نشریه تحلیل فضایی مخاطرات محیطی
سال سوم شماره 4 (زمستان 1395)

Accessibility to precise spatial and real time data plays a valuable role in the velocity and quality of flood relief operation and subsequently, scales the human and financial losses down. Flood real time data collection and processing, for instance, precise location and situation of flood victims may be a big challenge in Iran regarding the hardware facilities (such as high resolution aerial imagery devices) owned by the correspond organizations. To overcome the mentioned inabilities as well as reducing the financial costs for real time monitoring purpose of a flood, the current research intended to use the capacity of the flood victims and other volunteers to collect and upload real time data to rescue themselves. By means of this, flood real time spatial and non-spatial data collection is applicable via public and per-person participation based on the needs of each victims. The current Open Source workflow has been so designed that by using a browser like Mozilla, Explorer, Chrome and etc., and without the need for installing any software, the victim transmits his/her exact geographic location (captured automatically by the designed web service) and other multimedia data such as video-photo. Also, the flood-affected person announces the type of the damage and consequently, demanded rescue operation to the managers as a text information. After data processing on the server, the information is represented as a real time rescue map for decision making. The rescue plan may be mapped based on the singular aid as well as plural plan in the cluster form specialized for a particular group of victims in each bounding box. To design the web service, a client architecture for victims, other volunteers and managers has been developed, for implementing the service, Open Source technologies, server-side and client-side programming languages, Geoserver and WFS (Web Feature Service) standard adopted by OGC for spatially-enabled representation of victims demands, have been exploited. The research result is a browser-based service in which the client service offers automatic zooming to the current location of the clients and sends the rescue request including personal identifications and the type of injury using PHP (stands for Hypertext Preprocessor) and SQL (Structured Query Language). In the other side, on the client side designed for managers, the requested rescue submitted by the victims and other volunteers are mapped and displayed real time by OpenLayers and WFS. The result introduces an efficient applicable method for gathering real time and high accuracy geographic-multimedia-text data collection and consequently, extremely reduces the relief operation costs. Finally, the proposed methodology causes better performance and spatially clustering of victims to decrease the aftermath of the flood in a region like Iran suffers from the lack of expensive hardware technologies for precise data collection and transmission.

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.

Trees in urban areas have survived in a wide variety of conditions and constrains, whether developing in natural or manmade habitats. Due to environmental constrains and stresses, urban trees rarely achieve their biological potentials. Indeed, some of trees, in small groups, could excel in terms of age, biomass structure and dimensions in urban areas. In definition, tree hazard includes entirely dead or dying trees, dead parts of harmed live trees, or extremely unstable or unsteady live trees, which could be in result of structural defects and disorders or other factors that have the high risk to threaten the safety of people or property in the event of a failure especially in urban green spaces. Although the pruning or other rehabilitation and mitigation program of trees is known as the one of the principal domains of green space management, it is still includes shortcomings in terms of models and methodologies to classify or prioritize hazardous trees which need to be treated timely. The main objectives of this study were to: (1) model old Sycamore failure hazard in urban green spaces to elucidate the general and defects tree factors affecting on failure hazard; (2) prioritize the impacts of model inputs (general and defects tree factors) on tree failure hazard using model sensitivity analysis and (3) determining the trend model output changes in respond to model variables changes.
The following types of data (target trees characteristics) were solicited for each target tree: (1) General features: Tree Height (TH), trunk Diameter at Breast Height (DBH), Butt Diameter (BD) at ground surface and Vertical Length of Crown (VLC) were calculated from measured girth. Crown Spread (CS) was measured as the average of two diameters of projected drip line of the tree canopy.
(2) Tree defects: Detailed evaluation of individual trees was made according to 6 key physical defects, namely Internal Decay (ID) in percent, Length of Cracks (LC) in m, Crown Defoliation (CD) in percent, and Degree of Leaning (DL).
(3) Sycamore failure hazard classification: Sycamore Failure Hazard Risk (SFHR) classification was the probability that an entire tree, or part of it, will break and fall within the first or second year after study. Considering results of tree regular monitoring after two years, the following classes of tree failure hazard were determined. 1. Extremely Hazardous: Tree failure in the first year. 2. Semi-Hazardous: Tree failure in the second year.
ANN has been recently developed for data mining, pattern recognition, quality control, and has gained wide popularity in modeling of many processes in environmental sciences and engineering. ANN learns by examples and it can combine a large number of variables. In this study, an ANN is considered as a computer program capable of learning from samples, without requiring a prior knowledge of the relationships between parameters. To objectively evaluate the performance of the network, two different statistical indicators were used. These indicators are Mean-Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R2).
In this study, the year of Sycamore failure in urban ecosystems is evaluated using tree variables and artificial neural network to determine the most effective tree variables in SFHR in urban green space. Various MLFNs were designed and trained as one and two layers to find an optimal model prediction for the SFHR and variables. Training procedure of the networks was as follows: different hidden layer neurons and arrangements were adapted to select the best production results. Altogether, many configurations with different number of hidden layers (varied between one and two), different number of neurons for each of the hidden layers, and different inter-unit connection mechanisms were designed and tested.
In this research, 200 trees were totally selected, then general and defects tree variables were recorded in urban green space. Considering the aim of study, which is discovering the relation between general and defects tree variables with SFHR class for modeling, the year of tree failure, was recorded.
In the structure of artificial neural network, general and defects tree variables were tagged as inputs of artificial neural network and SFHR class was tagged as output layer. Considering trained networks (the structure of optimum artificial neural network has been summarized in Table1), Multilayer Perceptron network with one hidden layer and 4 neurons in layer created the best function of topology optimization (Table2) with higher coefficient of determination which equals 0.87 for class 1 and 0.9 for class 2. Sensitivity analysis respectively prioritizes Crown Spread (CS), Vertical Length of Crown (VLC), Degree of Leaning (DL) and Butt Diameter (BD), which effect on SFHR in class1 (Fig1) and class 2 (Fig2).
The determined procedure of SFHR changes with CS changes in the region declares SFHR increase nonlinearly with an increase in CS. The determined procedure of SFHR changes with VLC changes o declares that SFHR increase nonlinearly with an increase in VLC of tree. The determined procedure of SFHR changes with DL changes in the region declares SFHR increase nonlinearly with an increase in DL. The determined procedure of SFHR changes with BD changes o declares that SFHR increase nonlinearly with an increase in BD of tree.
Nowadays, artificial neural network modeling in natural environments has been applied successfully in many researches such as water resources management, forest sciences and environment assessment. The results of research declared that designed neural network shows high capability in SFHR modeling which is applicable in green space management of studied area. Sensitivity analysis identified the most effective variables which are influencing SFHR. So, to identify hazardous trees in study area, we should pay attention to the CS of Sycamore trees as the variable with high priority in determination of SFHR. We believe that, in hazardous trees management in urban green spaces, we should pay attention to some modifiable factors of tree, which are CS and VLC, by timely tree pruning. We suggest urban green space manager to run SFHR model, for tree stability assessment, before decision making on hazardous trees.

