Abstract
Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in the Indo-Gangetic plain region. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901–2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10 years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100 years of return occurred during 2008–2011 and 2016–2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010–2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts.
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The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Adhyani NL, June T, Sopaheluwakan A (2017) Exposure to drought: duration, severity and intensity (Java, Bali and Nusa Tenggara). IOP Conf Ser: Earth Environ Sci 58:012040. https://doi.org/10.1088/1755-1315/5
AghaKouchak A, Farahmand A, Melton FS, Teixeira J, Anderson MC, Wardlow BD, Hain CR (2015) Remote sensing of drought: progress, challenges and opportunities. Rev Geophys 53(2):452–480. https://doi.org/10.1002/2014RG000456
Aksoy H, Cetin M, Eris E, Burgan HI, Cavus Y, Yildirim I, Sivapalan M (2021) Critical drought intensity-duration-frequency curves based on total probability theorem-coupled frequency analysis. Hydrol Sci J 66(8):1337–1358. https://doi.org/10.1080/02626667.2021.1934473
Banerjee S, Pandey AC (2021) Catchment-level agricultural drought hazard vulnerability analysis of Ganga Basin (India) using spectral indices. Arab J Geosci 14(17). https://doi.org/10.1007/s12517-021-07825-6
Bento VA, Gouveia CM, DaCamara CC, Trigo IF (2018) A climatological assessment of drought impact on vegetation health index. Agric for Meteorol 259(February):286–295. https://doi.org/10.1016/j.agrformet.2018.05.014
Bera S (2017) Trend analysis of rainfall in Ganga Basin, India during 1901–2000. Am J Clim Chang 06(01):116–131. https://doi.org/10.4236/ajcc.2017.61007
Bera D, Dutta D (2021) Use of open source software to assess spatio-temporal variation of agricultural drought at regional scale. In Mapping, Monitoring, and Modeling Land and Water Resources, CRC Press, pp. 275–296. https://doi.org/10.1201/9781003181293-18
Bisht DS, Sridhar V, Mishra A, Chatterjee C, Raghuwanshi NS (2019) Drought characterization over India under projected climate scenario. Int J Climatol 39(4):1889–1911. https://doi.org/10.1002/joc.5922
Cavus Y, Aksoy H (2020) Critical drought severity/intensity-duration-frequency curves based on precipitation deficit. J Hydrol 584:124312. https://doi.org/10.1016/j.jhydrol.2019.124312
Chakraborty R, Guha BK, Talukdar S, Ratnam MV, Maitra A (2019) Growth in mid-monsoon dry phases over the Indian region: prevailing influence of anthropogenic aerosols. Atmos Chem Phys 19(19):12325–12341. https://doi.org/10.5194/acp-19-12325-2019
Choudhury A, Dutta D, Bera D, Kundu A (2021) Regional variation of drought parameters and long-term trends over India using standardized precipitation evapotranspiration index. J Environ Manag 296(May):113056. https://doi.org/10.1016/j.jenvman.2021.113056
Citakoglu H, Coşkun Ö (2022) Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey. Environ Sci Pollut Res 29(50):75487–75511
Citakoglu H, Minarecioglu N (2021) Trend analysis and change point determination for hydro-meteorological and groundwater data of Kizilirmak basin. Theor Appl Climatol 145:1275–1292. https://doi.org/10.1007/s00704-021-03696-9
Coşkun Ö, Citakoglu H (2023) Prediction of the standardised precipitation index based on the long short-term memory and empirical mode decomposition-extreme learning machine models: The Case of Sakarya, Türkiye. Phys Chem Earth, Parts a/b/c 131:103418
Dai A (2011a) Drought under global warming: a review. Wiley Interdiscip Rev: Climate Change 2(1):45–65. https://doi.org/10.1002/wcc.81
Dai A (2011b) Characteristics and trends in various forms of the Palmer drought severity index during 1900–2008. J Geophys Res 116(D12):D12115. https://doi.org/10.1029/2010JD015541
