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Assessment of the water inundation area due to the tropical cyclone Bulbul (2019) in the selected districts of West Bengal, India with the application of RS and GIS tools

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Abstract

Flood is one of the most commonly occurring natural disasters affecting lives and properties. One of the major causes of flood in low-lying areas or coastal areas is cyclones. The paper aims to assess the effect of cyclone Bulbul that occurred on 9th November 2019 and water inundation caused in South 24 Parganas, East Medinipur, and North 24 Parganas districts of West Bengal. Sentinel 1 data of 10 m spatial resolution for pre and post-event was used for the study. Remote sensing (RS) and geographic information system (GIS) tools were utilized to process and analyse the SAR data. The output of the study was prepared in the form of an illustrative water inundation map. The analysis result showed that out of the three districts, South 24 Parganas showed the maximum changes in the water inundation after the event. The changes in the water inundated area from pre-event to post-event were 99.922 km2 to 149.22 km2; 196.36 km2 to 195.93 km2 and 497.27 km2 to 505.14 km2 for South 24 Pargana, East Medinipur, and North 24 Pargana districts, respectively. From the study, it was concluded that RS and GIS applications are convenient, effective, and fast techniques for the assessment of water inundation caused due to natural disasters.

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References

  • Bagchi, E.: Development of basic infrastructure: an analysis of south 24 Parganas district in West Bengal, India. Bull. Geogr. Socio-Econ. Ser. 36, 33–60 (2017)

    Google Scholar 

  • Brivio, P.A., Colombo, R., Maggi, M., Tomasoni, R.: Integration of remote sensing data and GIS for accurate mapping of flooded areas. Int. J. Remote Sens. 23(3), 429–441 (2002)

    Article  Google Scholar 

  • Chittibabu, P., Dube, S.K., Macnabb, J.B., Murty, T.S., Rao, A.D., Mohanty, U.C., Sinha, P.C.: Mitigation of flooding and cyclone hazard in Orissa, India. Nat. Hazards 31(2), 455–485 (2004). https://doi.org/10.1023/B:NHAZ.0000023362.26409.22

    Article  Google Scholar 

  • Chowdhuri, I., Pal, S.C., Chakrabortty, R.: Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India. Adv. Space Res. 65(5), 1466–1489 (2020). https://doi.org/10.1016/j.asr.2019.12.003

    Article  Google Scholar 

  • Conde, F.C., Muñoz, M.D.M.: Flood monitoring based on the study of Sentinel-1 SAR images: the Ebro River case study. Water 11(12), 2454 (2019).  https://doi.org/10.3390/w11122454

    Article  Google Scholar 

  • Das, G.K.: Landfall of Bulbul: a Ravager cyclone. Frontier, an independent weekly since 1968. Landfall of Bulbul-A Ravager Cyclone (2019)

  • Denis, A.: Adapted transcription of the tutorial video “ESA Echoes in Space-Hazard: Flood mapping with Sentinel-1 (ESA EO College), by Chris Stewart, 5 November 2017” Augmented with additional illustrations and comments (2019)

  • Dhali, M.K., Chakraborty, M., Sahana, M.: Assessing spatio-temporal growth of urban sub-centre using Shannon’s entropy model and principal component analysis: a case from North 24 Parganas, lower Ganga River Basin, India. Egypt. J. Remote Sens. Space Sci. 22(1), 25–35 (2019)

    Google Scholar 

  • Dhara, S., Paul, A.K.: Impact of cyclone and flood on social vulnerability “A case study at Kakdwip Block, South 24 Parganas, West Bengal” (2016)

  • Dube, S.K., Mazumder, T., Das, A.R.: An approach to vulnerability assessment for tropical cyclones: a case study of a coastal district in West Bengal. ITPI J. 3, 15–27 (2006)

    Google Scholar 

  • Filipponi, F.: Sentinel-1 GRD preprocessing workflow. Multidiscipl. Digit. Publ. Inst. Proc. 18(1), 11 (2019)

