Floods are considered one of the most important and abundant geomorphic Hazards in the country, which cause a lot of damage every year. Aji Chai basin, located in East Azerbaijan province, witnesses devastating floods every year due to its large area and special topographical conditions. Therefore, the main aim of this study is to prepare a flood Hazard Potential Map in this basin. To achieve this aim, 18 parameters effective in the occurrence of this Hazard and two statistical methods of frequency ratio (FR) and statistical index (SI) have been used. The investigated parameters were Elevation, Slope, Aspect, Rainfall, Distance to the river, River density, Normalized Difference Vegetation Index, land use, Distance to bridge, Distance to dam, lithology, hydrological soil groups, Topographic wetness index, Sediment transport index, Stream power index, Drainage texture, Geomorphology and earth curvature. The location of the past flood points in the area was used to determine the parameters weight and implement the research models. The final Maps were prepared from the product of the weights of each parameter class in their information layers and were classified into five classes using the Natural Breaks tool. Study the final Maps showed that Hazard zones spatial distribution patterns were similar in both models. In this way, the areas downstream of the basin and around the main streams of the area are the most dangerous zones. The accuracy evaluation of the results of both models with the ROC curve showed that the values of the area under the curve for SI and FR models were 0.945 and 0.919, respectively, which shows the excellent performance of both models in preparing flood Hazard Maps.

Background and objectives: In preventing fire and reducing their effects, forest fire management is important. The purpose of this study was to provide a Map of fire Hazard Potential and determine the effective factors on forest fires using GIS and artificial neural network for the cities of Ali-Abad, Ramayan, Azadshahr, Minoodasht and Kalaleh in Golestan province. Materials and methods: The criteria used in this research included forest and rangeland lands, temperature, rainfall and evapotranspiration, slope, aspect, elevation of the sea level, distance from urban areas, distance from rural areas, distance from agricultural land and distance from the road. Vegetation Map, digital elevation Map and land use Map provided from the forests of the rangelands and watersheds of the country, and the Maps of temperature, rainfall, and evapotranspiration obtained from the organization of the meteorological for the whole of Iran. The influence of each parameter on fire ignition was determined by collecting of 37 samples from burned area and 37 sample from not burned area. 15 fire points that were not used in the modeling process was used For Validation the Potential fire Hazard Map. For formation network between criteria and fire occurrence used of Multilayer perception (MLP) with Hyperbolic Pattern Algorithms. To this end, 70% of the data was used to train the network, 15% of the tests were tested and 15% of the data were used to validate the results. Results: The results were shown raining and distance from the road had must be influenced on forest fire ignition. Validation test showed that the best network was obtained in run 4 and epoch 450 with 0. 0038 Final Mean Square Error (FMSE) in training steps. Furthermore, about 95 percent of area burned and 84 of unburned areas has been properly classified. Finally, forest fire Hazard Maps was obtained based on each criteria weight. Results showed this network with 2 hidden layers and 12 neurons in each of them has best accuracy, and correlation coefficient (R) was 0. 80. Furthermore, after determining the location of the 15 forest fire points on the Map of Potential fire Hazard, the results showed that 7 points located in the area were very high fire risk, and 6 points in the area with a high fire risk, and 2 points located in the area with a low fire Hazard. Conclusion: According to the findings of this research, roads and rain reduction have a growing impact on the development of fire and natural forest fire managers need to adoption the necessary measures to better manage the forest and rangeland areas in these situations to prevent the occurrence or spread of fire.

One of the important problems in earthquake geotechnical engineering is liquefaction phenomenon that happens in loose saturated granular soils. This phenomenon can cause great damages to underground structures and buildings and lifelines. Liquefaction resistance of soils can be evaluated by experimental and field tests. In this research, results of liquefaction Potential evaluation based on standard penetration test (SPT) were proposed. Case study area is Ghazan Chay Dam at Southeast of Khoy city at West Azerbaijan province in Iran. In this study 18 boreholes was collected. With considering type of soils and ground-water table level liquefaction Potential evaluated. Then, liquefaction Potential index (LPI) assessed. Obtained results showed that almost more of 50% alluvium sediments deposits is included sand and silty sand. Also, liquefaction Potential Hazard with considering ground water table level is high.

Liquefaction is one of the most determinant factors in the collapse of transportation infrastructures. This is especially true for roads and railroads located on saturated, fine-sand substrates under seismic conditions. The damage and human casualties resulting from liquefaction highlight the importance of understanding and Mapping this phenomenon. Soil liquefaction occurs as a natural Hazard in saturated, loose sand due to increased pore pressure and low shear strength. The purpose of this study was to prepare a soil liquefaction Hazard zonation Map for Kordkuy County, located in Golsetan Province, using data collection, basic digital Mapping (soil deposits Map, ground water depth and earthquake acceleration Map), three parametric Stanford Watershed Models (SWM) and ArcGIS software. An empirical liquefaction model as a function of the three studied variables was used to model liquefaction in four Hazard classes using ArcGIS software. According to the results, most areas fall into the nonHazardous and moderately Hazardous risk classes. A portion of the Eastern County was classified as highly Hazardous due mostly to its close proximity to an earthquake focal point.

