Skip to main content

Advertisement

SpringerLink
Log in

Local-level impacts of Cyclone Yaas on the Islands of the Indian Sundarbans Delta

  • Short Communication
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

The low-lying islands of the Indian Sundarbans Delta (ISD) contain a unique ecosystem with rich biodiversity, which are at the forefront of the impacts of climate change and natural disasters, such as cyclones. Therefore, in this study, we have analyzed the impact of Cyclone Yaas at the local level in the ISD. We utilized various indices derived from MODIS satellite images to analyze the local-level impacts. The results of our study revealed widespread impacts from high storm surges of 9–16 feet. In general, the daytime land surface temperatures (LSTs) were higher before compared to during the storm, due to lower insolation associated with cloudy skies. However, higher values were observed during the storm for nighttime LSTs and the vegetation indices. More specifically, at the local level, the differences were more pronounced in the vegetated and low-lying coastal areas of the islands. The results of the image analyses were also corroborated with field observations in some of the islands, which showed saltwater encroachment in agricultural lands, collapsed embankments built for protection against storm surge, and food insecurity. The results of our study highlighted the vulnerability of these islands to extreme weather events, and long-lasting impacts on the local communities.

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

References

  • Alongi DM (2008) Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuar Coast Shelf Sci 76:1–13

    Article  Google Scholar 

  • Anderson MC, Norman JM, Kustas WP, Houborg R, Starks PJ, Agam N (2008) A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales. Remote Sens Environ 112(12):4227–4241

    Article  Google Scholar 

  • Ayala-Silva T, Twumasi YA (2004) Hurricane Georges and vegetation change in Puerto Rico using AVHRR satellite data. Int J Remote Sens 25:1629–1640. https://doi.org/10.1080/01431160310001595037

    Article  Google Scholar 

  • Ba R, Song W, Lovallo M, Lo S, Telesca L (2020) Analysis of multifractal and organization/order structure in Suomi-NPP VIIRS normalized difference vegetation index series of wildfire affected and unaffected sites by using the multifractal detrended fluctuation analysis and the Fisher-Shannon analysis. Entropy 22(4):415. https://doi.org/10.3390/e22040415

    Article  Google Scholar 

  • Bellanthudawa BKA, Chang NB (2021) Hurricane Irma impact on biophysical and biochemical features of canopy vegetation in the Santa Fe River Basin, Florida. Int J Appl Earth Obs Geoinf 102:102427

    Google Scholar 

  • Bhatia K, Baker A, Yang W, Vecchi G, Knutson T, Murakami H, Kossin J, Hodges K, Dixon K, Bronselaer B, Whitlock C (2022) A potential explanation for the global increase in tropical cyclone rapid intensification. Nat Commun 13(1):6626

    Article  CAS  Google Scholar 

  • Carle MV, Sasser CE (2016) Productivity and resilience: Long-term trends and storm-driven fluctuations in the plant community of the accreting Wax Lake Delta. Estuaries Coasts 39:406–422

    Article  CAS  Google Scholar 

  • Castañeda-Moya E et al (2020) Hurricanes fertilize mangrove forests in the Gulf of Mexico (Florida Everglades, USA). Proc Natl Acad Sci USA 117:4831–4841

    Article  Google Scholar 

  • Chaudhuri AB, Chaudhury A (1994) Mangrove of the Sundarbans, vol 1. The IUCN Wetlands Programme, Bangkok

    Google Scholar 

  • Chaves MED, Alves MDC, Safadi T, Oliveira MSD, Picoli MCA, Simoes REO, Mataveli GAV (2021) Time-weighted dynamic time warping analysis for mapping interannual cropping practices changes in large-scale agro-industrial farms in Brazilian Cerrado. Sci Remote Sens 3:100021. https://doi.org/10.1016/j.srs.2021.100021

    Article  Google Scholar 

  • Das S, Siddiqi NA (1985) The mangrove and mangrove forests of Bangladesh. Mangrove silviculture division, Bulletin No. 2. BFRI and UNDP/FAO project, BGD/79/017, Chittagong, Bangladesh

