IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v77y2015i2p663-677.html
   My bibliography  Save this article

Monitoring spatio-temporal pattern of drought stress using integrated drought index over Bundelkhand region, India

Author

Listed:
  • N. Patel
  • Kamana Yadav

Abstract

Monitoring of drought and associated agricultural production deficit using meteorological indices is essential component for drought preparedness. Remote sensing-based NDVI also plays a key role in drought assessment, but alone it fails due to time lag of 3–4 weeks. In view of improving drought monitoring in Bundelkhand region of India, it was proposed to use combination of meteorological and remote sensing-based approach. The study aims to monitor and assess inter-annual variability in spatial drought and related crop loss in Bundelkhand region using time series of daily rainfall of Climate Prediction Centre (NOAA) and SPOT-VGT-based normalized difference vegetation index. Instead of NDVI, vegetation condition index (VCI) was used to normalize geographical differences in vegetation types and physiographical setting. The new approach is linear weighted index called spatial vegetation drought index (SVDI) constructed from VCI derived from SPOT-VGT and meteorological index named rainfall anomaly index (RAI) for monitoring short-term drought stress in Bundelkhand region. The spatial and temporal pattern of drought matches well with RAI. VCI found to be significantly related to drought stress in terms of rainfall anomaly for majority of decades as well as crop yield anomaly of both food grains and pulses. A modified rainfall anomaly (MRAI) was also constructed by assigning weights to RAI of past three decades to normalize the residual moisture status. The newly formulated SVDI obtained by integrating MRAI and VCI improved the spatial prediction of drought and to detect crop loss associated with short-term drought stress. Comparing real-time drought condition from the observation around the concerned area showed that SVDI was able to illustrate drought stress on large-scale efficiently and can give information about the departure in crop productivity when correlated with crop yield anomaly. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • N. Patel & Kamana Yadav, 2015. "Monitoring spatio-temporal pattern of drought stress using integrated drought index over Bundelkhand region, 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. 77(2), pages 663-677, June.
    • Handle: RePEc:spr:nathaz:v:77:y:2015:i:2:p:663-677
    DOI: 10.1007/s11069-015-1614-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-015-1614-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-015-1614-0?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. 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.
    2. Hong Wu & Donald Wilhite, 2004. "An Operational Agricultural Drought Risk Assessment Model for Nebraska, USA," 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. 33(1), pages 1-21, September.
    3. Sanjay Jain & Ravish Keshri & Ajanta Goswami & Archana Sarkar, 2010. "Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, 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. 54(3), pages 643-656, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manojit Chattopadhyay & Subrata Kumar Mitra, 2018. "Assessing the predictability of different kinds of models in estimating impacts of climatic factors on food grain availability in India," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 50-64, March.
    2. Moumita Palchaudhuri & Sujata Biswas, 2016. "Application of AHP with GIS in drought risk assessment for Puruliya district, 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. 84(3), pages 1905-1920, December.
    3. Varsha Pandey & Prashant K Srivastava & Sudhir K Singh & George P. Petropoulos & Rajesh Kumar Mall, 2021. "Drought Identification and Trend Analysis Using Long-Term CHIRPS Satellite Precipitation Product in Bundelkhand, India," Sustainability, MDPI, vol. 13(3), pages 1-19, January.
    4. Hongbo Zhang & Nan Li & Wengang Zhang & Xiaofang Pei, 2016. "Experiments to automatically monitor drought variation using simulated annealing algorithm," 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. 84(1), pages 175-184, October.
    5. Abhishek Danodia & Anuradha Kushwaha & N. R. Patel, 2021. "Remote sensing-derived combined index for agricultural drought assessment of rabi pulse crops in Bundelkhand region, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15432-15449, October.
    6. V. K. Prajapati & M. Khanna & M. Singh & R. Kaur & R. N. Sahoo & D. K. Singh, 2021. "Evaluation of time scale of meteorological, hydrological and agricultural drought indices," 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. 109(1), pages 89-109, October.
    7. Omvir Singh & Divya Saini & Pankaj Bhardwaj, 2021. "Characterization of meteorological drought over a dryland ecosystem in north western 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. 109(1), pages 785-826, October.
    8. Iman Khosravi & Yaser Jouybari-Moghaddam & Mohammad Reza Sarajian, 2017. "The comparison of NN, SVR, LSSVR and ANFIS at modeling meteorological and remotely sensed drought indices over the eastern district of Isfahan, Iran," 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. 87(3), pages 1507-1522, July.

