IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v120y2024i14d10.1007_s11069-024-06739-2.html
   My bibliography  Save this article

Comparative evaluation of meteorological and hydrological drought using stationary and non-stationary indices in a semi-arid river basin in India

Author

Listed:
  • Arya Sajeev

    (National Institute of Technology Karnataka)

  • Subrahmanya Kundapura

    (National Institute of Technology Karnataka)

Abstract

Few researchers have incorporated climate change in drought indices calculations and conducted comparative analyses of meteorological and hydrological droughts using non-stationary indices. The primary objective of this research is to develop non-stationary indices for assessing meteorological and hydrological droughts in the Shetrunji River basin in India. The climate oscillations are used as covariates to create non-stationary models by applying the generalized additive model in location, scale, and shape from 1971 to 2015. The statistical performance of stationary and non-stationary models has been compared across various time scales (3-, 6-, 12- and 24-months), and the results indicate that non-stationary models more effectively capture meteorological and hydrological drought events than stationary models. The drought and flood events detected by non-stationary indices are compared with historical episodes to assess the robustness of the indices. The results are also compared with drought events obtained from rainfall and streamflow departures. The annual and seasonal departures in rainfall and streamflow show the highest deficiency of rainfall and streamflow in 1987. The probability of different drought classes is calculated, and a higher likelihood of severe to extreme dry conditions is observed compared to very wet and extreme wet conditions in the basin. Investigation has been conducted on the impact of meteorological drought on hydrological drought and a correlation analysis between both types of drought. A significant correlation is observed between meteorological and hydrological drought at all analyzed time scales. Meteorological drought impacts surface water resources with a one-month lag at all time scales, with the highest response rate obtained at 6-month scale (91.13%). The study also examines the impact of drought on yield loss in kharif (bajra) and rabi (wheat) crops. Bajra and wheat yield loss rates strongly correlate with non-stationary drought indices, with a more significant effect of drought on bajra yield than wheat during major drought events. This novel dimension of drought studies provides practical insights into semi-arid regions in a changing environment. The findings can be utilized by various sectors, including drought management, agricultural planners, and policymakers, to reduce crop loss due to drought.

