Multidimensional Vulnerability Assessment of Flood-Prone Rural Communities of Pakistan

Abstract

Rural settlements have experienced a noticeable increase in extreme weather events and associated disasters in recent years. Pakistan is consistently ranked as one of the most affected regions globally, and the catastrophic floods of 2022 further underscored its vulnerability to floods, causing unprecedented human, economic, and environmental losses. This study conducted a multidimensional vulnerability assessment of flood-prone rural areas in Dera Ismail Khan, Pakistan, using a composite index approach informed by principal component analysis (PCA). Principal component analysis was employed to assign statistically robust weights to selected indicators, ensuring an objective aggregation of vulnerability components. A questionnaire with a mix of closed-ended and open-ended items was used to collect data through a household survey. The findings revealed that a substantial proportion (40%) of respondents experienced high multidimensional vulnerability, while approximately 30% exhibited moderate vulnerability. Factors such as age distribution, household income, infrastructure quality, and risk perception significantly contributed to overall vulnerability. This study developed a scalable and replicable model for assessing rural flood vulnerability, offering practical insights for policymakers, planners, and disaster management authorities.

Keywords

Developing countries / Pakistan / Principal component analysis / Rural flooding / Vulnerability

References

[1] Abdi H, Williams LJ. Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2010, 2(4): 433-459.

[2] Ajtai, I., H. Ştefănie, C. Maloş, C. Botezan, A. Radovici, M. Bizău-Cârstea, and C. Baciu. 2023. Mapping social vulnerability to floods. A comprehensive framework using a vulnerability index approach and PCA analysis. Ecological Indicators 154: Article 110838.

[3] Ali, A., W. Ullah, U.A. Khan, S. Ullah, A. Ali, M.A. Jan, A.S. Bhatti, and Q. Jan. 2024. Assessment of multi-components and sectoral vulnerability to urban floods in Peshawar – Pakistan. Natural Hazards Research 4(3): 507–519.

[4] Andy F. Discovering statistics using SPSS, 2009, London. SAGE

[5] Ashraf, A., M.B. Iqbal, N. Mustafa, R. Naz, and B. Ahmad. 2021. Prevalent risk of glacial lake outburst flood hazard in the Hindu Kush-Karakoram-Himalaya region of Pakistan. Environmental Earth Sciences 80(12). https://doi.org/10.1007/s12665-021-09740-1.

[6] Aslam, A.B., I.A. Rana, S.S. Shah, and G. Mohuddin. 2022. Climate change and glacial lake outburst flood (GLOF) risk perceptions: An empirical study of Ghizer District, Gilgit-Baltistan Pakistan. International Journal of Disaster Risk Reduction 83: Article 103392.

[7] Bartlett MS. A note on the multiplying factors for various χ 2 approximations. Journal of the Royal Statistical Society: Series B (Methodological), 1954, 6(2): 296-298.

[8] Birkmann, J., and B. Wisner. 2006. Measuring the un-measurable: The challenge of vulnerability. Bonn: United Nations University Institute for Environmentand Human Security (UNU-EHS).

[9] Birkmann J, Cardona OD, Carreño ML, Barbat AH, Pelling M, Schneiderbauer S, Kienberger S, Keiler M, et al. . Framing vulnerability, risk and societal responses: The MOVE framework. Natural Hazards, 2013, 67(2): 193-211.

[10] Bohle, H.G. 2001. Vulnerability and criticallity: Perspectives from social geography. Newsletter of the International Human Dimensions Programme on Global Environmental Change, 2/01.

[11] Ciurean, R.L., D. Schröter, and T. Glade. 2013. Conceptual frameworks of vulnerability assessments for natural hazards reduction. In Approaches to disaster management – Examining the implications of hazards, emergencies and disasters, ed. J.P. Tiefenbacher. London: IntechOpen Limited.

[12] Cutter SL, Boruff BJ, Shirley WL. Social vulnerability to environmental hazards. Social Science Quarterly, 2003, 84(2): 242-261.

