Skip to main content

Advertisement

Log in

Analysis of flood damage and influencing factors in urban catchments: case studies in Manila, Philippines, and Jakarta, Indonesia

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

The sustainability and efficiency of flood risk management depends on the assessment of flood hazards and on the quantification of flood damage. Under the conditions of climate change and rapid urbanization, the evaluation of flood risk can lead to the success of adaptation strategies. The main objectives of this study are the estimation of future direct flood damage in two urban watersheds: The Pasig–Marikina–San Juan River in Metro Manila, Philippines, and the Ciliwung River in Jakarta, Indonesia, as well as the determination of the relation between factors that drive floods and flood damage. A spatial analysis approach based on the integration of several parameters, such as flood hazard, climate, and property value, was applied using a Geographic Information System (GIS). The flood depth-damage function generated from the field surveys was employed for the analysis to identify the spatial distribution of flood loss. The findings showed that, under future scenarios (target year: 2030), the total flood damage will increase by 212% and 80% in the target areas of Manila and Jakarta, respectively, compared to the current scenarios. This growth is due to the higher level of extreme rainfall events and to the degree of urbanization in the future. A comparative analysis of the two study areas highlighted the significant effects of the level of water depth and the inundated areas on flood damage, depending on the sites. This study is useful for local decision makers to implement suitable strategies for urban planning and flood control.

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

Access this article

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

Instant access to the full article PDF.

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

Data availability

The data collected and used in this study are strictly anonymous and are used for research purposes only.

References

  • ADB (Asian Development Bank) (2013) The rise of natural disasters in Asia and the Pacific: learning from ADB’s experience. Independent Evaluation at ADB. ADB (Asian Development Bank), Mandaluyong

    Google Scholar 

  • ADB (Asian Development Bank) (2015) Global increase in climate-related disasters, working paper November 2015. Independent evaluation at ADB. ADB (Asian Development Bank), Metro Manila

    Google Scholar 

  • Afifi Z, Chu HJ, Kuo YL, Hsu YC, Wong HK, Zeeshan Ali M (2019) Residential flood loss assessment and risk mapping from high-resolution simulation. Water 11:751. https://doi.org/10.3390/w11040751

    Article  Google Scholar 

  • Albano R, Mancusi L, Sole A, Adamowski J (2015) Collaborative strategies for sustainable EU flood risk management: FOSS and geospatial tools—challenges and opportunities for operative risk analysis. ISPRS Int J Geo-Inf 4:2704–2727. https://doi.org/10.3390/ijgi4042704

    Article  Google Scholar 

  • Asdak C, Supian S, Subiyanto (2018) Watershed management strategies for flood mitigation: a case study of Jakarta’s flooding. Weather Clim Extrem 21:117–122. https://doi.org/10.1016/j.wace.2018.08.002

    Article  Google Scholar 

  • Bathrellos GD, Karymbalis E, Skilodimou HD, Gaki-Papanastassiou K, Baltas EA (2016) Urban flood hazard assessment in the basin of Athens Metropolitan city, Greece. Environ Earth Sci 75:319. https://doi.org/10.1007/s12665-015-5157-1

    Article  Google Scholar 

  • Campbell JB (2007) Introduction to remote sensing, 4th edn. The Guilford press, New York

    Google Scholar 

  • Centre for Research on the Epidemiology of Disasters (2018) EM-DAT: the emergency events database. https://www.emdat.be. Accessed 03 May 2018

  • Chiba Y, Shaw R, Prabhakar S (2017) Climate change related non-economic loss and damage in Bangladesh and Japan. Int J Clim Change Strateg 9(2):166–183. https://doi.org/10.1108/IJCCSM-05-2016-0065

    Article  Google Scholar 

  • CTI Engineering International Co., Ltd and WCI, Woodfields Consultants, Inc. (2013) Master plan for flood management in Metro Manila and surrounding areas. Department of Public Works and Highways, the World Bank and AusAID, Tokyo

    Google Scholar 

  • Dang NM, Babel MS, Luong HT (2011) Evaluation of flood risk parameters in the day river flood diversion area, Red River Delta, Vietnam. Nat Hazards 56(1):169–194. https://doi.org/10.1007/s11069-010-9558-x

    Article  Google Scholar 

  • De Moel H, Aerts JCJH (2011) Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates. Nat Hazards 58(1):407–425. https://doi.org/10.1007/s11069-010-9675-6

