Skip to main content

Advertisement

SpringerLink
Log in

Application of GIS-based analytic hierarchy process and frequency ratio model to flood vulnerable mapping and risk area estimation at Sundarban region, India

  • Original Article
  • Published:
Modeling Earth Systems and Environment Aims and scope Submit manuscript

Abstract

Flood is one of the most devastating natural calamities with environmental and socio-economic impacts. Comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main objective of this study was to examine the capability of geographic information system (GIS) in coupling with analytic hierarchy process (AHP) and frequency ratio (FR) model for flood vulnerability mapping. The study was carried out in two stages of analysis. First of all, a flood inventory map was prepared. Consequently, seven flood contributing factors viz. land elevation, slope angle, topographic wetness index, rainfall deviation, land use land cover, clay content in soil and distance from rivers were prepared for spatial analysis. Looking toward the flood records, a total of 270 flood points were marked from field study area, out of which 200 (75%) flood points were randomly selected for training data and the remaining 70 (25%) flood points were used for testing or validation purposes using prediction accuracy and success rate. The result revealed that distance from river, rainfall deviation and land use land cover have the great role for flood occurring in the study area with selected factor weight value (SFWV) of 0.33, 0.21 and 0.14, respectively. The validation result showed that prediction accuracy was 0.8142 and success rate was 0.8450 which may consider for validating the frequency ratio model that applied in present study. The application of AHP and frequency ratio model helps in identifying flood vulnerable zonation and potential risk area estimation. The findings from present study will be helpful for planner in flood mitigation strategies as a part of flood preparedness and will appear as a source for further research in the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Adiat KAN, Nawawi MNM, Abdullah K (2012) Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool—a case of predicting potential zones of sustainable groundwater resources. J Hydrol 440–41:75–89

    Article  Google Scholar 

  • Ali SA, Ahmad A (2018) Using analytic hierarchy process with GIS for dengue risk mapping in Kolkata Municipal Corporation, West Bengal, India. Spat Inf Res 26(4):449–469. https://doi.org/10.1007/s41324-018-0187-x

    Article  Google Scholar 

  • Ali SA, Ahmad A (2019) Mapping of mosquito-borne diseases in Kolkata municipal corporation using GIS and AHP based decision making approach. Spat Inf Res. https://doi.org/10.1007/s41324-019-00242-8

    Article  Google Scholar 

  • Alvarado-Aguilar D, Jiménez JA, Nicholls RJ (2012) Flood hazard and damage assessment in the Ebro Delta (NW Mediterranean) to relative sea level rise. Nat Hazards 62:1301–1321

    Article  Google Scholar 

  • Aniya M (1985) Landslide-susceptibility mapping in the Amahata river basin, Japan. Ann Assoc Am Geogr 75(1):102–114

    Article  Google Scholar 

  • Billa L, Shattri M, Mahmud AR, Ghazali AH (2006) Comprehensive planning and the role of SDSS in flood disaster management in Malaysia. Disaster Prev Manag 15:233–240

    Article  Google Scholar 

  • Booij MJ (2005) Impact of climate change on river flooding assessed with different spatial model resolutions. J Hydrol 303:176–198

    Article  Google Scholar 

  • Bunruamkaewa K, Murayamaa Y (2011) Site suitability evaluation for ecotourism using GIS & AHP: a case study of Surat Thani Province, Thailand. Proc Soc Behav Sci 21:269–278. https://doi.org/10.1016/j.sbspro.2011.07.024

    Article  Google Scholar 

  • Chen Y, Yua J, Khan S (2010) Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation. Environ Model Softw 25:1582–1591. https://doi.org/10.1016/j.envsoft.2010.06.001

    Article  Google Scholar 

  • Chung CF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazard 30:451–472

    Article  Google Scholar 

  • Cloke H, Pappenberger F (2009) Ensemble flood forecasting: a review. J Hydrol 375(3):613–626

    Article  Google Scholar 

  • Danda AA (ed) (2010) Sundarbans: future imperfect climate adaptation report. WWF-India, Kolkata

    Google Scholar 

  • Dang NM, Babel MS, Luong HT (2011) Evaluation of food risk parameters in the day river flood diversion area, Red river delta, Vietnam. Nat Hazards 56:169–194

    Article  Google Scholar 

  • Eskandari M, Homaee M, Falamaki A (2016) Landfill site selection for municipal solid wastes in mountainous areas with landslide susceptibility. Environ Sci Pollut Res 23(12):12423–12434. https://doi.org/10.1007/s11356-016-6459-x