[13] Ding T, Liang L, Yang M, Wu H. Multiple attribute decision making based on cross-evaluation with uncertain decision parameters. Mathematical Problems in Engineering, 2016

[14] D’Silva S, Mathew BP, Vijesh VK, Bhadran A, Girishbai D, Gopinath G. Geomorphic evolution of a tropical river basin in the Deccan Volcanic Province: A critical water supply source to Mumbai Metropolitan Region (MMR), India. Geology, Ecology, and Landscapes, 2025, 9(3): 988-999.

[15] Doocy S, Leidman E, Aung T, Kirsch T. Household economic and food security after the 2010 Pakistan floods. Food and Nutrition Bulletin, 2013, 34(1): 95-103.

[16] Ebert U, Welsch H. Meaningful environmental indices: A social choice approach. Journal of Environmental Economics and Management, 2004, 47(2): 270-283.

[17] Fekete A. Validation of a social vulnerability index in context to river-floods in Germany. Natural Hazards and Earth System Sciences, 2009, 9(2): 393-403.

[18] Few R. Flooding, vulnerability and coping strategies: Local responses to a global threat. Progress in Development Studies, 2003, 3(1): 43-58.

[19] Fothergill A. Heads above water: Gender, class, and family in the Grand Forks flood, 2004, Albany, NY. State University of New York Press.

[20] Frigerio I, De Amicis M. Mapping social vulnerability to natural hazards in Italy: A suitable tool for risk mitigation strategies. Environmental Science & Policy, 2016, 63: 187-196.

[21] Fuchs S, Kuhlicke C, Meyer V. Vulnerability to natural hazards?. The challenge of integration. Natural Hazards, 2011, 58(2): 621-840

[22] Godfrey A, Ciurean R, Van Westen C, Kingma N, Glade T. Assessing vulnerability of buildings to hydro-meteorological hazards using an expert based approach – An application in Nehoiu Valley, Romania. International Journal of Disaster Risk Reduction, 2015, 13: 229-241.

[23] Gurney GG, Blythe J, Adams H, Adger WN, Curnock M, Faulkner L, James T, Marshall NA. Redefining community based on place attachment in a connected world. Proceedings of the National Academy of Sciences, 2017, 114(38): 10077-10082.

[24] Hadi, N.U., N. Abdullah, and I. Sentosa. 2016. An easy approach to exploratory factor analysis: Marketing perspective. Journal of Educational and Social Research 6(1): Article 215.

[25] Hahn MB, Riederer AM, Foster SO. The livelihood vulnerability index: A pragmatic approach to assessing risks from climate variability and change – A case study in Mozambique. Global Environmental Change, 2009, 19(1): 74-88.

[26] Hamidi, A.R., L. Jing, M. Shahab, K. Azam, M.A.U.R. Tariq, and A.W.M. Ng. 2022. Flood exposure and social vulnerability analysis in rural areas of developing countries: An empirical study of Charsadda District, Pakistan. Water 14(7): Article 1176.

[27] IPCC (Intergovernmental Panel on Climate Change). 2007. AR4 climate change 2007: Synthesis report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva: IPCC.

[28] IPCC (Intergovernmental Panel on Climate Change). 2022. Climate change 2022: Impacts, adaptation, and vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.

[29] Islam, M.B., T. Sultana, I.A. Rana, H.B. Waseem, P. Murray-Tuite, T. Tingsanchali, and M. Mahfuz. 2024. Assessing the vulnerability of selected coastal informal settlements to floods in the Old Brahmaputra River floodplain, Bangladesh. Urban Climate 56: Article 102078.

[30] Kaiser HF. A second generation little jiffy. Psychometrika, 1970, 35: 401-415.

[31] Kaiser HF. An index of factorial simplicity. Psychometrika, 1974, 39(1): 31-36.

[32] Kar N. Psychological impact of disasters on children: Review of assessment and interventions. World Journal of Pediatrics, 2009, 5: 5-11.

[33] Khalid, Z., X. Meng, I.A. Rana, M. u. Rehman, and X. Su. 2021. Holistic multidimensional vulnerability assessment: An empirical investigation on rural communities of the Hindu Kush Himalayan region, northern Pakistan. International Journal of Disaster Risk Reduction 62: Article 102413.

