ارزیابی خطر وقوع زمین لغزش در حوضه ابخیز اوغان استان گلستان با استفاده از فراینده تحلیل شبکه(ANP)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 مشاور سازمان هلال احمر

2 استاد تمام -دانشگاه علوم تحقیقات تهران

3 دانشیار. دانشگاه آزاد واحد شهر ری

چکیده

چکیده
سابقه و هدف
زمینلغزش یکی از مخربترین حوادث طبیعی در مناطق شیبدار می باشد. کشور ایران با توجه به موقعیت جغرافیایی، تنوع اقلیمی و ژئومورفولوژیکی، افزایش جمعیت و فشار بر منابع طبیعی در معرض این مخاطره طبیعی است. از این رو تهیه نقشههای پهنهبندی خطر وقوع زمینلغزش دارای اهمیت فراوان است. بنابراین با توجه به گزارشات وقوع زمین لغزش در حوضه آبخیز اوغان استان گلستان، هدف این پژوهش پهنهبندی این مخاطره در قالب مدل فرایند تحلیل شبکه(ANP) میباشد.
مواد و روش‌ها
برای پهنهبندی زمینلغزش در حوضه آبخیز اوغان، در مرحله اول نقشه عوامل موثر بر وقوع زمینلغزش از منابع اطلاعاتی مانند نقشههای توپوگرافی 1:50000، زمینشناسی 1:100000، آمار بارش و عکسهای هوایی و تصاویر ماهوارهای تهیه و با پیمایش صحرایی در حوضه مذکور که در موقعیت جغرافیایی´9 °37 تا´15 °37 عرض شمالی و ´5 °55 تا ´43 °55 طول شرقی با مساحت 40352 هکتار قرار دارد، تکمیل و اصلاح شد، در ادامه نقشه عوامل موثر شامل: شیب، جهت دامنه، ارتفاع، بارندگی، فاصله از جاده، فاصله از گسل، فاصله از آبراهه، کاربری ارضی منطقه، سنگشناسی و همچنین لایه پراکنش زمین لغزشها در محیط نرمافزار ArcGIS ساماندهی شده و در مرحله دوم وزن عوامل موثر، بوسیله مدل ANP محاسبه و بر لایههای اطلاعاتی برای در محیط GIS اعمال و با همپوشانی آنها نقشه پهنهبندی وقوع زمینلغزش تهیه گردید. در مرحله سوم دقت نقشه پهنهبندی شده با کاربرد شاخص نسبت تراکمی (Dr) و مقدار درجه تناسب مورد ارزیابی قرار گرفت.
یافته‌ها
نتیجه شناسایی 88 عدد زمینلغزش به مساحت 181 هکتار(شکل5) و بررسی ارتباط با عوامل موثر بر وقوع زمین لغزش نشان داد، که بیشتر لغزشها در واحدهای سنگشناسی شیل، مارن، سنک آهک ورقهای، ماسهسنگ و نهشتههای کواترنری قرار دارد (جدول1). همچنین نتایج بررسی طبقات مختلف شیب نشان میدهد که بیشتر زمین لغزشها در طبقه شیب 15-30 درصد لغزیدهاند در بررسی طبقات بارش روند وقوع زمینلغزشها با افزایش طبقه بارش صعودی بوده و طبقات700-500 و بالاتر از700 میلیمتر بارش سالانه، درصدی قابل توجه از زمین لغزشها را در خود جای دادهاست. نتایج عوامل موثر فاصله از جاده و آبراهه نشانداد که بیشترین لغزشها در فاصله کمتر از صد متری این عوارض میباشد و این موضوع تائید کننده نقش برداشت پای شیب دامنهها توسط یک عامل انسان ساخت و یک عامل طبیعی میباشد. در نهایت بررسی عامل فاصله از گسل بر وقوع زمین لغزش نشان میدهد که بیشترین زمینلغزشها در فاصله بیشتر از 400متری قرار دارند(جدول 2).
نتیجه گیری
نتایج پهنهبندی با بکارگیری مدل ANP در حوضه اوغان نشان داد: 29 درصد حوضه در طبقات چهارگانه در محدوده خطر زیاد وخیلی زیاد قرار دارد. از بین لایههای اطلاعاتی 8 گانه، عامل شیب با امتیاز وزنی(215/0)، لیتولوژی(182/0) و فاصله از جاده(173/0) بالاترین وزن و جهت شیب با امتیاز وزنی(018/0) پایین ترین امتیاز را در پهنهبندی به خود اختصاص دادند. بررسی امتیاز وزنی طبقات مختلف عوامل موثر نیز نشان داد که طبقه 100-0 متر فاصله از آبراهه با امتیاز وزنی(080/0) ، طبقه شیب 30-15درصد با امتیاز وزنی (078/0) و طبقه 100-0 متر فاصله از جاده با امتیاز وزنی(068/0) بالاترین امتیازات وزنی را به دست آوردهاند. نتایج حاصل از این مدل در نهایت نشانداد، که همگرایی عواملی مانند شیب، لیتولوژی، فاصله از آبراهه بعنوان عوامل طبیعی در کنار عامل انسانی، همچون جاده سازی تاثیر بسیار زیادی در وقوع مخاطره زمینلغزش دارد در نهایت با بررسی نسبت تراکم 88 زمین لغزش رخداده و روند صعودی منحنی آن و انطباق پهنههای لغزشی با کاربرد درجه تناسب به میزان 7/69 درصد بر طبقات زیاد و خیلی زیاد در نقشه نهایی، میتوان نتیجه گرفت که فرایند تحلیل شبکه کارائی مناسب در پهنه بندی خطر زمین لغزش در حوضه اوغان را دارا می باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Landslide hazard mapping of oghan watershed basin in Golestan province using Analytic Network Process (ANP) model

نویسندگان [English]

  • Golamreza Golamei Kalateh 1
  • Parviz Kardavani 2
  • Mohsen Ranjbar 3
1 Consultant of Red Crescent
2 Professor- azad nive.science and research branch
3 Assistant. Professor
چکیده [English]

Extended abstract​
Background and objectives
Landslide is one of the most destructive natural events in steep areas. Due to its geographical position, climatic and geomorphological conditions, population increase, pressure on natural resources and land use change, Iran is exposed to natural hazards. Therefore, preparation of landslide hazards mapping is very important. So according to landslide events reports of Oghan watershed basin in Golestan province, The aim for this research is landslide hazards mapping using Analytic Network Process model.
Materials and methods
For landslide hazard mapping in Oghan watershed basin, At first step, maps of effective factors were prepared by using of information sources, 1:50000 topographic and 1:100000 geological maps, rain statistics, aerial photos and satellite images. Then, these information were completed by field surveying in mentioned region that its geographical position is between37° 9´ to 37° 15´ northern latitude and 55° 5´ to 55° 43´eastern longitude with area and average altitude of 40352 ha. After that, maps of the effective factors were organized, such as: slope, aspect, elevation, rain, distance from streams, roads and fault, land use, lithology and landslide dispersion layer at ArcGIS. In the second step, the weight of effective factors was calculated by ANP model and applied to the information layers in the GIS environment. By overlapping them, a map of zonation of landslide occurrence was prepared. In the third step, the accuracy of the map of zonation was evaluated using the degree of proportionality and index Density ratio.
Results
Result of identification of 88 landslide zones with area of 181ha and investigation of their relationship with effective factors showed that most of landslides are located in lithological units of shale, marl, bedded limestone, sandstone and quaternary deposits (Table1). Furthermore, results of elevation and slope layers assessment show that most landslides were happened in slope of 15-30% . In rain classes assessment, landslide occurrence has direct relationship with rain increase and classes of 500-700 and more than 700mm of annual rain have considerable percent of landslide. Results of distance from road and stream showed that most of occurred landslides are in distance less than 100m from these features and it demonstrates the role of mass taking from downhill via human or natural factors. Finally, assessment of distance from fault showed that most of landslides are located in distance classes of more than 400m (Table1).
Conclusion
The results of zonation with the ANP model in the Oghan watershed basin showed that 29 percent of the basin in the four classes is in high and very high hazard areas. Among the eight information layers, the slop factor (0.215), lithology (0.182) and distance from the road with score weighted (0.173) had the highest weight and gradient direction with the score weight (0.018), the lowest Points in the zonation. Evaluation of different classes of effective factors also showed that the class is 100 m distance from the distance from streams with score weight (0.08), slope class of 15-15% with a rate weight (0,788) and a class of 100-0 (m) distance from the road With a score weight of 0.068, they earned the highest rating weighted. The results of this model finally showed that the convergence of factors such as slope, lithology, distance from the river as natural factors along with the human factor, such as road construction, has a great influence on the hazard of landslide. Finally, by studying the density rate of 88 landslide occurrence in the basin and its upward curve and the adaptation of the sliding zones with the application of the degree of proportionality of 69.7% on the high and very high classes in the final map

کلیدواژه‌ها [English]

  • Mapping
  • Landslide
  • ANP model
  • Oghan
  • Golestan Province
-1.Abedini, M., Fathi, M., and Beheshti Javid, E. 2014. Landslide hazard zonation by fuzzy logic
model (Case study: Ghouri Chay river basin), the first Iranian Geosciences Conference.
2.Ahmadi, H., Mohammad Khan, S., Feiznia, S., and Ghoddoosi. J. 2006. Landslide hazard
zonation by AHP hierarchical analysis method in Taleghan basin, Natur. Resour. J. 58: 14-3.
3.Anbalagan, R. 2004. Landslide hazard evaluation and zoning mapping in Mount- Ainous
Terrain, Engineering Geol. 36p.
4.Azimpour, A., Sadoughi, H., Dahaloghly, A., and Richard, M. 2008. Evaluation of AHP
model results in landslide hazard zonation Case Study: Ahar Chay Basin, Geological Survey
of Iran, J. Geol. Survey. 9: 26. 87-71.
5.Bharat Prashad, B., Keshab Datt, A., Binod Prasad, H., Thakur, S., and Gandhiv, K. 2013.
Using Geographic Information System and Analytical HierarchyProcess in Landslide Hazard
Zonation Applied Ecology and Environmental Sciences. 1.2. Doi10.1296.1-2.
6.Castellanos Abella, E.A., and Van Westen, C.J. 2007. Generation of a landslide risk index
map for Cuba using spatial multi-criteria evaluation. Landslides, 4: 311-325.
7.Cruden, D.M. 1991. A Simple Definition of a landslide, Bulletin of International Association
of Engineering Geology, 43: 27-29.
8.Faraji Sabokbar, H.A., Salmani, M., Fereidouni F., Karimzadeh, H., and Rahimi, H. 2010.
Rural waste sanitary landfill location using a network process model (ANP): A case study of
rural areas in Ghoochan city, Quarterly J. Human. 14: 1. 149-12.
9.Fathi, M.H., Khohdel Kazem, A., Kandi, S., Ashrafifeini, Z., and Haliji, M.A. 2015. The
combination of spectral and spatial data in zoning oflandslidesusceptibility (Case study:
Sangorchay reservoir) J. Biodiv. Environ. Sci. (JBES) ISSN: 2220-6663. 6: 2. 515-527.
10.Fizaniya, S., Chalarstagi, A., Ahmadi, H., and Wasefayy, M. 2004. Investigation of Factors
Influencing Landslides and Landslide Risking - A Study of a Man: Shahranrood Basin of
Tajan Dam, Iran. J. Natur. Resour. 57: 1. 22-3.
11.Gee, M.D. 1992, Classification of Landslide Hazard Zonation Methods and a Test of
Predictive Capability, 6th International Symposium on Landslides: Christchurch, New
Zealand, Pp: 947-952.
12.Ghomiyan, J., Fatemi Aqda, M., Ashloqi Farahani, A., and Teshneh Lab, M. 2002. Landslide
hazard zonation using a fuzzy multi-index decision making method (Case study: Roodbar
Gilan area), Quar. J. Res. Technol. 56: 80-67.
13.Hussin, H., Zumpano, Y.V., Reichenbach, P., Sterlacchini, S., and Micu, M. 2016. Different
landslide sampling strategies in a grid-based bi-variate statistical susceptibility model,
Geomorphology , Volume 253, 15 January 2016, Pp: 508-523.
14.Jalali, N. 2002. Evaluation of conventional landslide hazard zonation in Taleghan watershed.
