Articles | Volume 28, issue 5
https://doi.org/10.5194/hess-28-1107-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1107-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Mar 2024
Research article |
| 04 Mar 2024
| 04 Mar 2024
Flood risk assessment for Indian sub-continental river basins
Urmin Vegad
Civil Engineering, Indian Institute of Technology (IIT), Gandhinagar, India
Yadu Pokhrel
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, USA
Civil Engineering, Indian Institute of Technology (IIT), Gandhinagar, India
Earth Sciences, Indian Institute of Technology (IIT), Gandhinagar, India
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Cited articles
Acreman, M.: Managed Flood Releases from Reservoirs: Issues and Guidance, Centre for Ecology and Hydrology, Wallingford, UK, https://sswm.info/sites/default/files/reference_attachments/ACREMAN 2000 Managed Flood Releases from Reservoirs.pdf (last access: 2 December 2023), 2000.
Agarwal, A. and Narain, S.: Floods, flood plains and environmental myths, Centre for Science and Environment, https://cdn.downtoearth.org.in/dte/userfiles/images/soe3_20130618.pdf (last access: 2 December 2023) 1991.
Alfieri, L., Dottori, F., Betts, R., Salamon, P., and Feyen, L.: Multi-Model Projections of River Flood Risk in Europe under Global Warming, Climate, 6, 6, https://doi.org/10.3390/CLI6010006, 2018.
Ali, H., Modi, P., and Mishra, V.: Increased flood risk in Indian sub-continent under the warming climate, Weather Clim. Extrem., 25, 100212, https://doi.org/10.1016/J.WACE.2019.100212, 2019.
Allen, S. K., Linsbauer, A., Randhawa, S. S., Huggel, C., Rana, P., and Kumari, A.: Glacial lake outburst flood risk in Himachal Pradesh, India: an integrative and anticipatory approach considering current and future threats, Nat. Hazards, 84, 1741–1763, https://doi.org/10.1007/s11069-016-2511-x, 2016.
Apel, H., Aronica, G. T., Kreibich, H., and Thieken, A. H.: Flood risk analyses – How detailed do we need to be?, Nat, Hazards, 49, 79–98, https://doi.org/10.1007/s11069-008-9277-8, 2009.
Bernhofen, M. V., Cooper, S., Trigg, M., Mdee, A., Carr, A., Bhave, A., Solano-Correa, Y. T., Pencue-Fierro, E. L., Teferi, E., Haile, A. T., Yusop, Z., Alias, N. E., Sa'adi, Z., Bin Ramzan, M. A., Dhanya, C. T., and Shukla, P.: The Role of Global Data Sets for Riverine Flood Risk Management at National Scales, Water Resour. Res., 58, e2021WR031555, https://doi.org/10.1029/2021wr031555, 2022.
Birkmann, J. and Welle, T.: Assessing the risk of loss and damage: Exposure, vulnerability and risk to climate-related hazards for different country classifications, Int. J. Global Warm., 8, 191–212, https://doi.org/10.1504/IJGW.2015.071963, 2015.
Boulange, J., Hanasaki, N., Yamazaki, D., and Pokhrel, Y.: Role of dams in reducing global flood exposure under climate change, Nat. Commun., 12, 417, https://doi.org/10.1038/s41467-020-20704-0, 2021.
Brown, J. D. and Heuvelink, G. B. M.: Assessing Uncertainty Propagation through Physically Based Models of Soil Water Flow and Solute Transport, Encyclopedia of Hydrological Sciences, https://doi.org/10.1002/0470848944.HSA081, 2005.
Chaudhari, S. and Pokhrel, Y.: Alteration of River Flow and Flood Dynamics by Existing and Planned Hydropower Dams in the Amazon River Basin, Water Resour. Res,. 58, e2021WR030555, https://doi.org/10.1029/2021WR030555, 2022.
Chuphal, D. S. and Mishra, V.: Hydrological model-based streamflow reconstruction for Indian sub-continental river basins, 1951–2021, Sci. Data, 10, 1–11, https://doi.org/10.1038/s41597-023-02618-w, 2023.
Cook, A. and Merwade, V.: Effect of topographic data, geometric configuration and modeling approach on flood inundation mapping, J. Hydrol., 377, 131–142, https://doi.org/10.1016/J.JHYDROL.2009.08.015, 2009.
