ALIREZA Arabameri; khalil rezaei; mojtaba yamani
Abstract
Gully erosion is one of the erosive processes that mostly change the shape of the earth surface and has severe environmental and economic damages. The aim of this research is modeling between geo-environmental parameters effective in gully erosion and gully occurrence in the study area and gully erosion ...
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Gully erosion is one of the erosive processes that mostly change the shape of the earth surface and has severe environmental and economic damages. The aim of this research is modeling between geo-environmental parameters effective in gully erosion and gully occurrence in the study area and gully erosion susceptibility mapping using evidential belief function (EBF) data driven model in toroud watershed that has high susceptibility to gully erosion. At first, a gully erosion inventory map is prepared, using extensive field surveys and 80 gullies which have been identified, 70 percentage (56 gully location) randomly selected to modeling, while the remaining 30 percentage (24 gully location) are used to validation. In modeling, if there was high correlation among parameters, reduce accuracy of model, thus has done multi-collinearity test among independent variables. Tolerance and the variance inflation factor (VIF) are two important indexes for multi-collinearity diagnosis. Finally 15 parameters including geomorphological, geological, environmental and hydrological are selected for modeling. In evidential belief function model four relationships were calculated: belief (Bel), disbelief (Dis), uncertainty (Unc), and plausibility (Pls) and belief function are used for gully erosion susceptibility mapping. Area under the curve are used for model validation. According to results, EBF model with prediction rate (1) and success rate (0.959) had excellent accuracy and capability in identification of prone areas to gully erosion in study area. The results indicates that 21.79 percentage (90.84 km2) in study area located in high and very high susceptibility class.
ALIREZA Arabameri; kourosh shirani; khalil rezai; mojtaba yamani
Abstract
landslides situation recognized using interpreting the aerial photos and extensive field measurements. Among total number of 200 identified landslides, %70 (140 landslides) of them have been utilized for model executing and %30 (60 landslides) of them for verification randomly. This research criteria ...
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landslides situation recognized using interpreting the aerial photos and extensive field measurements. Among total number of 200 identified landslides, %70 (140 landslides) of them have been utilized for model executing and %30 (60 landslides) of them for verification randomly. This research criteria including geomorphological parameters, hydrological parameters , geological parameters and environmental parameters . The Shannon’s entropy model have been used for defining the criteria weight and Area density model for defining classes weight, then the regionalization map obtained by combining the criteria and classes weight in ArcGIS 10.2 software environment and classified to 5 classes very little, little , moderate, high and very high according to natural fractures. The Roc curve have been used for model verification. The clerical accuracy results indicated that the compound model have the high accuracy 0.877 (87.7%) for identifying the regions susceptible to landslide. According to the results, slope length, slope and topography wetness index have had the most effect in occurring the landslide. Among total area of region (168547 hectar), 27.39% (46165.02 hectar) have been placed in high and very high sensitive. The prepared regionalization map can be useful for planning land use and building the infrastructure installations such as road.
