Journal of Spatial Analysis

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Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered.     Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data.  Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country.     According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.

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Hazard is potential source of harm or a situation to create a damage. So identification of zones exposed to hazards is necessary for planning or land use planning. But this situation becomes more critical when they appear at the population centers. So applying the principle of passive defense based on environmental capabilities is unarmed action that caused the reduction of human resources vulnerability, buildings, equipment, documents and arteries of the country against the crisis by natural factors such as drought, flood, earthquake, etc. Considering the possible occurrence of such risks in population centers, ready to deal with what is known unpleasant and undesirable consequences is necessary. On this basis and given the importance of population centers in Helle and Mond basins, in this study, the authors tried to analyze the Rain hazards of drought and flood.

The study area,Helle and Mond basins, with about 21,274, 47653 km² area, respectively are located in the south of Iran. The Helle basin approximately is between 28° 20'N and 30° 10'N latitudes and between 50° E and 52° 20'E longitudes and Mond basin is between 27° 20' and 29° 55' latitudes and between 51° 15' and 30° 27'E longitudes.These basins are located in sides of a massive sources of moisture, Persian Gulf.

In this study, data from 23meteorological and synoptic stationsstations, during aperiod of20 years (1992-2011)in northern region of the Persian Gulf (Mond and helle basins)were used to calculate Standardized Precipitation Index (SPI). The data were collected by the Iranian Meteorological data website (http://www.weather.ir). The SPI is primarily a tool for defining and monitoring drought events. This index may be computed with different time steps (e.g. 1 month, 3months, 24 months). The SPI is defined for each of the above time scales as the difference between monthly precipitation (xi) and the mean value ( ), divided by the standard deviation. To assess flood risk zones, the flood, annual evapotranspiration, cities and populations centers layers were collected in Helle and Mond basins position. The annual precipitations and the SPI maps were drawn by Geostatistics, Kriging. It also the flood and annual evapotranspiration layers were weighted by Euclidian distance method, separately. Finally, all layers are weighted by AHP and fuzzy-linear methods (descending and ascending linear function) into vulnerable layers. The final map of vulnerable areas with flood and drought high risk was drawn based on the algorithm of linear-Fuzzy in a raster format.

According to the results, eastern, north eastern and south eastern part of Mond basin had high annual precipitation. Based on this result, it said that these parts of study area were known the least dangerous areas of vulnerability. The results also showed that with passing of the western regions and going to the center of the study area the annual rainfall have been added over the years. Kazeron, Chenar Shahijan, Firouz Abad, Borm plains and some parts of Khane Zenyan and Dash Arzhan are cities located in this regions. Low latitude, Proximity to the warm waters of the Persian Gulf, low annual precipitation and high temperature causing evaporation and inappropriate environmental conditions in Boushehr province and some coastal cities such as Genaveh, Deilam, Boushehr, Baghan, Lar and Khonj. Accordingly, west, north west, south and south west regions in Helle basin were located in extreme vulnerability zone with a loss of annual rainfall for drinking and agricultural production and poor nutrition underground aquifers.

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Developing urbanization and changing hydrological conditions of natural streams increases the flooding risk. This study tries to do flood hazard zoning in the Ilam city and determine the critical area of the urban regions against flooding by using AHP method and GIS environment. For this purpose, the parameters of the curve number, height, distance from the river, geology, land use, population, slope, soil, building density, worn texture buildings and accumulated flow as effective parameters in flooding hazard in Ilam city selected and of these parameters weighted by using Expert Choice software. The result of the Expert Choice software is transferred to the environment of GIS software and flood hazard map of study area prepared. Results of the study and flood hazard map show that areas with very low-risk, low risk, intermediate-risk, high-risk and very high-risk form the 0.8%, 8.5%, 49.6%, 32.54% and 8.56% of the of Ilam city area, respectively. Also, the central area of the city has the highest risk and the probability of occurrence of the flood due to the high density of population and residential areas in this area and its proximity to the seasonal rivers and old part of the city. Therefore, by examining the results of Expert Choice software, it is possible to identify the most effective factors in the occurrence of flood risk and prioritize them to address management solutions to eliminate or mitigate the effects of these factors.