Dang, H., Pokhrel, Y., Shin, S., Stelly, J., Ahlquist, D., and Du Bui, D.: Hydrologic balance and inundation dynamics of Southeast Asia's largest inland lake altered by hydropower dams in the Mekong River basin, Sci. Total Environ., 831, 154833, https://doi.org/10.1016/J.SCITOTENV.2022.154833, 2022.
Dang, T. D., Chowdhury, A. F. M. K., and Galelli, S.: On the representation of water reservoir storage and operations in large-scale hydrological models: implications on model parameterization and climate change impact assessments, Hydrol. Earth Syst. Sci., 24, 397–416, https://doi.org/10.5194/hess-24-397-2020, 2020.
Dangar, S. and Mishra, V.: Natural and anthropogenic drivers of the lost groundwater from the Ganga River basin, Environ. Res. Lett., 16, 114009, https://doi.org/10.1088/1748-9326/ac2ceb, 2021.
de Moel, H., Jongman, B., Kreibich, H., Merz, B., Penning-Rowsell, E., and Ward, P. J.: Flood risk assessments at different spatial scales, Mitig. Adapt. Strateg. Global Change, 20, 865–890, https://doi.org/10.1007/s11027-015-9654-z, 2015.
Dey, S., Saksena, S., Winter, D., Merwade, V., and McMillan, S.: Incorporating Network Scale River Bathymetry to Improve Characterization of Fluvial Processes in Flood Modeling, Water Resour. Res., 58, e2020WR029521, https://doi.org/10.1029/2020WR029521, 2022.
Di Baldassarre, G. and Montanari, A.: Uncertainty in river discharge observations: A quantitative analysis, Hydrol. Earth Syst. Sci., 13, 913–921, https://doi.org/10.5194/hess-13-913-2009, 2009.
Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., and Feyen, L.: Development and evaluation of a framework for global flood hazard mapping, Adv. Water Resour., 94, 87–102, https://doi.org/10.1016/J.ADVWATRES.2016.05.002, 2016.
Dottori, F., Szewczyk, W., Ciscar, J. C., Zhao, F., Alfieri, L., Hirabayashi, Y., Bianchi, A., Mongelli, I., Frieler, K., Betts, R. A., and Feyen, L.: Increased human and economic losses from river flooding with anthropogenic warming, Nat. Clim. Change, 8, 781–786, https://doi.org/10.1038/s41558-018-0257-z, 2018.
Duc Dang, T., Kamal Chowdhury, A. F. M., and Galelli, S.: On the representation of water reservoir storage and operations in large-scale hydrological models: Implications on model parameterization and climate change impact assessments, Hydrol. Earth Syst. Sci., 24, 397–416, https://doi.org/10.5194/hess-24-397-2020, 2020.
Eidsvig, U. M. K., Kristensen, K., and Vangelsten, B. V.: Assessing the risk posed by natural hazards to infrastructures, Nat. Hazards Earth Syst. Sci., 17, 481–504, https://doi.org/10.5194/nhess-17-481-2017, 2017.
Fredrick, O.: Excavators allege debris was used to bury storey in Chhatar Manzil, Hindustan Times, https://www.hindustantimes.com/lucknow/excavators-allege-debris-was-used-to-bury-storey-in-chhatar (last access: 2 December 2023), 19 May 2017.
Gaur, A. and Gaur, A.: Future Changes in Flood Hazards across Canada under a Changing Climate, Water, 10, 1441, https://doi.org/10.3390/w10101441, 2018.
Ghosh, A. and Kar, S. K.: Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal, India, Nat. Hazards, 94, 349–368, https://doi.org/10.1007/s11069-018-3392-y, 2018.
Gu, X., Zhang, Q., Li, J., Chen, D., Singh, V. P., Zhang, Y., Liu, J., Shen, Z., and Yu, H.: Impacts of anthropogenic warming and uneven regional socio-economic development on global river flood risk, J. Hydrol., 590, 125262, https://doi.org/10.1016/j.jhydrol.2020.125262, 2020.
Hanasaki, N., Kanae, S., Oki, T., Masuda, K., Motoya, K., Shirakawa, N., Shen, Y., and Tanaka, K.: An integrated model for the assessment of global water resources – Part 1: Model description and input meteorological forcing, Hydrol. Earth Syst. Sci., 12, 1007–1025, https://doi.org/10.5194/hess-12-1007-2008, 2008.
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., and Kanae, S.: A global hydrological simulation to specify the sources of water used by humans, Hydrol. Earth Syst. Sci., 22, 789–817, https://doi.org/10.5194/hess-22-789-2018, 2018.
He, X., Bryant, B. P., Moran, T., Mach, K. J., Wei, Z., and Freyberg, D. L.: Climate-informed hydrologic modeling and policy typology to guide managed aquifer recharge, Sci. Adv., 7, 6025–6046, https://doi.org/10.1126/sciadv.abe6025, 2021.
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., and Kanae, S.: Global flood risk under climate change, Nat. Clim. Change, 3, 816–821, https://doi.org/10.1038/nclimate1911, 2013.
Hirabayashi, Y., Tanoue, M., Sasaki, O., Zhou, X., and Yamazaki, D.: Global exposure to flooding from the new CMIP6 climate model projections, Sci. Rep., 11, 3740, https://doi.org/10.1038/s41598-021-83279-w, 2021.
Hochrainer-Stigler, S., Schinko, T., Hof, A., and Ward, P. J.: Adaptive risk management strategies for governments under future climate and socioeconomic change: An application to riverine flood risk at the global level, Environ. Sci. Policy, 125, 10–20, https://doi.org/10.1016/j.envsci.2021.08.010, 2021.
Hooper, E. and Chapman, L.: The impacts of climate change on national road and rail networks, in: Transport and Sustainability, vol. 2, Emerald Group Publishing Ltd., 105–136, https://doi.org/10.1108/S2044-9941(2012)0000002008, 2012.
Hu, P., Zhang, Q., Shi, P., Chen, B., and Fang, J.: Flood-induced mortality across the globe: Spatiotemporal pattern and influencing factors, Sci. Total Environ., 643, 171–182, https://doi.org/10.1016/J.SCITOTENV.2018.06.197, 2018.
IPCC: Climate Change 2014: Synthesis Report, in: Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva, Switzerland, IPCC, Geneva, Switzerland, https://www.ipcc.ch/report/ar5/syr/ (last access: 2 December 2023), 2014.
IPCC: Climate Change 2022: Impacts, Adaptation and Vulnerability, Cambridge University Press, Cambridge, UK and New York, USA, 3–33, https://www.ipcc.ch/report/ar6/wg2/ (last access: 2 December 2023), 2022.
Jain, G., Singh, C., Coelho, K., and Malladi, T.: Long-term implications of humanitarian responses The case of Chennai, IIED – International Institute for Environment and Development, London, https://www.iied.org/10840iied (last access: 2 December 2023), 2017.
Joint Research Centre (JRC), European Commission and Center for International Earth Science Information Network (CIESIN), and Columbia University: Global Human Settlement Layer: Population and Built-Up Estimates, and Degree of Urbanization Settlement Model Grid, NASA Socioeconomic Data and Applications Center (SEDAC), Palisades, NY, https://doi.org/10.7927/h4154f0w, 2021.
Joshi, V.: Have we learnt from past floods? Clearly not!, Hindustan Times (Lucknow), https://www.pressreader.com/india/hindustan-times-lucknow/20140914/281646778342401 (last access: 2 December 2023), 14 September 2014.
Kalantari, Z., Briel, A., Lyon, S. W., Olofsson, B., and Folkeson, L.: On the utilization of hydrological modelling for road drainage design under climate and land use change, Sci. Total Environ., 475, 97–103, https://doi.org/10.1016/J.SCITOTENV.2013.12.114, 2014.
Khalaj, M. R., Noor, H., and Dastranj, A.: Investigation and simulation of flood inundation hazard in urban areas in Iran, Geoenviron. Disast., 8, 1–13, https://doi.org/10.1186/s40677-021-00191-1, 2021.
Kimuli, J. B., Di, B., Zhang, R., Wu, S., Li, J., and Yin, W.: A multisource trend analysis of floods in Asia-Pacific 1990–2018: Implications for climate change in sustainable development goals, Int. J. Disast. Risk Reduct., 59, 102237, https://doi.org/10.1016/j.ijdrr.2021.102237, 2021.
Koks, E. E., Rozenberg, J., Zorn, C., Tariverdi, M., Vousdoukas, M., Fraser, S. A., Hall, J. W., and Hallegatte, S.: A global multi-hazard risk analysis of road and railway infrastructure assets, Nat. Commun., 10, 2677, https://doi.org/10.1038/s41467-019-10442-3, 2019.
Krysanova, V., Donnelly, C., Gelfan, A., Gerten, D., Arheimer, B., Hattermann, F., and Kundzewicz, Z. W.: How the performance of hydrological models relates to credibility of projections under climate change, Hydrolog. Sci. J., 63, 696–720, https://doi.org/10.1080/02626667.2018.1446214, 2018.
Kushwaha, A. P., Tiwari, A. D., Dangar, S., Shah, H., Mahto, S. S., and Mishra, V.: Multimodel assessment of water budget in Indian sub-continental river basins, J. Hydrol., 603, 126977, https://doi.org/10.1016/J.JHYDROL.2021.126977, 2021.
Laiolo, P., Gabellani, S., Campo, L., Cenci, L., Silvestro, F., Delogu, F., Boni, G., Rudari, R., Puca, S., and Pisani, A. R.: Assimilation of remote sensing observations into a continuous distributed hydrological model: Impacts on the hydrologic cycle, in: International Geoscience and Remote Sensing Symposium (IGARSS), 26–31 July 2015, Milan, Italy, 1308–1311, https://doi.org/10.1109/IGARSS.2015.7326015, 2015.
Lehner, B., Liermann, C. R., Revenga, C., Vörömsmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N., and Wisser, D.: High-resolution mapping of the world's reservoirs and dams for sustainable river-flow management, Front. Ecol. Environ., 9, 494–502, https://doi.org/10.1890/100125, 2011.
Marchand, M., Dahm, R., Buurman, J., Sethurathinam, S., and Sprengers, C.: Flood protection by embankments in the Brahmani–Baitarani river basin, India: a risk-based approach, Int. J. Water Resour. Dev., 38, 242–261, https://doi.org/10.1080/07900627.2021.1899899, 2022.
Mateo, C. M., Hanasaki, N., Komori, D., and Tanaka, K.: Assessing the impacts of reservoir operation to floodplain inundation by combining hydrological, reservoir management, and hydrodynamic models, Water Resour. Res., 50, 7245–7266, https://doi.org/10.1002/2013WR014845, 2014.
Mateo, C. M. R., Hanasaki, N., Komori, D., Yoshimura, K., Kiguchi, M., Champathong, A., Yamazaki, D., Sukhapunnaphan, T., and Oki, T.: A simulation study on modifying reservoir operation rules: Tradeoffs between flood mitigation and water supply, IAHS-AISH Proc. Rep., 362, 33–40, 2013.
Mateo, C. M. R., Hanasaki, N., Komori, D., Yoshimura, K., Kiguchi, M., Champathong, A., Yamazaki, D., Sukhapunnaphan, T., and Oki, T.: Flood risk and climate change: global and regional perspectives, Hydrolog. Sci. J., 59, 1–28, https://doi.org/10.1080/02626667.2013.857411, 2014.
Mishra, D. K.: 1948 Floods in Bihar-2 Inaugural flood after Independence – Official Version of Floods and its Aftermath, SANDRP, https://sandrp.in/2015/03/10/1948-floods-in-bihar-2-inaugural-flood-after-independence (last access: 2 December 2023), 10 March 2015.
Mishra, V. and Shah, H. L.: Hydroclimatological Perspective of the Kerala Flood of 2018, J. Geol. Soc. India, 92, 645–650, https://doi.org/10.1007/s12594-018-1079-3, 2018.
Mishra, V., Tiwari, A. D., and Kumar, R.: Warming climate and ENSO variability enhance the risk of sequential extremes in India, One Earth, 5, 1250–1259, https://doi.org/10.1016/J.ONEEAR.2022.10.013, 2022.
Mittal, N., Bhave, A. G., Mishra, A., and Singh, R.: Impact of human intervention and climate change on natural flow regime, Water Resour. Manage., 30, 685–699, https://doi.org/10.1007/s11269-015-1185-6, 2016.
Mohanty, M. P., Mudgil, S., and Karmakar, S.: Flood management in India: A focussed review on the current status and future challenges, Int. J. Disast. Risk Reduct., 49, 101660, https://doi.org/10.1016/j.ijdrr.2020.101660, 2020.
Mohapatra, P. K. and Singh, R. D.: Flood management in India, Nat. Hazards, 28, 131–143, https://doi.org/10.1177/0019556120120109, 2003.
Mukherjee, S., Aadhar, S., Stone, D., and Mishra, V.: Increase in extreme precipitation events under anthropogenic warming in India, Weather Clim. Extrem., 20, 45–53, https://doi.org/10.1016/J.WACE.2018.03.005, 2018.
Nanditha, J. S. and Mishra, V.: On the need of ensemble flood forecast in India, Water Secur., 12, 100086, https://doi.org/10.1016/J.WASEC.2021.100086, 2021.
Nanditha, J. S. and Mishra, V.: Multiday Precipitation Is a Prominent Driver of Floods in Indian River Basins, Water Resour. Res., 58, e2022WR032723, https://doi.org/10.1029/2022WR032723, 2022.
Nanditha, J. S., Kushwaha, A. P., Singh, R., Malik, I., Solanki, H., Singh Chupal, D., Dangar, S., Shwarup Mahto, S., Mishra, V., Vegad, U., Chuphal, D. S., and Mahto, S. S.: The Pakistan flood of August 2022: causes and implications, ESS Open Archive, https://doi.org/10.1002/ESSOAR.10512560.1, 2022.
NDMA – National Disaster Management Authority: Annual report of 2016–2017, https://ndma.gov.in/sites/default/files/PDF/Reports/ENG-2016-17-AR.pdf (last access: 2 December 2023), 2016.
Nguyen, P., Thorstensen, A., Sorooshian, S., Hsu, K., AghaKouchak, A., Sanders, B., Koren, V., Cui, Z., and Smith, M.: A high resolution coupled hydrologic–hydraulic model (HiResFlood-UCI) for flash flood modeling, J. Hydrol., 541, 401–420, https://doi.org/10.1016/J.JHYDROL.2015.10.047, 2016.
Nilsson, C., Catherine, A. R., Reidy, A., Dynesius, M., and Revenga, C.: Fragmentation and Flow Regulation of the World's Large River Systems, Science, 308, 405–408, https://doi.org/10.1126/science.1107887, 2005.
NRLD – National Register of Large Dams: Central Water Commission (CWC), Ministry of Water Resources, Government of India, http://cwc.gov.in/sites/default/files/NRLD_04012017.pdf (last access: 4 October 2022), 2017.
Padhra, A.: Tourism in India and the Impact of Weather and Climate, in: Indian Tourism, Emerald Publishing Limited, 187–197, https://doi.org/10.1108/978-1-80262-937-820221013, 2022.
Pai, D. S., Sridhar, L., Rajeevan, M., Sreejith, O. P., Satbhai, N. S., and Mukhopadhyay, B.: Development of a new high spatial resolution (0.25°×0.25°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region, Mausam, 65, 1–18, 2014.
Pathak, S., Liu, M., Jato-Espino, D., and Zevenbergen, C.: Social, economic and environmental assessment of urban sub-catchment flood risks using a multi-criteria approach: A case study in Mumbai City, India, J. Hydrol., 591, 125216, https://doi.org/10.1016/J.JHYDROL.2020.125216, 2020.
Peduzzi, P., Dao, H., Herold, C., and Mouton, F.: Assessing global exposure and vulnerability towards natural hazards: the Disaster Risk Index, Nat. Hazards Earth Syst. Sci., 9, 1149–1159, https://doi.org/10.5194/nhess-9-1149-2009, 2009.
Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, https://doi.org/10.1038/nature20584, 2016.
Pokhrel, Y., Shin, S., Lin, Z., Yamazaki, D., and Qi, J.: Potential Disruption of Flood Dynamics in the Lower Mekong River Basin Due to Upstream Flow Regulation, Sci. Rep., 8, 17767, https://doi.org/10.1038/s41598-018-35823-4, 2018.
Poulin, A., Brissette, F., Leconte, R., Arsenault, R., and Malo, J. S.: Uncertainty of hydrological modelling in climate change impact studies in a Canadian, snow-dominated river basin, J. Hydrol., 409, 626–636, https://doi.org/10.1016/J.JHYDROL.2011.08.057, 2011.
