Sima Pourhashemi; mehdi boroghani; abolghasem Amirahmadi; MohamadAli Zanganeh Asadi; Mahdi Salhi
Abstract
Due to the drought and land use changes in recent years, dust storm phenomenon in Iran has increased. The purpose of this research is to identify and prioritize dust source areas using bivariate models (probability model of event weight and frequency ratio model) in R software environment and determine ...
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Due to the drought and land use changes in recent years, dust storm phenomenon in Iran has increased. The purpose of this research is to identify and prioritize dust source areas using bivariate models (probability model of event weight and frequency ratio model) in R software environment and determine the importance of each of the environmental factors affecting it in Khorasan Razavi province. To this porpuse, 65 dust extraction points were identified in the study area and a dust distribution map was prepared. Then maps of each of the factors influencing the occurrence of dust including soil maps, lithology, slope, vegetation index (NDVI), distance from the river, geomorphology and land use were prepared. Using the frequency and event weighting models, the weight of each effective factor and the relationship between each of the factors and the points of dust source were determined and, finally, priority maps of the dust source areas were prepared for the case study. Models were evaluated using the ROC curve. According to the results of both models, geomorphology units, land use and slope have the most effect on the occurrence of dust in the region, and both models have a frequency ratio and event weight with a sub-curve of 0.818 and 0.825, respectively. They accept.
mahvash gholami; karim soleymani; esmaeil nekoee
Abstract
Landslide is one of the major natural hazards caused financial losses, in lives and destruction of natural resources each year. The aim of this study was comparisons of three models, namely WofE, FR and DSH to the determination of the landslide prone areas in Sari-Kiasar watershed. In the first, 105 ...
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Landslide is one of the major natural hazards caused financial losses, in lives and destruction of natural resources each year. The aim of this study was comparisons of three models, namely WofE, FR and DSH to the determination of the landslide prone areas in Sari-Kiasar watershed. In the first, 105 landslides occurred in the study area were collected based on aerial photographs in the 1:25,000 scale and field studies divided into two group haphazardly to generate training 75% and testing 25% dataset. Then, 17 landslide conditioning factors including geological, geomorphological, hydrological and anthropogenic were prepared to spatial relationship with landslide occurrence in the study area. The most important factors in the occurrence of landslides in the study area were rainfall followed by slope and vegetation. The validation results as a percentage of the cumulative area under the curve (AUC) showed that the success rate of WofE, FR and DSH models are 92.05, 92.05 and 91.31 percent respectively and the prediction rate are 92.72, 92.73 and 85.44 percent respectively. The results show that in terms of the accuracy of the model used to base on success rate, three models are placed in excellent group (0.9 to 1), also in terms of the accuracy of the model used to base on prediction rate, WofE, FR models are placed in excellent group (0.9 to 1) and DSH is placed in good group (0.8 to 0.9). The results showed that the WofE and FR model have a higher prediction accuracy than of DSH model.