  • Didan K (2015) MOD13Q1 MODIS/Terra vegetation indices 16-Day L3 Global 250m SIN Grid V006. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD13Q1.006

  • Donato DC et al (2011) Mangroves among the most carbon-rich forests in the tropics. Nat Geosci 4:293–297

    Article  CAS  Google Scholar 

  • Dutta D, Das PK, Paul S et al (2015) Assessment of ecological disturbance in the mangrove forest of Sundarbans caused by cyclones using MODIS time-series data (2001–2011). Nat Hazards 79:775–790. https://doi.org/10.1007/s11069-015-1872-x

    Article  Google Scholar 

  • Frazier AE, Renschler CS, Miles SB (2013) Evaluating post-disaster ecosystem resilience using MODIS GPP data. Int J Appl Earth Obs Geoinform 21:43–52

    Google Scholar 

  • Ghosh T, Hajra R, Mukhopadhyay A (2014) Island erosion and afflicted population: crisis and policies to handle climate change. In: International perspectives on climate change. Springer, Cham, pp 217–225

  • GOB, UNDP, World Bank (1993) Multipurpose cyclone shelter programme. Executive summary of final report

  • Hajra R, Ghosh A, Ghosh T (2016) Comparative assessment of morphological and landuse/landcover change pattern of Sagar, Ghoramara, and Mousani Island of Indian Sundarban Delta Through Remote Sensing. In: Hazra et al. (eds) Environment and earth observation: case studies in India. Springer. https://doi.org/10.1007/978-3-319-46010-9_11

  • Hazra S, Ghosh T, Das Gupta R, Sen G (2002) Sea Level and associated changes in the Sundarbans. Sci Cult 68(9–12):309–321

    Google Scholar 

  • He Y, Jia G, Hu Y, Zhou Z (2013) Detecting urban warming signals in climate records. Adv Atmos Sci 30(4):1143–1153

    Article  Google Scholar 

  • Hu T, Smith RB (2018) The impact of Hurricane Maria on the vegetation of Dominica and Puerto Rico using multispectral remote sensing. Remote Sens 10(6):827

    Article  Google Scholar 

  • Hulley G (2017) MOD21A2 MODIS/Terra land surface temperature/3-band emissivity 8-Day L3 Global 1km SIN Grid V006. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD21A2.006

  • IPCC (2021) Summary for Policymakers. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press (in press)

  • Ishtiaque A, Myint SW, Wang C (2016) Examining the ecosystem health and sustainability of the world’s largest mangrove forest using multi-temporal MODIS products. Sci Total Environ 569:1241–1254

    Article  Google Scholar 

  • Kerr YH, Lagouarde JP, Nerry F, Ottlé C (2000) Land surface temperature retrieval techniques and applications. In: Quattrochi DA, Luvall JC (eds) Thermal remote sensing in land surface processes. CRC Press, Boca Raton, Fla, pp 33–109

    Google Scholar 

  • Lee MF, Lin TC, Vadeboncoeur MA, Hwang JL (2008) Remote sensing of forest damage in relation to the 1996 strong typhoon Herb at Lienhuachi Experimental Forest. Taiwan Forest Ecol Manag 255:3297–3306. https://doi.org/10.1016/j.foreco.2008.02.010

    Article  Google Scholar 

  • Li C, Sen Roy S, Grant R, Rhode-Barbarigos L (2023) Analysis of the spatial and temporal patterns in land use land cover in Belize City from 1991 to 2021. Remote Sens Appl Soc Environ. https://doi.org/10.1016/j.rsase.2023.101000

    Article  Google Scholar 

  • Lovelock CE (2008) Soil respiration and belowground carbon allocation in mangrove forests. Ecosystems 11:342–354

    Article  CAS  Google Scholar 

  • Madani N, Parazoo NC, Kimball JS, Ballantyne AP, Reichle RH, Maneta M, Saatchi S, Palmer PI, Liu Z, Tagesson T (2020) Recent amplified global gross primary productivity due to temperature increase is offset by reduced productivity due to water constraints. AGU Adv. https://doi.org/10.1029/2020AV000180

