Abstract
This study attempts to develop a composite index by integrating meteorological, hydrological and agricultural droughts over semi-arid Banas River basin, Rajasthan, India. To affect this, the standardized precipitation index (SPI), streamflow drought index (SDI), and vegetation condition index (VCI) have been used at 1-, 3-, 5-, 9- and 12-month time scales using station and remote sensing-based data for the period 2000 to 2020. To identify the occurrence of above-stated droughts and most vulnerable drought period at different time scales (1-, 3-, 5-, 9- and 12-month) regarding SPI, SDI and VCI has been validated with foodgrains produced and occurrence of historical drought years. This validation has been found significant with SPI-3 (r = − 0.81), SDI-3 (r = − 0.78) and VCI-5 (r = − 0.80) time scales. Subsequently, these time scales have been coalesced using weights obtained from principal component analysis (PCA) to develop the composite drought index (CDI). The annual CDI developed this way has been further validated with foodgrains produced and occurrence of historical drought years. The results of CDI demonstrate the maximum area under mild drought (73 percent) followed by moderate (21 percent) and severe (4 percent), whereas minuscule area has been detected under wet conditions (2 percent). Finally, this study suggests that individual drought types (meteorological, hydrological, agricultural) do not appropriately arrest the drought severity, hence, the usage of multiple droughts based composite index can be more realistic for effective drought assessment and monitoring in hydrologic systems.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Data will be made available on reasonable request.
References
Akbari H, Rakhshandehroo G, Sharifloo AH, Ostadzadeh E (2015) Drought analysis based on standardized precipitation index (SPI) and streamflow drought index (SDI) in Chenar Rahdar river basin, Southern Iran. In: Watershed Management 2015 (pp. 11-22).
Attri SD, Tyagi A (2010) Climate profile of India. Environment Monitoring and Research Center, India Meteorology Department, New Delhi, India
Azhdari A, Bazrafshan J (2022) A hybrid drought index for assessing agricultural drought in arid and semi-arid coastal areas of Southern Iran. Int J Environ Sci Technol 19:9409–9426. https://doi.org/10.1007/s13762-022-04154-3
Azmi M, Rüdiger C, Walker JP (2016) A data fusion-based drought index. Water Resour Res 52:2222–2239. https://doi.org/10.1002/2015WR017834
Bae H, Ji H, Lim YJ, Ryu Y, Kim MH, Kim BJ (2019) Characteristics of drought propagation in South Korea: relationship between meteorological, agricultural, and hydrological droughts. Nat Hazards 99:1–16. https://doi.org/10.1007/s11069-019-03676-3
Barker LJ, Hannaford J, Chiverton A, Svensson C (2016) From meteorological to hydrological drought using standardized indicators. Hydrol Earth Syst Sci 20(6):2483–2505. https://doi.org/10.5194/hess-20-2483-2016
Bazrafshan J, Nadi M, Ghorbani K (2015) Comparison of empirical copula-based joint deficit index (JDI) and multivariate standardized precipitation index (MSPI) for drought monitoring in Iran. Water Resour Manag 29:2027–2044. https://doi.org/10.1007/s11269-015-0926-x
Bhuiyan C, Saha AK, Bandyopadhyay N, Kogan FN (2017) Analyzing the impact of thermal stress on vegetation health and agricultural drought–a case study from Gujarat, India. Gisci Remote Sens 54:678–699. https://doi.org/10.1080/15481603.2017.1309737
Bhukya S, Tiwari MK, Patel GR (2023) Assessment of spatiotemporal variation of agricultural and meteorological drought in Gujrat (India) using remote sensing and GIS. J Indian Soc Remot 51:1493–1510. https://doi.org/10.1007/s12524-023-01715-y
Biswas B, Karmegam D (2023) Long-term spatio-temporal analysis and trends of precipitation over semi-arid region of Rajasthan. Meteorol Atmos Phys 135(6):53. https://doi.org/10.1007/s00703-023-00991-0
Byun HR, Wilhite DA (1999) Objective quantification of drought severity and duration. J Climate 12(9):2747–2756. https://doi.org/10.1175/1520-0442