Dai M, Huang S, Huang Q, Leng G, Guo Y, Wang L, Fang W, Li P, Zheng X (2020) Assessing agricultural drought risk and its dynamic evolution characteristics. Agric Water Manag 231(September 2019):106003. https://doi.org/10.1016/j.agwat.2020.106003
Das J, Jha S, Goyal MK (2020a) On the relationship of climatic and monsoon teleconnections with monthly precipitation over meteorologically homogenous regions in India: Wavelet & global coherence approaches. Atmos Res 238(January):104889. https://doi.org/10.1016/j.atmosres.2020.104889
Das P, Naganna SR, Deka PC, Pushparaj J (2020b) Hybrid wavelet packet machine learning approaches for drought modeling. Environm Earth Sci 79(10):221. https://doi.org/10.1007/s12665-020-08971-y
Dharpure JK, Goswami A, Patel A, Kulkarni AV, Meloth T (2022) Drought characterization using the combined terrestrial evapotranspiration index over the Indus, Ganga and Brahmaputra river basins. Geocarto Int 37(4):1059–1083. https://doi.org/10.1080/10106049.2020.1756462
Dinku T, Ceccato P, Connor SJ (2011) Challenges of satellite rainfall estimation over mountainous and arid parts of east Africa. Int J Remote Sens 32(21):5965–5979. https://doi.org/10.1080/01431161.2010.499381
Döll P, Lehner B (2002) Validation of a new global 30-min drainage direction map. J Hydrol 258(1–4):214–231. https://doi.org/10.1016/S0022-1694(01)00565-0
Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto Int 28(3):192–209. https://doi.org/10.1080/10106049.2012.679975
Dutta D, Kundu A, Patel NR, Saha SK, Siddiqui AR (2015) Assessment of agricultural drought in Rajasthan (India) using remote sensing derived vegetation condition index (VCI) and standardized precipitation index (SPI). Egypt J Remote Sens Space Sci 18(1):53–63. https://doi.org/10.1016/j.ejrs.2015.03.006
Funk C, Nicholson SE, Landsfeld M, Klotter D, Peterson P, Harrison L (2015) The Centennial Trends Greater Horn of Africa precipitation dataset. Sci Data 2(1):150050. https://doi.org/10.1038/sdata.2015.50
Ganguli P, Reddy MJ (2014) Ensemble prediction of regional droughts using climate inputs and the SVM-copula approach. Hydrol Process 28(19):4989–5009. https://doi.org/10.1002/hyp.9966
Ganga Basin Report (2014)Government of India Ministry of Water Resources. Version. 2.0. https://indiawris.gov.in/downloads/Ganga%20Basin.pdf
Gocic M, Trajkovic S (2015) Water surplus variability index as an indicator of drought. J Hydrol Eng 20(2):04014038. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001008
González J, Valdés JB (2003) Bivariate drought recurrence analysis using tree ring reconstructions. J Hydrol Eng 8(5):247–258. https://doi.org/10.1061/(asce)1084-0699(2003)8:5(247)
Goyal MK, Gupta V (2014) Identification of homogeneous rainfall regimes in northeast region of India using fuzzy cluster analysis identification of homogeneous rainfall regimes in northeast region of India using fuzzy cluster analysis. January 2015. https://doi.org/10.1007/s11269-014-0699-7
Guenang GM, Kamga FM (2014) Computation of the standardized precipitation index (SPI) and its use to assess drought occurrences in Cameroon over recent decades. J Appl Meteorol Climatol 53(10):2310–2324. https://doi.org/10.1175/JAMC-D-14-0032.1
Guo H, Bao A, Liu T, Jiapaer G, Ndayisaba F, Jiang L (2018) Science of the total environment spatial and temporal characteristics of droughts in Central Asia. Sci Total Environ 624:1523–1538. https://doi.org/10.1016/j.scitotenv.2017.12.120
Guo Y, Huang S, Huang Q, Leng G, Fang W, Wang L, Wang H (2020) Propagation thresholds of meteorological drought for triggering hydrological drought at various levels. Sci Total Environ 712:136502. https://doi.org/10.1016/j.scitotenv.2020.136502
Gupta V, Jain MK (2018) Investigation of multi-model spatiotemporal mesoscale drought projections over India under climate change scenario. J Hydrol 567:489–509. https://doi.org/10.1016/j.jhydrol.2018.10.012
