Abstract
The entire Indian subcontinent experienced devastating floods in the year 2022. The central section of the Godavari river basin (GRB) received torrential rainfall from the southwest monsoon during the second week of July 2022. This study exhibits how Earth observation (EO) datasets and cloud platforms like Google Earth Engine (GEE) can be used for swift, lucid and accurate decoding of the flood inundation signatures. Geospatial analysts can estimate concurrent floods using high-resolution C-band SAR/Sentinel-1 images, gridded precipitation and streamflow forecast datasets. The GPM (IMERG) precipitation data showed an incremental trend with prime hotspots, rainfall dissemination and retrieval from 01–20 July 2022 in the mid-GRB. The flood inundation layers were derived based on Otsu’s method with selective topographic conditions from Sentinel-1 in GEE. Five significant flood affected case sites were identified in the lower GRB from Kothapalli to Yanam town, where the Godavari river meets the Bay of Bengal. Large stretches of agricultural lands were found to be inundated, resulting in extensive economic losses. Such flooded farmlands surrounding Kothapalli, Bhadrachalam, Kunavaram, Polavaram and Yanam towns were estimated as 60, 91, 86, 170 and 142 km2 on 16 and 21 July 2022, respectively. The results were validated and cross-verified using bulletins and maps issued by various national agencies. Hence, EO, GEE and cloud analytical techniques are modern untapped potential e-assets vital for incorporation in policy frameworks helping disaster managers with comprehensive flood condition analysis.
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Adnan, R.M., Liang, Z., Trajkovic, S., Zounemat-Kermani, M., Li, B., and Kisi, O. (2019) Daily streamflow prediction using optimally pruned extreme learning machine. Jour. Hydrol., v.577, 123981. doi:https://doi.org/10.1016/j.jhydrol.2019.123981.
Anaraki, M.V., Farzin, S., Mousavi, S. F., and Karami, H. (2021) Uncertainty analysis of climate change impacts on flood frequency by using hybrid machine learning methods. Water Resourc. Managmt., v.35(1), pp.199–223. doi:https://doi.org/10.1007/s11269-020-02719-w.
Bagaria, P., Nandy, S., Mitra, D., and Sivakumar, K. (2021) Monitoring and predicting regional land use and land cover changes in an estuarine landscape of India. Environ. Monit. Assess., v.193(3), pp.1–27. doi:https://doi.org/10.1007/s10661-021-08915-4.
Anaraki, M.V., Farzin, S., Mousavi, S.F., and Karami, H. (2021) Uncertainty analysis of climate change impacts on flood frequency by using hybrid machine learning methods. Water Resourc. Managmt., v.35(1), pp.199–223. doi:https://doi.org/10.1007/s11269-020-02719-w.
Berghuijs, W.R., Harrigan, S., Molnar, P., Slater, L J. and Kirchner, J.W. (2019) The relative importance of different flood generating mechanisms across Europe. Water Resourc. Res., v.55(6), pp.4582–4593. doi:https://doi.org/10.1029/2019WR024841.
Blöschl, G., Gaál, L., Hall, J., Kiss, A., Komma, J., Nester, T., … and Viglione, A. (2015) Increasing river floods: fiction or reality? Wiley Interdisciplinary Reviews: Water, v.2(4), pp.329–344. doi:https://doi.org/10.1002/wat2.1079.
Blöschl, G., Nester, T., Komma, J., Parajka, J., and Perdigão, R. A. (2013) The June 2013 flood in the Upper Danube Basin, and comparisons with the 2002, 1954 and 1899 floods. Hydrol. Earth Syst. Sci., v.17(12), pp.5197–5212. doi:https://doi.org/10.5194/hess-17-5197-2013.
Bürgi, M., Hersperger, A. M., and Schneeberger, N. (2005) Driving forces of landscape change-current and new directions. Landscape Ecol. v.19(8), pp.857–868. doi:https://doi.org/10.1007/s10980-005-0245-3.
Coelho, S. (2013) Assam and the Brahmaputra: Recurrent Flooding and Internal Displacement. In: The State of Environmental Migration 2013: A Review of 2012. Institute for Sustainable Development and International Relations (IDDRI)/International Organization for Migration (IOM), pp.63–73. http://labos.ulg.ac.be/hugo/wp-content/uploads/sites/38/2017/11/The-State-of-Environmental-Migration-2013-63-73.pdf. Accessed on–24 Nov.2022.
Das, S., Kandekar, A. M., and Sangode, S. J. (2022) Natural and anthropogenic effects on spatio-temporal variation in sediment load and yield in the Godavari basin, India. Sci. Total Environ., 157213. doi:https://doi.org/10.1016/j.scitotenv.2022.157213.
Douglas, I. (2009) Climate change, flooding and food security in south Asia. Food Security, v.1(2), pp.127–136. doi:https://doi.org/10.1007/s12571-009-0015-1.
Douglas, I., Alam, K., Maghenda, M., Mcdonnell, Y., McLean, L., and Campbell, J. (2008) Unjust waters: climate change, flooding and the urban poor in Africa. Environ. Urbaniz., v.20(1), pp.187–205. doi:https://doi.org/10.1177/0956247808089156.
Garg, S. and Mishra, V. (2019) Role of extreme precipitation and initial hydrologic conditions on floods in Godavari River basin, India. Water Resourc. Res., v.55(11), pp.9191–9210. doi:https://doi.org/10.1029/2019WR025863.
Ghosh, S., and Mukherjee, J. (2023) Earth observation data to strengthen flood resilience: a recent experience from the Irrawaddy River. Natural Hazards, v.115(3), pp.2749–2754. doi:https://doi.org/10.1007/s11069-022-05644-w
Ghosh, S., Nandy, S., and Kumar, S.A. (2016) Rapid assessment of recent flood episode in Kaziranga National Park, Assam using remotely sensed satellite data. Curr. Sci., v.111(9), pp.1450–1451. https://www.currentscience.ac.in/Volumes/111/09/1450.pdf. Accessed on–03 May 2023.
Huffman, G., Bolvin, D., Braithwaite, D., Hsu, K., Joyce, R., and Xie, P. (2014) Integrated multi-satellite retrievals for GPM (IMERG), version 4.4. NASA’s Precipitation Processing Center. Jour. ISMAC, 1(02).
Ivancic, T.J., and Shaw, S. B. (2015) Examining why trends in very heavy precipitation should not be mistaken for trends in very high river discharge. Climatic Change, v.133(4), pp.681–693. doi:https://doi.org/10.1007/s10584-015-1476-1.
Jarvis, A., H.I. Reuter, A. Nelson and E. Guevara. (2008) Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90 m Ddatabase: https://srtm.csi.cgiar.org. Accessed on–05 November 2022.
Kale, V. S. (2007) Geomorphic effectiveness of extraordinary floods on three large rivers of the Indian Peninsula. Geomorphology, v.85(3–4), pp.306–316. doi:https://doi.org/10.1016/j.geomorph.2006.03.026.
Kirkels, F.M., Zwart, H.M., Basu, S., Usman, M.O., and Peterse, F. (2020) Seasonal and spatial variability in ä18O and äD values in waters of the Godavari River basin: Insights into hydrological processes. Jour. Hydrol.: Regional Studies, v.30, 100706. doi:https://doi.org/10.1016/j.ejrh.2020.100706.
Krishnan, S. (2022) Gender, disasters and climate: Case of internal displacement in Assam, India. Jindal Global Law Review, pp.1–15. doi:https://doi.org/10.1007/s41020-022-00163-y.
Kumar, L., and Mutanga, O. (2018) Google Earth Engine applications since inception: Usage, trends, and potential. Remote Sensing, v.10(10), 1509. doi:https://doi.org/10.3390/rs10101509
Merz, B., Blöschl, G., Vorogushyn, S., Dottori, F., Aerts, J. C., Bates, P., … and Macdonald, E. (2021) Causes, impacts and patterns of disastrous river floods. Nature Rev. Earth Environ. v.2(9), pp.592–609. doi:https://doi.org/10.1038/s43017-021-00195-3.
Mukherjee J., and Ghosh S., (2023) Earth observation data to strengthen flood management in the Lower Godavari River Basin, India. In: Book of Abstracts: Chemistry, Earth Science, Mathematics, Physics of the Fifth Regional Science and Technology Congress (Region 3). West Bengal State University, v.1, p.42. doi: https://doi.org/10.13140/RG.2.2.15649.89446.
Mutanga, O., and Kumar, L. (2019) Google earth engine applications. Remote Sensing, v.11(5), 591. doi:https://doi.org/10.3390/rs11050591
Overeem, I., and Brakenridge, R. G. (Eds.). (2009) Dynamics and vulnerability of delta systems (Vol. 35). GKSS Research Centre, LOICZ Internat. Project Office, Inst. for Coastal Research. http://futureearthcoasts.s3.amazonaws.com/wp-content/uploads/2018/05/30151147/LOICZ-RS35.pdf. Accessed on–24 November 2022.
Pal, S. C., Chowdhuri, I., Das, B., Chakrabortty, R., Roy, P., Saha, A., and Shit, M. (2022). Threats of climate change and land use patterns enhance the susceptibility of future floods in India. Jour. Environ. Managmt., v.305, 114317. doi:https://doi.org/10.1016/j.jenvman.2021.114317.
Panikkar, P., Sarkar, U.K., and Das, B.K. (2022) Exploring climate change trends in major river basins and its impact on the riverine ecology, fish catch and fisheries of the Peninsular region of India: Issues and a brief overview. Jour. Water and Climate Change, v.13(7), pp.2690–2699. doi:https://doi.org/10.2166/wcc.2022.054.
Rahman, M.A., Mallick, F.H., Mondal, M.S., and Rahman, M.R. (2015) Flood shelters in Bangladesh: Some issues from the user’s perspective. In: Hazards, Risks, and Disasters in Society. Academic Press. pp.145–159. doi:https://doi.org/10.1016/B978-0-12-396451-9.00009-3.
Rahmayati, Y., Parnell, M., and Himmayani, V. (2017) Understanding community-led resilience: the Jakarta floods experience. Australian Jour. Emergency Managm., v.32(4), pp.58–66. https://search.informit.org/doi/epdf/10.3316/informit.222414535944596. Accessed on - 24 November 2022.
Rakhecha, P.R., and Clark, C. (2002) The probable maximum flood at the Ukai and. The Extremes of the Extremes: Extraordinary Floods, (271), 283p.
Rakhecha, P., and Singh, V. (2017) Enveloping Curves for the Highest Floods of River basins in India. Internat. Jour. Hydrol., v.1(3), pp.79–84.
Ramakrishna, G., Gaddam, S.R., and Daisy, I. (2014) Impact of Floods on Food Security and Livelihoods of IDP tribal households: The case of Khammam region of India. Internat.l Jour. Develop. Econ. Sustain., v.2(1), pp.11–24.
Ramasubramanian, R., Gnanappazham, L., Ravishankar, T., and Navamuniyammal, M. (2006) Mangroves of Godavari-analysis through remote sensing approach. Wetlands Ecol. Managmt., v.14(1), pp.29–37. doi:https://doi.org/10.1007/s11273-005-2175-x.
Ramaswamy, C., and Rao, V.S. (1980) Record discharge and severe floods in the Godavari. Curr. Sci., v.49(15), pp.571–578. https://www.jstor.org/stable/24083055. Accessed on - 24 November 2022.
Sagarika, S., Kalra, A., and Ahmad, S. (2014) Evaluating the effect of persistence on long-term trends and analyzing step changes in streamflows of the continental United States. Jour. Hydrol., v.517, pp.36–53. doi:https://doi.org/10.1016/j.jhydrol.2014.05.002.
Singha, M., Dong, J., Sarmah, S., You, N., Zhou, Y., Zhang, G., … and Xiao, X. (2020) Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine. ISPRS Jour. Photogrammetry and Remote Sens., v.166, pp.278–293. doi:https://doi.org/10.1016/j.isprsjprs.2020.06.011.
Souffront Alcantara, M. A., Nelson, E. J., Shakya, K., Edwards, C., Roberts, W., Krewson, C., … and Gutierrez, A. (2019). Hydrologic modeling as a service (HMaaS): a new approach to address hydroinformatic challenges in developing countries. Front. Environ. Sci., v.7, 158. doi:https://doi.org/10.3389/fenvs.2019.00158.
Szabo, S., Brondizio, E., Renaud, F.G., Hetrick, S., Nicholls, R.J., Matthews, Z., … and Dearing, J.A. (2016) Population dynamics, delta vulnerability and environmental change: comparison of the Mekong, Ganges–Brahmaputra and Amazon delta regions. Sustain. Sci., v.11(4), pp.539–554. doi:https://doi.org/10.1007/s11625-016-0372-6.
Trenberth, K.E. (2005) The impact of climate change and variability on heavy precipitation, floods, and droughts. Encyclopedia Hydrol. Sci., v.17, pp.1–11. https://www2.cgd.ucar.edu/staff/trenbert/books/EHShsa211.pdf. Accessed on - 08 November 2022.
Uddin, K., Matin, M.A., and Meyer, F.J. (2019) Operational flood mapping using multi-temporal Sentinel-1 SAR images: A case study from Bangladesh. Remote Sensing, v.11(13), 1581. doi:https://doi.org/10.3390/rs11131581.
Zanaga, D., Van De Kerchove, R., De Keersmaecker, W., Souverijns, N., Brockmann, C., Quast, R., …and Arino, O. (2021) ESA WorldCover 10 m 2020 v100. doi:https://doi.org/10.5281/zenodo.5571936.
Zhang, M., Chen, F., Liang, D., Tian, B., and Yang, A. (2020). Use of Sentinel-1 GRD SAR images to delineate flood extent in Pakistan. Sustainability, v.12(14), 5784. doi:https://doi.org/10.3390/su12145784.
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Mukherjee, J., Ghosh, S. Decoding the Vitality of Earth Observation for Flood Monitoring in the Lower Godavari River Basin, India. J Geol Soc India 99, 802–808 (2023). https://doi.org/10.1007/s12594-023-2387-9
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DOI: https://doi.org/10.1007/s12594-023-2387-9