    Google Scholar 

  • Gao Qi Mehrez, Z., Maria Jose, E.: Synergetic use of sentinel-1 and sentinel-2 data for soil moisture mapping at 100 m resolution. Sensors (2017). https://doi.org/10.3390/s17091966

    Article  Google Scholar 

  • Ghosh, M., Ghosal, S.: Climate change vulnerability of rural households in flood-prone areas of Himalayan foothills, West Bengal, India. Environ. Dev. Sustain. (2020). https://doi.org/10.1007/s10668-020-00687-0

    Article  Google Scholar 

  • Hoque, E., Arafat, Y., Alam, H.E., Ahmed, K.T.: Rapid assessment of SST and chlorophyll concentration variability due to cyclone Bulbul in the Bay of Bengal using remotely sensed satellite image data. AGU J. (2020). https://doi.org/10.1002/essoar.10502414.1

    Article  Google Scholar 

  • Islam, N., Dharanirajan, K.: Flood impact assessment in Murshidabad District of West Bengal using remote sensing and GIS. Int. J. Adv. Remote Sens. GIS 5(1), 48–57 (2017)

    Google Scholar 

  • Islam, T., Peterson, R.E.: Climatology of landfalling tropical cyclones in Bangladesh 1877–2003. Nat. Hazards 48(1), 115–135 (2009). https://doi.org/10.1007/s11069-008-9252-4

    Article  Google Scholar 

  • Jha, A., Lamond, J., Bloch, R., Bhattacharya, N., Lopez, A., Papachristodoulou, N., Barker, R.: Five feet high and rising: cities and flooding in the 21st century. The World Bank (2011)

  • Kumar, S., Lal, P., Kumar, A.: Turbulence of tropical cyclone ‘Fani’in the Bay of Bengal and Indian subcontinent. Nat. Hazards 103, 1613–1622 (2020). https://doi.org/10.1007/s11069-020-04033-5

    Article  Google Scholar 

  • Lee, J.S., Jurkevich, L., Dewaele, P., Wambacq, P., Oosterlinck, A.: Speckle filtering of synthetic aperture radar images: a review. Remote Sens. Rev. 8(4), 313–340 (1994)

    Article  Google Scholar 

  • Limlahapun, P., Fukui, H.: SAR imagery-based detection to support inundated observation using web technology. Int. J. Soc. Sci. Hum. (2017). https://doi.org/10.18178/ijssh.2017.7.7.869

  • Malnes, E., Guneriussen, T., Høgda, K.A.: Mapping of flood-area by Radarsat in Vannsjø, Norway. In: Proceedings of International Symposium on Remote Sensing of Enviromnent (2002).

  • Manavalan, R.: SAR image analysis techniques for flood area mapping-literature survey. Earth Sci. Inf. 10(1), 1–14 (2017). https://doi.org/10.1007/s12145-016-0274-2

    Article  Google Scholar 

  • Mohan, S.: Development of vulnerability indices for flood damage estimation using remote sensing data in part of Bhagalpur, Bihar (Master's thesis, University of Twente) (2014)

  • Mondal, I., Bandyopadhyay, J., Chakrabarti, P., Santra, D.: Morphodynamic change of Fraserganj and Bakkhali coastal stretch of Indian Sundarban, South 24 Parganas, West Bengal, India. Int. J. Remote Sens. Appl. 5, 1–10 (2015)

    Google Scholar 

  • Park, J.W., Korosov, A., Babiker, M. (2017, April). Efficient thermal noise removal of Sentinel-1 image and its impacts on sea ice applications. In: EGU General Assembly Conference Abstracts (p. 12613).