Proceedings of the first gathering of landslide research projects, Soil and Watershed
Protection Research Center, Pp: 115-103.
15.Kanungo, D.P., Arora, M.K., Sarkar, S., and Gupta, R.P. 2006, A Comparative Study of
Conventional, ANN Black Box, Fuzzy and Combined Neural and Fuzzy Weighting
Procedures for Landslide Susceptibility Zonation in Darjeeling Himalayas, Engineering
Geology, 85: 347-366.
16.Lan, H.X., Zhou, C.H., Wang, L.J., Zhang, H.Y., and Li, R.H. 2004. Landslide hazard spatial
analysis and prediction using GIS in the Xiaojiang Watershed, Yunnan, China. Engineering
Geology, 76: 109-128.
17.Marrapu Balendra Mouli and Ravi Sankar Jakka. 2014. Landslide Hazard Zonation Methods:
A Critical Review International Journal of Civil Engineering Research. ISSN 2278-3652.
5: 3. 215-220
18.Mayavan, N., and Sundaram, A. 2012. Statistical analysis for landslide in relation to landuse,
in Sirumalai Hill, Dindigul district, Tami Nadu, India, using GIS. Res. J. Recent Sci.
1: 12. 36-39.
19.Mirasani, R. 1999. Analytical Attitudes on Landslide Features of the Country, Proceedings
of the first Geological Conference on Environmental Engineering in Iran, First Edition,
Tarbiat Moallem University of Tehran, Pp: 71-70.
20.Moghimi, E., Yamani, M., and Vahimi, S. 1392. Landslide hazard assessment and zoning
in Roodbar using network analysis process, Quantitative Research, No. 4, Spring 2013,
Pp: 118-103.
21.Mohammadi, A., Heshmatpoor, A., and Mosaedi, A. 2004. Study on Efficiency of an Iranian
Method for Landslide Hazard Zonation in Golestan province (Iran), Geophysical Research
Abstracts, 6: 10-22.
22.Mosafaei, J., Onagh, M., Mosadaghi, M., and Shariat Jafari, M. 2009 Comparison of the
Efficiency of Empirical and Statistical Models of Landslide Risk Alignment in Alamot
Basin, Water and Soil Conservation Researches, Pp: 61-43.
23.Naderi, F., Naseri, B., Karimi, H. and Habibi Bibalani, Gh. 2010. Efficiency evaluation of
different landslide susceptibility mapping methods (Case study: Zangvan watershed, Ilam
province): First ternational conference of soil and roots engineering relationship
(LANDCON1005), Ardebil, Iran.
24.Neaupane, K.M., and Piantanakulchai, M. 2006. Analytic network process model for
landslide hazard zonation Engineering Geology, Volume 85, Issues 3-4, 21 June 2006,
Pp: 281-294.
25.Pour Hashemi, S., Amir Ahmadi, A., and Akbari, E. 2014. Selection of a suitable model
for two-way statistical methods for studying arid areas, Fourth year, No.15, Spring 2014,
Pp: 89-71.
26.Ramezani, B., and Ebrahimi, H. 2009. Recognition of the Effective Factors of Landslide in
the Barnstadt Dam Ghaemshahr Dam, Quar. J. Hum. Geograph. First Year, 4: 126-127.
27.Riedel, L., Vacik, H., and Kalasek, R. 2000. Map Models, a new approach for spatial
decision support in silvicultural decision making. Computers and Electronics in Agriculture,
27: 407-412.