Nowadays, the severity of the drought hazard has reached a point that has affected all the rural and urban areas surrounding it. Increasing the resilience of villages via livelihood solutions, is one of the best strategies for reducing the vulnerability of villages against natural hazards such as drought. The eastern side of the Lake Urmia consists of the six cities of Osku, Azarshahr, Bonab, Shabestar, Ajabshir and Malekan. Totally, there are 199 villages in this region, which are affected by the drought of the Lake, directly and indirectly and according to the statistics, the quantitative and qualitative reduction in agricultural and livestock productions and soil quality, the incidence of respiratory diseases and … have risen sharply compared to the past and a number of villages have been evacuated. Also because of the lack of a coherent strategy, which should be taken by the planners and authorities, the important measures to revitalize the Lake has not been taken yet and the dimensions of the threat are increasing day by day.
Current study investigate the factors affecting the resilience of rural settlements of the eastern side of the Lake Urmia against Drought. This is an applied and analytic-explanatory research. The data is collected by questionnaire from the villagers living in rural areas of the six cities, which are the statistical population of the research and the total number of the villages estimated 199 with 232295 persons.
The standardized Perception Index (SPI) is used to estimate the varying degrees of the villages in the eastern side of the Lake Urmia. In the next step, the possession index for each of the villages was calculated and the studied villages were classified based on it. On this basis and by considering the four status of drought and the three levels of possession, after sorting the villages on the basis of these two indexes, 43 villages were chosen from different regions of the eastern side of the Lake as the first level of analysis, using systematic random selection. Also, to classify the villages in the regard of possessing of the development facilities, the composite indicators called Morris pattern and 47 existing items are used, which are calculated in 9 different indexes. Finally, the obtained information were analyzed using SPSS and GIS software.
Regarding to the research findings at the eastern side of the Lake and on the basis of Standardized Precipitation Index (SPI), about 78% of this area has been experiencing drought. Also, the status of the overall indicators of household's livelihood capital on the basis of the Normal Scale from 0 to 10 is 3.34, which shows the unfavorable status of this index. The results of the study in the field of the level of civil and institutional development showed that on the basis of the Normal scale from 0 to 10, civil development is 4.86 and institutional development is 3.69. Lastly, the research findings for the three levels of the sustainable development of the livelihood shows that the livelihood diversification is 3.61, in depth agriculture 3.24 and migration strategy is 3.02. The analysis of the results of the sustainable livelihood shows that the decrease of drought of the villages increases the diversity of the livelihood of the villagers. According to the results obtained, the mean of the resilience index of the investigated households on the basis of 0 to 10 equals to 4.86, which is close to the average level. The classified distribution of the resilience level and the focus of the more than of 56% of the households with average level of resilience confirms this situation. 30.26% of the households has low resilience and 15.64% has high resilience in the face of existing conditions. Upon this basis, the highest amount of the resilience equals to 5.38, which exists in the villages with severe drought conditions and by decrease of the drought, the resilience of household’s decreases. Finally it can be said that the villages with a long history of vulnerability from drought and also having more intense droughts, has a higher resilience level in dealing with the situation.
According to the results, the highest amount of vulnerability exists in the villages with low experience in dealing with the long-term conditions of drought, which their economic and social structures are not prepared to deal with the conditions. While the average amount of the livelihood capitals and the resilience of the studied statistical population do not show an appropriate conditions, but totally, the results and relationships of the studied variables conforms the role of possessing all dimensions of livelihood capital on taking appropriate approach to dealing with the conditions of drought in the Lake Urmia. In the field of taking the approaches of diversifying the livelihood resources of the villagers, there are several scientific and examined solutions, such as considering the education and awareness as a definite reality, also the knowledge and skills of the villagers in the fields of modifying the crop patterns, water saving strategies, the use of efficient products and making use of the other high-income jobs must be increased.
In the field of educational solutions, besides providing modern knowledge and international successful experiences, it must be possible to make use of the indigenous knowledge and experiences of the villagers.

