Investigatory analysis of the natural hazards on the Indian coastline

Predictive analysis, comparative analysis, and image processing can provide vital insights into understanding natural phenomena.  Water bodies surround India on three sides, so natural disasters (cyclones, floods, and other related hazards) and rising water levels due to meteorological fluctuations are common occurrences.  The coastal states of India, due to their diverse nature, are constantly exposed to various risks. The study focuses on the changes and disasters in the Indian Ocean surrounding the Indian shorelines.  A systematic approach has been employed to examine the fluctuations in meteorological factors of nine Indian coastal states for the period of 2001–2021.  The fluctuations were computed for four meteorological seasons Summer (March–May), Monsoon (June–September), Post-monsoon (October–November), and Winter (December–February).  These fluctuations are studied, and trends are put forward to examine their effects on natural disasters.  The results of the study focus on the correlations between the factors and disasters and their respective predictions.

  1. Rehman S., Sahana M., Kumar P., Ahmed R., Sajjad H.  Assessing hazards induced vulnerability in coastal districts of India using site-specific indicators: An integrated approach. GeoJournal.  86, 2245–2266 (2021).
  2. Unnikrishnan A. S., Kumar K. R., Fernandes S. E., Michael G. S., Patwardhan S. K.  Sea level changes along the Indian coast: Observations and projections.  Current Science.  90 (3), 362–368 (2006).
  3. Church J. A., Gregory J. M., Huybrechts P., Kuhn M., Lambeck K., Nhuan M. T., Qin D., Woodworth P. L.  Changes in Sea Level. Climate Change 2001: The Scientific Basis.  Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK. 639–693 (2001).
  4. Nurholis, Gaol J. L., Syah A. F., Dewi A. K.  GIS-based Spatio-temporal analysis on Yellow Fin Tuna catch in Eastern Indian Ocean off Sumatera.  IOP Conference Series: Earth and Environmental Science.  429, 012041 (2020).
  5. Lubna K., Kobra K., Saifullah A. S. M., Mallik M., Quarnrul S., Uddin M., Diganta M. T., Muktadir G.  Spatio-temporal analysis for Sea surface temperature in the Bay of Bengal. 7 (2017).
  6. Balasaraswathi P., Srinivasalu S.  Spatio-temporal analysis of Muthupet Lagoon using Geomatic Techniques.  Indian Journal of Geo Marine Sciences.  46 (01), 74–77 (2017).
  7. Anderegg W. R. L., Ballantyne A. P., Smith W. K., Majkut J., Rabin S., Beaulieu C., Birdsey R., Dunne J. P., Houghton R. A., Myneni R. B. et al.  Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink.  Proceedings of the National Academy of Sciences, USA.  112 (51), 15591–15596 (2015).
  8. Cubasch U., Meehl G. A., Boer G. J., Stouffer R. J., Dix M., Noda A., Senior C. A., Raper S., Yap K. S.  Projections of Future Climate Change.  Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK. 525–582 (2001).
  9. Hassell D., Jones R. G.  Simulating climatic changes of the Southern Asian monsoon using a nested regional climate model (HadRM2).  Hadley Centre Technical Note, HCTN-8 (1999).
  10. Flather R. A.  A storm surge prediction model for the northern Bay of Bengal with application to the cyclone disaster in April 1991.  Journal of Physical Oceanography.  24 (1), 172–186 (1994).
  11. Murty T. S., Flather R. A., Henry R. F.  The storm surge problem in the Bay of Bengal.  Progress in Oceanography.  16 (4), 195–233 (1986).
  12. Dube S. K., Gaur V. K.  A PC-based operational storm surge prediction system for disaster management in coastal India.  Current Science.  68, 1103–1113 (1995).
  13. Le Provost C., Genco M. L., Lyard F., Vincent P.  Spectroscopy of the world ocean tides from a finite element hydrodynamic model.  Journal of Geophysical Research.  99 (C12), 24777–24797 (1994).
  14. Emery K. O., Aubrey D. G.  Tide Gauges of India.  Journal of Coastal Research.  5 (3), 489–501 (1989).
  15. Unnikrishnan A. S., Shetye S. R., Michael G. S.  Tidal propagation in the Gulf of Khambhat, Bombay High and surrounding areas.  Proceedings of the Indian Academy of Sciences.  108 (3), 155–177 (1999).