[34] Kienberger S, Lang S, Zeil P. Spatial vulnerability units – Expert-based spatial modelling of socio-economic vulnerability in the Salzach catchment, Austria. Natural Hazards and Earth System Sciences, 2009, 9(3): 767-778.

[35] Kumpulainen, S. 2006. Vulnerability concepts in hazard and risk assessment. Special Paper-Geological Survey of Finland 42: Article 65.

[36] Kurek KA, Heijman W, van Ophem J, Gędek S, Strojny J. Measuring local competitiveness: Comparing and integrating two methods PCA and AHP. Quality & Quantity, 2022, 56(3): 1371-1389.

[37] Lamb VL, Land KCBen-Arieh A, Casas F, Frønes I, Korbin JE. Methodologies used in the construction of composite child well-being indices. Handbook of child well-being: Theories, methods and policies in global perspective, 2013, Dordrecht. Springer2739-2755

[38] Lan, T., Y. Hu, L. Cheng, L. Chen, X. Guan, Y. Yang, Y. Guo, and J. Pan. 2022. Floods and diarrheal morbidity: Evidence on the relationship, effect modifiers, and attributable risk from Sichuan Province, China. Journal of Global Health 12: Article 11007.

[39] Li, R., G. Zhu, S. Lu, G. Meng, L. Chen, Y. Wang, E. Huang, Y. Jiao, and Q. Wang. 2025. Effects of cascade hydropower stations on hydrologic cycle in Xiying River basin, a runoff in Qilian Mountain. Journal of Hydrology 646: Article 132342.

[40] Liu DL, Li Y, Fang S, Zhang Y. Influencing factors for emergency evacuation capability of rural households to flood hazards in western mountainous regions of Henan Province, China. International Journal of Disaster Risk Reduction, 2017, 21: 187-195.

[41] Mahmood, S., A.-u. Rahman, and A. Sajjad. 2019. Assessment of 2010 flood disaster causes and damages in district Muzaffargarh, Central Indus Basin, Pakistan. Environmental Earth Sciences 78(3): Article 63.

[42] Nardo, M., M. Saisana, A. Saltelli, and S. Tarantola. 2005. Tools for composite indicators building. Ispra. Italy: European Comission.

[43] Ndue, K., M.M. Baylie, and P. Goda. 2023. Determinants of rural households’ intensity of flood adaptation in the Fogera Rice Plain, Ethiopia: Evidence from generalised Poisson regression. Sustainability 15(14): Article 11025.

[44] Ngo EB. When disasters and age collide: Reviewing vulnerability of the elderly. Natural Hazards Review, 2001, 2(2): 80-89.

[45] Pallant J. SPSS survival manual: A step by step guide to data analysis using IBM SPSS, 2020, New York. Routledge.

[46] PBS (Pakistan Bureau of Statistics). 2023. 7th population and housing census – 2023. Government of Pakistan.

[47] Phillips BD, Hewett PLJr. Home alone: Disasters, mass emergencies, and children in self-care. Journal of Emergency Management, 2005, 3(2): 31-35.

[48] Polsky C, Neff R, Yarnal B. Building comparable global change vulnerability assessments: The vulnerability scoping diagram. Global Environmental Change, 2007, 17(3–4): 472-485.

[49] Rana IA, Routray JK. Multidimensional model for vulnerability assessment of urban flooding: An empirical study in Pakistan. International Journal of Disaster Risk Science, 2018, 9(3): 359-375.

[50] Rana, I.A., M.M. Khan, R.H. Lodhi, S. Altaf, A. Nawaz, and F.A. Najam. 2023. Multidimensional poverty vis-à-vis climate change vulnerability: Empirical evidence from flood-prone rural communities of Charsadda and Nowshera Districts in Pakistan. World Development Sustainability 2: Article 100064.

[51] Rasool S, Rana IA, Waseem HB. Assessing multidimensional vulnerability of rural areas to flooding: An index-based approach. International Journal of Disaster Risk Science, 2024, 15(1): 88-106.