One of the most important calamities that affect the arid and semi- arid regions and is taken into account as threatening factors for human- life and destroying the natural resources is desertification, so recognizing and forecasting this phenomenon is very important. Desertification is a complex phenomenon, which as environmental, socio-economical, and cultural impacts on natural resources. In recent years, the issues of desertification and desert growth have been stated as important debate on global, regional and national levels and extensive activities have been carried out to control and reduce the its consequences. Desertification is considered as the third important global challenge in the 21th century after two challenges of climate change and scarcity of fresh water. At present, desertification as a problem, involves many countries, especially developing countries and includes some processes that caused by natural factors as well as human incorrect activities. In the other word, Desertification is the ecological and biological reduction of land that maybe occur naturally or unnaturally. The desertification process influences the arid and semiarid regions essentially and decrease the lands efficiency with increment speeds. The study area is located in the east and south of Isfahan. This region has been faced to increasing rate of desertification, because of drought, vegetation removal, change of rangelands to dry farming lands, water and wind erosion and lack of proper land management over previous years. Hence, aim of this research is monitor and forecasting of desertification changes in the east and south of Isfahan during the period of (1986-2016). In this research, the Landsat satellite images used as studies base for studying region desertification. Therefore, at first, satellite images of the study area were extracted from United States geological survey(USGS)website during the period of (1986-2016) and data and satellite images of TM5, ETM 7 and LDCM8 sensors of Landsat satellite were used which include thermal and spectral bands. In this relation, for studying the desertification condition in the south and east region of Isfahan, the Landsat satellite images of 4, 7 and 8 during 5 periods of 1986, 1994, 2000, 2008 and 2016 have been utilized. After completing the information data base, first, the soil salinity(S1, S2 and S3) and vegetation NDVI indices exerted on the satellite images. According to Fuzzy ARTMAP method, the land use changes during the period of (1986-2016) recognized in the studied region. In the other word, the vegetation NDVI and soil salinity (S1, S2 and S3) indices have been utilized for identifying vegetation and the desert and salty regions. For preparing the region land use map, the Fuzzy ARTMAP supervised classification method have been utilized and 5 land uses(desert and salty lands, vegetation, city, arid and Gavkhouni) in the region were identified by TerrSet software. The changes calculation in region uses during 5 periods accomplished by LCM model. Also, the Markov chain and Cellular automata synthetic model have been utilized for changes forecasting. This research results indicated that the greatest changes during studied period belonged to vegetation. This volume of change had been during 1986- 1994 that indicate 1062 km2 desertification. In the other hand, the greatest intensity of increasing the salty and desert regions have been occurred during 1994-2000 which indicate 495 km2 increasing. The CA- Markov synthetic method have been utilized for forecasting the land uses changes trend, too. In this relation, for assessing the forecast accuracy, the Kappa coefficient have been utilized which indicate 78%. Finally, it has been specified that the greatest changes during 2016-2024 will be in vegetation which about 60% of region vegetation will disappear and arid lands will be replace them. The salty and desert lands will disappear about 1% of vegetation, 3.3% of arid land and less than 0.01% of city and Gavkhouni. During 2016-2024 about 32% of Gavkhouni lagoon area will disappear and arid lands will be replace them.