Chahal M, Bhardwaj P, Singh O (2021) Exploring the trends and pattern of rainfall extremes over the semiarid Sahibi basin in Rajasthan, India. Arabian J Geosci 14:966. https://doi.org/10.1007/s12517-021-07320-y
Degefu MA, Bewket W (2015) Trends and spatial patterns of drought incidence in the Omo-Ghibe River basin, Ethiopia. Geogr Ann B 97:395–414. https://doi.org/10.1111/geoa.12080
Dhakar R, Sehgal VK, Pradhan S (2013) Study on inter-seasonal and intra-seasonal relationships of meteorological and agricultural drought indices in the Rajasthan State of India. J Arid Environ 97:108–119. https://doi.org/10.1016/j.jaridenv.2013.06.001
Ding Y, Xu J, Wang X, Cai H, Zhou Z, Sun Y, Shi H (2021) Propagation of meteorological to hydrological drought for different climate regions in China. J Environ Manage 283:111980. https://doi.org/10.1016/j.jenvman.2021.111980
Dodamani B, Anoop R, Mahajan D (2015) Agricultural drought modeling using remote sensing. Int J Environ Sci Dev 6:326–331. https://doi.org/10.7763/IJESD.2015.V6.612
Du L, Tian Q, Yu T, Meng Q, Jancso T, Udvardy P, Huang Y (2013) A comprehensive drought monitoring method integrating MODIS and TRMM data. Int J Appl Earth Obs Geoinf 23:245–253. https://doi.org/10.1016/j.jag.2012.09.010
Dubey SK, Sharma D (2018) Spatio-temporal trends and projections of climate indices in the Banas River basin, India. Environ Process 5:743–768. https://doi.org/10.1007/s40710-018-0332-5
Dubey SK, Sharma D, Mundetia N (2015) Morphometric analysis of the Banas River basin using the geographical information system Rajasthan India. Hydrol 3(5):47–54. https://doi.org/10.11648/j.hyd.20150305.11
Durowoju OS, Ologunorisa TE, Akinbobola A (2021) Assessing agricultural and hydrological drought vulnerability in a savanna ecological zone of Sub-Saharan Africa. Nat Hazards 111(2):1–28. https://doi.org/10.1007/s11069-021-05143-4
Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto Int 28:192–209. 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
Edwards DC, McKee TB (1997) Characteristics of 20th century drought in the United States at multiple time scales. Climatology Report 97–2, Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
Everard M, Sharma OP, Vishwakarma VK, Khandal D, Sahu YK, Bhatnagar R, Singh JK, Kumar R, Nawab A, Kumar A, Kumar V, Kashyap A, Pandey DN, Pinder AC (2018) Assessing the feasibility of integrating ecosystem-based with engineered water resource governance and management for water security in semi-arid landscapes: a case study in the Banas catchment, Rajasthan, India. Sci Total Environ 612:1249–1265. https://doi.org/10.1016/j.scitotenv.2017.08.308
Ganguli P, Reddy MJ (2013) Analysis of ENSO based climate variability in modulating drought risks over western Rajasthan in India. J Earth Syst Sci 122:253–269. https://doi.org/10.1007/s12040-012-0247-x
Ghasemi MM, Zarei AR, Mokarram M (2022) A new version of the reconnaissance drought index, N-RDI. Climate Res 89:29–39. https://doi.org/10.3354/cr01705
Hao C, Zhang J, Yao F (2015) Combination of multi-sensor remote sensing data for drought monitoring over Southwest China. Int J Appl Earth Obs Geoinf 35:270–283. https://doi.org/10.1016/j.jag.2014.09.011
Jalayer S, Sharifi A, Abbasi-Moghadam D, Tariq A, Qin S (2023) Assessment of spatiotemporal characteristic of drought using in situ and remote sensing-based drought indices. J Sel Top Appl Earth Obs Remote Sens 16:1483–1502. https://doi.org/10.1109/JSTARS.2023.3237380
Kalyan S, Sharma D, Sharma A (2021) Spatio-temporal variation in desert vulnerability using desertification index over the Banas River Basin in Rajasthan. India Arab J Geosci 14:54. https://doi.org/10.1007/s12517-020-06417-0
Kao SC, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380:121–134. https://doi.org/10.1016/j.jhydrol.2009.10.029
Karimi M, Shahedi K, Raziei T, Miryaghoubzadeh M (2019) Analysis of Performance of vegetation indices on agricultural drought using remote sensing technique in Karkheh basin. J Remote Sens GIS 11(4):29–46. https://doi.org/10.52547/gisj.11.4.29
