Heavy metal contents and contamination characteristics of the water and sediment of the Khoshk River, Shiraz, Southwest Iran were investigated. The abundance of heavy metals decreases as Zn > Mn > Cr > Ni >Pb > Cu > Cd in water samples and Mn > Cr > Pb > Ni > Zn > Cu > Cd in sediments, respectively. Based on the enrichment factor and geoaccumulation index values, sediments were loaded with Cr, Zn, Pb, Cu, and Cd. Pearson correlation matrix as well as cluster and principal components analyses and analysis of variance were implemented on data from sampling sites. Based on the locations of sampling sites in clusters and variable concentrations at these stations, it was concluded that municipal, industrial, and domestic discharges in the Shiraz urban area strongly affected heavy metals concentrations in the Khoshk River water and sediment. Results obtained from principal components analysis of sediment samples showed that the high concentration of Ni was mainly from natural origin, related to the composition of parent rocks, while the elevated values of Cr, Zn, Pb, Cd, and Cu were due to anthropogenic activities.

Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected by remote sensing. This paper aims at the detection of mineral alteration induced by gas seeps in a marly limestone formation, SW Iran. For this purpose, the multispectral Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the high spatial resolution WorldView-2 (WV-2) data were utilized for mapping surficial rock alteration. In addition, the potential of Visible Near Infrared (VNIR) bands of the WV-2 and its high spatial resolution for mapping alterations was determined. Band ratioing, principal component analysis (PCA), data fusion and the boosted regression trees (BRT) were applied to enhance and classify the altered and unaltered marly limestone formation. The alteration zones were identified and mapped by remote sensing analyses. Integrating the WV-2 into the ASTER data improved the spatial accuracy of the BRT classifications. The results showed that the BRT classification of the multiple band imagery (created from ASTER and WV-2) using regions of interest (ROIs) around field data provides the best discrimination between altered and unaltered areas. It is suggested that the WV-2 dataset can provide a potential tool along higher spectral resolution data for mapping alteration minerals related to hydrocarbon seeps in arid and semi-arid areas.

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