Estimation of groundwater recharge has an essential role in water resources management. Base flow component of stream flow is one of the main recharge sources. Base flow is sometimes used as an approximation of recharge when underflow, evapotranspiration from riparian vegetation, and other sources of ground water transfer to/ or from the watershed are minimal. In this research, Honifaghan station on Honifaghan River with 415 km2 watershed area in 110 km southwestern Shiraz was selected. Recharge estimates were made using stream flow records collected during 1353-1384. The base flows were predicted by Part Program and groundwater recharges were predicted by RORA program. The result shows that Part and RORA programs show the same results with high correlation to each other. Also it is found that base flow component shows about 87 percent of stream flow in average. The study shows the importance of managing surface and groundwater together.

Image Segmentation is a fundamental approach in the field of image processing and based on user’ sapplication. This paper propose an original and simple Segmentation strategy based on the EM approach thatresolves many informatics problems about hyperspectral images which are observed by airborne sensors. In afirst step, to simplify the input color textured image into a color image without texture. The final Segmentationis simply achieved by a spatially color Segmentation using feature vector with the set of color valuescontained around the pixel to be classified with some mathematical equations. The spatial constraint allowstaking into account the inherent spatial relationships of any image and its color. This approach provideseffective PSNR for the segmented image. These results have the better performance as the segmented imagesare compared with Watershed & Region Growing Algorithm and provide effective Segmentation for theSpectral Images & Medical Images.

The Kerman region stands out as one of the most significant mining areas globally, owing to its extensive and abundant mineral resources. Bam County, situated in the southeastern Part of Kerman, has historically served as a crucial hub connecting the southeast of Iran with Sistan and Afghanistan, attributed to its distinctive geological and geomorphological characteristics. Enjoying considerable commercial and military importance since the Sassanid era, Bam County has garnered attention in archaeological research as a strategically vital region. The exploration of Bam's archaeological sites becomes imperative for historical governments, highlighting the need to investigate and comprehend ancient centers engaged in metal smelting and mining activities. Consequently, an archaeological survey of the central Part of Bam County was initiated in 2018-2019 with the specific objective of identifying metal smelting workshops and ancient mines. This article presents the outcomes of a field survey conducted in the central Part of Bam County, shedding light on evidence of metal smelting centers, furnaces, and historical mining activities. The primary research inquiries center around the chronology of mining evidence in the central Part of Bam County, the types of metals extracted, and the processes involved in metal mining and metallurgy within this region. Employing field and documentary methods, the research adopts a descriptive-analytical approach. The study identified and examined eight sites showcasing evidence of smelting and slag, one ancient mine, and two active mines. These sites have been associated with the extraction and processing of metals and elements such as tin, zinc, lead, silver, iron, and, to a lesser extent, gold. Notably, the substantial volume of zinc and zinc oxide processing in seven sites holds significance. Although cultural materials for chronological dating were absent in the investigated sites, historical sources indicate that the extraction and smelting of these metals in the region date back to at least the 3rd century AH (9th century AD) and persisted until the Qajar period