Karimi M, Vicente-Serrano SM, Reig F, Shahedi K, Raziei T, Miryaghoubzadeh M (2020) Recent trends in atmospheric evaporative demand in Southwest Iran: implications for change in drought severity. Theoret Appl Climatol 142(3):945–958. https://doi.org/10.1007/s00704-020-03349-3
Karimi M, Shahedi K, Raziei T, Miryaghoubzadeh M (2022) Meteorological and agricultural drought monitoring in southwest of Iran using a remote sensing based combined drought index. Stoch Environ Res Risk Assess 36:3707–3724. https://doi.org/10.1007/s00477-022-02220-3
Karnieli A, Agam N, Pinker RT, Anderson M, Imhoff ML, Gutman GG, Panov N, Goldberg A (2010) Use of NDVI and land surface temperature for drought assessment: merits and limitations. J Climatol 23(3):618–633. https://doi.org/10.1175/2009JCLI2900.1
Keyantash JA, Dracup JA (2004) An aggregate drought index: assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resour Res 40:W09304. https://doi.org/10.1029/2003WR002610
Kogan FN (1995) Droughts of the late 1980s in the United States as derived from NOAA polar orbiting satellite data. B Am Meteorol Soc 76:655–668. https://doi.org/10.1175/1520-0477
Kogan FN (1997) Global drought watch from space. Bull Am Meteor Soc 78(4):621–636. https://doi.org/10.1175/1520-0477
Li J, Wu C, Chuan-An X, Yeh Pat J-F, Hu BX, Huang G (2021) Assessing the response of hydrological drought to meteorological drought in the Huai River basin, China. Theor Appl Climatol 144:1043–1057. https://doi.org/10.1007/s00704-021-03567-3
Liu WT, Kogan FN (1996) Monitoring regional drought using the vegetation condition index. Int J Remote Sens 17(14):2761–2782. https://doi.org/10.1080/01431169608949106
Liu ZY, Menzel L, Dong CY, Fang RH (2016) Temporal dynamics and spatial patterns of drought and the relation to ENSO: a case study in northwest China. Int J Climatol 36:2886–2898. https://doi.org/10.1002/joc.4526
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
Ma BL, Dwyer LM, Costa C, Cober ER, Morrison MJ (2001) Early prediction of soybean yield from canopy reflectance measurements. Agron J 93:1227–1234. https://doi.org/10.2134/agronj2001.1227
Maccioni P, Kossida M, Brocca L, Moramarco T (2014) An assessment of the drought hazard in the Tiber River basin in central Italy and a comparison of new and commonly used meteorological indicators. J Hydrol Eng 20(8):05014029. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001094
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. B Am Meteorol Soc, 17:179–183
McKee TB, Doesken NJ, Kleist J (1995) Drought monitoring with multiple time scales. B Am Meteorol Soc pp 233–236.
Mehla KM, Kothari M, Singh PK, Bhakar SR, Yadav KK (2022) Assessment of water footprint for a few major crops in Banas River Basin of Rajasthan. J Appl Nat Sci 14:1264–1271
Mehta D, Yadav SM (2021) An analysis of rainfall variability and drought over Barmer district of Rajasthan. Northwest India Water Supply 21(5):2505–2517. https://doi.org/10.2166/ws.2021.053
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 D, Goswami S, Matin S, Sarup J (2022) Analyzing the extent of drought in the Rajasthan state of India using vegetation condition index and standardized precipitation index. Model Earth Syst Environ 8:601–610. https://doi.org/10.1007/s40808-021-01102-x
Morán-Tejeda E, Ceglar A, Medved-Cvikl B, Vicente-Serrano SM, López-Moreno JI, González-Hidalgo JC, Pasho E (2013) Assessing the capability of multi-scale drought datasets to quantify drought severity and to identify drought impacts: an example in the Ebro Basin. Int J Climatol 33(8):1884–1897. https://doi.org/10.1002/joc.3555
Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manage 23:881–897. https://doi.org/10.1007/s11269-008-9305-1
NCDC (2016) Billion-dollar U.S. weather and climate disaster, 1980–2015
Orimoloye IR, Belle JA, Olusola AO, Busayo ET, Ololade OO (2020) Spatial assessment of drought disasters, vulnerability, severity and water shortages: a potential drought disaster mitigation strategy. Nat Hazards 105(3):2735–2754. https://doi.org/10.1007/s11069-020-04421-x
Pai DS, Sridhar L, Guhathakurta P, Hatwar HR (2011) District-wise drought climatology of the south-west monsoon season over India based on standardized precipitation index (SPI). Nat Hazards 59:1797–1813. https://doi.org/10.1007/s11069-011-9867-8