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Analysis and zoning of thermal physiological stresses in Iran
 
Abstract
Human health is influenced by weather variables in all circumstances, including atmospheric pressure, humidity and temperature around them. Based on climate hazard and climate changes, different parts of human life and economic and social strategies such as health, hydrological pollutants And agriculture had a profound effect, including the discussion of the effects of thermal stress on human health over the last few decades, and has become a major issue in the world's scientific circles. Heat and cold stresses, the exposure of humans to extreme heat and cold, are part of the extreme events, often encountered by people during daily activities or in the workplace, and affecting human physical activities. It is important that, if the body is not cooled through transpiration or cooling mechanism, severe deaths are inflicted on human health; therefore, the person has to reduce his activity in order to reduce the adverse effects of heat stress. Hence, many researchers consider the thermal stress component more important than other components in assessing human health.
In this study, using the physiological equivalent thermometer of PET thermal stress assessment and zoning of human thermal physiological stresses in Iran, with the length of the common statistical period from 1959 to 2011, and for the arsenal of thermal physiological stresses of Iran Forty stations have been used as representatives of Iranian cities. To calculate the physiological equivalent thermal temperature, all the effective meteorological elements in the human energy bill are measured at an appropriate height of climate biology, such as 1/5 meters above the Earth's surface. Data on climatic elements are provided by the Meteorological Organization of Iran. In the absence of data for some courses, linear regression method was used to reconstruct these missing data. After calculating the indices, the frequencies were also monitored and finally, using the GIS technique, the Kriging method of the study area was based on the frequency of occurrence of the indicators. Therefore, in order to achieve the results and objectives of the present study, software such as SPSS for data normalization as well as missing data was analyzed and analyzed using Ray Man's model based on meteorological elements to calculate the equivalent thermal physiological temperature of humans. Also, using the GIS software and Ordinary Kriging method, the best interpolation method was used to zon the human cysiological stresses.
Today, in the planning of human health and comfort, the study of the physiological thermal stress plays an important role. In this regard, weather conditions can be used in the long-term planning of climate and in the short term planning of atmospheric conditions. In the present study, using the thermophysical Thermal Equivalent Thermal Index (PET), the climate climatic Atlas of Iran was prepared on a monthly basis. Calculated values for 40 stations in the country with a total statistical period of 52 years (1959-2011) were prepared. The results of this study showed that the spatial distribution of the physiological equivalent thermal temperature index in the country follows the altitudes, roughness and latitude. Accordingly, the low values of the indicator, which relate to the stresses of the cold, are consistent with the high and mountainous regions as well as the high latitudes, and vice versa, the thermal stresses occur in low and low elevations, as well as low latitudes, which of course, severe heat stresses occurred in the summer. Because throughout this season, the entire country of Iran is dominated by high tidal altitudes at high and low levels of ground pressure (1000 hp) with its warm and dry air, causing extreme heat and The term effects of heat waves on humans, heat loss, thermal contraction of the muscles and skin dryness, infectious or skin diseases, inflammation, sunburn, dizziness, fatigue, and mortality due to an increase in allergies can be mentioned. Significant differences in the environmental conditions of the mountainous masses of Kerman, Yazd and Sistan and Baluchestan provinces with their surrounding areas or low and low northern areas, and especially the Moghan Plain and Sarakhs plain, located in the upper latitudes of the country The issue is that the role of elevation in spatial distribution of the country's climate is much more colorful than factors such as latitude and longitude. The results of the analysis of the monthly thermal physiological stress maps showed that in terms of the area without tension, the march of the month with 47/8% of the area (778424/2km²) is in the first place and has the most favorable environmental conditions, The moon with 43/5 percent of the area (709275/2km²) is in the second position and also in March with 22.6 (359128/9km²) in the third, August and the last month. The highest thermal stresses (29

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Evaluating and comparing the performance of Frequency ratio coefficient models and network analysis in Rock fall zoning
(A case study of Zanjan-Taham-Tarom Road)

