JOURNAL OF NATURAL ENVIRONMENT HAZARDS
Year:2016 | Volume:4 | Issue:6|Papers Count:7

There are several ways to study drought. Method of analysis rainfall data, Public Sector analysis methods is drought. Therefore, accurate prediction and before the outbreak precipitation could provide the conditions for assessing the drought situation. The purpose of this study is investigating the effect of data preprocessing on the performance of the decision tree model to predict drought in synoptic station in Sanandaj. In this study, CART algorithms (Classification and regression tree) has been used as variety of decision tree regression in order to predict precipitation forecast of12months. The data used in this study are the monthly precipitation, relative humidity, the maximum temperature, the average temperature, wind direction and wind speed in a specific statistical period (1970-2010). To assess the created trees in this study, different statistical measures have been sed which in the end results show that in synoptic station in Sanandaj, decision tree regression model is a relatively efficient model to predict drought in which using a moving averages compared to other states led to Increasing the efficiency of decision tree mode land providing thread just mint in the range of changes, the input data with a high reliability is able to estimate the amount ofprecipitation12months before it occurs which in the simulation carried outing this study, when the five-year moving average of the data has been used to implement the model ,combination of previous rainfall, maximum temperature has been identified as the most appropriate states. The findings show that applying moving average to the original data, dramatically improves the performance of the model. In these circumstances, the decision tree method regression in Sanandaj station with high reliability level estimate the occurrence of precipitation in 12 months ago.

Drought has gripped a serious problem in many countries of the world. So great is the importance of drought prediction. In this research, performances Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for Drought Prediction Techniques in Mond Basin of Fars Province have been comparatively evaluated on the basis of the monthly data for a 32-year period (1978-2012) including rainfall, temperature and drought indices SPI, the training data length of %70 and the testing data length of %30 were determined. After conducting prediction by using ANN and ANFIS models, the performances of these models were evaluated on the basis of statistical criteria of Nash index (E), correlation coefficient (R) and Root Mean Square Error (RMSE). The obtained results indicated higher accuracy of ANN model rather than ANFIS model in orther to Drought Prediction Techniques in Mond Basin of Fars Province.

The Earthquake Vulnerability one of the important challenges confront of big cities in Iran. Sensitivity of this matter reduplicate when the cities moreover exhaustion contain slums area and informal settlements. The Tabriz city one of the populous city in Iran that from earthquake risks on high Vulnerability position. Tabriz city like as other cities containing informal settlements and this sector establishment on active fault side. This sector of construction and urban planning (urban land use planning) aspects in the unsuitable position. While the earthquake happened as regards high population density and other effective factors on Vulnerability increasing due earthquake human disaster in this area can happened. This article surveyed 1 and 5 zone of Tabriz city that contain informal settlements between Tabriz city zones، from Vulnerability due earthquake for as much as earthquake nature and study it’s relation with four factors population density, construction density, constructions quality and type of the construction materials also for evaluation of Vulnerability amount and effective factors in Vulnerability used from geographic information system (GIS) and Analytical Hierarchy process (AHP) and for density estimation used from the kernel density estimation (KDE). Research results showed that 1 and 5 of Tabriz ity zones because high population concentration, low constructions quality, constructions high ages and used from unresisting materials in opposition of earthquake and established in proximity of fault and slum texture in other side while the earthquake occurrence can endure irrecoverable damage.

Not only is energy self-produced greenhouse gases, but its use in heating, cooling under the impact of climate change and global warming caused by greenhouse gases is. In this study, data obtained via EH5OM model from Max Planck Institute for Meteorology in Hamburg, Germany, were used to simulate Fars province average daily emperature during the first period (2015-2050) under the A1B scenario of the Intergovernmental Panel on Climate Change with a resolution of 1.75 degrees longitude and latitude. Then, the regional climate model was used to downscale the average daily temperature data at a 0.27´0.27o latitude and longitude covering a 30´30 km area of Fars province. To calculate the parameters of temperature threshold of 23.9oC was used for cooling. The average monthly temperature cooling at 13140´12 matrix calculation and maps that were drawn in the next phase relationship between the width, height and longitude to calculate cooling degree days and it was traced images. Most cooling needs in the southern part of the province in June and July 4200 and 3800, respectively cooling needs of the province an important loss in peak hours. the need for this parameter is also visible in the northern strip, especially city Abade. Most latitude to May correlation with the amount of cooling needed is 0.878 percent. The role of latitude over during the province-is cooling needs change.