  16. Walter K., Graf H.-F.  On the changing nature of the regional connection between the North Atlantic Oscillation and sea surface temperature.  Journal of Geophysical Research.  107 (D17), ACL 7-1–ACL 7-13 (2002).
  17. Collier N., Hoffman F. M., Lawrence D. M., Keppel-Aleks G., Koven C. D., Riley W. J., Mu M., Randerson J. T.  The International Land Model Benchmarking (ILAMB) system: design, theory, and implementation.  Journal of Advances in Modeling Earth Systems.  10 (11), 2731–2754 (2018).
  18. Ratna S. B., Cherchi A., Osborn T. J., Joshi M., Uppara U.  The extremely positive Indian Ocean dipole of 2019 and associated Indian summer monsoon rainfall response.  Geophysical Research Letters.  48 (2), e2020GL091497 (2021).
  19. Pradhan P. K., Preethi B., Ashok K., Krishnan R., Sahai A. K.  Modoki, Indian Ocean Dipole, and western North Pacific typhoons: Possible implications for extreme events.  Journal of Geophysical Research.  116, D18108 (2011).
  20. Behera S., Yamagata T.  Imprint of the El Ni\ {n}o Modoki on decadal sea level changes.  Geophysical Research Letters.  37 (23), L23702 (2010).
  21. Schott F. A., Xie S.-P., McCreary J. P. Jr.  Indian Ocean circulation and climate variability.  Reviews of Geophysics.  47 (1), RG1002 (2009).
  22. Wang X., Wang D., Zhou W.  Decadal variability of twentieth century El Niño and La Niña occurrence from observations and IPCC AR4 coupled models.  Geophysical Research Letters.  36 (11), L11701 (2009).
  23. Zhang L., Han W.  Impact of Ningaloo Niño on Tropical Pacific and an Interbasin Coupling Mechanism.  Geophysical Research Letters.  45 (20), 11300–11309 (2018).
  24. Agrawal M., Agrawal T., Gupta S.  Statistical Analysis of Ozone Pollution in Delhi: Before and After Lockdown.  Revista Investigacion Operacional.  45 (1), 56–63В (2024).
  25. Agrawal M., Agrawal M., Aslan Z., Dönmez I., Güneş A.  Monitoring Air Pollution Impacts of COVID-19 in India.  EURAS Journal of Health.  2 (2), 93–103 (2021).
  26. Agrawal M., Deokate A. R., Agrawal M.  Atmospheric Factors on Land Surface Temperature.  OSTIV MET PANEL 2021 Abstract Booklet: Istanbul Aydin University Publications.  45–47 (2021).
  27. Puhan M. A., Schunemann H. J., Murad M. H., Li T., Brignardello-Petersen R., Singh J. A., Kessels A. G., Guyatt G. H., Group G. W.  A GRADE working group approach for rating the quality of treatment effect estimates from network meta-analysis.  BMJ.  349, g5630 (2014).
  28. Salanti G., Marinho V., Higgins J. P. T.  A case study of multiple-treatments meta-analysis demonstrates that covariates should be considered.  Journal of Clinical Epidemiology.  62 (8), 857–864 (2009).
  29. Liu J., Ren H.-L., Li W., Zuo J.  Remarkable Impacts of Indian Ocean Sea Surface Temperature on Interdecadal Variability of Summer Rainfall in Southwestern China.  Atmosphere.  9 (3), 103 (2018).
  30. Lee S.-K., Enfield D. B., Wang C.  Why do some El Niños have no impact on tropical North Atlantic SST?  Geophysical Research Letters.  35 (16), L16705 (2008).
  31. Mandal A. K., Ratheesh R., Pandey S., Rao A. D., Kumar P.  An early warning system for inundation forecast due to a tropical cyclone along the east coast of India.  Natural Hazards.  103, 2277–2293 (2020).
  32. Sahoo B., Bhaskaran P. K.  A comprehensive data set for tropical cyclone storm surge-induced inundation for the east coast of India.  International Journal of Climatology.  38 (1), 403–419 (2018).