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Showing 2 results for Vulnerability.

Esmaeil Ali Akbari, Nafiseh Saadat Miraii,
Volume 2, Issue 1 (4-2015)
Abstract

Urban planning has to perform seismic pathology of urban streets in seismic cities. Streets and roads are the most important spaces and urban elements in the cities which should be considered not only in space occupation and connecting spaces and urban activities but also in seismic vulnerability and on this basis it is planned to reduce environmental hazards and on top of earthquake-related. Many physical and functional characteristics of urban spaces and the distribution and concentration of the urban population take shape to comply with the location, capacity and function of the city streets network. Therefore, one of the most essential and the most important topics in the study of seismic cities is understanding of the relation between seismicity and urban streets through seismic vulnerability studies. This paper aims to assess factors and patterns of seismic vulnerability of urban networks with a prevention planning view in the 3rd district of Tabriz City.

    This research has descriptive-analytic method and the statistical population is street network of 3rd district of Tabriz city. Data and layers of information have been prepared by documentary method and have been processed using the Delphi method and the method of ranking and rating IHWP in GIS. The main factors and indicators influencing streets vulnerability have been selected based on the eight indicators. These indicators include distance and proximity to faults, quality of buildings, the degree of closeness (width of the wall), building density, population density, the traffic service or traffic volume toward roads capacity, access to health centers and services and the land use system. The final map of seismic vulnerability has been produced by combining eight layers of information related to above mentioned indicatorsand based on it the seismic vulnerability levels and factors of the street network has been analyzed.

    The final results of the seismic vulnerability of streets have been categorized in the 5 classes of vulnerability including very low, low, medium, high and very high. From total area 18.4% is estimated very low, 29.37% low, 31.77% medium, 14.21% high and 6.22% very high. Thus, taking into account the streets with medium, high and very high degree as vulnerable axes, it is concluded that 52.2% or more than half of the streets are seismic vulnerable and other half are relatively stable.

    Within the vulnerable and unstable network, more than 20% of the streets are in high and very high vulnerable classes. Street network with high and very high vulnerability are mainly arterial streets with commercial and service land uses in the scale of trans-regional or secondary roads leading to artery of trans-regional which have high population density. These streets compose a high degree of closeness, increase in traffic service level, population density and land use system with the concentration of commercial, recreational and trans-regional land uses are the main causes of vulnerability. But, in the narrow streets (8 to 10 meters), the degree of closeness of arterial streets, traffic parameters and user system have increased the seismic vulnerability index. Spatial pattern of streets vulnerability has an increasing trend from East to West and from North to south. The results show Spatial intensity of vulnerable streets is located at the center of the district and on Vali Asr, Shariati, Aref  and Razi Streets. Thus, the efficient and sustainable streets are located in the East of the under studied district.

    The results also show that high vulnerable streets has less distance to fault and more distance from medical centers. In addition, they have high traffic and lower quality buildings and high risk land uses (electric and gas infrastructure) are located there. Since the wide streets are more often subject to less obstruction, this characteristic in seismic time cause to transfer the traffic of narrow passage to the main streets. Grid pattern of streets and frequency of intersections by slowing down the speed of the vehicle increase the volume of traffic and lead to an increase in seismic vulnerability.


Fateme Emadoddin, Dr Amir Safari,
Volume 9, Issue 4 (3-2023)
Abstract

 Vulnerability assessment of karst aquifer using COP and PI model (Case study: Bisotun and Paraw aquifers)


 Introduction
Drinking karst water resources, especially in arid and semi-arid regions, like Iran, are considered as valuable and strategic water resources. A sharp decrease in rainfall reduces the quality and quantity of karst water sources (Christensen et al., 2007). On the other hand, urban and industrial development, which is accompanied by the increase in population growth, increases the risk of underground water pollution caused by the dumping of chemicals, waste and change of use (McDonald et al., 2011). Protection of karst aquifer is one of the most important measures in the management of karst water resources due to its vulnerability and high sensitivity to pollution (Khoshakhlagh et al., 2014, Afrasiabian, 2007). Therefore, With the advancement of geographic information system technology, rapid progress was made in the ability to identify and model groundwater pollution, as well as the vulnerability of water sources from these pollutants (Babiker et al., 2004, Rahman, 2008). The pollution potential decreases from the center to the periphery (Saffari et al., 2021).

 Materials and methods
In this study to evaluate the vulnerability of Bisotun and Paraw aquifer which is karstically developed and has, crack and fissure and various landforms; COP and PI vulnerability models have been used to identify areas at risk of contamination. The COP model includes three main factors including concentration of flow (C), overlaying layers (O) and precipitation (P). Factor C, which indicates surface features (Sf), slope and vegetation (Sv). It was obtained between 0.8-0.0 in 5 classes. From the overlap of the subfactores soil, layer index and lithology, the O factor map was prepared in three classes, including class 2 with low protection value, 2-4 with medium protection value and 4-8 with high protection value.  The P factor, which is the temporal distribution of precipitation along with the intensity and duration of precipitation, can show the ability of precipitation to transfer pollutants from the surface to the underground water. P factor was 0.8 in 2 layers in the northwest of the study area and 0.8-0.9 with low protection value. Furthermore, top Soil, precipitation, net recharge, fracture density, bedrock and lithology maps were used for the protective cover factor (P) in the PI model. The zoning of the P factor showed 2 classes such as very low and low most of the study area is in the low class. The infiltration condition factor (I) using the characteristics of the soil, the slope layer, and the land use in four layers showed high, aamedium, low, very low, which due to the high slope of the area of ​​the high layer has the highest dispersion, which causes the reduction of the protective cover.

 Results and discussion
Consequently, COP vulnerability map in 5 classes with very high vulnerability (0-0.5) equal to 38774.74 hectares (41.4%) and very low vulnerability (4-9-4) with 57.86 hectares (0.06%) of the largest and smallest area respectively. Also, the PI vulnerability map of the combination of these two factors showed very high vulnerability with the largest area of ​​about 68,783 hectares and 72.9% scattered throughout the study area and the high vulnerability class with an area of ​​about 25,526 hectares and 27%.

 Conclusion
The results of this research showed that the simulation performance of each COP and PI vulnerability model is closely related to the amount of pollution in the environment. It seems that the COP vulnerability model can better and more accurately showed the level of vulnerability in the karst aquifers of Bisotun and Paraw.



Keywords: karst aquifer, Bisotun and Paraw, COP model, PI model, vulnerability.


 


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