Sediment yield estimation using a semi-quantitative model and GIS-remote sensing data
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Department of Soil Science, Agriculture Faculty, Shahid Bahonar University of Kerman, Kerman, Iran
Int. Agrophys. 2011, 25(3): 241-247
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ABSTRACT
This study applies the MPSIAC semi-quantitative model along with geographical information system and remote sensing techniques to estimate sediment yield in a semi-arid region in central Iran. Nine data layers of the model were generated from Landsat ETM+ imagery, adapted regional maps and field surveys. The GIS was applied to integrate the layers together and generate the sediment yield map. The results showed a range of sediment yield from 263.3 to 496.9 t km-2 year-1 with an average of 356.4 t km-2 year-1. However, it seems that descriptions of the model are sometimes too broad for making reliable scoring. Nevertheless, this model is generally less data demanding and provides an efficient way to estimate sediment yield in ungauged basins. It was found that hills are the most sensitive land types to sediment yield in the region.