  • Paul, S.K., Routray, J.K.: Household response to cyclone and induced surge in coastal Bangladesh: coping strategies and explanatory variables. Nat. Hazards 57(2), 477–499 (2011)

    Article  Google Scholar 

  • Perrou, T., Garioud, A., Parcharidis: Use of Sentinel-1 imagery for flood management in a reservoir-regulated river basin. Front. Earth Sci. 12(3), 506–520 (2018)

    Article  CAS  Google Scholar 

  • Rahman, R., Salehin, M.: Flood risks and reduction approaches in Bangladesh. In Disaster risk reduction approaches in Bangladesh, Springer, Tokyo, pp. 65–90 (2013)

  • Rüetschi, M., Schaepman, M.E., Small, D.: Using multitemporal sentinel-1 c-band backscatter to monitor phenology and classify deciduous and coniferous forests in northern Switzerland. Remote Sens. 10(1), 55 (2018). https://doi.org/10.3390/rs10010055

    Article  Google Scholar 

  • Samanta, A.: Cyclone hazards and community response in coastal West Bengal: an anthropo-historical perspective. Economic and Political Weekly 2424–2428 (1997)

  • Sanyal, J., Lu, X.X.: Remote sensing and GIS-based flood vulnerability assessment of human settlements: a case study of Gangetic West Bengal, India. Hydrol. Process. 19(18), 3699–3716 (2005). https://doi.org/10.1002/hyp.5852

    Article  Google Scholar 

  • Singh, O., Kumar, M.: Flood occurrences, damages, and management challenges in India: a geographical perspective. Arab. J. Geosci. 10(5), 102 (2017)

    Article  Google Scholar 

  • Solbø, S., Solheim, I.: Towards operational flood mapping with satellite SAR. In: Envisat & ERS Symposium 572 (2005)

  • Srivastava, H.S., Rajesh, C., Shankar, M.U.: Feasibility of temporal monitoring of flood inundated areas and crop damage assessment using multi-polarised temporal SAR data without any ground truth campaign (2020)

  • Temmerman, S., Meire, P., Bouma, T.J., Herman, P.M., Ysebaert, T., De Vriend, H.J.: Ecosystem-based coastal defence in the face of global change. Nature 504(7478), 79–83 (2013). https://doi.org/10.1038/nature12859

    Article  CAS  Google Scholar 

  • Townsend, P.A.: Mapping seasonal flooding in forested wetlands using multi-temporal Radarsat SAR. Photogramm. Eng. Remote. Sens. 67(7), 857–864 (2001)

    Google Scholar 

  • Twele, A., Cao, W., Plank, S., Martinis, S.: Sentinel-1-based flood mapping: a fully automated processing chain. Int. J. Remote Sens. 37(13), 2990–3004 (2016). https://doi.org/10.1080/01431161.2016.1192304

    Article  Google Scholar 

  • Wang, S., Shi, S., Ni, B.: Joint use of spaceborne microwave sensor data and CYGNSS data to observe tropical cyclones. Remote Sens. 12(19), 3124 (2020a)

    Article  Google Scholar 

  • Wang, S., Shi, S., Ni, B.: Joint use of spaceborne microwave sensor data and CYGNSS data to observe tropical cyclones. Remote Sens. 12(19), 3124 (2020b). https://doi.org/10.1088/1755-1315/569/1/012055

    Article  Google Scholar 

  • Woodruff, J.D., Irish, J.L., Camargo, S.J.: Coastal flooding by tropical cyclones and sea-level rise. Nature 504(7478), 44–52 (2013)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors are thankful to NECTAR, Dept. of Science and Technology, India, for providing financial assistance under the agriculture crop analysis project in NECTAR under Technology outreach. The first author is thankful to Guru Gobind Singh Indraprastha University, India, for the Indraprastha Research Fellowship. The authors are thankful to the Dean, USEM, Guru Gobind Singh Indraprastha University, India, for providing the facility in carrying out the research work.

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  1. University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi, 110078, India

    Prakash Biswakarma & Varun Joshi

  2. North East Centre for Technology Application and Research, Shillong, India

    Manjusha Singh & Arun Kumar Sarma

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  1. Prakash Biswakarma
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  2. Manjusha Singh
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Correspondence to Prakash Biswakarma.

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Biswakarma, P., Singh, M., Sarma, A.K. et al. Assessment of the water inundation area due to the tropical cyclone Bulbul (2019) in the selected districts of West Bengal, India with the application of RS and GIS tools. Proc.Indian Natl. Sci. Acad. 87, 628–639 (2021). https://doi.org/10.1007/s43538-021-00056-z

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