[52] Rehman S, Sahana M, Hong H, Sajjad H, Ahmed BB. A systematic review on approaches and methods used for flood vulnerability assessment: Framework for future research. Natural Hazards, 2019, 96: 975-998.

[53] Riedler B, Pernkopf L, Strasser T, Lang S, Smith G. A composite indicator for assessing habitat quality of riparian forests derived from Earth observation data. International Journal of Applied Earth Observation and Geoinformation, 2015, 37: 114-123.

[54] Saisana, M., and S. Tarantola. 2002. State-of-the-art report on current methodologies and practices for composite indicator development. Ispra, Italy: Joint Research Center, European Commission.

[55] Sarwar A, Ali M, Israr M, Gulzar S, Khan MI, Ali MAS, Majid A, Rukh S. Mapping annual soil loss in the southeast of Peshawar Basin, Pakistan, using RUSLE model with geospatial approach. Geology, Ecology, and Landscapes, 2024, 9(3): 1102-1113.

[56] Schmidtlein MC, Deutsch RC, Piegorsch WW, Cutter SL. A sensitivity analysis of the social vulnerability index. Risk Analysis, 2008, 28(4): 1099-1114.

[57] Senna, L.D.d., A.G. Maia, and J.D.F.d. Medeiros. 2019. The use of principal component analysis for the construction of the water poverty index. Brazilian Journal of Water Resources 24: Article e19.

[58] Shah AA, Ye J, Abid M, Khan J, Amir SM. Flood hazards: Household vulnerability and resilience in disaster-prone districts of Khyber Pakhtunkhwa Province. Pakistan. Natural Hazards, 2018, 93(1): 147-165.

[59] Smith, L.I. 2002. A tutorial on principal components analysis. arXiv:1404.1100v1.

[60] Smith SM, Tremethick MJ, Johnson P, Gorski J. Disaster planning and response: Considering the needs of the frail elderly. International Journal of Emergency Management, 2009, 6(1): 1-13.

[61] Vitunskiene V, Dabkiene V. Framework for assessing the farm relative sustainability: A Lithuanian case study. Agricultural Economics, 2016, 62(3): 134-148

[62] Wang, Q., Y. Liu, G. Zhu, S. Lu, L. Chen, Y. Jiao, W. Li, W. Li, and Y. Wang. 2025. Regional differences in the effects of atmospheric moisture residence time on precipitation isotopes over Eurasia. Atmospheric Research 314: Article 107813.

[63] Waseem HB, Rana IA. Floods in Pakistan: A state-of-the-art review. Natural Hazards Research, 2023, 3(3): 359-373.

[64] Waseem HB, Rana IA. A meta-review of disaster research. Natural Hazards, 2025, 121: 12427-12460.

[65] Wehbe, C., and H. Baroud. 2024. Limitations and considerations of using composite indicators to measure vulnerability to natural hazards. Scientific Reports 14(1): Article 19333.

[66] Wisner B. Are we there yet? Reflections on integrated disaster risk management after ten years. Journal of Integrated Disaster Risk Management, 2011, 1(1): 1-14.

[67] Yamane T. Statistics: An introductory analysis, 19672New York. Harper and Row

[68] Zhang, Y., and X. Wu. 2025. Global space-time patterns of sub-daily extreme precipitation and its relationship with temperature and wind speed. Environmental Research Letters 20: Article 085009.

[69] Žurovec, O., S. Čadro, and B.K. Sitaula. 2017. Quantitative assessment of vulnerability to climate change in rural municipalities of Bosnia and Herzegovina. Sustainability 9(7): Article 1208.

RIGHTS & PERMISSIONS

The Author(s)

Just Accepted

This article has successfully passed peer review and final editorial review, and will soon enter typesetting, proofreading and other publishing processes. The currently displayed version is the accepted final manuscript. The officially published version will be updated with format, DOI and citation information upon launch. We recommend that you pay attention to subsequent journal notifications and preferentially cite the officially published version. Thank you for your support and cooperation.