    Article  Google Scholar 

  • Masuoka E, Fleig A, Wolfe RE, Patt F (1998) Key characteristics of MODIS data products. IEEE Trans Geosci Remote Sens 36:1313–1323

    Article  Google Scholar 

  • Miller B (1964) A study of the filling of hurricane Donna (1960). Mon Wea Rev 92:389–406

    Article  Google Scholar 

  • Mishra M, Acharyya T, Santos CAG, da Silva RM, Kar D, Kamal AHM, Raulo S (2021) Geo-ecological impact assessment of severe cyclonic storm Amphan on Sundarban mangrove forest using geospatial technology. Estuar Coast Shelf Sci 260:107486

    Article  Google Scholar 

  • NASA. 2022. Evapotranspiration. Accessed on August 11, 2022: https://modis-land.gsfc.nasa.gov/ET.html.

  • NASA. 2022. MODIS Data Product Non-Technical Description - MOD 17. Accessed on August 11, 2022: https://modis.gsfc.nasa.gov/data/dataprod/nontech/MOD17.php

  • Rashid SH, Biswas SR, Bocker R, Kruse M (2009) Mangrove community recovery potential after catastrophic disturbances in Bangladesh. For Ecol Manage 257:923–930

    Article  Google Scholar 

  • Rasquinha DN, Mishra DR (2021) Tropical cyclones shape mangrove productivity gradients in the Indian subcontinent. Sci Rep 11:17355. https://doi.org/10.1038/s41598-021-96752-3

    Article  CAS  Google Scholar 

  • Rodgers JC, Murrah AW, Cooke WH (2009) The Impact of Hurricane Katrina on the coastal vegetation of the weeks bay reserve, alabama from NDVI data. Estuaries Coasts 32:496–507. https://doi.org/10.1007/s12237-009-9138-z

    Article  Google Scholar 

  • Running S, Mu Q, Zhao M (2017) MOD16A2 MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC. Accessed 2022-02-09 from https://doi.org/10.5067/MODIS/MOD16A2.006

  • Running S, Mu Q, Zhao M (2022) MOD17A2H MODIS/Terra Gross Primary Productivity 8-Day L4 Global 500m SIN Grid V006. 2015, distributed by NASA EOSDIS Land Processes DAAC. Accessed 2022-02-09 https://doi.org/10.5067/MODIS/MOD17A2H.006

  • Santhana Vannan SK, Cook RB, Holladay SK, Olsen LM, Dadi U, Wilson BE (2009) A web-based subsetting service for regional scale modis land products. IEEE J Sel Top Appl Earth Obs Remote Sens 2(4):319–328. https://doi.org/10.1109/JSTARS.2009.2036585

    Article  Google Scholar 

  • Santhana Vannan SK, Cook RB, Pan JY, Wilson BE (2011) A SOAP web service for accessing MODIS land product subsets. Earth Sci Inform 4(2):97–106. https://doi.org/10.1007/s12145-011-0079-2

    Article  Google Scholar 

  • Sen Roy S, Keikhosravi Kiany MS, Balling RC (2016) A significant population signal in Iranian temperature records. Int J Atmos Sci.

  • Sen Roy S, Yuan F (2007) Patterns and variability of summer NDVI in response to climate variables in Minnesota. Gisci Remote Sens 44(2):166–181

    Article  Google Scholar 

  • Shan K, Yu X (2021) Variability of tropical cyclone landfalls in China. J Clim 34(23):9235–9247

    Article  Google Scholar 

  • Shen W, Ginis ISAAC, Tuleya RE (2002) A numerical investigation of land surface water on landfalling hurricanes. J Atmos Sci 59(4):789–802