Raghav, P. and Eldho, T. I.: Investigations on the hydrological impacts of climate change on a river basin using macroscale model H08, J. Earth Syst. Sci., 132, 1–23, https://doi.org/10.1007/s12040-023-02102-4, 2023.
Rentschler, J., Salhab, M., and Jafino, B. A.: Flood exposure and poverty in 188 countries, Nat. Commun., 13, 3527, https://doi.org/10.1038/s41467-022-30727-4, 2022.
Roxy, M. K., Ghosh, S., Pathak, A., Athulya, R., Mujumdar, M., Murtugudde, R., Terray, P., and Rajeevan, M.: A threefold rise in widespread extreme rain events over central India, Nat. Commun., 8, 708, https://doi.org/10.1038/s41467-017-00744-9, 2017.
Roy, B., Khan, M. S. M., Saiful Islam, A. K. M., Khan, M. J. U., and Mohammed, K.: Integrated flood risk assessment of the arial khan river under changing climate using ipcc ar5 risk framework, J. Water Clim. Change, 12, 3421–3447, https://doi.org/10.2166/wcc.2021.341, 2021.
Shah, H. L. and Mishra, V.: Hydrologic Changes in Indian Subcontinental River Basins (1901–2012), J. Hydrometeorol., 17, 2667–2687, https://doi.org/10.1175/JHM-D-15-0231.1, 2016.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling, J. Climate, 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006.
Singh, A., Mani, M., and Vishnoi, R. K.: Tehri Dam – A Savior from Climate Change Led Extreme Events, INCOLD J., 10, 44–50, 2021.
Singh, P., Sinha, V. S. P., Vijhani, A., and Pahuja, N.: Vulnerability assessment of urban road network from urban flood, Int. J. Disast. Risk Reduct., 28, 237–250, https://doi.org/10.1016/J.IJDRR.2018.03.017, 2018.
Smith, A., Bates, P. D., Wing, O., Sampson, C., Quinn, N., and Neal, J.: New estimates of flood exposure in developing countries using high-resolution population data, Nat Commun, 10, 1814, https://doi.org/10.1038/s41467-019-09282-y, 2019.
Srivastava, A. K., Rajeevan, M., and Kshirsagar, S. R.: Development of a high resolution daily gridded temperature data set (1969–2005) for the Indian region, Atmos. Sci. Lett., 10, 249–254, https://doi.org/10.1002/asl.232, 2009.
Stephens, E. M., Bates, P. D., Freer, J. E., and Mason, D. C.: The impact of uncertainty in satellite data on the assessment of flood inundation models, J. Hydrol., 414–415, 162–173, https://doi.org/10.1016/J.JHYDROL.2011.10.040, 2012.
Tabari, H., Hosseinzadehtalaei, P., Thiery, W., and Willems, P.: Amplified Drought and Flood Risk Under Future Socioeconomic and Climatic Change, Earths Future, 9, e2021EF002295, https://doi.org/10.1029/2021EF002295, 2021.
Tanoue, M., Taguchi, R., Alifu, H., and Hirabayashi, Y.: Residual flood damage under intensive adaptation, Nat. Clim. Change, 11, 823–826, https://doi.org/10.1038/s41558-021-01158-8, 2021
Teng, J., Jakeman, A. J., Vaze, J., Croke, B. F. W., Dutta, D., and Kim, S.: Flood inundation modelling: A review of methods, recent advances and uncertainty analysis, Environ. Model. Softw., 90, 201–216, https://doi.org/10.1016/J.ENVSOFT.2017.01.006, 2017.
United Nations International Strategy for Disaster Reduction Secretariat: Global Assessment Report on Disaster Risk Reduction: Revealing Risk, Redefining Development, United Nations International Strategy for Disaster Reduction Secretariat, Geneva, https://www.undp.org/publications/2011-global-assessment-report-disaster-risk-reduction
United Nations International Strategy for Disaster Reduction Secretariat: Global Assessment Report on Disaster Risk Reduction 2013, From Shared Risk to Shared Value: the Business Case for Disaster Risk Reduction, United Nations International Strategy for Disaster Reduction Secretariat, Geneva, https://www.undrr.org/publication/global-assessment-report-disaster-risk-reduction-2013 (last access: 26 December 2022), 2013.
van der Knijff, J. M., Younis, J., and de Roo, A. P. J.: LISFLOOD: a GIS-based distributed model for river basin scale water balance and flood simulation, Int. J. Geogr. Inform. Sci., 24, 189–212, https://doi.org/10.1080/13658810802549154, 2010.
