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The disposal is the final step of any hazardous waste management plan. An inappropriate landfill site may have negative environmental, economical, and ecological impacts. Therefore, landfills should be sited carefully by taking into account various rules, regulations, factors, and constraints. In this study, candidate sites for hazardous landfills in the northeastern Khorasan Razavi province are determined using the integration of geographic information system and landfill susceptibility zonation methods. For this, the inappropriate areas were first removed from the model, and the suitability of remaining regions were evaluated using 15 different criteria in two steps. With this done, nine candidate sites were selected as the most suitable locations. Finally, the selected landfill sites were proposed based on environmental impact assessment (Leopold matrix) and economical studies. This study shows that Maasumabad, Kheirabad, Mayamey, and Yonsi are the best locations for the constitution of landfill in Khorasan Razavi province, respectively.

Abstract. This paper investigates the correlation between shear wave velocity and some of the index parameters of soils, including Standard Penetration Test blow counts (SPT), FineContent (FC), soil moisture (W ), Liquid Limit (LL), and Depth (D). The study attempts to show the application of arti cial neural networks and multiple regression analysis to the prediction of the shear wave velocity (V S ) value of soils. New prediction equations are suggested to correlate VS with the mentioned parameters based on a dataset collected from Mashhad city in the north east of Iran. The results suggest that, in the case of ANN method use, highly accurate correlations in the estimation of VS are acquired. The predicted values using ANN method are checked against the real values of V S to evaluate the performance of this method. The minimum correlation coe cient obtained in ANN method is higher than the maximum correlation coe cient obtained from the MLR. In addition, the value of estimation error in the ANN method is much less than that in the MLR method, indicating the role of higher con dence coe cient of the ANN in estimating VS of soil.

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Knowing the current condition of the faults and fractures in a reservoir is crucial for production and injection activities. A good estimation of the fault reactivation potential in the current stress field is a useful tool for locating the appropriate spot to drill injection wells and to calculate the maximum sustainable pore pressure in enhanced oil recovery and geosequestration projects. In this study, after specifying the current stress state in the Gachsaran oilfield based on Anderson's faulting theory, the reactivation tendency of four faults (F1, F2, F3, and F4) in the Asmari reservoir is analyzed using 3D Mohr diagrams and slip tendency factors. Results showed that all the faults are stable in the current stress state, and F2 has the potential to undergo the highest pore pressure build-up in the field. On the other hand, F3 has the proper conditions (i.e., strike and dip referring to σ Hmax orientation) for reactivation. Stress polygons were also applied to show the effect of the pore pressure increase on fault stability, in a graphical manner. According to the results, the best location for drilling a new injection well in this part of the field is the NW side of F2, due to the lower risk of reactivation. It was found that both methods of 3D Mohr diagrams and slip tendency factors predict similar results, and with the lack of image logs for stress orientation determination, the slip tendency method can be applied. The results of such studies can also be used for locating safe injection points and determining the injection pressure prior to numerical modeling in further geomechanical studies.