Extended Abstract
One of the natural hazards of the collapse of rocks from the foothills of the mountains, causing great financial losses and loss of life. Especially when it comes to the path of communication. The rock fall is a rapid movement of a mass without cohesion in the powder or a mixture of soil and rock, so that the initial construction is not discernible, the level that occurs along that rupture it is often unclear. The falling stones of a mountain depend on several factors, which have the natural origin or origin of human origin. Natural factors influencing the fall can be rock factors, slopes and altitudes, geological structure, fault and slope of the geological layers, rainfall and temperature changes distance from the river, etc. human factors can also be referred to as road, land use and mining, destruction of vegetation, etc. in Iran, the collapse of rock parts on mountain roads causes massive loss of life and financial damage. Therefore, it is necessary to identify and classify the roads in terms of risk of suitable methods. In the north west of Iran it has mountainous topography and due to the state of tectonic and its seismic and climatic conditions, suitable conditions for landslide are provided in some domains. So, due to the fact that the area studied in the mountainous north - west region and the possession of all the crumbling conditions are very prone to collapse.
The research method is applicable in terms of practical purpose and the process of doing work on a combination of library and field methods. In this study, it has been used to determine the prone areas of collapse and zoning of anp models and frequency ratio. Two models that differ in terms of process and mechanism. In order to organize the research framework, first, a field study of the study area has been studied and the mathematical position of falling points is recorded with gps. Then, in order to model the mentioned models, the layers of GIs for the shape of the Georeferenced and digital were prepared. to provide the zoning layers of geology , slope and Aspect , elevation levels , land use and vegetation , fault , and land cover maps , annual temperature and precipitation , distance from the road , distance from the stream were used . The 20 m x 20 m contour line were originally prepared using the topography map of 1: 25,000 in the ArcGIS environment. Then, the contour line and Dem of the area were constructed. The slope and Aspect maps, elevation levels, Isothermal and isohyet map frost and stream network were created via Dem and meteorological data. Geological map and fault map were created using digital map 1: 100,000 Zanjan and map and vegetation map and road distance using Landsat 8 - 2017 OLI and ArcGIS images. To produce linear layers, the Distance function was used.
Using the statistical method, the frequency ratio and the network analysis method are using the landslide hazard zonation using the statistical method, the frequency ratio and analysis of network analysis to zoning the risk of falling by combination and sum of maps in class were low-risk to very high. From the tangible results of this study, the relationship between slope maps, elevation levels, rock material, Isothermal and isohyet is done. So that each side of the road had operated on the five factors that had happened. With regard to the output of the maps, the risk zones were high to very high for ANP models 14/17, 35/27 and FR 02/6, 35/14 percent. Ranges from high to very high with slopes between 40 and 80 percent and Sedimentary formations such as sandstone, siltstone with tuff layers, elevation levels 1,500 – 2300, Southern and Eastern slopes, Distance between 0 and 500 faults, Road and stream have adaptations . The changes in the percentage of area in both models show despite the difference in the size of the risk zones, Follow a similar process. To assess the zoning accuracy of these methods, two sets of quality and accuracy index (experimental probability) were used. The evaluation of the models showed that in the network analysis model, the indexes were 0.76 and 0.88, respectively, that the relation of frequency ratio coefficient model had optimal quality and accuracy.
In this research, various factors influencing the occurrence of rock falls on Zanjan-Taham-Tarom road were investigated. From there, mass movements such as rock fall on the roads act as a system, as a result, all factors play a role in the occurrence of such phenomena. But some elements have a more vibrant role. In the studied area, among the factors affecting lithology, slop, elevation levels, precipitation, temperature changes, number of freezing days and distance from the road and land use are more than other factors in the occurrence of rock fall. Assessing the quality and accuracy of zoning maps while confirming zoning accuracy showed that the network analysis method has better performance. The risk of collapse on Zanjan – taham- tarom road is always exists. Therefore, we need to use sustainable methods to reduce the risks. Domain stabilization methods are generally done in the form of mechanical, biological and bio-mechanical which, according to the long course of the road and the duration of the road, Mechanical methods such as unloading , embankment , drainage , use of separation walls as well as the use of  net Grid are suggested .
 
Keywords: Frequency ratio, Network analysis, Zanjan Road - Taham - Tarom
 
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Spatial analysis of natural resilience in border areas
Case study: Zahak county
problem statement
Occurrence of natural disasters such as drought, floods and earthquakes in geographical areas, especially in rural areas, often have devastating effects. Hence, resilience has become doubly important, especially in special areas that are of special importance and sensitivity. On the other hand, border areas have a special place in policy-making and planning is important in this areas. One of these areas is Zahak county in Sistan and Balochestan province, which due to the instability and reduction of the inflow of river water resources, as well as climatic conditions and drought in combination with other factors, the traditional employment opportunities of the often rural population face serious challenges and therefore the county5b is deprived. Increasingly, the sustainability of livelihoods is facing problems. The question is, how do the spatial zones and the villages located in these zones react to the change of internal and external natural factors? Which areas and villages are more resilient?
 