    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. Ping Zhang & Zhuo Chen & Gang Ding & Jiaqi Fang & Jinglong Fan & Shengyu Li, 2024. "Spatial Analysis and Risk Assessment of Meteorological Disasters Affecting Cotton Cultivation in Xinjiang: A Comprehensive Model Approach," Sustainability, MDPI, vol. 16(12), pages 1-17, June.
    2. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," 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. 83(3), pages 1605-1634, September.
    3. Francisco José Del-Toro-Guerrero & Luis Walter Daesslé & Rodrigo Méndez-Alonzo & Thomas Kretzschmar, 2022. "Surface Reflectance–Derived Spectral Indices for Drought Detection: Application to the Guadalupe Valley Basin, Baja California, Mexico," Land, MDPI, vol. 11(6), pages 1-19, May.
    4. Sergio Vicente-Serrano, 2007. "Evaluating the Impact of Drought Using Remote Sensing in a Mediterranean, Semi-arid Region," 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. 40(1), pages 173-208, January.
    5. Yaojie Yue & Jian Li & Xinyue Ye & Zhiqiang Wang & A-Xing Zhu & Jing-ai Wang, 2015. "An EPIC model-based vulnerability assessment of wheat subject to drought," 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. 78(3), pages 1629-1652, September.
    6. Juan Quijano & Miguel Jaimes & Marco Torres & Eduardo Reinoso & Luisarturo Castellanos & Jesús Escamilla & Mario Ordaz, 2015. "Event-based approach for probabilistic agricultural drought risk assessment under rainfed conditions," 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(2), pages 1297-1318, March.
    7. Lu Liu & Yang Hong & Christopher Bednarczyk & Bin Yong & Mark Shafer & Rachel Riley & James Hocker, 2012. "Hydro-Climatological Drought Analyses and Projections Using Meteorological and Hydrological Drought Indices: A Case Study in Blue River Basin, Oklahoma," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(10), pages 2761-2779, August.
    8. Hao Guo & Xingming Zhang & Fang Lian & Yuan Gao & Degen Lin & Jing’ai Wang, 2016. "Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize," Sustainability, MDPI, vol. 8(8), pages 1-22, August.
    9. Alex Dunne & Yuriy Kuleshov, 2023. "Drought risk assessment and mapping for the Murray–Darling Basin, Australia," 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. 115(1), pages 839-863, January.
    10. Mohamed Mouafik & Abdelghani Chakhchar & Mounir Fouad & Ahmed El Aboudi, 2024. "Remote Sensing Technologies for Monitoring Argane Forest Stands: A Comprehensive Review," Geographies, MDPI, vol. 4(3), pages 1-21, July.
    11. Leisenheimer, Leonie & Wellmann, Thilo & Jänicke, Clemens & Haase, Dagmar, 2024. "Monitoring drought impacts on street trees using remote sensing - Disentangling temporal and species-specific response patterns with Sentinel-2 imagery," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 82, pages 1-14.
    12. Mohammad Mokhtari & Robiah Adnan & Ibrahim Busu, 2013. "A new approach for developing comprehensive agricultural drought index using satellite-derived biophysical parameters and factor analysis method," 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. 65(3), pages 1249-1274, February.
    13. Iman Khosravi & Yaser Jouybari-Moghaddam & Mohammad Reza Sarajian, 2017. "The comparison of NN, SVR, LSSVR and ANFIS at modeling meteorological and remotely sensed drought indices over the eastern district of Isfahan, Iran," 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. 87(3), pages 1507-1522, July.
    14. Renata Kuśmierek-Tomaszewska & Jacek Żarski, 2021. "Assessment of Meteorological and Agricultural Drought Occurrence in Central Poland in 1961–2020 as an Element of the Climatic Risk to Crop Production," Agriculture, MDPI, vol. 11(9), pages 1-17, September.
    15. Swati Pandey & A. Pandey & M. Nathawat & Manoj Kumar & N. Mahanti, 2012. "Drought hazard assessment using geoinformatics over parts of Chotanagpur plateau region, Jharkhand, 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. 63(2), pages 279-303, September.
    16. Xiao-Chen Yuan & Yu-Liang Zhou & Ju-Liang Jin & Yi-Ming Wei, 2013. "Risk analysis for drought hazard in China: a case study in Huaibei Plain," 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. 67(2), pages 879-900, June.
    17. Mehmet Dikici, 2022. "Drought Analysis for the Seyhan Basin with Vegetation Indices and Comparison with Meteorological Different Indices," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    18. T. V. Lakshmi Kumar & Humberto Barbosa & S. Madhu & K. Koteswara Rao, 2019. "Studies on Crop Yields and Their Extreme Value Analysis over India," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
    19. Omvir Singh & Divya Saini & Pankaj Bhardwaj, 2021. "Characterization of meteorological drought over a dryland ecosystem in north western 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. 109(1), pages 785-826, October.
    20. Z. Popova & M. Ivanova & D. Martins & L. Pereira & K. Doneva & V. Alexandrov & M. Kercheva, 2014. "Vulnerability of Bulgarian agriculture to drought and climate variability with focus on rainfed maize systems," 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. 74(2), pages 865-886, November.

    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:77:y:2015:i:2:p:663-677. 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.