Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Zonation of Avalanche Pathways of Kurdistan Province

Authors
Hadi Nayyeri
Mohammadreza Karami
Bahram Charehkhah
10.18869/acadpub.jsaeh.3.2.35
Abstract
Risk is an inevitable part of life, every day people are somehow at risk. Different risks in various forms and perspectives have different functions. Kurdistan province, with various heights and relatively good rainfall, It results the country's cold spots. Since most of seasonal rainfall occurs in winter, Snow cover is often the domain and passes it hillsides. One of the concerns of people in the mountainous area is a snow avalanche phenomenon. Sudden loss of massive snow is avalanche snow that may include rocks, soil, plants or ice. It seems that the name of the snow avalanche adopted from the eleventh month of the solar year. The possibility of snow in mountainous areas during this month of year is more than other months. Snow avalanches every year around the world, especially in alpine impose huge human and financial losses. Statistics and local evidence also show that the province of Kurdistan expect or accept to soil erosion and destruction of infrastructure and natural resources had a casualty. Actually, this is the most vital reason why zoning area danger avalanche was conducted in this study.

First, avalanche pathways was recognised and selected as a field visit by department of urban development The purpose of the visit was to extract the geography’s coordinates of the avalanche. The Background of the study shows some of the land criteria are more important than others. For this purpose we performed a literature survey to explore indicators that had a significant impact on avalanche snow like such as; slope, aspect, elevation, convexity and concavity, distance to roads and land. To facilitate greater accuracy, all criteria were used in geographic information system (GIS) for mapping. Thereafter, produced map can be categorised into four classes of low, moderate, high and very high. In the next step. Analytic hierarchy process (AHP) and Analytic Network Process (ANP) model were used for weighting and ranking all criteria (slope, aspect, elevation, convexity and concavity, distance to roads and land use) by using pairwise comparisons with judgments that represent the dominance of one element over another with respect to a property that they share. The Analytic Hierarchy Process (AHP) is a method for decision making which includes qualitative factors. In this method, ratio scales are obtained from ordinal scales which are derived from individual judgments for qualitative factors using the pairwise comparison matrix. The Analytic Network Process (ANP) is a more general form and extension of Analytical Hierarchy Process also uses a pairwise comparison matrix to obtain ratio scales. The difference between these two methods appears in modelling the problem and computing the final priorities for the criteria from ratio scales previously obtained. The ANP feedback approach replaces hierarchies with networks, and emphasizes interdependent relationships among all decision criteria were used in this study).

Based on the resultant Maps, AHP and ANP had a good overlap with visited points and with high accuracy lay in areas of high risk and very high risk. According to the map provided by Analytic Hierarchy Process from the total number of 30 hillsides, thirteen of them lay in very high risk and seventeen of them in the area of high risk. Thereafter, resultant maps of Analytic network Process shows from the total number of 30 hillsides twelve of them lay in very high risk area and eighteen of them in the high risk area.

The results of (AHP) indicates that from the total area of Kurdistan province, about 1049.7 square kilometres is classified in the low risk area, 11.392 square kilometres in moderate, 14.341 in the high risk area and 2009.1 square kilometres in very high risk area, respectively . In view of the process of the network as map about 978 square kilometres is in low risk area, 10245 square kilometres in moderate risk area, 15410 square kilometres in the high danger area and 2158 square kilometres is located in very high danger area. Therefore, we can use ground data for snow avalanche zoning areas along with Analytic Hierarchy Process and Analytic Network in zoning areas avalanche risk which is applicable. Weather parameters like snow, wind and temperature have an important role in terms of snow avalanche. Decreasing rainfall from west to east of study area. The number of freezing and snowing days indicates the critical situation for snow avalanche in the highlands and the pathways. More prevailing wind direction in the cities are in the Southern west, Southern and in area with high elevation blowing from western direction. Looking at the range of high and very high can be seen, mostly in the North and South and North East which show the impact of prevailing wind upon snow and putting snow in hillsides that can produce snow avalanches

. The hillsides show most of avalanche dangers are at west, northwest and south of Kurdistan thus they are compatible with rainy areas. To build any recreation centred including, winter sports, road construction and expansion, snow avalanche risk areas should be considered. Now pathways don’t have any risk signs warning about avalanches. The warning signs of avalanche at the pathways are essential.In the hierarchical model 198 villages lay at low-risk areas and 20 villages in the area were extremely dangerous. Also in the network model 184 villages in low-risk areas and 23 villages in the area were very dangerous.
Keywords
Risk
Avalanche
land criteria
Passway
Analytic hierarchy process
analytic network process
Kurdistan
Ayala, A.; Goudie, A. 2014. Geomorphological Hazards and Disaster Prevention. Chapter 5 – Review and future challenges in snow avalanche risk analysis pp. 49-62. DOI http://dx.doi.org/10.1017/CB09780511807527.
Jaedicke, C.; Bakkehoi, S. 2007. Climate database for avalanche consulting and warning in Norway. Cold region science and technology, 47: 171-179.
Cappabianca, F.; Barbolini, M.; Natale, l. 2008. Snow avalanche risk assessment and mapping: a new method based on a combination of statistical analysis, avalanche dynamics simulation and empirically-based vulnerability relations integrated in a GIS platform. Cold region science and technology 54: 193-205.
Garcia, C. ; Gloria, M.; Oller, P.; Moner, I.; Gavalda, J.; Martinez, P.; Carlos Pena, J. 2009. Major avalanches occurrence at regional scale and related atmospheric circulation patterns in Eastern Pyrenees. Cold region science and technology 59: 106-118.
Jamieson, B.; Haegeli, P.; Schweizer, J. 2009. Field observation for estimating the local avalanche danger in the Colombia Mountain of Canada. Cold region science and technology 58 : 84-91.
Eckert, N.; Coleou, Casterbrunet, H.; Deschatres, M.; Giraud, G.; Gaume, J.2010. Cross-comparison of meteorological and avalanche data for characterizing avalanche cycles: The example of December 2008 in the eastern part of the French Alps. Cold region science and technology 64: 119-136.