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
Porhemat J, Razi T, Rahimibandarabadi S (2015) Investigation on spatio-temporal variability of meteorological drought in Southwestern Iran (case study in Karkheh basin). Irrigat Water Eng 5(3):60–79
Portela MM, Zeleňáková M, Santos JF, Purcz P, Silva AT, Hlavatá H (2015) A comprehensive drought analysis in Slovakia using SPI. European Water 51:15–31
Prajapati VK, Khanna M, Singh M, Kaur R, Sahoo RN, Singh DK (2021) Evaluation of time scale of meteorological, hydrological and agricultural drought indices. Nat Hazards 109:89–109. https://doi.org/10.1007/s11069-021-04827-1
Prajapati VK, Khanna M, Singh M, Kaur R, Sahoo RN, Singh DK (2022) PCA- based composite drought index for drought assessment in Marathwada region of Maharashtra state, India. Theor Appl Climatol 149:207–220. https://doi.org/10.1007/s00704-022-04044-1
Rajsekhar D, Singh VP, Mishra AK (2015) Multivariate drought index: an information theory-based approach for integrated drought assessment. J Hydrol 526:164–182. https://doi.org/10.1016/j.jhydrol.2014.11.031
Rani A, Sharma D, Babel MS, Sharma A (2022) Spatio-temporal assessment of agro-climatic indices and the monsoon pattern in the Banas River basin. India Environ Chall 7:100483. https://doi.org/10.1016/j.envc.2022.100483
Rathore MS (2009) State level analysis of drought policies and impacts in Rajasthan, India. Working paper 93, Drought Series, Paper-6
Rhee J, Im J, Carbone GJ (2010) Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sens Environ 114(12):2875–2887. https://doi.org/10.1016/j.rse.2010.07.005
Saini D, Singh O, Bhardwaj P (2022a) Standardized precipitation index based dry and wet conditions over a dryland ecosystem of northwestern India. Geol Ecol Landsc 6(4):252–264. https://doi.org/10.1080/24749508.2020.1833614
Saini D, Singh O, Sharma T, Bhardwaj P (2022b) Geoinformatics and analytic hierarchy process-based drought vulnerability assessment over a dryland ecosystem of north-western India. Nat Hazards 114:1427–1454. https://doi.org/10.1007/s11069-022-05431-7
Sardou FS, Bahramand A (2014) Hydrological drought analysis using SDI index in Halilrud basin of Iran. Environ Resour Res 2(1):47–56. https://doi.org/10.22069/IJERR.2014.1678
Shen R, Huang A, Li B, Guo J (2019) Construction of a drought monitoring model using deep learning based on multi-source remote sensing data. Int J Appl Earth Obs 79:48–57. https://doi.org/10.1016/j.jag.2019.03.006
Shi H, Chen J, Wang K, Niu J (2018) A new method and a new index for identifying socioeconomic drought events under climate change: a case study of the East River basin in China. Sci Total Environ 616–617:363–375. https://doi.org/10.1016/j.scitotenv.2017.10.321
Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35:L02405. https://doi.org/10.1029/2007GL032487
Singh O, Saini D, Bhardwaj P (2021) Characterization of meteorological drought over a dryland ecosystem in north western India. Nat Hazards 109:785–826. https://doi.org/10.1007/s11069-021-04857-9
Sobral BS, Oliveira-Júnior JF, Gois G, Pereira-Júnior ER, Terassi PMB, Muniz-Júnior JGR, Lyra GB, Zeri M (2019) Drought characterization for the state of Rio de Janeiro based on the annual SPI index: trends, statistical tests and its relation with ENSO. Atmos Res 220:141–154. https://doi.org/10.1016/j.atmosres.2019.01.003
Surendran U, Kumar V, Ramasubramoniam S, Raja P (2017) Development of drought indices for semi-arid region using drought indices calculator (DrinC)–a case study from Madurai District, a semi-arid region in India. Water Resour Manag 31:3593–3605. https://doi.org/10.1007/s11269-017-1687-5
Tabari H, Nikbakht J, Talae H (2013) Hydrological drought assessment in northwestern Iran based on streamflow drought index (SDI). Water Resour Manag 27:137–151. https://doi.org/10.1007/s11269-012-0173-3
Tabari H, Zamani R, Rahmati H, Willems P (2015) Markov chains of different orders for streamflow drought analysis. Water Resour Manag 29(9):3441–3457. https://doi.org/10.1007/s11269-015-1010-2