Method of research
This article deals with the spatial analysis of environmental resilience in Zahak county and its purpose is to investigate the differences in resilience in different areas of the county. The general approach to the study is integrated and descriptive-analytical in terms of method. Data were collected using documentary and field methods with observation tools and questionnaires and findings of a specialized panel. The statistical population of this research is the villages of more than 20 households in Zahak city that have had governor of a rural district or village council.
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Description and interpretation of results
The villages of Zahak county are threatened by the threat of these resources due to their dependence on natural resources. The results show that none of the defined geographical areas in the rural area is sustainable and three rural areas are semi-sustainable and one rural is unstable. Assessment of sustainability in micro zones also shows that naturally unstable villages are often sparsely populated, which means that activity has not developed either. After qualitative and quantitative evaluation of various natural and environmental indicators in the county and their impact on the resilience of places and settlements in the county, settlements and places in terms of resilience were classified into three levels of high, medium and low resilience. In total, 46.7% of settlements and places are at high level of resilience, 37% at medium level and 16.3% at low level of resilience. After matching the settlements and places with the geographical area of ​​the village, three of the four geographical areas are in transition and one is unstable. This study shows that the resilience of individual villages cannot perform well when it is located in areas surrounded by villages with low resilience and the whole area becomes unstable. Thus, in special areas such as Zahak county, crisis management should focus on providing natural resources and preventing vulnerability to natural crises, and it is expected that with natural stability, housing and activity will be sustainable.
 
Key word
Resilience, special areas, Zahak county, border areas, geographic zoning
 

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One of the causes of environmental hazards is the change in the pattern of surface water flow in floodplains following the construction of flood Spreading networks. The purpose of this study is to prepare a zoning map of vulnerable areas of the flood Spreading station of Musian plain  in Ilam province after the implementation of the aquifer project in this plain. To prepare this map, five factors influencing the change in flow pattern including elevation, slope, flow direction, geological formations, and landuse change were examined. Then, in the GIS environment, each class of the mentioned factors was given a score of zero to 10 based on the range and the corresponding weight layers were created. Then, by combining the created weight layers, the vulnerability zoning map of the area was created based on 5 classes: very low, low, medium, high and very high. The results showed that the most important threat and danger factor is the concentration of waterways behind erosion-sensitive embankments. Also, the study area in terms of vulnerability includes three classes with medium risk, high and very high and covers 16, 62 and 22% of the area, respectively. Flood and upland Spreading areas, risk areas and lowland lands are the most vulnerable parts of the basin in terms of floods and sedimentary deposits.

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Zoning the possibility of landslides downstream of Sanandaj Dam
1-Introduction
The purpose of this study is to select the best model and identify landslide risk areas in the downstream basins of Sanandaj Dam. Every year, mass movements in the region cause damage to roads, power lines, natural resources, farms and residential areas, and increase soil erosion. Kurdistan province, with its mostly mountainous topography, high tectonic activity, diverse geological and climatic conditions, has the most natural conditions for mass movements. According to the available statistics, this province is the third province in terms of landslides after Mazandaran and Golestan. (Naeri, &Karami, 2018). The Gheshlagh River Basin is a mountainous region with a north-south trend. In terms of construction land, it is located on the structural zone of Sanandaj-Sirjan. The study area with an area of 970.7 square kilometers is located downstream of Sanandaj Dam. The city of Sanandaj is being studied within the region. Due to the type of climate and morphological processes, effective parameters are provided for landslides in the geography of the region.
2-Methodology
In this study, 9 effective factors for landslides, including slope, slope direction, fault distance, road distance, waterway distance, lithology, land use and precipitation were used. Using Google Landsat 8 ETM satellite imagery, Google Earth software identified 237 slip points. Then, the coordinates of the slip points were transferred to the Arc GIS software and a map of the landslide distribution area in this environment was prepared. Also, in this study, 89 non-slip points were prepared for use in the training and testing stages of Persephone neural network inside slopes less than 5 degrees. Artificial neural networks are made up of a large number of interconnected processing elements called neurons that act to solve a coordinated problem and transmit information through synapses. Neural networks begin to learn using the pattern of data entered into them. Learning models, which is actually determining their internal parameters, is based on the law of error correction. In this method, by correcting the error regularly, the best weights that create the most correct output for the network are identified. The neurons are in the form of an input layer, an output layer, and an intermediate layer. ahp includes a weighting matrix based on pairwise comparisons between factors and determines the level of participation of each factor in the occurrence of landslides. In this model, a large number of factors can be involved and the weight of each factor can be obtained using expert opinion.
3-Results
According to the results of the high-risk class neural network model, which occupies 31% of the basin area, it is the widest risk zone in the region. The middle class also accounts for more than 29 percent of the area, followed by the low-risk class. The results of the AHP model show that the middle class, with 32% of the area, has the highest dispersion in the region, the low-risk class and then the high-class are in the next position. The AHP model was used to prioritize the parameters affecting the landslide. The parameters of slope, lithology and land use play the most important role in the occurrence of landslides, respectively, and have the least role for slope direction, distance from fault and height. The results of the models used are consistent with the reality of the region's wide-risk hazards, and high-risk areas based on the models used are mostly located in the west and southwest of the basin. These areas correspond to the mountain unit and the steep slope. Based on the results of AHP model, the impact of human factors in the occurrence of landslides is weaker than the natural factors of the region and human factors play a stimulating and aggravating role in primary factors. Five methods for error detection were used to evaluate the models used
4-Discussion and conclusion
 .Due to the sensitivity of unstable slopes in the region, any planning to change the use and construction that increases the weight of the load on unstable slopes should be done in terms of geomorphological and geological conditions of the region.
Keywords: hazard zoning, landslide, neural network, AHP. Sanandaj Gheshlagh Watershed
 

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The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.

