IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v101y2020i1d10.1007_s11069-020-03872-6.html
   My bibliography  Save this article

Quantification of agricultural drought over Indian region: a multivariate phenology-based approach

Author

Listed:
  • Prabir Kumar Das

    (NRSC)

  • Rituparna Das

    (TERI School of Advanced Studies)

  • Dilip Kumar Das

    (University of Calcutta)

  • Subrata Kumar Midya

    (University of Calcutta)

  • Soumya Bandyopadhyay

    (NRSC)

  • Uday Raj

    (NRSC)

Abstract

The objective, accurate and rapid quantification of agricultural drought is the key component of effective drought planning and management mechanism. The present study proposed a new index, i.e. multivariate phenology-based agricultural drought index (MADI), for quantification of the agricultural drought using long-term (1982–2015) crop phenological parameters. The 15-day global inventory modelling and mapping studies time-series normalized difference vegetation index (NDVI) data (~ 8 km) were interpolated at daily scale and smoothened using Savitzky and Golay filtering technique. Different crop phenological parameters, i.e. start of season, end of season, length of the growing period (lgp), integrated NDVI (iNDVI), etc., were estimated using a combination of threshold and derivative approaches for individual pixels during kharif season. Based on the time of occurrence, the agricultural droughts may lead to delay in crop sowing, reduction in cropped area and/or decreased production. Hence, the lgp and iNDVI were selected among all phenological parameters for their capability to represent alterations in crop duration and crop production, respectively. The long-term lgp and iNDVI of individual pixel were detrended and transformed into standardized lgp (Slgp) and standardized iNDVI (SiNDVI) to eliminate the existing trends developed due to technological improvements during study period and existing heterogeneity of Indian agricultural system, respectively. The MADI was calculated by fitting Slgp and SiNDVI into joint probability distribution, where the best joint distribution family along with associated parameters was selected based on the goodness-of-fit for individual pixel. The values of MADI vary between − 4 and + 4, where the negative and positive values represent drought and non-drought conditions, respectively. The efficacy of the proposed index was tested over the Indian region by comparing with the multivariate standardized drought index, which considers the impacts of both meteorological and soil moisture drought using copula approach.

Suggested Citation

  • Prabir Kumar Das & Rituparna Das & Dilip Kumar Das & Subrata Kumar Midya & Soumya Bandyopadhyay & Uday Raj, 2020. "Quantification of agricultural drought over Indian region: a multivariate phenology-based approach," 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. 101(1), pages 255-274, March.
    • Handle: RePEc:spr:nathaz:v:101:y:2020:i:1:d:10.1007_s11069-020-03872-6
    DOI: 10.1007/s11069-020-03872-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-03872-6
    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/s11069-020-03872-6?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. Aiguo Dai, 2013. "Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(1), pages 52-58, January.
    2. Aiguo Dai, 2013. "Erratum: Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(2), pages 171-171, February.
    3. Sonia I. Seneviratne, 2012. "Historical drought trends revisited," Nature, Nature, vol. 491(7424), pages 338-339, November.
    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. Zheng Li & Tao Zhou & Xiang Zhao & Kaicheng Huang & Shan Gao & Hao Wu & Hui Luo, 2015. "Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index," IJERPH, MDPI, vol. 12(7), pages 1-20, July.
    2. Brigitte Mueller & Xuebin Zhang, 2016. "Causes of drying trends in northern hemispheric land areas in reconstructed soil moisture data," Climatic Change, Springer, vol. 134(1), pages 255-267, January.
    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. 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.
    5. Anna Jędrejek & Rafał Pudełko, 2023. "Exploring the Potential Use of Sentinel-1 and 2 Satellite Imagery for Monitoring Winter Wheat Growth under Agricultural Drought Conditions in North-Western Poland," Agriculture, MDPI, vol. 13(9), pages 1-17, September.
    6. Rengui Jiang & Jiancang Xie & Hailong He & Jungang Luo & Jiwei Zhu, 2015. "Use of four drought indices for evaluating drought characteristics under climate change in Shaanxi, China: 1951–2012," 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. 75(3), pages 2885-2903, February.
    7. 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.
    8. Gilles Dufrénot & William Ginn & Marc Pourroy, 2023. "ENSO Climate Patterns on Global Economic Conditions," AMSE Working Papers 2308, Aix-Marseille School of Economics, France.
    9. Nabeel Bani Hani & Fakher J. Aukour & Mohammed I. Al-Qinna, 2022. "Investigating the Pearl Millet ( Pennisetum glaucum ) as a Climate-Smart Drought-Tolerant Crop under Jordanian Arid Environments," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    10. 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.
    11. Hong, Minki & Lee, Sang-Hyun & Lee, Seung-Jae & Choi, Jin-Yong, 2021. "Application of high-resolution meteorological data from NCAM-WRF to characterize agricultural drought in small-scale farmlands based on soil moisture deficit," Agricultural Water Management, Elsevier, vol. 243(C).
    12. Shan Jiang & Jian Zhou & Guojie Wang & Qigen Lin & Ziyan Chen & Yanjun Wang & Buda Su, 2022. "Cropland Exposed to Drought Is Overestimated without Considering the CO 2 Effect in the Arid Climatic Region of China," Land, MDPI, vol. 11(6), pages 1-21, June.
    13. L. Lin & A. Gettelman & Q. Fu & Y. Xu, 2018. "Simulated differences in 21st century aridity due to different scenarios of greenhouse gases and aerosols," Climatic Change, Springer, vol. 146(3), pages 407-422, February.
    14. 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.
    15. 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).
    16. 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.
    17. Yuan Li & Yi Dong & Dongqin Yin & Diyou Liu & Pengxin Wang & Jianxi Huang & Zhe Liu & Hongshuo Wang, 2020. "Evaluation of Drought Monitoring Effect of Winter Wheat in Henan Province of China Based on Multi-Source Data," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    18. Jing Peng & Li Dan & Jinming Feng & Kairan Ying & Xiba Tang & Fuqiang Yang, 2021. "Absolute Contribution of the Non-Uniform Spatial Distribution of Atmospheric CO 2 to Net Primary Production through CO 2 -Radiative Forcing," Sustainability, MDPI, vol. 13(19), pages 1-18, September.
    19. 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.
    20. Huailei Cheng & Yuhong Wang & Dan Chong & Chao Xia & Lijun Sun & Jenny Liu & Kun Gao & Ruikang Yang & Tian Jin, 2023. "Truck platooning reshapes greenhouse gas emissions of the integrated vehicle-road infrastructure system," Nature Communications, Nature, vol. 14(1), pages 1-10, 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:101:y:2020:i:1:d:10.1007_s11069-020-03872-6. 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.