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Meteorological drought analysis over India using analytical framework on CPC rainfall time series

Author

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  • C. S. Murthy

    (Agricultural Sciences and Applications Group, National Remote Sensing Centre, Balanagar)

  • Jyoti Singh

    (Forest and Ecology Group, National Remote Sensing Centre, Balanagar)

  • Pavan Kumar

    (Kumaun University)

  • M. V. R. Sesha Sai

    (Agricultural Sciences and Applications Group, National Remote Sensing Centre)

Abstract

Drought is a natural climatic phenomenon occurring due to deficiency of precipitation. It is precursor of famine and is difficult to monitor due to its slow progression. The present study employs understanding drought and analyzing its various parameters such as rainfall. One of the main aspects of drought planning and mitigation includes hazard assessment, which describes the physical nature of drought and plays an important role in the relationship between vulnerability and risk. The study uses CPC rainfall time series of 12 years, 2001–2012, during the major rainfall period, i.e., southwest monsoon (June–September) over India at 10 km × 10 km pixel for the meteorological drought analysis. Drought occurrence patterns in the country in the 12-year time series period were analyzed using mean, inter-annual variability (coefficient of variation CV) and drought frequency of rainfall and rainy days. The analysis has highlighted the areas with lower mean rainfall and higher CV and higher drought frequency. Meteorological drought map based on rainfall and rainy day deviations was prepared separately, for all the 12 years, based on IMD criteria of rainfall deviations. Spatial agreement analysis between rainfall-based drought map and rainy days-based drought map was performed using kappa index. It is interesting to note that the agreement between the two maps was

Suggested Citation

  • C. S. Murthy & Jyoti Singh & Pavan Kumar & M. V. R. Sesha Sai, 2016. "Meteorological drought analysis over India using analytical framework on CPC rainfall time series," 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. 81(1), pages 573-587, March.
    • Handle: RePEc:spr:nathaz:v:81:y:2016:i:1:d:10.1007_s11069-015-2097-8
    DOI: 10.1007/s11069-015-2097-8
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    References listed on IDEAS

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    4. Klein, K. K. & Kulshreshtha, S. N. & Klein, S. A., 1989. "Agricultural drought impact evaluation model: Description of components," Agricultural Systems, Elsevier, vol. 30(2), pages 117-138.
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    Cited by:

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    2. Nazla Bushra & Robert V. Rohli & Nina S. N. Lam & Lei Zou & Rubayet Bin Mostafiz & Volodymyr Mihunov, 2019. "The relationship between the Normalized Difference Vegetation Index and drought indices in the South Central United States," 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. 96(2), pages 791-808, March.
    3. Sohail Abbas & Shazia Kousar, 2021. "Spatial analysis of drought severity and magnitude using the standardized precipitation index and streamflow drought index over the Upper Indus Basin, Pakistan," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15314-15340, October.
    4. Nayan D. Zagade & Bhavana N. Umrikar, 2021. "Drought severity modeling of upper Bhima river basin, western India, using GIS–AHP tools for effective mitigation and resource management," 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. 105(2), pages 1165-1188, January.

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