    Article  Google Scholar 

  • Dutta D, Herath S, Musiake K (2003) A mathematic model for loss estimation. J Hydrol 227(1–2):24–49. https://doi.org/10.1016/S0022-1694(03)00084-2

    Article  Google Scholar 

  • Dutta D, Wright W, Rayment P (2011) Synthetic impact response functions for flood vulnerability analysis and adaptation measures in coastal zones under changing climatic conditions: a case study in Gippsland coastal region, Australia. Nat Hazards 59(2):967–986. https://doi.org/10.1007/s11069-011-9812-x

    Article  Google Scholar 

  • Fankhauser S, Dietz S, Gradwell P (2014) Non-economic losses in the context of the UNFCCC work programme on loss and damage (policy paper). Centre for Climate Change Economics and Policy, Grantham Research Institute on Climate Change and the Environment, London

    Google Scholar 

  • Feldman AD (2000) Hydrologic modeling system HEC-HMS technical reference manual, U.S. Army Corps of Engineers, Hydrologic Engineering Center, HEC Davis, CA, USA

  • Fohrer N, Haverkamp S, Eckhardt K, Frede HG (2001) Hydrologic response to land use changes on the catchment scale. Phys Chem Earth Part B Hydrol Oceans Atmos 26(7–8):577–582. https://doi.org/10.1016/S1464-1909(01)00052-1

    Article  Google Scholar 

  • Foudi S, Oses-Eraso N, Tamayo I (2015) Integrated spatial flood risk assessment: the case of Zaragoza. Land Use Policy 42:278–292. https://doi.org/10.1016/j.landusepol.2014.08.002

    Article  Google Scholar 

  • Glas H, Jonckheere M, Mandal A, James-Williamson S, De Maeyer P, Deruyter G (2017) A GIS-based tool for flood damage assessment and delineation of a methodology for future risk assessment: case study for Annotto Bay, Jamaica. Nat Hazards 88:1867–1891. https://doi.org/10.1007/s11069-017-2920-5

    Article  Google Scholar 

  • Guha-Sapir D, Hoyois Ph, Wallemacq P, Below R (2016) Annual disaster statistical review 2016, the numbers and trends. CRED, Brussels

    Google Scholar 

  • Handmer J (2002) The chimera of precision: inherent uncertainties in disaster loss assessment. Int J Mass Emerg Disaster 20(2):325–346

    Google Scholar 

  • Huizinga J, De Moel H, Szewczyk W (2017). Global flood depth-damage functions. Methodology and the database with guidelines. EUR 28552 EN. https://doi.org/10.2760/16510

  • IPCC (Intergovernmental Panel on Climate Change) (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. In: Field CBV, Barros TF, Stocker D, Qin DJ, Dokken KL, Ebi MD, Mastrandrea KJ, Mach GK, Plattner SK, Allen M et al (eds) A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Jalilov SM, Kefi M, Kumar P, Masago Y, Mishra BK (2018) Sustainable urban water management: application for integrated assessment in Southeast Asia. Sustainability 10(1):122. https://doi.org/10.3390/su10010122

    Article  Google Scholar 

  • Jongman B, Kreibich H, Barredo JI, Bates PD, Feyen L, Gericke A, Neal J, Aerts JCJH, Ward PJ (2012) Comparative flood damage model assessment: towards a European approach. Nat Hazard Earth Syst 12:3733–3752. https://doi.org/10.5194/nhess-12-3733-2012

    Article  Google Scholar 

  • Jonkman SN, Bockarjova M, Kok M, Bernardini P (2008) Integrated hydrodynamic and economic modelling of flood damage in the Netherlands. Ecol Econ 66(1):77–90. https://doi.org/10.1016/j.ecolecon.2007.12.022

    Article  Google Scholar 

  • Kefi M, Mishra BK, Kumar P, Masago Y, Fukushi K (2018) Assessment of tangible direct flood damage using a spatial analysis approach under the effects of climate change: case study in an urban watershed in Hanoi, Vietnam. ISPRS Int J Geo-Inf 7(1):29. https://doi.org/10.3390/ijgi7010029

    Article  Google Scholar 

  • Komolafe AA, Herath S, Avtar R (2015) Sensitivity of flood damage estimation to spatial resolution. J Flood Risk Manag. https://doi.org/10.1111/jfr3.12224

    Article  Google Scholar 

  • Komolafe AA, Herath S, Avtar R (2018) Development of generalized loss functions for rapid estimation of flood damages: a case study in Kelani River basin, Sri Lanka. Appl Geom 10(1):13–30. https://doi.org/10.1007/s12518-017-0200-4

    Article  Google Scholar 

  • Komori D, Nakamura S, Kiguchi M, Nishijima A, Yamazaki D, Suzuki S, Kawasaki A, Oki K, Oki T (2012) Characteristics of the 2011 Chao Phraya River flood in Central Thailand. Hydrol Res Lett 6:41–46. https://doi.org/10.3178/hrl.6.41

    Article  Google Scholar 

  • Kreibich H, Thieken AH (2008) Assessment of damage caused by high groundwater inundation. Water Resour Res 44:W09409. https://doi.org/10.1029/2007WR006621

    Article  Google Scholar 

  • Kundzewicz ZW, Kanae S, Seneviratne SI, Handmer J, Nicholls N, Peduzzi P, Mechler R, Bouwer LM, Arnell N, Mach K, Muir-Wood R, Brakenridge GR, Kron W, Benito G, Honda Y, Takahashi K, Sherstyukov B (2014) Flood risk and climate change: global and regional perspectives. Hydrol Sci J 59(1):1–28. https://doi.org/10.1080/02626667.2013.857411

    Article  Google Scholar 

  • Lagmay AM, Mendoza J, Cipriano F, Delmendo PA, Lacsamana MN, Moises MA, Pellejera NIII, Punay KN, Sabio G, Santos L, Serrano J, Taniza HJ, Tingin NE (2017) Street floods in Metro Manila and possible solutions. J Environ Sci 59:39–47. https://doi.org/10.1016/j.jes.2017.03.004

    Article  Google Scholar 

  • Lechowska E (2018) What determines flood risk perception? A review of factors of flood risk perception and relations between its basic elements. Nat Hazards 94:1341–1366. https://doi.org/10.1007/s11069-018-3480-z

    Article  Google Scholar 

  • Mall RK, Srivastava RK (2012) Sustainable flood management in changing climate. Mishra OP, Ghatak M, Kamal A (eds) SAARC workshop on flood risk management in South Asia FLOOD, 9–10 October 2012, Islamabad, Pakistan. Published by the SAARC Disaster Management Centre, New Delhi

  • Mardiah ANR, Lovett JC, Evanty N (2017) Toward integrated and inclusive disaster risk reduction in Indonesia: review of regulatory frameworks and institutional networks. In: Djalante R, Garschagen M, Thomalla F, Shaw R (eds) Disaster risk reduction in Indonesia: progress, challenges, and issues. Springer, Berlin

    Google Scholar 

  • Merz B, Kreibich H, Schwarze R, Thieken A (2010) Assessment of economic flood damage. Nat Hazard Earth Syst 10:1697–1724. https://doi.org/10.5194/nhess-10-1697-2010

    Article  Google Scholar 

  • Messner F, Penning Rowsell E, Green C, Meyer V, Tunstall S, Vander Veen A (2007) Evaluating flood damages : guidance and recommendations on principles and methods; FLOOD site integrated flood risk analysis and management methodologies report T09-06-01; HR Wallingford: Oxfordshire, UK

  • Mishra B, Herath S (2011) Climate projections downscaling and impact assessment on precipitation over upper Bagmati River Basin. In: Proceedings of third international conference on addressing climate change for sustainable development through up-scaling renewable energy technologies. Tribhuvan University, Kathmandu, Nepal, 2011, pp 275–281

  • Mishra BK, Rafiei Emam A, Masago Y, Kumar P, Regmi RK, Fukushi K (2017) Assessment of future flood inundations under climate and land use change scenarios in the Ciliwung River Basin. J Flood Risk Manag, Jakarta. https://doi.org/10.1111/jfr3.12311

    Book  Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JF, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756. https://doi.org/10.1038/nature08823

    Article  Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I: a discussion of principles. J Hydrol 10:282–290. https://doi.org/10.1016/0022-1694(70)90255-6

    Article  Google Scholar 

  • Neal JC, Bates PD, Fewtrell TJ, Hunter NM, Wilson MD, Horritt MS (2009) Distributed whole city water level measurements from the Carlisle 2005 urban flood event and comparison with hydraulic model simulations. J Hydrol 368:42–55. https://doi.org/10.1016/j.jhydrol.2009.01.026