Gupta V, Kumar Jain M, Singh VP (2020) Multivariate modeling of projected drought frequency and hazard over India. J Hydrol Eng 25(4):1–19. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001893
Haile GG, Tang Q, Leng G, Jia G, Wang J, Cai D, Sun S, Baniya B, Zhang Q (2019) Long-term spatiotemporal variation of drought patterns over the Greater Horn of Africa. Sci Total Environ 704:135299. https://doi.org/10.1016/j.scitotenv.2019.135299
Haktanir T, Citakoglu H (2014) Trend, independence, stationarity, and homogeneity tests on maximum rainfall series of standard durations recorded in Turkey. J Hydrol Eng 19. https://doi.org/10.1061/(asce)he.1943-5584.0000973
Hu T, Myers Toman E, Chen G, Shao G, Zhou Y, Li Y, Zhao K, Feng Y (2021) Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS J Photogramm Remote Sens 176:250–261. https://doi.org/10.1016/j.isprsjprs.2021.04.008
Jehanzaib M, Yoo J, Kwon HH, Kim TW (2021) Reassessing the frequency and severity of meteorological drought considering non-stationarity and copula-based bivariate probability. J Hydrol. https://doi.org/10.1016/j.jhydrol.2021.126948
Jena P, Garg S, Azad S (2020) Performance analysis of IMD high-resolution gridded rainfall (0.25° × 0.25°) and satellite estimates for detecting cloudburst events over the northwest Himalayas. J Hydrometeorol 21(7):1549–1569. https://doi.org/10.1175/JHM-D-19-0287.1
Jha S, Sehgal VK, Raghava R, Sinha M (2013) Trend of standardized precipitation index during Indian summer monsoon season in agroclimatic zones of India. Earth Syst Dyn Discuss 4(1):429–449. https://doi.org/10.5194/esdd-4-429-2013
Jiang R, Liang J, Zhao Y, Wang H, Xie J, Lu X, Li F (2021) Assessment of vegetation growth and drought conditions using satellite-based vegetation health indices in Jing-Jin-Ji region of China. Sci Rep 11(1):13775. https://doi.org/10.1038/s41598-021-93328-z
Joshi N, Gupta D, Suryavanshi S, Adamowski J, Madramootoo CA (2016) Analysis of trends and dominant periodicities in drought variables in India: a wavelet transform based approach. Atmos Res 182:200–220. https://doi.org/10.1016/j.atmosres.2016.07.030
Kakade SB, Kulkarni A (2017) Seasonal prediction of summer monsoon rainfall over cluster regions of India. J Earth Syst Sci 126(3):34. https://doi.org/10.1007/s12040-017-0811-5
Kalisa W, Zhang J, Igbawua T, Ujoh F, Ebohon OJ, Namugize JN, Yao F (2020) Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016. Agric Water Manag 237(April):106195. https://doi.org/10.1016/j.agwat.2020.106195
Kogan FN (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int J Remote Sens 11(8):1405–1419. https://doi.org/10.1080/01431169008955102
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100. https://doi.org/10.1016/0273-1177(95)00079-T
Kogan F, Guo W, Yang W (2018) Drought and food security prediction from NOAA new generation of operational satellites. Geomat Nat Haz Risk 10(1):651–666. https://doi.org/10.1080/19475705.2018.1541257
Kumar D (2017) River Ganges-Historical, cultural and socioeconomic attributes. Aquat Ecosyst Health Manag 20(1–2):8–20. https://doi.org/10.1080/14634988.2017.1304129
Liu Q, Zhang S, Zhang H, Bai Y, Zhang J (2020) Monitoring drought using composite drought indices based on remote sensing. Sci Total Environ 711:134585. https://doi.org/10.1016/j.scitotenv.2019.134585
Mahto SS, Mishra V (2020) Dominance of summer monsoon flash droughts in India. Environ Res Lett. https://doi.org/10.1088/1748-9326/abaf1d
Mallya G, Mishra V, Niyogi D, Tripathi S, Govindaraju RS (2016) Trends and variability of droughts over the Indian monsoon region. Weather Clim Extremes 12:43–68. https://doi.org/10.1016/j.wace.2016.01.002
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology Vol. 17, No. 22, pp. 179–183
Mesbahzadeh T, Mirakbari M, Mohseni Saravi M, Soleimani Sardoo F, Miglietta MM (2019) Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP). Meteorol Appl 1–20. https://doi.org/10.1002/met.1856
Mishra V (2020) Long-term (1870–2018) drought reconstruction in context of surface water security in India. J Hydrol 580(October 2019):124228. https://doi.org/10.1016/j.jhydrol.2019.124228
Mishra AK, Singh VP (2009) Analysis of drought severity-area-frequency curves using a general circulation model and scenario uncertainty. J Geophys Res 114(D6):D06120. https://doi.org/10.1029/2008JD010986
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012
Mishra AK, Singh VP (2011) Drought modeling – A review. J Hydrol 403(1–2):157–175. https://doi.org/10.1016/j.jhydrol.2011.03.049
Mishra A, Singh R, Raghuwanshi NS, Chatterjee C, Froebrich J (2013) Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin. Sci Total Environ 468–469:S132–S138. https://doi.org/10.1016/j.scitotenv.2013.05.080
Mishra V, Aadhar S, Asoka A, Pai S, Kumar R (2016) On the frequency of the 2015 monsoon season drought in the Indo-Gangetic Plain. Geophys Res Lett 43(23):12102–12112. https://doi.org/10.1002/2016GL071407
Mishra V, Tiwari AD, Aadhar S, Shah R, Xiao M, Pai DSS, Lettenmaier D (2019) Drought and famine in India, 1870–2016. Geophys Res Lett 46(4):2075–2083. https://doi.org/10.1029/2018GL081477
Mishra V, Thirumalai K, Jain S, Aadhar S (2021) Unprecedented drought in South India and recent water scarcity. Environ Res Lett 16(5):054007. https://doi.org/10.1088/1748-9326/abf289
Nabaei S, Sharafati A, Yaseen ZM, Shahid S (2019) Copula based assessment of meteorological drought characteristics: regional investigation of Iran. Agric for Meteorol 276–277(January):107611. https://doi.org/10.1016/j.agrformet.2019.06.010
Nam W-H, Choi J-Y, Yoo S-H, Jang M-W (2012) A decision support system for agricultural drought management using risk assessment. Paddy Water Environ, 10(3):197–207. https://doi.org/10.1007/s10333-012-0329-z
Nath R, Nath D, Li Q, Chen W, Cui X (2017) Impact of drought on agriculture in the Indo-Gangetic Plain, India. Adv Atmos Sci 34(3):335–346. https://doi.org/10.1007/s00376-016-6102-2
Niranjan Kumar K, Rajeevan M, Pai DSS, Srivastava AKK, Preethi B, Kumar KN, Rajeevan M, Pai DSS, Srivastava AKK, Preethi B (2013) On the observed variability of monsoon droughts over India. Weather Clim Extremes 1:42–50. https://doi.org/10.1016/j.wace.2013.07.006
Pai DS, Sridhar L, Rajeevan M, Sreejith OP, Satbhai NS, Mukhopadhyay B (2014) (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam 1(January):1–18
Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise 21(4):156–161. https://doi.org/10.1080/00431672.1968.9932814
Palmer WC (1965) Meteorological drought (Vol. 30). US Department of Commerce, Weather Bureau.
Pandey V, Misra AK, Yadav SB (2019) Impact of El-Nino and La-Nina on Indian climate and crop production. In: Climate Change and Agriculture in India: Impact and Adaptation, Springer International Publishing, (Issue September 2018), pp. 11–20. https://doi.org/10.1007/978-3-319-90086-5_2
Parajuli B, Zhang X, Deuja S, Liu Y (2021) Regional and seasonal precipitation and drought trends in Ganga-Brahmaputra basin. Water (Switzerland) 13(16). https://doi.org/10.3390/w13162218
Patel NR, Yadav K (2015) Monitoring spatio-temporal pattern of drought stress using integrated drought index over Bundelkhand region, India. Nat Hazards 77(2):663–677. https://doi.org/10.1007/s11069-015-1614-0
Poonia V, Jha S, Goyal MK (2021) Copula based analysis of meteorological, hydrological and agricultural drought characteristics across Indian river basins. Int J Climatol 41(9):4637–4652. https://doi.org/10.1002/joc.7091
Prakash S, Mitra AK, Momin IM, Rajagopal EN, Basu S, Collins M, Turner AG, Achuta Rao K, Ashok K (2015) Seasonal intercomparison of observational rainfall datasets over India during the southwest monsoon season. Int J Climatol 35(9):2326–2338. https://doi.org/10.1002/joc.4129
Rajeevan M, Bhate J (2009) A high resolution daily gridded rainfall dataset (1971–2005) for mesoscale meterological studies. Curr Sci 96(4):558–562
Rajeevan M, Bhate J, Kale JD, Lal B (2006) A high resolution daily gridded rainfall data for the Indian Region.pdf. Curr Sci 91(3):296–307
Rhee J, Cho J (2016) Future changes in drought characteristics: regional analysis for South Korea under CMIP5 projections. J Hydrometeorol 17(1):437–451. https://doi.org/10.1175/JHM-D-15-0027.1
Sahoo RN, Dutta D, Khanna M, Kumar N, Bandyopadhyay SK (2015) Drought assessment in the Dhar and Mewat Districts of India using meteorological, hydrological and remote-sensing derived indices. Nat Hazards 77(2):733–751. https://doi.org/10.1007/s11069-015-1623-z
Schwalm CR, Anderegg WRL, Michalak AM, Fisher JB, Biondi F, Koch G, Litvak M, Ogle K, Shaw JD, Wolf A, Huntzinger DN, Schaefer K, Cook R, Wei Y, Fang Y, Hayes D, Huang M, Jain A, Tian H (2017) Global patterns of drought recovery. Nature 548(7666):202–205. https://doi.org/10.1038/nature23021
Shah D, Mishra V (2020) Drought onset and termination in India. J Geophys Res: Atmos 125(15). https://doi.org/10.1029/2020JD032871
Sharma A, Goyal MK (2020) Assessment of drought trend and variability in India using wavelet transform. Hydrol Sci J 65(9):1539–1554. https://doi.org/10.1080/02626667.2020.1754422
She D, Xia J (2018) Copulas-based drought characteristics analysis and risk assessment across the Loess Plateau of China. Water Resour Manag 32(2):547–564. https://doi.org/10.1007/s11269-017-1826-z
Shepard D (1968) Two- dimensional interpolation function for irregularly- spaced data. Proc 23rd Nat Conf, New York, 27-29 August, 517–524. https://dl.acm.org/doi/10.1145/800186.810616
Shewale MP, Kumar S (2005) Climatological features of drought incidences in India, Meteorological Monograph (Climatology 21/2005), National Climate Centre, India Meteorological Department, 22 pp. http://www.inderscience.com/link.php?id=57217
Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resour Manag 20(5):795–815. https://doi.org/10.1007/s11269-005-9008-9
Spinoni J, Naumann G, Carrao H, Barbosa P, Vogt J (2014) World drought frequency, duration, and severity for 1951–2010. Int J Climatol 34(8):2792–2804. https://doi.org/10.1002/joc.3875
Tyalagadi MS, Gadgil A, Krishnakumar G (2015) Monsoonal droughts in India – a recent assessment. Papers Glob Chang IGBP 22(1):19–35. https://doi.org/10.1515/igbp-2015-0013
United Nations (2014) Land and Drought | UNCCD, New York, USA [WWW Document]. URL https://www.unccd.int/issues/land-and-drought. Accessed 10.18.18
Varikoden H, Revadekar JV, Choudhary Y, Preethi B (2015) Droughts of Indian summer monsoon associated with El Niño and Non-El Niño years. Int J Climatol 35(8):1916–1925. https://doi.org/10.1002/joc.4097
Vergni L, Todisco F, Di Lena B, Mannocchi F (2020) Bivariate analysis of drought duration and severity for irrigation planning. Agric Water Manag 229(September):105926. https://doi.org/10.1016/j.agwat.2019.105926
Vicente-Serrano SM, Beguería S, López-Moreno JI, Angulo M, El Kenawy A (2010) A new global 0.5° gridded dataset (1901–2006) of a multiscalar drought index: comparison with current drought index datasets based on the Palmer drought severity index. J Hydrometeorol 11(4):1033–1043. https://doi.org/10.1175/2010JHM1224.1
Wang Q, Wu J, Lei T, He B, Wu Z, Liu M, Mo X, Geng G, Li X, Zhou H, Liu D (2014) Temporal-spatial characteristics of severe drought events and their impact on agriculture on a global scale. Quatern Int 349:10–21. https://doi.org/10.1016/j.quaint.2014.06.021
Wang F, Wang Z, Yang H, Zhao Y, Zhang Z, Li Z, Hussain Z (2019) Copula-based drought analysis using standardized precipitation evapotranspiration index: a case study in the Yellow river basin, China. Water (switzerland) 11(6):1–20. https://doi.org/10.3390/w11061298