    Article  Google Scholar 

  • Esteves LS (2013) Consequences to flood management of using different probability distributions to estimate extreme rainfall. J Environ Manag 115:98–105

    Article  Google Scholar 

  • Feng CC, Wang YC (2011) GIS science research challenges for emergency management in southeast Asia. Nat Hazards 59:597–616

    Article  Google Scholar 

  • Fernandez DS, Lutz MA (2010) Urban flood hazard zoning in Tucuman Province, Argentina, using GIS and multicriteria decision analysis. Eng Geol 111:90–98

    Article  Google Scholar 

  • Ghosh A, Schmidt S, Fickert T, Nusser M (2015) The Indian Sundarban Mangrove forests: history, utilization, Conservation Strategies and Local Perception. Diversity 7(2):149–169. https://doi.org/10.3390/d7020149

    Article  Google Scholar 

  • Glenn E, Morino K, Nagler P, Murray R, Pearlstein S, Hultine K (2012) Roles of salt cedar (Tamarix spp.) and capillary rise in salinizing a non-flooding terrace on a flow-regulated desert river. J Arid Environ 79:56–65

    Article  Google Scholar 

  • Guler D, omralıoglu T (2017) Alternative suitable landfill site selection using analytic hierarchy process and geographic information systems: a case study in Istanbul. Environ Earth Sci 76:678. https://doi.org/10.1007/s12665-017-7039-1

    Article  Google Scholar 

  • Haghizadeh A, Siahkamari S, Haghiabi AH, Rahmati O (2017) Forecasting flood-prone areas using Shannon’s entropy model. J Earth Syst Sci 126:39. https://doi.org/10.1007/s12040-017-0819-x

    Article  Google Scholar 

  • Haq M, Akhtar M, Muhammad S, Paras S, Rahmatullah J (2012) Techniques of remote sensing and GIS for flood monitoring and damage assessment: a case study of Sindh province, Pakistan. Egypt J Remote Sens Space Sci 15(2):135–141. https://doi.org/10.1016/j.ejrs.2012.07.002

    Article  Google Scholar 

  • Hazra S, Ghosh T, DasGupta R, Sen G (2002) Sea level and associated changes in the Sundarbans. Sci Cult 68:309–321

    Google Scholar 

  • Huang X, Tan H, Zhou J, Yang T, Benjamin A, Wen SW, Li S, Liu A, Li X, Fen S, Li X (2008) Flood hazard in Hunan Province of China: an economic loss analysis. Nat Hazards 47:65–73

    Article  Google Scholar 

  • Kay S, Caesar J, Wolf J, Bricheno L, Nicholls RJ, Islam AS, Lowe JA (2015) Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change. Environ Sci Process Impacts 17:1311–1322

    Article  Google Scholar 

  • Khosravi K, Nohani E, Maroufinia E, Pourghasemi HR (2016) A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making technique. Nat Hazards 1:2. https://doi.org/10.1007/s11069-016-2357-2

    Article  Google Scholar 

  • Kia MB, Pirasteh S, Pradhan B, Rodzi MA, Sulaiman WNA, Moradi A (2012) An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ Earth Sci 67:251–264

    Article  Google Scholar 

  • Lee MJ, Kang JE, Jeon S (2012a) Application of frequency ratio model and validation for predictive flooded area susceptibility mapping using GIS. Geoscience and Remote Sensing Symposium (IGARSS), Munich; 895–898

  • Markantonis V, Meyer V, Lienhoop N (2013) Evaluation of the environmental impacts of extreme floods in the Evros river basin using contingent valuation method. Nat Hazards 69:1535–1549

    Article  Google Scholar 

  • Messner F, Meyer V (2006) Flood damage, vulnerability and risk perception-challenges for flood damage research. Springer, Amsterdam, pp 149–167

    Google Scholar 

  • Minea G (2013) Assessment of the flash flood potential of Basca river catchment (Romania) based on physiographic factors. Cent Eur J Geosci 5:344–353

    Google Scholar 

  • Mishra K (2013) Geomorphological studies and flood risk assessment of Kosi river basin using remote sensing and GIS techniques. 57. www.iirs.gov.in. Accessed 13 Dec 2018

  • Moel HD, Vliet MV, Aerts JCJH (2014) Evaluating the effect of flood damage-reducing measures: a case study of the unembanked area of Rotterdam, the Netherlands. Reg Environ Change 14(895):908. https://doi.org/10.1007/s10113-013-0420-z