Suggested Citation

  • Arya Sajeev & Subrahmanya Kundapura, 2024. "Comparative evaluation of meteorological and hydrological drought using stationary and non-stationary indices in a semi-arid river basin in India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 13433-13468, November.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:14:d:10.1007_s11069-024-06739-2
    DOI: 10.1007/s11069-024-06739-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-024-06739-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-024-06739-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. N. H. Saji & B. N. Goswami & P. N. Vinayachandran & T. Yamagata, 1999. "A dipole mode in the tropical Indian Ocean," Nature, Nature, vol. 401(6751), pages 360-363, September.
    2. Yixuan Wang & Jianzhu Li & Ping Feng & Fulong Chen, 2015. "Effects of large-scale climate patterns and human activities on hydrological drought: a case study in the Luanhe River basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(3), pages 1687-1710, April.
    3. N. Bandyopadhyay & C. Bhuiyan & A. K. Saha, 2016. "Heat waves, temperature extremes and their impacts on monsoon rainfall and meteorological drought in Gujarat, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 367-388, May.
    4. Pravat Jena & K. S. Kasiviswanathan & Sarita Azad, 2020. "Spatiotemporal characteristics of extreme droughts and their association with sea surface temperature over the Cauvery River basin, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 2239-2259, December.
    5. Aiguo Dai, 2013. "Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(1), pages 52-58, January.
    6. Dong-dong Zhang & Deng-hua Yan & Yi-Cheng Wang & Fan Lu & Shao-hua Liu, 2015. "GAMLSS-based nonstationary modeling of extreme precipitation in Beijing–Tianjin–Hebei region of China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1037-1053, June.
    7. Aiguo Dai, 2013. "Erratum: Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(2), pages 171-171, February.
    8. Karumuri Ashok & N. Saji, 2007. "On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 42(2), pages 273-285, August.
    9. Desalegn Edossa & Mukand Babel & Ashim Das Gupta, 2010. "Drought Analysis in the Awash River Basin, Ethiopia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(7), pages 1441-1460, May.
    10. T. Lakshmi Kumar & K. Koteswara Rao & Humberto Barbosa & R. Uma, 2014. "Trends and extreme value analysis of rainfall pattern over homogeneous monsoon regions of India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 1003-1017, September.
    11. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    12. Javad Bazrafshan & Somayeh Hejabi, 2018. "A Non-Stationary Reconnaissance Drought Index (NRDI) for Drought Monitoring in a Changing Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2611-2624, June.
    13. Poulomi Ganguli & M. Reddy, 2012. "Risk Assessment of Droughts in Gujarat Using Bivariate Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3301-3327, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lei Zou & Jun Xia & Dunxian She, 2018. "Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1421-1438, March.
    2. Jenq-Tzong Shiau, 2020. "Effects of Gamma-Distribution Variations on SPI-Based Stationary and Nonstationary Drought Analyses," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2081-2095, April.
    3. Jale Amanuel Dufera & Tewodros Addisu Yate & Tadesse Tujuba Kenea, 2023. "Spatiotemporal analysis of drought in Oromia regional state of Ethiopia over the period 1989 to 2019," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1569-1609, June.
    4. Ashenafi Yimam Kassaye & Guangcheng Shao & Xiaojun Wang & Shiqing Wu, 2021. "Quantification of drought severity change in Ethiopia during 1952–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5096-5121, April.
    5. D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2617-2646, July.
    6. Soumyashree Dixit & K. V. Jayakumar, 2022. "A Non-stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1217-1236, March.
    7. Jenq-Tzong Shiau & Jia-Wei Lin, 2016. "Clustering Quantile Regression-Based Drought Trends in Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1053-1069, February.
    8. Ge, Yan & Cai, Ximing & Zhu, Tingju & Ringler, Claudia, 2016. "Drought frequency change: An assessment in northern India plains," Agricultural Water Management, Elsevier, vol. 176(C), pages 111-121.
    9. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    10. Jinhua Wen & Yian Hua & Chenkai Cai & Shiwu Wang & Helong Wang & Xinyan Zhou & Jian Huang & Jianqun Wang, 2023. "Probabilistic Forecast and Risk Assessment of Flash Droughts Based on Numeric Weather Forecast: A Case Study in Zhejiang, China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    11. Gilles Dufrénot & William Ginn & Marc Pourroy, 2023. "ENSO Climate Patterns on Global Economic Conditions," AMSE Working Papers 2308, Aix-Marseille School of Economics, France.
    12. Dingcai Yin & Xiaohua Gou & Haijiang Yang & Kai Wang & Jie Liu & Yiran Zhang & Linlin Gao, 2023. "Elevation-dependent tree growth response to recent warming and drought on eastern Tibetan Plateau," Climatic Change, Springer, vol. 176(6), pages 1-18, June.
    13. Adeline Bichet & Arona Diedhiou & Benoit Hingray & Guillaume Evin & N’Datchoh Evelyne Touré & Klutse Nana Ama Browne & Kouakou Kouadio, 2020. "Assessing uncertainties in the regional projections of precipitation in CORDEX-AFRICA," Climatic Change, Springer, vol. 162(2), pages 583-601, September.
    14. Trnka, Miroslav & Vizina, Adam & Hanel, Martin & Balek, Jan & Fischer, Milan & Hlavinka, Petr & Semerádová, Daniela & Štěpánek, Petr & Zahradníček, Pavel & Skalák, Petr & Eitzinger, Josef & Dubrovský,, 2022. "Increasing available water capacity as a factor for increasing drought resilience or potential conflict over water resources under present and future climate conditions," Agricultural Water Management, Elsevier, vol. 264(C).
    15. Yu, Chaoqing & Huang, Xiao & Chen, Han & Huang, Guorui & Ni, Shaoqiang & Wright, Jonathon S. & Hall, Jim & Ciais, Philippe & Zhang, Jie & Xiao, Yuchen & Sun, Zhanli & Wang, Xuhui & Yu, Le, 2018. "Assessing the impacts of extreme agricultural droughts in China under climate and socioeconomic changes," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6, pages 689-703.
    16. Ding, Yugang & Xu, Jiangmin, 2023. "Global vulnerability of agricultural commodities to climate risk: Evidence from satellite data," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 669-687.
    17. Weili Duan & Bin He & Daniel Nover & Jingli Fan & Guishan Yang & Wen Chen & Huifang Meng & Chuanming Liu, 2016. "Floods and associated socioeconomic damages in China over the last century," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 401-413, May.
    18. Sergio M. Vicente-Serrano & Miquel Tomas-Burguera & Santiago Beguería & Fergus Reig & Borja Latorre & Marina Peña-Gallardo & M. Yolanda Luna & Ana Morata & José C. González-Hidalgo, 2017. "A High Resolution Dataset of Drought Indices for Spain," Data, MDPI, vol. 2(3), pages 1-10, June.
    19. Jinquan Li & Junmin Pei & Changming Fang & Bo Li & Ming Nie, 2024. "Drought may exacerbate dryland soil inorganic carbon loss under warming climate conditions," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    20. Zefeng Chen & Weiguang Wang & Giovanni Forzieri & Alessandro Cescatti, 2024. "Transition from positive to negative indirect CO2 effects on the vegetation carbon uptake," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:120:y:2024:i:14:d:10.1007_s11069-024-06739-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.