    Article  Google Scholar 

  • Smith TJ et al (2009) Cumulative impacts of hurricanes on Florida mangrove ecosystems: sediment deposition, storm surges and land crabs of Corcovado national park view project hydrologic response to increased water management capability at the great dismal swamp National Wildl. Wetlands. https://doi.org/10.1672/08-40.1

    Article  Google Scholar 

  • Subhani R, Saqib SE, Rahman M, Ahmad MM, Pradit S (2021) Impact of cyclone Yaas 2021 aggravated by COVID-19 Pandemic in the Southwest Coastal Zone of Bangladesh. Sustainability 13(23):13324

    Article  CAS  Google Scholar 

  • Thakur S, Maity D, Mondal I, Basumatary G, Ghosh PB, Das P, De TK (2021) Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environ Develop Sustain 23:1917–1943

    Article  Google Scholar 

  • Tuleya RE (1994) Tropical storm development and decay: Sensitivity to surface boundary conditions. Mon Wea Rev 122:291–304

    Article  Google Scholar 

  • Tuleya RE, Kurihara Y (1978) A numerical study of the landfall of tropical cyclones. J Atmos Sci 35:242–257

    Article  Google Scholar 

  • Turner DP, Ritts WD, Cohen WB, Gower ST, Running SW, Zhao M, Costa MH, Kirschbaum AA, Ham JM, Saleska SR, Ahl DE (2006) Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sens Environ 102(3–4):282–292

    Article  Google Scholar 

  • Wan Z (2019) MODIS Collection 6.1 (C61) Product user guide. Accessed on September 2, 2022: MODIS Collection 6.1 (C61) Product User Guide

  • Wang F, Ge QS (2012) Estimation of urbanization bias in observed surface temperature change in China from 1980 to 2009 using satellite land-use data”. Chin Sci Bull 57(14):1708–1715

    Article  Google Scholar 

  • Wentz EA, Nelson D, Rahman A, Stefanov WL, Sen Roy S (2008) Expert system classification of urban land use/cover for Delhi, India. Int J Remote Sens 29:4405–4427. https://doi.org/10.1080/01431160801905497

    Article  Google Scholar 

  • Wright J, Sen Roy S (2022) Geospatial characteristics of Colorado wildfire occurrences from 2001 to 2020. Remote Sens Appl Soc Environ. https://doi.org/10.1016/j.rsase.2022.100872

    Article  Google Scholar 

  • Wu C, Munger JW, Niu Z, Kuang D (2010) Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. Remote Sens Environ 114(12):2925–2939

    Article  Google Scholar 

  • Zhang Q, Middleton EM, Gao BC, Cheng YB (2011) Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPARchl) and Leaf Water Content (LWC). IEEE Trans Geosci Remote Sens 50(5):1844–1852

    Article  Google Scholar 

  • Zhang K, Kimball JS, Nemani RR, Running SW (2010) A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006. Water Resour Res 46(9)

Download references

Acknowledgements

This research was partially funded by a senior short-term fellowship from American Institute of Indian Studies. The authors are grateful to the residents of the Indian Sundarbans Delta for opening their homes and sharing their experiences with us, particularly Sanjoy, Gopal, Prateet, and others at https://www.sundarbansafari.com/ for arranging the logistics in the field.

Funding

This research was partially funded by a senior short-term fellowship from the American Institute of Indian Studies.

Author information

Authors and Affiliations

  1. Department of Geography and Sustainable Development, University of Miami, Coral Gables, FL, USA

    Shouraseni Sen Roy

  2. School of Oceanographic Studies, Jadavpur University, Kolkata, India

    Tuhin Ghosh

Authors
  1. Shouraseni Sen Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tuhin Ghosh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shouraseni Sen Roy.

Ethics declarations

Conflicts of interest

The authors declare no conflict of interest. The authors have no relevant financial or non-financial interests to disclose.

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

Roy, S.S., Ghosh, T. Local-level impacts of Cyclone Yaas on the Islands of the Indian Sundarbans Delta. Nat Hazards 120, 3995–4010 (2024). https://doi.org/10.1007/s11069-023-06304-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-023-06304-3

Keywords

Search

Navigation