Varis, O., Taka, M., and Tortajada, C.: Global human exposure to urban riverine floods and storms, River, 1, 80–90, https://doi.org/10.1002/rvr2.1, 2022.
Vu, D. T., Dang, T. D., Galelli, S., and Hossain, F.: Satellite observations reveal 13 years of reservoir filling strategies, operating rules, and hydrological alterations in the Upper Mekong River basin, Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, 2022.
Ward, P. J., Jongman, B., Weiland, F. S., Bouwman, A., Van Beek, R., Bierkens, M. F. P., Ligtvoet, W., and Winsemius, H. C.: Assessing flood risk at the global scale: Model setup, results, and sensitivity, Environ. Res. Lett., 8, 044019, https://doi.org/10.1088/1748-9326/8/4/044019, 2013.
Willner, S. N., Otto, C., and Levermann, A.: Global economic response to river floods, Nat. Clim. Change, 8, 594–598, https://doi.org/10.1038/s41558-018-0173-2, 2018.
Winsemius, H. C., van Beek, L. P. H., Jongman, B., Ward, P. J., and Bouwman, A.: A framework for global river flood risk assessments, Hydrol. Earth Syst. Sci., 17, 1871–1892, https://doi.org/10.5194/hess-17-1871-2013, 2013.
Winsemius, H. C., Jongman, B., Veldkamp, T. I. E., Hallegatte, S., Bangalore, M., and Ward, P. J.: Disaster risk, climate change, and poverty: Assessing the global exposure of poor people to floods and droughts, Environ. Dev. Econ., 23, 328–348, https://doi.org/10.1017/S1355770X17000444, 2018.
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour. Res., 47, 1–21, https://doi.org/10.1029/2010WR009726, 2011.
Yamazaki, D., De Almeida, G. A. M., and Bates, P. D.: Improving computational efficiency in global river models by implementing the local inertial flow equation and a vector-based river network map, Water Resour. Res., 49, 7221–7235, https://doi.org/10.1002/wrcr.20552, 2013.
Yamazaki, D., Watanabe, S., and Hirabayashi, Y.: Global Flood Risk Modeling and Projections of Climate Change Impacts, Geophys. Monogr. Ser., 233, 185–203, https://doi.org/10.1002/9781119217886.CH11, 2018.
Yang, T., Sun, F., Gentine, P., Liu, W., Wang, H., Yin, J., Du, M., and Liu, C.: Evaluation and machine learning improvement of global hydrological model-based flood simulations, Environ. Res. Lett., 14, 114027, https://doi.org/10.1088/1748-9326/ab4d5e, 2019.
Yoshida, T., Hanasaki, N., Nishina, K., Boulange, J., Okada, M., and Troch, P. A.: Inference of Parameters for a Global Hydrological Model: Identifiability and Predictive Uncertainties of Climate-Based Parameters, Water Resour. Res., 58, e2021WR030660, https://doi.org/10.1029/2021WR030660, 2022.
Zajac, Z., Revilla-Romero, B., Salamon, P., Burek, P., Hirpa, F., and Beck, H.: The impact of lake and reservoir parameterization on global streamflow simulation, J. Hydrol., 548, 552–568, https://doi.org/10.1016/j.jhydrol.2017.03.022, 2017.
Zhao, F., Veldkamp, T. I. E., Frieler, K., Schewe, J., Ostberg, S., Willner, S., Schauberger, B., Gosling, S. N., Schmied, H. M., Portmann, F. T., Leng, G., Huang, M., Liu, X., Tang, Q., Hanasaki, N., Biemans, H., Gerten, D., Satoh, Y., Pokhrel, Y., Stacke, T., Ciais, P., Chang, J., Ducharne, A., Guimberteau, M., Wada, Y., Kim, H., and Yamazaki, D.: The critical role of the routing scheme in simulating peak river discharge in global hydrological models, Environ. Res. Lett., 12, 075003, https://doi.org/10.1088/1748-9326/aa7250, 2017.
Short summary
A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
A large population is affected by floods, which leave their footprints through human mortality,...