Wang F, Wang Z, Yang H, Di D, Zhao Y, Liang Q (2020) A new copula-based standardized precipitation evapotranspiration streamflow index for drought monitoring. J Hydrol 585:124793. https://doi.org/10.1016/j.jhydrol.2020.124793
Whitehead PG, Jin L, Macadam I, Janes T, Sarkar S, Rodda HJE, Sinha R, Nicholls RJ (2018) Modelling impacts of climate change and socio-economic change on the Ganga, Brahmaputra, Meghna, Hooghly and Mahanadi river systems in India and Bangladesh. Sci Total Environ 636:1362–1372. https://doi.org/10.1016/j.scitotenv.2018.04.362
Wu PY, You GJY, Chan MH (2020) Drought analysis framework based on copula and Poisson process with nonstationarity. J Hydrol 588(September 2019):125022. https://doi.org/10.1016/j.jhydrol.2020.125022
Xiao HM, Lo MH, Yu JY (2022) The increased frequency of combined El Niño and positive IOD events since 1965s and its impacts on maritime continent hydroclimates. Sci Rep 12:1–10. https://doi.org/10.1038/s41598-022-11663-1
Yang P, Xia J, Zhang Y, Zhan C, Sun S (2019) How is the risk of hydrological drought in the Tarim River Basin, Northwest China? Sci Total Environ 693:133555. https://doi.org/10.1016/j.scitotenv.2019.07.361
Yang Y, Gan TY, Tan X (2020) Spatiotemporal changes of drought characteristics and their dynamic drivers in Canada. Atmos Res 232(September 2019):104695. https://doi.org/10.1016/j.atmosres.2019.104695
Yevjevich V (1967) An objective approach to definitions and investigations of continental hydrologic droughts. J Hydrol 7(3):353. https://doi.org/10.1016/0022-1694(69)90110-3
Zerouali B, Pawar UV, Elbeltagi A, Abda Z, Chettih M, Santos CAG, Difi S (2023) Change-point detection in monsoon rainfall of Narmada River (central India) during 1901–2015. J Earth Syst Sci 132. https://doi.org/10.1007/s12040-023-02140-y
Zhang X, Obringer R, Wei C, Chen N, Niyogi D (2017) Droughts in India from 1981 to 2013 and Implications to Wheat Production. Sci Rep 7(1):44552. https://doi.org/10.1038/srep44552
Zhao K, Wulder MA, Hu T, Bright R, Wu Q, Qin H, Li Y, Toman E, Mallick B, Zhang X, Brown M (2019) Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: a Bayesian ensemble algorithm. Remote Sens Environ 232:111181. https://doi.org/10.1016/j.rse.2019.04.034
Zhong R, Chen X, Lai C, Wang Z, Lian Y, Yu H, Wu X (2019) Drought monitoring utility of satellite-based precipitation products across mainland China. J Hydrol 568(Novemebr 2018):343–359. https://doi.org/10.1016/j.jhydrol.2018.10.072
Zhou Y, Zhou P, Jin J, Wu C, Cui Y, Zhang Y, Tong F (2022) Drought identification based on Palmer drought severity index and return period analysis of drought characteristics in Huaibei Plain China. Environ Res 212(March). https://doi.org/10.1016/j.envres.2022.113163
Acknowledgements
Authors acknowledge the gridded rainfall data collected from IMD used for this study.
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This research study was financially supported by the University Grants Commission, Govt. of India (grant ref. 190510114219) to the first author.
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Debarati Bera: conceptualisation, methodology, analysis, visualisation, and writing—original draft. Dipanwita Dutta: supervision, project administration, conceptualisation, methodology, formal analysis, visualisation, investigation, and writing—review and editing.
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Bera, D., Dutta, D. Analysing spatio-temporal drought characteristics and copula-based return period in Indian Gangetic Basin (1901–2021). Environ Sci Pollut Res 31, 22471–22493 (2024). https://doi.org/10.1007/s11356-024-32286-1
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DOI: https://doi.org/10.1007/s11356-024-32286-1