    Article  Google Scholar 

  • Mondal S, Maiti R (2013) Integrating the analytical hierarchy process (AHP) and the frequency ratio (FR) model in landslide susceptibility mapping of Shiv-khola watershed Darjeeling Himalaya. Int J Disaster Risk Sci 4(4):200–212. https://doi.org/10.1007/s13753-013-0021-y

    Article  Google Scholar 

  • Montenegroa LV, Baviera-Puig A, García-Álvarez-Coquec JM (2014) Multi-criteria methodology: AHP and Fuzzy logic in the selection of post-harvest technology for smallholder Cocoa production. Int Food Agribus Manag Rev 17(2):107–124

    Google Scholar 

  • Naghadehi MZ, Mikaeil R, Ataei M (2009) The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm Bauxite Mine, Iran. Expert Syst Appl 36:8218–8226. https://doi.org/10.1016/j.eswa.2008.10.006

    Article  Google Scholar 

  • Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas. Eng Geol 69:331–343

    Article  Google Scholar 

  • Pal B, Samanta S (2011) Surface runoff estimation and mapping using remote sensing and geographic information system. Int J Adv Sci Technol 3(2):106–114

    Google Scholar 

  • Patil VD, Sankhua RN, Jain RK (2012) Analytic hierarchy process for evaluation of environmental factors for residential land use suitability. Int J Comput Eng Res 2(7):182–189

    Google Scholar 

  • Permana AR, Hadiani RS (2017) A Fuzzy analytical hierarchy process approach in irrigation networks maintenance. IOP Conf Ser J Phys 909:012070. https://doi.org/10.1088/1742-6596/909/1/012070

    Article  Google Scholar 

  • Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63(2):965–996

    Article  Google Scholar 

  • Pourtaghi ZS, Pourghasemi HR (2015) GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeol J 22:643–662

    Article  Google Scholar 

  • Poussin JK, Botzen WJW, Aerts JCJH (2014) Factors of influence on flood damage mitigation behavior by households. Environ Sci Policy 40:69–77

    Article  Google Scholar 

  • Pradhan B (2010) Flood susceptible mapping and risk area estimation using logistic regression, GIS and remote sensing. J Spat Hydrol 9:1–18

    Google Scholar 

  • Pradhan B, Youssef AM (2010) Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arab J Geosci 3:319–326

    Article  Google Scholar 

  • Pradhan B, Oh HJ, Buchroithner M (2010) Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area. Geomat Nat Hazards Risk 1(3):199–223. https://doi.org/10.1080/19475705.2010.498151

    Article  Google Scholar 

  • Rahmati O, Haghizadeh A, Stefanidis S (2016a) Assessing the accuracy of GIS-based analytical hierarchy process for watershed prioritization; Gorganrood River Basin. Iran. Water Resour Manag 30(3):1131–1150

    Article  Google Scholar 

  • Rahmati O, Haghizadeh A, Pourghasemi HR, Noormohamadi F (2016b) Gully erosion susceptibility mapping: The role of GIS-based bivariate statistical models and their comparison. Nat Hazards 82(2):1231–1258

    Article  Google Scholar 

  • Rattan L (1990) Soil erosion in the tropics: Principles and management. McGraw-Hill Inc, New York, USA

    Google Scholar 

  • Rikalovic A, Cosic I, Lazarevic D (2014) GIS based multi-criteria analysis for industrial site selection. Proc Eng 69:1054–1063. https://doi.org/10.1016/j.proeng.2014.03.090

    Article  Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281

    Article  Google Scholar 

  • Saaty TL (1980) The analytical hierarchy process. McGraw Hill, New York

    Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  Google Scholar 

  • Saaty TL, Vargas LG (2000) Models, methods, concepts and applications of the analytic hierarchy process. Kluwer Academic, Boston

    Google Scholar 

  • Samanta S, Pal DK, Lohar D, Pal B (2012) Interpolation of climate variables and temperature modeling. Theor Appl Climatol 107(1):35–45. https://doi.org/10.1007/s00704-011-0455-3

    Article  Google Scholar 

  • Samanta S, Pal DK, Palsamanta B (2018) Flood susceptibility analysis through remote sensing, GIS and frequency ratio model. Appl Water Sci 8:66. https://doi.org/10.1007/s13201-018-0710-1

    Article  Google Scholar 

  • Sánchez-Triana E, Paul T, Ortolano L, Ruitenbeek J (2014) Building resilience for sustainable development for the West Bengal Sundarbans—Strategy report (Report No. 88061-IN). Washington, DC: World Bank. Retrieved March 6, 2019, from http://documents.worldbank.org/curated/en/2014/01/20162806/building-resilience-sustainable-development-sundarbans-strategy-report