PM2.5 pollution is one of the critical environmental problems that occurs after industrialization and the increase in the population of cities. Information about pollutant concentration, including PM2.5 pollutants, significantly impacts how city managers make decisions to improve cities' health. This study used the ordered weighted averaging (OWA) technique to produce PM2.5 pollutant zonation. For this purpose, meteorological information layers include wind speed, maximum temperature, minimum temperature, average temperature, 24-hour precipitation and humidity, normalized vegetation difference index layers (NDVI), and road density are used. The gradient descent algorithm has been used to calculate the weights related to the order of the values to apply the OWA algorithm. The optimal learning rate parameter has been obtained to achieve the optimal value of the weights. Also, the layers of information were combined based on the obtained weights from OWA. Finally, the RMSE index was used to evaluate the obtained results, and the PM2.5 pollutant estimated for the summer and winter seasons had the lowest and highest errors, respectively. The error values for these two seasons were 0.129 and 0.190, respectively. Also, Aqdasiyeh station had the lowest error in all seasons, and Golberg, Region 11, and Shahr-e-ray stations had the highest error.

Every year, many deaths, injuries and much economic loss due to falling rocks and boulders occur to the people who live in and pass through mountainous regions worldwide. Closed transportation corridors and damage to infrastructures, like rock sheds, due to rock falls, are common phenomena in some countries, especially during rainfall or earthquake. Realistic simulation of rock falls, along with defining their most vulnerable fall trajectories, can result in providing mitigation measures in the right places with the least cost. While many numerical approaches have been developed to predict the trajectory of falling rocks, none of them consider the interaction between the blocks of falling objects. In this paper, a common discrete element software (i.e., Working Model 3D) has been employed as a new tool to model rock fall. The interaction between falling masses, i.e., the impact between falling rock blocks, is considered.The results are compared to those obtained from traditional rock fall simulations. While the recent approach gives a more realistic result, its drawback is the enormous time needed to perform calculations, i.e. more than ten to a hundred fold, depending on the number of falling objects involved. The results show that existing simulation techniques give a lower bound for the Hazard zone scattering and, consequently, the measuring structures will not be very efficient. On the other hand, designers should over-design to cover unseen Hazard zones, which lead to heavy project costs.

Nowadays in countries involved with landslide problem, there is an increase trend to evaluation and zonation of risk and damage of this phenomena. Identification of regions having Potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide Hazard zonation models are proposed based on the environmental condition and goals. In this research landslide Hazard zonation Map using information value model was provided and applicability of this model is investigated in Bagh Dasht watershed. Existing landslides as earth evidence was identified and landslide inventory Map was provided. information layers as Geology, slope, aspect, distance from river, distance from road, distance from fault, land use, rain and elevation was provided. For doing this, existing landslides have been identified and an inventory Map made. The landslide Hazard zonation Map is based on the information value in Arc-GIS environment provided. The level of similarity Potential Hazard classes and figures of this model were compared with the landslide inventory Map in the SPSS environments. Results of research showed that there is a significant correlation between the Potential Hazard classes and figures with the area of landslides. So the information value model is suitable for application in the Bagh Dasht Watershed.

In an airshed without stationary and mobile recording of index pollutants density and emission, air pollution Potential Hazard assessing with quantiative experimental models provide a valuable basic data for determination of industry allocation regulations and emission standards of air pollution in Golestan province, a widespread weighted numerical model was prepared with 44 bio-physico-chemical  effective parameters and implemented in the framework of 198 equi-poteial environmental units (a 44*198 matrix). This model according to the effect of each parameter upon air pollution, contains three groups of parameters including I-decreasing (8, indicator of environment refinery capacity), 2- increasing (31, indicator of environment pollution susceptibility), and 3-decreasing-increasing parameters (8,related to critical limits or specific standards). Weight of each parameter was determined according to its relative importance in air pollution Potential and exceeding from ambient air standard in a-3 to +3 graded scale, and also rate of parameter class (2 to 5 class) was determined on the range and allowable limit of ambient air standard in a 1to 5 value scale. Total number or Hazard index of air pollution in each environmental unit was calculated by multiplying of weight to rate of every parameter and sum of positive and negative values of all parameters, and finally divided to 5 classes. With implementation of model with different data sources, the Potential Hazard of air pollution in Golestan province evaluated and Mapped as choropleth on a semi-detailed level at 1:250000 scale. Results show that the province contains all of the 5 Hazard classes of the model, and there are significant differences (at P<0.01 level) between number (and area of the polygons of Hazard classes). This numerical model has actually a necessary spatial and thematic resolution for planning of air quality management and control. So that, there are close spatial fitness between high Hazard classes with densely populated and urban-industry concentrated area of foot hill belt, and low Hazard classes with less populated and rural-agricultural areas of province. Therefore, it is possible to calibrate the regional model via systematic watching and monitoring of index pollutants in different part of the J province especially in the critical areas.    

The Maps of Potential flooding areas can be the appropriate tool for urban planning in the future. In this research, Potential flooding areas criteria viz. the urban land use, distance of river, elevation, slope and ground water level were considered. The weight of decision criteria were evaluated by paired comparison matrix. The final Potential flooding Map was divided to five different risk classes. About 15 percentage of the study area were belongs to very high and high risk classes. Including areas located in high risk near to the river, impermeable areas, low topography and slope less than two percent in these areas. Focus on areas with historical flood events showed that areas with slope less than two percent are more affect by flood. The results of the Analytical Hierarchy Process showed that ten percentage of the area with historical flood events is located in very high and high classes. The results show that percentage of the class area with high and very high risk according to historical flood events are 43, 34 and 26 percent for gaussian, triangular and generalizedbell-shaped membership functions, respectively. The result of Gaussian membership function is more similar to historical flood events reports.