28.Yalcin, A. 2008. GIS-based landslide susceptibility mapping using analytical hierarchy
process and bivariate statistics in Ardesen (Turkey): Comparisons of results and
confirmations, Catena, 72: 1-12.
29.Rostaei, S., Khodai, L., and Vakhshlag, F. 2014. Evaluation of Network Analysis (ANP) and
Multi-dimensional Spatial Analysis in the Study of the Potential of Landslide occurrence in
the Range of Dam and Shaft of the Dam (Case study: Ghaleh Dam), Research Natural
Geography, 46: 4. 495-508.
30.Sabuya, F.M., Alves, G., and Pinto, W.D. 2006. Assessment of failure susceptibility of soil
slopes sings fuzzy logic, Engineering Geology, 14p.
31.Sarolee, K.M. 2001. Statistical Analysis of landslide susceptibility at Yonging, Korea.
Environmental Geology, 40: 1095-1113.
32.Shadfar, S. 2005. Analytical evaluation of landslide quantitative models in order to achieve a
suitable model for Chalkarood watershed, Ph.D. Thesis, Geomorphology University of
Tehran, 225p.
33.Shadfar, S., and Yamani, M. 2006. Landslide hazard zonation in Jalisan watershed using
LNRF model, Geographical research, 39: 1. 68-62.
34.Shariat Jafari, M. 1996. Landslide (principles and principles of stability of natural slopes),
Sazeh Publication, 218p.
35.Shirani, K. 2006. Survey and Evaluation of Landslide Hazard Zoning Methods in Semiroma
Subsidy, J. Res. Bas. Sci. Isfahan University, No. 961, 96p.
36.Sidle, R.C., and Ochiai, H. 2006. Landslides: Processes, Prediction, and Landuse,
WaterResource Monograph: 18, AGU books, ISSN: 0170-9600.
37.Soltani, A., and Talebi, T. 2013. Investigating the spatial distribution system and location
analysis of Shiraz-based interurban bus terminals using the network analysis process (ANP),
regional studies and researches, the fifth year, the eighteenth issue, Pp: 122-107.
38.Talaei, R. 2014. Estimation of Landslide Risk in Hashtchin Area for Use in Development
Design, Journal of Engineering and Management of Watershed Management, Volume 6,
Issue No. 1. 2014, Pp: 21-41.
39.Tuzkaya, G., Tuzkaya, O.S., Umut, R., and Bahadır, G. 2008. An analytic network process
approach for locating undesirable facilities: An example from Istanbul, Turkey,
Environmental Management, 88: 4. 970-983.
40.Wu, C.I., Kung, Y., Chen, H., and Chia Kuo, L. 2014. An intelligent slopedisasterprediction
and monitoring system based on WSN and ANP Expert Systems with, Applications Volume
41, Issue 10, August 2014, Pp: 4554-4562.
41.Yamani, M., and Shadfar, S. 2010. The zoning of landslide in Tonekabon watershed using
quantitative models, Geography and Development Magazine, Pp: 98-85.
42.Zare, M., Ahmadi, H., and Gholami, S.A. 2010. Estimation of Landslide Risk Using MultiCriteria Decision Making Process and Geographical Information-Information, Case Study,
Waza Watershed, J. Iran. Natur. Ecosyst. Year One, Number two, Winter 2010, Pp: 168-179.