Classifying daily climate circulation patterns has always been considered by climatologists. Investigating climate changes such as rainfall and the temperature in a same single time and place suggests that these changes are strongly influenced by atmospheric circulation patterns.
Regarding so, climate changes, known as variables here, such as rainfall, temperature, and other related phenomena, which are exemplified as flood, drought, glacial, and etc. are associated with special types of climate circulation patterns. The continuity and alternation of the systems are classified or identified climatically, therefore weather classification system is one of the main objectives of the synoptic climatology (Huth, 1996). Since every weather type creates its own special environmental condition, lack of identification in weather type frequencies leads to a difficult environmental explanation and alternation (Alijani, 1380:64).
Identifying atmospheric circulation patterns different things that can be expressed inductively such as frequency, intensity, and spatial distribution of climate changes in rainfall and its physical causers (VicenteSerrano and LopezMoreno, 2006).
Heavy rainfall in many watersheds, particularly in the basin and sub-basin which involve less time exposure, causes floods and it also damages human, natural resources, infrastructure utilities and equipment. Before the occurrence of this kind of rainfall, it requires a deep understanding of the synoptic systems of their creator. This understanding is only possible through the classification and identification of rainfall patterns which used to cause floods in the studied basins.
The present study also aims at identifying and classifying the synoptic patterns of rainfall during the statistical stage of the study in the basin which caused flood in Taleqhan basin.
Taleqhan basin with area of (65/1242) per square kilometers is located in "36֯, 5', 20" to "36֯, 21', 30" north latitude and "50֯, 36', 26" to eastern longitude "51֯, 10', 18".
The study area is 120 kilometers away from North West of Tehran and located in a relatively high mountainous area in Alborz Mountain. This area is ranging from 1700 meters to 4400 meters above sea level. Average rainfall in this basin ara is 515/16 mm and its annual temperature fits 10. 5 centigrade. About 79 percent of rainfalls occurs from the cold weather period in November to March. It is also know as semi-humid cold weather based on the De Martonne classification.
Circulation algorithm (CA) and pattern clustering algorithm (PCA) were determined based on the daily methods in synoptic scale by applying information from stations in Taleqhan basin (Gateh deh, Dehdar, Dizan, Snkranchal, armouth, Ange, Joostan, Zidasht). In order to classify the weather type, daily average rate of 500 HPa and the sea level pressure (SLP) were extracted and reconstructed over the period (1980-2011) at the 2. 5 degree of NCEP. Selected range includes 608 points from latitude of 10 to the 60 of northern degree, and latitude of 10 to 80 of eastern degree.
Principal components method mixes the interrelated points and reduces the matrix size, so 13 main components are remained that they includes 93 percent of the total variance. This study employs S array and Varimax rotation to identify different types of weather. It also makes use of K-Means clustering method to classify daily weather types. And finally, a matrix was formed in 118×608 dimension for 118 common days of rainfall among stations. All days were divided into four groups. They offer the most common climate circulation patterns in the proposed area. At the end, and finally integrated maps of sea level pressure and 500 HPa were drawn for each weather type.
According to the results from factor analysis, 13 main elements were selected that they included 93% of the total variance of the data. According to the above mentioned method, all days (118 days) during the statistical period (1980-2011) were divided into 4 groups which provide the most climate circulation patterns in the study area. Then, integrated maps of sea level pressure and 500 HPa range were drawn for each of the types. Clusters were numbered according to the K-Means arrangement, and they were named based on the pressure patterns and the way circulation lines were ordered.
The classification shows two different resources for rainfall in this basin.
A: Those rain systems that are entered to the country from the West and South affect this basin. These systems humidity are caused by the Red Sea, the Mediterranean sea, the Black Sea, and the Atlantic Ocean. (B) Some parts of the Caspian coast rainfalls and the northern part of the Alborz mountain that has received their humidity from the Caspian Sea and it has infiltrated northern high-land, causes the rainfalls. It enters the basin from the wide valley of Sefid Rood. According to the rainfall measuring stations data, the least rainfall area is in western, which includes low-land areas. And the most rainfall area is its northern east. Rainfall in this area, in terms of rainfall time distribution in a year, is the Mediterranean. It does not involve a complete dry climate in summer and it takes 3 to 4 percent of the total rainfall. Rainfall in the basin, respectively, is distributed in winter, spring, fall, and summer.

Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.
In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.
The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert