Volume 10, Issue 1 (5-2023)
Journal of Spatial Analysis Environmental Hazards 2023, 10(1): 23-40 |
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Hosseinzadeh M M, Salehipor Milani A R, Rezaian Zarandini F. The zoning of flood risk potential in the Nekarod Cachment, Neka- Mazandaran. Journal of Spatial Analysis Environmental Hazards 2023; 10 (1) :23-40
URL: http://jsaeh.khu.ac.ir/article-1-3352-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3352-en.html
1- Earth Sciences Faculty, Shahid Beheshti University, Tehran , m_hoseinzadeh@sbu.ac.ir
2- Earth Sciences Faculty, Shahid Beheshti University, Tehran
2- Earth Sciences Faculty, Shahid Beheshti University, Tehran
Abstract: (2419 Views)
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 1922Km 2
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 982Km 2 Km 2
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.
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
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
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.
Keywords: Flood, Multi-criteria decision making system(MCDA), Hazard zoning, Nekarod, Natural disaster
Type of Study: Research |
Subject:
Special
Received: 2022/12/23 | Accepted: 2023/05/5 | Published: 2023/10/4
Received: 2022/12/23 | Accepted: 2023/05/5 | Published: 2023/10/4
References
1. ابراهیمیان قاجاری، یاسر و محمد براری سیاوشکلایی. 1397. پهنهبندی پتانسیل تولید رواناب با استفاده از مدل GIS-MCDA فازی (مطالعه موردی: حوضه آبریز تجن). نشریه علمی-پژوهشی علوم و فنون نقشهبرداری، 9 (1): 14-2.
2. احمدی ایلخچی، عباس؛ محمدعلی حاج عباسی و احمد جلالیان. 1381. اثر تغییر کاربری زمین های مرتعی به دیم کاری بر تولید رواناب، هدر رفت و کیفیت خاک در منطقه دوراهان، چهارمحال و بختیاری. نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی، 6 (4): 121-10
3. اسفندیاری درآباد، فریبا؛ صدیقه لایقی، رئوف مصطفی زاده و خدیجه حاجی. 1400. پهنهبندی پتانسیل خطر وقوع سیلاب حوضه آبخیز قطورچای با روشهای تصمیمگیری چندمعیاره ANP و WLC . تحلیل فضایی مخاطرات محیطی، 8 (2): 135-150.
4. امیری، مهدیس؛ حمیدرضا پورقاسمی و علیرضا عربعامری. 1397. اولویتبندی سیلخیزی زیرحوزههای آبخیز مهارلو در استان فارس با استفاده از پارامترهای مورفومتریک و مدل تصمیمگیری ویکور. اکوهیدرولوژی، 5 (3): 813-827.
5. پناهی، رویا؛ محمدمهدی حسینزاده و سمیه خالقی. پهنهبندی احتمال خطر سیلاب در اراضی حاشیه رودخانه گاماسیاب در محدوده شهر صحنه تا شهر بیستون-استان کرمانشاه. مجله علمی پژوهشی مخاطرات محیط طبیعی، 26: 66-53.
6. ثقفی، مهدی و محمد حسین رضایی مقدم. 1391. ارزیابی کاربرد روش ژئومورفولوژی جهت طبقه بندی ریسک مخاطرات سیل با استفاده از منطق فازی (مطالعه موردی: حوضه آبریز اوجانچای) پژوهش های فرسایش محیطی، 2 (1): 13-28.
7. حجازی، اسدالله؛ صغری اندریانی، فرهاد الماس پور و ابوالفضل مختاری اصل. 1394. استفاده از تکنیکهای تصمیمگیری چندمعیاره و سنجش از دور در محیط GIS برای بررسی مناطق حساس به وقوع سیلاب درحوضه لیقوان چای. هیدروژئومورفولوژی، 2 (3): 61-80.
8. حسن زاده نفوتی، محمد و حبیب الله خواجه بافقی. 1395. پهنه بندی خطر سیلاب با استفاده از سیستم تصمیم گیری چندمعیاره (مطالعه موردی: حوزه آبخیز شیطور بافق). پژوهشنامه مدیریت حوزه آبخیز، ۷ (۱۴) :۲۹-۳۷.
9. حمیدی، نعمت اله؛ مهدی وفاخواه و اکبر نجفی. 1395. تهیه نقشه خطرپذیری سیلاب در حوزه آبخیز شهری نور با استفاده از تحلیل سلسله مراتبی و منطق فازی. پژوهشنامه مدیریت حوزه آبخیز، 14: 19-11.
