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Landslides are major natural hazards which not only result in the loss of human life but also cause economic burden on the society. Therefore, it is essential to develop suitable models to evaluate the susceptibility of slope failures and their zonations. This paper scientifically assesses various methods of landslide susceptibility zonation in GIS environment. A comparative study of Weights of Evidence (WOE), Analytical Hierarchy Process (AHP), Artificial Neural Network (ANN), and Generalized Linear Regression (GLR) procedures for landslide susceptibility zonation is presented. Controlling factors such as lithology, landuse, slope angle, slope aspect, curvature, distance to fault, and distance to drainage were considered as explanatory variables. Data of 151 sample points of observed landslides in Mazandaran Province, Iran, were used to train and test the approaches. Small scale maps (1:1,000,000) were used in this study. The estimated accuracy ranges from 80 to 88 percent. It is then inferred that the application of WOE in rating maps’ categories and ANN to weight effective factors result in the maximum accuracy.

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Hydrologic Evaluation of Landfill Performance (HELP) model is one of the most accepted tools to simulate

the hydrological attributes of landfills. Although some major deviations from real values has been reported about the

calculated results for leachate generation by HELP model but other researchers and/or engineers in practice have

used it in some places to estimate amount of leachate produced in the landfills. On the Other hand this model is

elaborated and mainly used in developed countries with the waste having low moisture content and also in climatic

conditions with high precipitation. This research investigated the applicability of the model in arid areas, by

construction of two 30m× 50m (effective horizontal length) test cells in Kahrizak landfill (longitude=51°, 20',

latitude= 35° 27' degrees), and monitoring the real leachate generation from each one. A set of field capacity and

saturated water conductivity tests were also performed to determine basic hydrologic properties of municipal waste

landfilled. A comparison was made between values calculated by HELP model and recorded values, shows that a

prediction of leachate on annual basis can be done by HELP model with acceptable accuracy but when the infiltration

of water to waste body increases due to leachate production, the model intents to underestimate water storage capacity

of the landfill, which lead to deviation of calculated values from real ones.