  • Sánchez-Triana E, Ortolano L, Paul T (2018) Managing water-related risks in the West Bengal Sundarbans: policy alternatives and institutions. Int J Water Resour Dev 34(1):78–96. https://doi.org/10.1080/07900627.2016.1202099

    Article  Google Scholar 

  • Schober B, Hauer C, Habersack H (2015) A novel assessment of the role of Danube floodplains in flood hazard reduction (FEM method). Nat Hazards 75:33–50

    Article  Google Scholar 

  • Shafapour Tehrani M, Pradhan B, Neamah Jebur M (2013) Spatial prediction of flood susceptible areasusing rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. J Hydrol 504:69–79. https://doi.org/10.1016/j.jhydrol.2013.09.034

    Article  Google Scholar 

  • Tavares G, Zsigraiova Z, Semiao V (2011) Multi-criteria GIS-based siting of an incineration plant for municipal solid waste. Waste Manag 31(9–10):1960–1972. https://doi.org/10.1016/j.wasman.2011.04.013

    Article  Google Scholar 

  • Tehrany MS, Pradhan B, Jebur MN (2013) Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. J Hydrol 504:69–79

    Article  Google Scholar 

  • Tehrany MS, Lee MJ, Pradhan B, Jebur MN, Lee S (2014) Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environ Earth Sci 72:4001–4015

    Article  Google Scholar 

  • Tehrany MS, Pradhan B, Jebur MN (2015a) Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stoch Environ Res Risk Assess 29:1149–1165. https://doi.org/10.1007/s00477-015-1021-9

    Article  Google Scholar 

  • Tehrany MS, Pradhan B, Jebur MN (2015b) Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stoch Environ Res Risk Assess 29:1149–1165

    Article  Google Scholar 

  • Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB (2012) Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS. Comput Geosci 45:199–211

    Article  Google Scholar 

  • Tunusluoglu M, Gokceoglu C, Nefeslioglu H, Sonmez H (2008) Extraction of potential debris source areas by logistic regression technique: a case study from Barla, Besparmak and Kapi mountains (NW Taurids, Turkey). Environ Geol 54:9–22

    Article  Google Scholar 

  • Xu C, Chen Y, Chen Y, Zhao R, Ding H (2013) Responses of surface runoff to climate change and human activities in the arid region of Central Asia: a case study in the Tarim River Basin, China. Environ Manag 51:926–938

    Article  Google Scholar 

  • Yang YCE, Ray PA, Brown CM, Khalil AF, Yu WH (2015) Estimation of flood damage functions for river basin planning: a case study in Bangladesh. Nat Hazards 75:2773–2791

    Article  Google Scholar 

  • Yodmani S (2001) Disaster risk management and vulnerability reduction: protecting the poor. Asia and Pacific Forum for Poverty: reforming policies and institutions for poverty reduction Manila: Asian Development Bank

  • Youssef AM, Pradhan B, Hassan AM (2011) Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environ Earth Sci 62:611–623

    Article  Google Scholar 

  • Yu JJ, Qin XS, Larsen O (2013) Joint Monte Carlo and possibilistic simulation for flood damage assessment. Stoch Environ Res Risk Assess 27(3):725–735. https://doi.org/10.1007/s00477-012-0635-4

    Article  Google Scholar 

  • Zou Q, Zhou J, Zhou C, Song L, Guo J (2013) Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stoch Environ Res Risk Assess 27(2):525–546

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the anonymous reviewers and the editor for their valuable time, productive comments and appreciated suggestions during the review which helped in improving the overall quality of the manuscript.

Author information

Authors and Affiliations

  1. Department of Geography, Faculty of Science, Aligarh Muslim University, Aligarh, UP, 202002, India

    Sk Ajim Ali, Rumana Khatun, Ateeque Ahmad & Syed Naushad Ahmad

Authors
  1. Sk Ajim Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rumana Khatun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ateeque Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Syed Naushad Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sk Ajim Ali.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ali, S.A., Khatun, R., Ahmad, A. et al. Application of GIS-based analytic hierarchy process and frequency ratio model to flood vulnerable mapping and risk area estimation at Sundarban region, India. Model. Earth Syst. Environ. 5, 1083–1102 (2019). https://doi.org/10.1007/s40808-019-00593-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40808-019-00593-z

Keywords

Search

Navigation