10. رستمی، سعید؛ بابک شاهی نژاد، حجت اله یونسی، حسن ترابی پوده و رضا دهقانی. 1400. تحلیل مدلهای هوش مصنوعی هیبریدی نوین در برآورد دبی سیلابی:مطالعه موردی: حوضه آبریز کشکان. هیدروژئومورفولوژی، 29: 201-187.
11. رضوی زاده، سمانه و کاکا شاهدی. اولویت بندی سیلخیزی زیرحوضههای حوزه آبخیز طالقان با استفاده از تلفیق AHP و تاپسیس. اکوسیستم های طبیعی ایران، 7 (4): 33-46.
12. سلیمانی، کریم و محمود حبیب نژاد روشن. 1381. مقاله نقش عوامل هیدرواقلبم در وقوع سیل حوضه نکارود. مجله منابع طبیعی ایران، 55 (1) : 23-35.
13. ضیائی، خدایار؛ اباذر اسمعلی، رئوف مصطفیزاده و محمد گلشن. 1400. ارزیابی سناریوهای بهینه تغییر کاربری اراضی و تأثیر آن بر واکنش هیدرولوژیک جریان در حوضه آبریز اهل ایمان. هیدروژئومورفولوژی، 27: 138-123.
14. غلامی، محمد و مهدی احمدی. 1398. ریز پهنه بندی خطر سیلاب در شهر لامِرد با استفاده از AHP، GIS و منطق فازی. مخاطرات محیط طبیعی، 20: 114-101.
15. کارآموز، محمد و مهکامه طاهری. 1397. ارائهی راهکارهای مدیریتی در مقابله با مخاطرات همزمان سیلابهای ساحلی و درون شهری. تحقیقات منابع آب ایران، 14 (5): 71-84.
16. وهابی، جلیل. 1385 .پهنه بندی خطر سیل با استفاده از مدلهای هیدرولوژیکی و هیدرولیکی(مطالعه موردی طالقان رود). پژوهش و سازندگی در منابع طبیعی، 71: 40-33.
17. Falah, F.; O. Rahmati, M. Rostami, E. Ahmadisharaf, I. N. Daliakopoulos and H. R. Pourghasemi. 2019. Artificial neural networks for flood susceptibility mapping in data-scarce urban areas. Spatial Modeling in GIS and R for Earth and Environmental Sciences, 14: 323-336. DOI:
18. Fernández, D. S. and M. A. Lutz. 2010. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1-4): 90-98.
19. Hajkowicz, S. and K. Collins. 2007. A review of multiple criteria analysis for water resource planning and management. Water resources management, 21(9): 1553-1566.
21. Hudson, P. G. M. B.; W. J. W. Botzen, H. Kreibich, P. Bubeck, and J. C. J. H. Aerts. 2014. Evaluating the effectiveness of flood damage mitigation measures by the application of propensity score matching. Natural Hazards and Earth System Sciences, 14(7): 1731-1747.
23. Li, K.; S. Wu, E. Dai, and Z. Xu. 2012. Flood loss analysis and quantitative risk assessment in China. Natural hazards, 63(2): 737-760.
25. Lyu, H. M.; S. L. Shen, A. Zhou, and J. Yang. 2019. Perspectives for flood risk assessment and management for mega-city metro system. Tunneling and Underground Space Technology, 84: 31-44.
27. Malczewski, J. 2004. GIS-based land-use suitability analysis: a critical overview. Progress in planning, 62(1): 3-65.
29. Mishra, K. and R. Sinha. 2020. Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydro-geomorphic approach. Geomorphology, 350: 1-19.
31. Mostafazadeh, R.; A. Sadoddin, A. Bahremand, V.B. Sheikh, A. Zare Garizi. 2017. Scenario analysis of flood control structures using a multi-criteria decision-making technique in Northeast Iran. Natural Hazards, 87: 1827-1846.
33. Ogato, G. S.; A. Bantider, K. Abebe, and D. Geneletti. 2020. Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, West shoa zone, oromia regional State, Ethiopia. Journal of Hydrology: Regional Studies, 27: 100659-100687.
35. Papaioannou, G.; L. Vasiliades, and A. Loukas. 2015. Multi-criteria analysis framework for potential flood prone areas mapping. Water resources management, 29(2): 399-418.
37. Rashid, H. 2011. Interpreting flood disasters and flood hazard perceptions from newspaper discourse: Tale of two floods in the Red River valley, Manitoba, Canada. Applied Geography, 31(1): 35-45.
39. Samanta, S.; C. Koloa, D. Kumar Pal, and B. Palsamanta. 2016. Flood risk analysis in lower part of Markham river based on multi-criteria decision approach (MCDA). Hydrology, 3(3): 29-45.
41. Sun, H.T. and Y. K. 2013. Multi-criteria decision making under uncertainty for flood mitigation. Stochastic Environmental Research and Risk Assessment, 28(7): 1657-1670.
43. Xiao, Y.; S. Yi, and Z. Tang. 2017. Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference. Science of the Total Environment, 599: 1034-1046.
45. ابراهیمیان قاجاری، یاسر و محمد براری سیاوشکلایی. 1397. پهنهبندی پتانسیل تولید رواناب با استفاده از مدل GIS-MCDA فازی (مطالعه موردی: حوضه آبریز تجن). نشریه علمی-پژوهشی علوم و فنون نقشهبرداری، 9 (1): 14-2.
46. احمدی ایلخچی، عباس؛ محمدعلی حاج عباسی و احمد جلالیان. 1381. اثر تغییر کاربری زمین های مرتعی به دیم کاری بر تولید رواناب، هدر رفت و کیفیت خاک در منطقه دوراهان، چهارمحال و بختیاری. نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی، 6 (4): 121-103.
47. اسفندیاری درآباد، فریبا؛ صدیقه لایقی، رئوف مصطفی زاده و خدیجه حاجی. 1400. پهنهبندی پتانسیل خطر وقوع سیلاب حوضه آبخیز قطورچای با روشهای تصمیمگیری چندمعیاره ANP و WLC . تحلیل فضایی مخاطرات محیطی، 8 (2): 135-150.
48. امیری، مهدیس؛ حمیدرضا پورقاسمی و علیرضا عربعامری. 1397. اولویتبندی سیلخیزی زیرحوزههای آبخیز مهارلو در استان فارس با استفاده از پارامترهای مورفومتریک و مدل تصمیمگیری ویکور. اکوهیدرولوژی، 5 (3): 813-827.
49. پناهی، رویا؛ محمدمهدی حسینزاده و سمیه خالقی. پهنهبندی احتمال خطر سیلاب در اراضی حاشیه رودخانه گاماسیاب در محدوده شهر صحنه تا شهر بیستون-استان کرمانشاه. مجله علمی پژوهشی مخاطرات محیط طبیعی، 26: 66-53.
50. ثقفی، مهدی و محمد حسین رضایی مقدم. 1391. ارزیابی کاربرد روش ژئومورفولوژی جهت طبقه بندی ریسک مخاطرات سیل با استفاده از منطق فازی (مطالعه موردی: حوضه آبریز اوجانچای) پژوهش های فرسایش محیطی، 2 (1): 13-28.
51. حجازی، اسدالله؛ صغری اندریانی، فرهاد الماس پور و ابوالفضل مختاری اصل. 1394. استفاده از تکنیکهای تصمیمگیری چندمعیاره و سنجش از دور در محیط GIS برای بررسی مناطق حساس به وقوع سیلاب درحوضه لیقوان چای. هیدروژئومورفولوژی، 2 (3): 61-80.
52. حسن زاده نفوتی، محمد و حبیب الله خواجه بافقی. 1395. پهنه بندی خطر سیلاب با استفاده از سیستم تصمیم گیری چندمعیاره (مطالعه موردی: حوزه آبخیز شیطور بافق). پژوهشنامه مدیریت حوزه آبخیز، ۷ (۱۴) :۲۹-۳۷.
53. حمیدی، نعمت اله؛ مهدی وفاخواه و اکبر نجفی. 1395. تهیه نقشه خطرپذیری سیلاب در حوزه آبخیز شهری نور با استفاده از تحلیل سلسله مراتبی و منطق فازی. پژوهشنامه مدیریت حوزه آبخیز، 14: 19-11.
54. رستمی، سعید؛ بابک شاهی نژاد، حجت اله یونسی، حسن ترابی پوده و رضا دهقانی. 1400. تحلیل مدلهای هوش مصنوعی هیبریدی نوین در برآورد دبی سیلابی:مطالعه موردی: حوضه آبریز کشکان. هیدروژئومورفولوژی، 29: 201-187.
55. رضوی زاده، سمانه و کاکا شاهدی. اولویت بندی سیلخیزی زیرحوضههای حوزه آبخیز طالقان با استفاده از تلفیق AHP و تاپسیس. اکوسیستم های طبیعی ایران، 7 (4): 33-46.
56. سلیمانی، کریم و محمود حبیب نژاد روشن. 1381. مقاله نقش عوامل هیدرواقلبم در وقوع سیل حوضه نکارود. مجله منابع طبیعی ایران، 55 (1) : 23-35.
57. ضیائی، خدایار؛ اباذر اسمعلی، رئوف مصطفیزاده و محمد گلشن. 1400. ارزیابی سناریوهای بهینه تغییر کاربری اراضی و تأثیر آن بر واکنش هیدرولوژیک جریان در حوضه آبریز اهل ایمان. هیدروژئومورفولوژی، 27: 138-123.
58. غلامی، محمد و مهدی احمدی. 1398. ریز پهنه بندی خطر سیلاب در شهر لامِرد با استفاده از AHP، GIS و منطق فازی. مخاطرات محیط طبیعی، 20: 114-101.
59. کارآموز، محمد و مهکامه طاهری. 1397. ارائهی راهکارهای مدیریتی در مقابله با مخاطرات همزمان سیلابهای ساحلی و درون شهری. تحقیقات منابع آب ایران، 14 (5): 71-84.
60. وهابی، جلیل. 1385 .پهنه بندی خطر سیل با استفاده از مدلهای هیدرولوژیکی و هیدرولیکی(مطالعه موردی طالقان رود). پژوهش و سازندگی در منابع طبیعی، 71: 40-33.
61. Falah, F.; O. Rahmati, M. Rostami, E. Ahmadisharaf, I. N. Daliakopoulos and H. R. Pourghasemi. 2019. Artificial neural networks for flood susceptibility mapping in data-scarce urban areas. Spatial Modeling in GIS and R for Earth and Environmental Sciences, 14: 323-336. DOI:
62. Fernández, D. S. and M. A. Lutz. 2010. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1-4): 90-98.
63. Hajkowicz, S. and K. Collins. 2007. A review of multiple criteria analysis for water resource planning and management. Water resources management, 21(9): 1553-1566.
64. Hudson, P. G. M. B.; W. J. W. Botzen, H. Kreibich, P. Bubeck, and J. C. J. H. Aerts. 2014. Evaluating the effectiveness of flood damage mitigation measures by the application of propensity score matching. Natural Hazards and Earth System Sciences, 14(7): 1731-1747.
65. Li, K.; S. Wu, E. Dai, and Z. Xu. 2012. Flood loss analysis and quantitative risk assessment in China. Natural hazards, 63(2): 737-760.
66. Lyu, H. M.; S. L. Shen, A. Zhou, and J. Yang. 2019. Perspectives for flood risk assessment and management for mega-city metro system. Tunneling and Underground Space Technology, 84: 31-44.
67. Malczewski, J. 2004. GIS-based land-use suitability analysis: a critical overview. Progress in planning, 62(1): 3-65.
68. Mishra, K. and R. Sinha. 2020. Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydro-geomorphic approach. Geomorphology, 350: 1-19.
69. Mostafazadeh, R.; A. Sadoddin, A. Bahremand, V.B. Sheikh, A. Zare Garizi. 2017. Scenario analysis of flood control structures using a multi-criteria decision-making technique in Northeast Iran. Natural Hazards, 87: 1827-1846.
70. Ogato, G. S.; A. Bantider, K. Abebe, and D. Geneletti. 2020. Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, West shoa zone, oromia regional State, Ethiopia. Journal of Hydrology: Regional Studies, 27: 100659-100687.
71. Papaioannou, G.; L. Vasiliades, and A. Loukas. 2015. Multi-criteria analysis framework for potential flood prone areas mapping. Water resources management, 29(2): 399-418.
72. Rashid, H. 2011. Interpreting flood disasters and flood hazard perceptions from newspaper discourse: Tale of two floods in the Red River valley, Manitoba, Canada. Applied Geography, 31(1): 35-45.
73. Samanta, S.; C. Koloa, D. Kumar Pal, and B. Palsamanta. 2016. Flood risk analysis in lower part of Markham river based on multi-criteria decision approach (MCDA). Hydrology, 3(3): 29-45.
74. Sun, H.T. and Y. K. 2013. Multi-criteria decision making under uncertainty for flood mitigation. Stochastic Environmental Research and Risk Assessment, 28(7): 1657-1670.
75. Xiao, Y.; S. Yi, and Z. Tang. 2017. Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference. Science of the Total Environment, 599: 1034-1046.
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