIR BASIN, are Arosan, Irekan and Mohammad Abad. Similar geological - structural conditions for uranium mineralization is possible in the margent of GREAT KAVIR BASIN.

Geomorphic indices of active tectonics are useful tools to analyze the influence of active tectonics in an area. These indices have the advantage of being calculated using ArcGIS and RS (Remote Sensing) packages over large areas as a reconnaissance tool to identify geomorphic anomalies possibly related to active tectonics. This is particularly valuable in GREAT Karoun River BASIN of Zagros, where relatively little work on active tectonics based on this method was done. The study area in central Zagros fold- thrust-belt of the southwestern Iran is an area with NW–SE oriented structures provides an ideal location for testing the concept of an index to predict relative tectonic activity on a basis of river system or mountain front. Based upon values of the stream length-gradient index (SL), drainage BASIN asymmetry (Af), hypsometric integral (Hi), ratio of valley-floor width to valley height (Vf), index of drainage BASIN shape (Bs), and index of mountain front sinuosity (Smf), overall index as index of relative active tectonic (Iat) was resulted that is a combination of the other indices. This indices are used to divide the landscape into four classes of relative tectonic activity. After measuring indices it is concluded that this part of the Zagros zone has variable rates of active tectonics. Based on corrected Iat values, the study area was divided into three parts: class 1 (very high relative tectonic activity, %24 in area; such as some parts of the east and central zone where Main Zagros Reverse Fault and Dezful embayment fault have the most influence); class 2 (high relative tectonic activity, 63% in area; such as most parts of the area in east, west, north and center where action of faults are lower than the previous class); class 3(moderate, 10% in area; such as most parts of the area in north and south where action of faults are the lowest). Therefore, we don’t have class 4 in this area, and 1% of BASIN is not measured for the indices because it is located in coastal plain of Khuzestan.

Schizoyhorax pelzami is a member of Cyprinid family in the Dahst-e-KAVIR and Hari River BASINs of Iran. According to importance of osteological characters for taxonomy of fish species and lacking any information regarding osteological features of S. pelzami, this study was conducted to provide the detailed osteological characters. For this purpose, specimens were cleared and stained by alcian blue and alizarin red. Their skeletal structures were photographed using a scanner equipped with a glycerol bath. Drawing and nomenclature of the skeletal elements were done and studied under a stereomicroscope. Base on the results, S. pelzami species is distinguished from other species of this genus by having (1) 44 vertebrae, (2) a long nasal bone, (3) an anal fin with anterior position (close to 27th centrum), (4) a broader posterior part of basibranchial, (5) a flat posterior margin of urohyal and (6) lack a pre-palatine.

In this study by data of synoptic stations in Karoon BASIN, the intensive showers with 1, 2, 6 and 9 hour duration have been extracted and the precipitation time regime has been evaluated by ranking method and non dimensional accumulation curve. In ranking method, first the showers of each time base have been divided to smaller periods and on this basis different periods of showers have been ranked according to the amount of received precipitation. In accumulating curve method, the showers of all specific time bases have been depicted in non dimensional form and the regression line as a representative and the mean of all the showers has been implemented. The results of two mentioned methods show that the peak of shower precipitation occurred in 25 percent of first time and 25 percent of second time of precipitation. This means the dominant structure in the chosen time bases in the studied BASIN are the first and second quarter of showers.

A preliminary stock assessment of Artemia sp. has been carried out in Gonabad salt-waters, situated in the KAVIR-e-Namak BASIN of eastern Iran for the first time. We conducted seasonal analysis of physico-chemical and biological properties of salt-waters for two stations in the study area over the year 2002. Hand-held plankton net used with a mesh size of 20mm to collect phytoplankton samples. We identified five families of phytoplankton in the salt-waters of the area. These were Nitzschiaceae, Naviculaceae, Cymbellaceae, Oscillatoriaceae and Nostocaceae. Phytoplankton-species from family Nitzschiaceae were the most abundant, present in the waters -year-round and comprised the main food item for Artemia sp in the region.Phytoplankton abundance was highest during spring and earlier autumn and Artemia sp. showed -a fluctuation in their, density over the year, increasing gradually from spring to winter in one station and from spring to autumn in another. Considering the optimal physico-chamical and-biological properties for Artemia sp. production and, development, we concluded-that the best time period for Artemia sp. production is May to November in Kaleshor area.

Rainfall is considered a highly valuable climatologic resource, particularly in arid regions. As one of the primary inputs that drive watershed dynamics, rainfall has been shown to be crucial for accurate distributed hydrologic modeling. Precipitation is known only at certain locations; interpolation procedures are needed to predict this variable in other regions. In this study, the ordinary cokriging (OCK) and collocated cokriging (CCK) methods of interpolation were applied for rainfall depths as the primary variate associated with elevation and surface elevation values as the secondary variate. The different techniques were applied to monthly and annual precipitation data measured at 37 meteorological stations in the Central KAVIR BASIN. These sequential steps were repeated for the mean monthly rainfall of all twelve months and annual data to generate rainfall prediction maps over the study region. After carrying out cross validation, the smallest prediction errors were obtained for the two multivariate geostatistical algorithms. The cross validation error statistics of OCK and CCK presented in terms of root mean square error (RMSE) and average error (AE) were within the acceptable limits for most months. Then the two approaches were compared to select of the most accurate method (AE close to zero and RMSE from 0.53 to 1.46 for 37 rain gauge locations for all months). The exploratory data analysis, variogram model fitting, and generation precipitation prediction map were accomplished through use of ArcGIS software.

The purpose of this study is to detect structural fractures utilizing Landsat satellite data. Based on the regional fault-related morphologies, different techniques were utilized to detect fault lines and fractures. Several image (159-35, 159-36, 160-35, 160-36, 161-35, and 161-36) taken by Landsat ETM+images were used. The first method for detection of fault lines, lithological interruption and displacements due to faulting was the RGB technique and Grayscale images. In addition, to optimize the RGB composition, the OIF (Optimum Index Factor) formula was applied. In the next step, the resulting image merged with panchromatic band for increase the spatial resolution. The third utilized method was the NDVI technique, which was used to reconstruct the vegetation in studied region. The forth technique was applying Sunangel directional filters to detect sharp edges and fault lines. As the fifth method, the Digital Elevation Model (DEM) of under study region was shined with virtual sun light from different geographic directions using Sun-shading technique and the resulting image were used to detect linear fault-related valleys and ridges. In addition, Digital Elevation Model (DEM) was utilized to develop a 3D view of the region. The sixth method was the Principal Component Analysis (PCA), after which the PC1 was selected as the most suitable component for detecting fault lines. The seventh applied method was the Band Ratio technique, which was implemented in two steps. First, each fault line was detected separately in Grayscale images. Second, all fault lines were detected together in one RGB false color composite. Finally the Structural Map of GREAT KAVIR fault was constructed using the fractures detected by the above mentioned techniques.