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Introduction
A flood is a natural disaster caused by heavy rainfall, which causes casualties and damage to infrastructure and crops. Trend of floods in the world increasing due to climate change, changing rainfall patterns, rising sea levels in the future, and in addition, population growth and urban development and human settlements near river have caused floods to become a threat to humans. One of the most important and necessary tasks in catchments is to prepare flood risk maps and analyze them. In recent decades, researchers have been using remote sensing techniques and geographic information systems to obtain flood risk maps in an area. Due to the numerous floods that have occurred in the Neka river catchment, it is necessary to conduct a study entitled zoning of flood sensitivity in Neka river catchment for more effective management in this area.

Materials and methods
Study area: Neka river catchment area with an area of ​​1922 Km2 is part of Mazandaran province in terms of political divisions. This basin is between 53º 17´ 54 º44´ east and 36 º 28 ´to 36 º 42´ of north latitude. The highest point of the basin is 3500 m (Shahkuh peak) and the height of the lowest point of the basin in the Ablo station is about 50 m and at the connection to the Caspian Sea is -27 meters. The seven sub-basins of this basin are Laksha, Golord, Burma, Metkazin, Kiasar, Alarez and Sorkh Griyeh. Geologically, the basin is mostly of calcareous and marl formations. In the south and southwest of Neka River, the rock material is mostly clay and calcareous marl, which makes this basin has a high erosion potential
To study the flood zoning of the area using a multi-criteria decision model, 1: 25000 maps of the surveying organization and a digital elevation model with a resolution of 12.5 meters (Alos Palsar) were extracted. In order to study the flood risk in Neka river, 4 criteria of height, distance from the river, land use and slope have been used. In the present study, modeling and preparation of flood risk zoning map in 4 stage including descending valuation, normalization of each class, normalized index weight and integration of criteria has been done by the following linear weighting method. Performing linear weighting operations depends on the weighted average of a number of selected parameters in the opinion of the expert. According to the weight assigned to each criterion based on the expert opinion, each of the criteria was multiplied by the assigned weight and at the end the criteria were added together and the final zoning map was obtained.

Results and Discussion
In this study, using a multi-criteria decision-making system model, a flood risk zoning map in the Neka river catchment was prepared. According to the weight assigned to each criterion based on expert opinion, the final risk probability map has a value between 0.02 to 0.2, which is ultimately divided into 5 classes in terms of flood risk. Value range 0.02 to 0.06 component of very low risk zone, range 0.08 to 0.11 component of low-risk zone, range 0.11 to 0.13 component of medium-risk zone, range 0.13 to 0.16 component of high-risk zone, and finally domain 0.16 to 0.20 components of the area with very high risk potential have been obtained. According to the final divisions in the flood risk zoning map of the catchment area, a safe area means areas where the probability of flooding is very low and close to zero, and in contrast, the area with a high and very high risk potential for flooding has the probability of high-risk floods. According to the final flood risk zoning map, about 982 Km2 (51%) has high and very high vulnerability, as well as about 510 Km2 (26.69%) has medium vulnerability in Neka catchment area.

Conclusion
The results obtained from the model indicates that the highest risk of flooding points are located in the western parts of the Neka catchment area and the end of the catchment area that reach the city of Neka. According to the research findings, the most important factors in increasing the risk of floods were the slope in this area and the distance from the drainage network. According to the results of the model, a large area of ​​the basin is a component of high risk zone, that means the Neka river watershed has a high potential for floods. Evidence and documented reports show that the Neka river Basin has experienced several floods in the last two decades. The major part of the occurrence of floods is due to the natural conditions of the basin, thus it is necessary to reduce flood damage by changing the locations of various land uses based on flood vulnerability maps. Using multi-criteria decision making method can be used to prepare flood risk zoning maps in basins that do not have hydrometric data; It is also a more cost-effective method in terms of time. One of the important issues in the final result of this model is due to the weight of the layers, which should be used by experts, who are familiar with the region and this method and adapt to field evidence.

Keyworlds: Flood, Multi-criteria decision making system(MCDA), Hazard zoning, Nekarod, Natural hazard.



 

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