    Article  Google Scholar 

  • Pathirage C, Seneviratne K, Amaratunga D, Haigh R (2014) Knowledge factors and associated challenges for successful disaster knowledge sharing. Input paper Prepared for the global assessment report on disaster risk reduction 2015. The United Nations Office for Disaster Risk Reduction (UNISDR), Global Assessment Report on Disaster Risk Reduction (GAR)

  • Pistrika A, Tsakiris G, Nalbantis I (2014) Flood depth-damage functions for built environment. Environ Process 1(4):553–572. https://doi.org/10.1007/s40710-014-0038-2

    Article  Google Scholar 

  • PSA (Philippine Statistics Authority) (2010) Census of population and housing Philippines, 2010. https://psa.gov.ph/sites/default/files/attachments/hsd/article/Table%201_2.pdf. Accessed 03 May 2018

  • PSA (Philippine Statistics Authority) (2015) Census of population. Republic of the Philippines, 2015. Accessed 03 May 2018

  • Rafiei Emam A, Mishra BK, Kumar P, Masago Y, Fukushi K (2016) Impact assessment of climate and land-use changes on flooding behavior in the Upper Ciliwung River, Jakarta, Indonesia. Water 8(12):559. https://doi.org/10.3390/w8120559

    Article  Google Scholar 

  • Richards JA, Jia X (2006) Remote sensing digital image analysis. An introduction fourth edition. Springer, Berlin

    Google Scholar 

  • Serdeczny OM, Bauer S, Huq S (2018) Non-economic losses from climate change: opportunities for policy-oriented research. Climate Dev 10(2):97–101. https://doi.org/10.1080/17565529.2017.1372268

    Article  Google Scholar 

  • Smith DI (1994) Flood damage estimation—a review of urban stage-damage curves and loss functions. Water SA 20:231–238

    Google Scholar 

  • Srinivasa Raju K, Nagesh Kumar D (2018) Impact of climate change on water resources with modeling techniques and case studies. Springer, Singapore

    Google Scholar 

  • Stabinsky D, Singh H, Vaughan K, Champling R, Phillips J (2012) Tackling the limits to adaptation: an international framework to address “loss and damage” from climate change impacts. ActionAid. CARE International and WWF, Geneva

    Google Scholar 

  • Te Linde AH, Bubeck P, Dekkers JEC, De Moel H, Aerts JCJH (2011) Future flood risk estimates along the river Rhine. Nat Hazard Earth Syst 11:459–473. https://doi.org/10.5194/nhess-11-459-2011

    Article  Google Scholar 

  • Thieken AH, Muller M, Kreibich H, Merz B (2005) Flood damage and influencing factors: new insights from the August 2002 flood in Germany. Water Resour Res 41:W12430. https://doi.org/10.1029/2005WR004177

    Article  Google Scholar 

  • UNDESA (United Nations, Department of Economic and Social Affairs) (2015) Population division world urbanization prospects: the 2014 revision (ST/ESA/SER.A/366)

  • Win S, Zin W, Kawasaki W, San Z (2018) Establishment of flood damage function MODELS: a case study in the Bago River Basin, Myanmar. Int J Disast Risk Reduct 28:688–700. https://doi.org/10.1016/j.ijdrr.2018.01.030

    Article  Google Scholar 

  • Zischg AP, Hofer P, Mosimann M, Röthlisberger V, Ramirez JA, Keiler M, Weingartner R (2018) Flood risk (d)evolution: disentangling key drivers of flood risk change with a retro-model experiment. Sci Total Environ 639:195–207. https://doi.org/10.1016/j.scitotenv.2018.05.056

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the staff of Center of Environmental Research, Research and Community Services Institute, Bogor Agricultural University, Indonesia (PPLH –IPB), and local residents and local NGO in Metro Manila, Philippines, for their cooperation during the field survey.

Funding

This research was supported by the Japan Society for the Promotion of Science as Overseas researcher under Postdoctoral Fellowship of JSPS (Fellowship P16790). This work was also supported by the Water and Urban Initiative project of the United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), Tokyo, Japan.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Kefi.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Questionnaire about flood event in Jakarta

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kefi, M., Mishra, B.K., Masago, Y. et al. Analysis of flood damage and influencing factors in urban catchments: case studies in Manila, Philippines, and Jakarta, Indonesia. Nat Hazards 104, 2461–2487 (2020). https://doi.org/10.1007/s11069-020-04281-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-020-04281-5

Keywords

Navigation