One part of North-western Iran is Zanjan Prov. It receives the moisture of western weather systems. These systems are affected from latitude, height and the direction of mountains. The east-ward replacement of western and short air waves that are separated from Mediterranean one as a principal wave and so, the recurrence of trough and ridge can obtain enough moisture for the Heavy Rainfalls of Zanjan Province (hereafter HRZP) from Mediterranean as nearest sea one. Our aim was the determining of precipitable weather system that caused HRZPs. As a hypothesis we bring up Mediterranean Sea is the principal resource for heavy rainfalls in Zanjan Province. In first stage, we extracted the daily rainfall amounts for 9 weather stations inside and outside the province during spring season including April, May and June. When the daily tables of rainfalls set based on equal to 30 mm/day and more, we could determine 13 heavy rainfalls. Results showed April had most heavy rainfalls. In second stage, we determined 8 HRZPs based on their duration, the cumulative amounts of weather stations during peak days and the frequency of recorded ones. During final stage, we designed daily weather charts based on atmospheric data including slp, hgt, air, rhum, shum, uwnd and vwnd from NCEP/NCAR.Programming was accomplished in C++ software and modeling in GrADS and Surfer ones. The analysis of designed models showed water vapor has flowed from Mediterranean Sea toward study area in lower troposphere (750 HPA) during rainy days. So, we found the cores of maximum relative humidity (more than 80 percent) over study area during rainy days. It was detected that the most of HRZPs happened during April and the Mediterranean Sea is the principal resource of water vapor for them.

The occurrence of slop instability on the roads and communication domains, especially in the mountainous areas, is one of the cases the causes a lot of damages on the roads of country،and sometimes in the areas in where the slop is very sharp or the roads are more curved the occurrence of this type of natural hazards can cause death of passengers،therefore identification of the areas which because of their natural features are more dangerous and on the other hand they are chosen for construction projects such as roads ore dams, …, is really important .In this article the Logistic Regression was used for identifing the dangerous areas. For the study of the image sensor on Landsat 8 OLI-TIRS were used and the effective Factors, as ،instability slope (slope, aspect, lithology, land use, distance to fault, distance from the river, away from roads, elevation) in GIS environment survey and the most important factors was known, then the distribution layer of instability was adjusted to the hazard zonation map of slope instabilities in software Edrisi then likelihood of slop instability map was divided into five groups with very low sensitivity, low, medium, high, very high.

Nowadays, the city’s vulnerability to earthquakes is world’s major problem that is expert’s concern in various fields. Technical and historical studies of earthquake in Iran shows that devastating earthquakes along the Dorouneh fault, in many cases leads to deterioration and death of hundreds and sometimes thousands of people.Bardaskan, due to the presence of several active faults around and within it, is in a high risk of earthquakes. The purpose of this study is to determine the vulnerability of urban elements, using models and methods in reducing the vulnerability of this city against earthquake. To reach this purpose, 16 physical and spatial factors affecting the vulnerability of urban space were identified at the global level then using location data, structural elements description, building behavior data, and determining the impact of each criteria in vulnerability level, an appropriate estimation of city’s vulnerability to earthquake were presented in the framework of integrated and planning models such as fuzzy and Inversion Hierarchical Weight Process. We also discussed building damage modeling and micro-zoning against earthquake by presenting earthquake scenarios at different intensities. The results of this study show that by moving from the south to the north of Bardaskan, the vulnerability of the building’s block are increased. Earthquake scenarios modeling in the intensity of 6 and 8 Mercalli shows the vulnerability of the building were based on the 3, 1, 6, 5, 4 and 2 section respectively. The main reasons for this state are locating near the fault, peak ground acceleration, high density and low quality of building construction and building materials.