فصلنامه جغرافیا و پایداری محیط
پیاپی 9 (زمستان 1392)

Flood hazards is considered as one of the environmental reactions in rivers system that has exceptional flow and severe. This type of hazard is a function of a particular period or place.Essentially, the most important reason for its formation is the geographical distribution of river floodplains and coastal lines along which provide an appropriate conditions for the development of post settlement. Hence, human interventions in the river channel and violation of its privacy has always caused the river limit to be in the center of attention. In the present study, Totshami river bank, located in Kermanshah province, has been chosen to assess the limit of flood processing for different return periods. In this regard, necessary statistics and information about the hydrology of the region were collected. Then they were analyzed, reconstructed and completed.In field surveys, a period of seven kilometers of river channels was chosen and their transverse profiles were drawn.Roughness coefficient confines of left and right channel was determined.Finally, using the HEC-RAS software, midst River floodgate for return periods 2, 5, 25, 50, 100 and 200 years was determined. In this paper, not only is the boundary map of the river bank for different return periods determined,but also it is tried to assess the relationship between the development process and the pathology of settlement nearby river flood. The results showed that the extent of river frontage Totshami processes in different return periods is considerably affected by geomorphologic characteristics the channel and floodplain area.Moreover, Privacy settlements in the river bank are 25 to 200 years.

Dehyaran establishment was an important act in rural management in recent dedicate. This law is new but, today some senators and governments are debating about aggregating of dehyarans. This paper aims to study the factors affecting aggregation of dehyarans. Investigative method was quantitative one applying questionnaire to collect data. Statistical population includes 70 participants from Ravansar Dehyarans selected by census method. Reliability and validity of the data were proved by Alpha Cronbach and expert panel respectively. The findings show that dehyarans do not agree with aggregation project believing some possible problems like disagreements among selected dehyarans and rural council, cultural difference, and management challenges. Generally, there are 3 factors that affect the improvement of the project including economic, culture and management. This paper shows that cultural and social factors are more important than others.

The importance of precipitation forecasting as the most important climatologic element and the basis of all planning, especially in areas where there are significant changes in precipitation regimes, is considerable. The use of artificial neural networks is one of the forecasting methods that have been widely developed in recent years. In this research the data set of some climatologic elements, related to the cold seasons of previous year, were used to forecast the next year precipitations in Kermanshah and Nouje Hamedan synoptic stations. Therefore, time series of seven climatologic elements including mean temperature, precipitation, relative humidity, mixing ratio, vapor pressure, dew point temperature and sea level pressure were entered to the artificial neural networks as input, while next year precipitation was considered as the output of network. Due to nonlinear nature of selected climatologic elements of this research, the multi-layer perceptron (MLP) networks were applied. In fact, they are among the progressive networks with supervising training algorithms and suitable for nonlinear data. Other two categories of training algorithms including BP training algorithms and number normalization algorithm were used for training of networks. Eventually, the combination of these algorithms led to the production of 720 training networks at two stations, and finally the artificial neural network succeeded to proper forecasting of annual precipitation amounts. The best forecast for Kermanshah station is related to the traingd training function with mean and standard deviation normalization algorithm and testerror amount equal to 0.0195 in cold period of the year (overall autumn and winter), and in Nouje station is related to the traingdx training function with pca 0.06 normalization algorithm with testerror amount equal to 0.0047 in the winter.

Excessive growth of the population will increase waste production leading to the pollution of groundwater and groundwater, negative effects on the landscape and ecologists of the region, environment pollution and great charges on the community. Finding a suitable location for waste sanitary landfill is regarded as one of the best ways to reduce damages. Geomorphology, which intuitively studies the evolution of ground-level effects, can play an important role in landfill location. In this research, it was tried to focus on geomorphologic criteria and effective measures to optimize the location of landfills in West Islamabad, located in Kermanshah. In this research, various criteria such as slope, slope direction, elevation classes, geology, soil, distances from the communication network, distance from the river, land use, distance from rural residential areas, distance from urban areas and rainfall distribution have been evaluated. The required information is provided through topographic maps 1: 50000 and geological maps of 1: 100000 mapping and field studies. After preparing geomorphologic map and creating appropriate layers for GIS, four locations were fitted in the northeast and northwest of Islamabad for the sanitary landfill of garbage.

Using a model with integrity and high performance to simulate the hydrological process in deferent watersheds is very important. Present study aims to assess the efficiency of SWAT model in simulating the produced runoff of different precipitation in Khorramabad watershed with 2467 square kilometers and in Talar watershed with 2057 square kilometers. Average precipitation in Khorramabad and Talar watershed is 560 mm and 612 mm respectively. Besides, both of them have semi-hummed climate. Therefore, the maps of land use, soil, digital elevation model and meteorological data were collected for each region. Hydrological response units (HRU) was determined in 223 in Talar and 265 HRU khorramabad watershed by overlapping spatial layers. The SUFI2 algorithm was used to analyze parameter sensitivity and determine optimal values for parameters. The results showed that curve number parameters have high sensitivity in both watersheds. NS and R2 statistical coefficients were used to determine optimal values of model efficiency. The values of these coefficients in Khorramabad watershed are 0.74 and 0.72 respectively and in Talar Watershed are 0.64 and 0.66 respectively. The results showed that the types of precipitation have pivotal effect on model output and occurring snow precipitation decreases performance of the model. Overall, the results showed that the SWAT model availability is appropriate enough in both watershed and this model can be used for watershed management in these areas .

Curve Number (CN) is one of the required parameters for runoff calculation using SCS method. Considering spatial variability of factors affecting this parameter, different values of CN is expected within different parts across a catchment. The present research aims to map CN in Navdar catchment, Kermanshah province, Iran. Therefore, modern technologies such as geographical information system (GIS) and remote sensing (RS) have been used. First, land use map of the study area was determined based on Landsat satellite images (TM) using ERDAS software package. Then ground coverage density was determined based on Normalized Difference Vegetation Index (NDVI). The map of soil hydrological groups was prepared in GIS environment based on the available soil map in the study area. Finally, CN map was prepared based on SCS table and the maps of land-use, ground coverage density, and soil hydrological group. Average curve number under intermediate humidity conditions in the study area was calculated as 78. Simultaneously, CN in the catchment was determined as 76 by the analysis of recorded runoff events using HEC-HMS model. Results of this study indicate that the accuracy of calculated curve number via RS and GIS technique is high, so the obtained curve numbers using RS and GIS method across this catchment are reliable. Based on the determined curve number in the catchment (78), it can be concluded that this catchment has high potentials in terms of runoff generation.