Evaluating the Effect of Digital Elevation Model, Geostatistical Method and Vegetation Indices in Estimating Soil Erosion (Case Study: Rimeleh Watershed)
Subject Areas : Agriculture, rangeland, watershed and forestry
Saleh Arekhi
1
*
,
Afshin Shabani
2
,
Sayed Hussein Roshun
3
,
Benyamin Eshghi
4
1 - Associate Professor, Department of Geography, Faculty of Humanities, University of Golestan, Gorgan, Iran
2 - MSc. Remote Sensing and GIS, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
3 - Departement of watershed management engineering, faculty of natural resources, sari agricultural sciences and natural resources university
4 - MSc. Student in Geographic Information System, Department of Surveying Engineering, Faculty of Engineering Lamei Gorgani Institute of Higher Education, Gorgan, Iran
Keywords: Soil Loss, Sustainable Development, GIS, RS, RUSLE.,
Abstract :
Soil erosion is one of the important problems of watersheds in the country and is considered as one of the most important obstacles to achieving sustainable development of agriculture and natural resources. The high accuracy of the input parameters of the RUSEL model leads to a more accurate estimation of soil loss and erosion. In this study, while integrating the RUSLE model with remote sensing (RS) and geographic information system (GIS), parameters of rainfall erosivity (R), vegetation cover (C) and slope and length (LS) were prepared with different methods. In this way, the rainfall erosivity factor was obtained based on 25 years of data, 13 rain gauge stations and ordinary, simple and universal kriging methods. Vegetation factor was also produced based on NDVI, IPVI and NDBI indices using Landsat 8 satellite images. The length factor and slope were also prepared based on the SRTM DEM with 30- and 90-meters and NED with 10 meters. Finally, with 9 combinations, the amount of erosion and sediment estimated with the RUSLE model in the watershed. The results showed that the mean soil loss, the composition of the NDBI index, the length and slope steepness obtained from the NED with 10 meters resolution and the rainfall erosivity factor obtained from the simple kriging method is equal to 16.84 (t/y). And compared to the observed sediment (16.5 t/y). Based on this, the NDBI index in combination with other factors is more effective than the NDVI index in preparing the cover factor of the RUSLE model.
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