Prediction of gully erosion susceptibilityin Seimare region using certainty factor model and importance analysis of conditioning factors

Document Type : Research Article

Authors

1 Department of watershed management engineering, Faculty of Agriculture, Lorestan University, Khoramabad

2 Ph.D Student in watershed management engineering and sciences, Lorestan University, Khormabad

3 M.Sc. Student in watershed management engineering, Lorestan University, Khormabad

Abstract

Gully erosion constitutes a major problem in natural resources management and soil conservation, which causes severe land degradation in arid and semi-arid areas. Therefore, determination of gully prone area and identification of gully conditioning factors can help to managers and decision makers to reduce the hazard of gully erosion. The aim of this study is to predictthe gully erosion susceptibility usingcertainty factor (CF) model and importance analysis of gully conditioning factors in the Seimare region, Lorestan province.At first, the raster dataset of gully erosion conditioning factors (e.g. altitude, slope degree, slope aspect, distance from river, topographic wetness index, stream power index, landuse, soil and lithology) was created using geographic information system (GIS).By means of field surveys, a total of 100 gully locations were identified and these locations were divided into two groups (1) training of the model (70% gullies), and (2) validation of the model (30% gullies).After calculation of CF and Z indices of certainty factor model and model calibration, the gully erosion susceptibility map was prepared using ArcGIS10.2. The validation of the gully susceptibility map was conducted based on the receiver operating characteristic (ROC) curve method, and validation dataset. The resulting gully susceptibility maps showed 85.6% accuracy.Therefore, it was established in this study that the CF model is promising of make accurate and reliable spatial prediction of gully susceptibility.Furthermore, the result of sensitivity analysis indicated that soil, lithology, and slope angle are most important factors in gully susceptibility prediction.
 
 

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References

 
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Iranian journal of Ecohydrology
Volume 3, Issue 1
March 2016
Pages 83-93

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History

  • Receive Date: 22 January 2016
  • Revise Date: 17 April 2016
  • Accept Date: 17 March 2016
  • First Publish Date: 20 March 2016
  • Publish Date: 20 March 2016

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