Thavorntam W, Tantemsapya N, Armstrong L (2015) A combination of meteorological and satellite-based drought indices in a better drought assessment and forecasting in Northeast Thailand. Nat Hazards 77(3):1453–1474. https://doi.org/10.1007/s11069-014-1501-0
Thavorntam W, Saengavut V, Armstrong LJ, Cook D (2023) Association of farmers’ wellbeing in a drought-prone area Thailand: applications of SPI and VCI indices. Environ Monit Assess 195:612. https://doi.org/10.1007/s10661-023-11157-1
Tian L, Yuan S, Quiring SM (2018) Evaluation of six indices for monitoring agricultural drought in the south-central United States. Agr Forest Meteorol 249:107–119. https://doi.org/10.1016/j.agrformet.2017.11.024
Tigkas D, Vangelis H, Tsakiris G (2015) Drin C: a software for drought analysis based on drought indices. Earth Sci Inform 8:697–709. https://doi.org/10.1007/s12145-014-0178-y
Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21:821–833. https://doi.org/10.1007/s11269-006-9105-4
Ullah I, Ma X, Ren G, Yin J, Iyakaremye V, Syed S, Lu K, Xing Y, Singh VP (2022) Recent changes in drought events over South Asia and their possible linkages with climatic and dynamic factors. Remote Sens 14:3219. https://doi.org/10.3390/rs14133219
Valiya VA, Mishra A (2020) Multiscale hydrological drought analysis: role of climate, catchment and morphological variables and associated thresholds. J Hydrol 582:124533. https://doi.org/10.1016/j.jhydrol.2019.124533
Vicente-Serrano SM (2007) Evaluating the impact of drought using remote sensing in a Mediterranean, semi-arid region. Nat Hazards 40:173–208. https://doi.org/10.1007/s11069-006-0009-7
Vicente-Serrano SM, Begueria S, Lopez-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Climate 23(7):1696–1718. https://doi.org/10.1175/2009JCLI2909.1
Waseem M, Ajmal M, Kim TW (2015) Development of a new composite drought index for multivariate drought assessment. J Hydrol 527:30–37. https://doi.org/10.1016/j.jhydrol.2015.04.044
Yao N, Li Y, Lei T, Peng L (2018) Drought evolution, severity and trends in mainland China over 1961–2013. Sci Total Environ 616–617:73–89. https://doi.org/10.1016/j.scitotenv.2017.10.327
Zambrano F, Lillo-Saavedra M, Verbist K, Lagos O (2016) Sixteen years of agricultural drought assessment of the biobio region in Chile using a 250 m resolution vegetation condition index (VCI). Remote Sens 8(6):530. https://doi.org/10.3390/rs8060530
Zeng L, Shan J, Xiang D (2014) March. Monitoring drought using multi-sensor remote sensing data in cropland of Gansu Province. In: IOP Conference Series: Earth and Environmental Science, 17:012017. https://doi.org/10.1088/1755-1315/17/1/012017
Zhong F, Cheng Q, Wang P (2020) Meteorological drought, hydrological drought, and NDVI in the Heihe River basin, Northwest China: evolution and propagation. Adv Meteorol 2020:1–26. https://doi.org/10.1155/2020/2409068
Zou L, Cao S, Sanchez-Azofeifa A (2020) Evaluating the utility of various drought indices to monitor meteorological drought in tropical dry forests. Int J Biometeo 64:701–711. https://doi.org/10.1007/s00484-019-01858-z
Zuo D, Cai S, Xu Z, Peng D, Kan G, Sun W, Yang H (2019) and agricultural droughts using in-situ observations and in-situ observations and remote sensing data. Agr Water Manage 222:125–138. https://doi.org/10.1016/j.agwat.2019.05.046
Funding
The authors declare that no funds, grants, or other support have been received during the preparation of this manuscript.
Author information
Authors and Affiliations
Contributions
DS reviewed the literature, analyzed data, prepared tables, figures and initial draft. OS contributed to the study conception, designs, supervision and editing of the draft of manuscript. All the authors contributed significantly and duly approve this work.
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Saini, D., Singh, O. Comparison of meteorological, hydrological and agricultural droughts for developing a composite drought index over semi-arid Banas River Basin of India. Stoch Environ Res Risk Assess (2024). https://doi.org/10.1007/s00477-024-02704-4
Accepted:
Published:
DOI: https://doi.org/10.1007/s00477-024-02704-4